From 37e8a894e9bda460af7ff8668c18f8fc907a90fd Mon Sep 17 00:00:00 2001
From: Fabian Wachsmann <k204210@l40072.lvt.dkrz.de>
Date: Tue, 7 Jan 2025 11:33:53 +0100
Subject: [PATCH] Added nbs
---
workshop/1_start-an-app.ipynb | 314 +
workshop/2_data-access.ipynb | 3292 ++++
workshop/3_use-cases-and-preparations.ipynb | 1995 ++
workshop/4_kerchunk-input-kerchunk-api.ipynb | 16517 +++++++++++++++++
workshop/5_catalog-input.ipynb | 3695 ++++
5 files changed, 25813 insertions(+)
create mode 100644 workshop/1_start-an-app.ipynb
create mode 100644 workshop/2_data-access.ipynb
create mode 100644 workshop/3_use-cases-and-preparations.ipynb
create mode 100644 workshop/4_kerchunk-input-kerchunk-api.ipynb
create mode 100644 workshop/5_catalog-input.ipynb
diff --git a/workshop/1_start-an-app.ipynb b/workshop/1_start-an-app.ipynb
new file mode 100644
index 0000000..def3df9
--- /dev/null
+++ b/workshop/1_start-an-app.ipynb
@@ -0,0 +1,314 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "13ba06b9-5f2e-4de3-90da-511557166bfe",
+ "metadata": {},
+ "source": [
+ "# Cloudify\n",
+ "\n",
+ "This notebook series guides you through the *cloudify* service: Serving Xarray datasets as zarr-datasets with xpublish and enabled server-side processing with dask. It introduces to the basic concepts with some examples. It was designed to work on DKRZ's HPC."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a56b764b-23a7-4d86-84b2-bf419d989cb2",
+ "metadata": {},
+ "source": [
+ "## 1. Start an app\n",
+ "\n",
+ "In the following, you will learn how to start and control the cloudify service.\n",
+ "\n",
+ "**Is there any other reason why to run cloudify on the only internally accessible DKRZ HPC?**\n",
+ "\n",
+ "If you *cloudify* a virtual dataset prepared as a highly aggregated, analysis-ready dataset, clients can subset from this *one* large aggregated dataset instead of searching the file system."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0b17b450-716d-49b3-bbfa-aec943e47120",
+ "metadata": {},
+ "source": [
+ "1. Install a kernel for jupyterhub\n",
+ "\n",
+ "```bash\n",
+ "source activate /work/bm0021/conda-envs/cloudify\n",
+ "python -m ipykernel install --user --name cloudify_env\n",
+ "```\n",
+ "\n",
+ "- Choose the kernel"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "8cfb6129-aea7-4d87-a016-e04cee5bf084",
+ "metadata": {},
+ "source": [
+ "2. For being able to allow secure *https* access, we need a ssl certificate. For testing purposes and for levante, we can use a self-signed one. Additionally, right now, some applications do only allow access through https. We can create it like this:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "d5e47e26-93ac-465f-90a4-8d84762b1f80",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "#!openssl req -x509 -newkey rsa:4096 -keyout key.pem -out cert.pem -sha256 -days 3650 -nodes -subj \"/C=XX/ST=Hamburg/L=Hamburg/O=Test/OU=Test/CN=localhost\""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "190bde7f-6f36-4c87-a9f2-a82ee840302e",
+ "metadata": {},
+ "source": [
+ "3. We write a cloudify script for data serving and start to host an example dataset in a background process. We need to consider some settings:\n",
+ "\n",
+ "**Port**\n",
+ "\n",
+ "The resulting service listens on a specifc *port*. In case we share a node, we can only use ports that are not allocated already. To enbale us all to run an own app, we agree to use a port `90XX` where XX are the last two digits of our account.\n",
+ "\n",
+ "**Dask Cluster**\n",
+ "\n",
+ "Dask is necessary for lazy access of the data. Additionally, a dask cluster can help us to do server-side processing like uniform encoding. When starting the imported predefined dask cluster, it will use the following resources:\n",
+ "\n",
+ "```python\n",
+ "n_workers=2,\n",
+ "threads_per_worker=8,\n",
+ "memory_limit=\"16GB\"\n",
+ "```\n",
+ "\n",
+ "which should be sufficient for at least two clients in parallel. We store it in an environment variable so that xpublish can find it. We futhermore have to allign the two event loops of dask and xpublish's asyncio with `nest_asyncio.apply()`. Event loops can be seen as *while* loops for a permanently running main worker.\n",
+ "\n",
+ "\n",
+ "**Plug-ins**\n",
+ "\n",
+ "Xpublish finds pre-installed plugins like the intake-plugin by itself. Own plugins need to be registered.\n",
+ "\n",
+ "Further settings will be discussed later."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "e11d309f-c893-401a-ba5f-9f3f0046e039",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "xpublish_example_script=\"xpublish_example.py\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "571a82ea-d7bc-42e3-8169-ae22ef999065",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Overwriting xpublish_example.py\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%writefile {xpublish_example_script}\n",
+ "\n",
+ "port=9000\n",
+ "ssl_keyfile=\"/work/bm0021/k204210/cloudify/workshop/key.pem\"\n",
+ "ssl_certfile=\"/work/bm0021/k204210/cloudify/workshop/cert.pem\"\n",
+ "\n",
+ "from cloudify.plugins.stacer import *\n",
+ "from cloudify.utils.daskhelper import *\n",
+ "import xarray as xr\n",
+ "import xpublish as xp\n",
+ "import asyncio\n",
+ "import nest_asyncio\n",
+ "import sys\n",
+ "import os\n",
+ "\n",
+ "nest_asyncio.apply()\n",
+ "chunks={}\n",
+ "for coord in [\"lon\",\"lat\"]:\n",
+ " chunk_size=os.environ.get(f\"XPUBLISH_{coord.upper()}_CHUNK_SIZE\",None)\n",
+ " if chunk_size:\n",
+ " chunks[coord]=int(chunk_size)\n",
+ "\n",
+ "l_lossy=os.environ.get(\"L_LOSSY\",False)\n",
+ "\n",
+ "def lossy_compress(partds):\n",
+ " import numcodecs\n",
+ " rounding = numcodecs.BitRound(keepbits=12)\n",
+ " return rounding.decode(rounding.encode(partds))\n",
+ "\n",
+ "if __name__ == \"__main__\": # This avoids infinite subprocess creation\n",
+ " import dask\n",
+ " zarrcluster = asyncio.get_event_loop().run_until_complete(get_dask_cluster())\n",
+ " os.environ[\"ZARR_ADDRESS\"]=zarrcluster.scheduler._address\n",
+ " \n",
+ " dsname=sys.argv[1]\n",
+ " glob_inp=sys.argv[2:]\n",
+ "\n",
+ " dsdict={}\n",
+ " ds=xr.open_mfdataset(\n",
+ " glob_inp,\n",
+ " compat=\"override\",\n",
+ " coords=\"minimal\",\n",
+ " chunks=chunks\n",
+ " )\n",
+ " ds=ds.set_coords([a for a in ds.data_vars if \"bnds\" in a])\n",
+ " if l_lossy:\n",
+ " ds = xr.apply_ufunc(\n",
+ " lossy_compress,\n",
+ " ds,\n",
+ " dask=\"parallelized\", \n",
+ " keep_attrs=\"drop_conflicts\"\n",
+ " )\n",
+ " dsdict[dsname]=ds\n",
+ " \n",
+ " collection = xp.Rest(dsdict)\n",
+ " collection.register_plugin(Stac())\n",
+ " collection.serve(\n",
+ " host=\"0.0.0.0\",\n",
+ " port=port,\n",
+ " ssl_keyfile=ssl_keyfile,\n",
+ " ssl_certfile=ssl_certfile\n",
+ " )"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "ca64c11f-0846-4ddd-9e60-4b22dba8b32c",
+ "metadata": {},
+ "source": [
+ "You can run this app e.g. for:\n",
+ "```\n",
+ "dsname=\"example\"\n",
+ "glob_inp=\"/work/ik1017/CMIP6/data/CMIP6/ScenarioMIP/DKRZ/MPI-ESM1-2-HR/ssp370/r1i1p1f1/Amon/tas/gn/v20190710/*.nc\"\n",
+ "```\n",
+ "by applying:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "5da13d6b-05f1-4b3b-aecd-1ac3bb635526",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "%%bash --bg\n",
+ "#Cannot use variables from python script here so it is all hard-coded\n",
+ "\n",
+ "source activate /work/bm0021/conda-envs/cloudify\n",
+ "python xpublish_example.py \\\n",
+ " example \\\n",
+ " /work/ik1017/CMIP6/data/CMIP6/ScenarioMIP/DKRZ/MPI-ESM1-2-HR/ssp370/r1i1p1f1/Amon/tas/gn/v20190710/*.nc"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "634d1952-43a9-40a7-b7c3-9bbff5f07081",
+ "metadata": {
+ "tags": []
+ },
+ "source": [
+ "### Stop a running app\n",
+ "\n",
+ "Let us try to just run **one** app at the time. Otherwise, we would have multiple ports and dask clusters. It wouldnt end up well.\n",
+ "\n",
+ "You can check for the main *cloudify* processes by finding the dask workers. In a next step, you can *kill* by ID."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "9a43c4ce-be08-4493-8dd5-a3789f8c0647",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "k204210 1101280 1100112 0 07:33 ? 00:00:02 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-99eb3193-dfc0-45c3-9953-a1f29fb0888d.json\n",
+ "k204210 1101285 1100112 0 07:33 ? 00:00:02 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-0ac5cfbe-7cc6-4136-870a-cbac9aa18a7b.json\n",
+ "k204210 1101286 1100112 0 07:33 ? 00:00:30 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-947ea9d3-56f0-426e-9af8-8a5be0180793.json\n",
+ "k204210 1102668 1100112 0 09:10 ? 00:00:21 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-f59a40b2-6d4d-41dd-b768-7ee9040e362a.json\n",
+ "k204210 1109706 1100112 2 10:42 ? 00:00:00 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-edc24184-27e4-4966-beb3-6f926e2d6cf0.json\n",
+ "k204210 1109900 1109706 10 10:43 pts/3 00:00:00 /bin/bash -c ps -ef | grep cloudify\n",
+ "k204210 1109902 1109741 0 10:43 ? 00:00:00 /work/bm0021/conda-envs/cloudify/bin/python -c from multiprocessing.resource_tracker import main;main(26)\n",
+ "k204210 1109905 1109741 0 10:43 ? 00:00:00 /work/bm0021/conda-envs/cloudify/bin/python -c from multiprocessing.spawn import spawn_main; spawn_main(tracker_fd=27, pipe_handle=39) --multiprocessing-fork\n",
+ "k204210 1109907 1109741 0 10:43 ? 00:00:00 /work/bm0021/conda-envs/cloudify/bin/python -c from multiprocessing.spawn import spawn_main; spawn_main(tracker_fd=27, pipe_handle=39) --multiprocessing-fork\n",
+ "k204210 1109910 1109900 0 10:43 pts/3 00:00:00 grep cloudify\n"
+ ]
+ }
+ ],
+ "source": [
+ "!ps -ef | grep cloudify"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5b505b0a-2b48-4eb3-8c91-fb6b7fcdc54b",
+ "metadata": {
+ "tags": []
+ },
+ "source": [
+ "**Important note:**\n",
+ "\n",
+ "If you plan to continue with another notebook, do not stop the app now."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "af33c134-f4ba-42f7-9687-7bb9948d5dfe",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "!kill 813325"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "feacaed0-df8d-4e52-af8c-acd094cac6f4",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "cloudify",
+ "language": "python",
+ "name": "cloudify"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.0"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/workshop/2_data-access.ipynb b/workshop/2_data-access.ipynb
new file mode 100644
index 0000000..c9f6054
--- /dev/null
+++ b/workshop/2_data-access.ipynb
@@ -0,0 +1,3292 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "8e797fa6-8621-46c7-9dce-5b79adf714e3",
+ "metadata": {},
+ "source": [
+ "## 2.Data access\n",
+ "\n",
+ "**Requirement:** First run #1\n",
+ "\n",
+ "**Note**\n",
+ "\n",
+ "On levante, one would not want to open data with xarray through xpublish because we can just do the same *open* command *without* xpublish. Cdo would be an exception (see cdo).\n",
+ "\n",
+ "However, to run this notebook at one place, we use the node where you work on as the host. You can get the host url with the hostname of the respective levante node and the port that you used for the app. Accessing data through *eerie.cloud* works the same, just replace the `hosturl` with 'https://eerie.cloud.dkrz.de'."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "bd1abfca-5f10-4dfc-a71f-90f0257d10d1",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "https://l40348.lvt.dkrz.de:9000\n"
+ ]
+ }
+ ],
+ "source": [
+ "port=9000\n",
+ "hostname=!echo $HOSTNAME\n",
+ "hosturl=\"https://\"+hostname[0]+\":\"+str(port)\n",
+ "print(hosturl)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "84951ac0-8e70-4917-892a-01b236f7c0ba",
+ "metadata": {},
+ "source": [
+ "We have to tell the python programs to do not verify ssl certificates for our purposes:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "e3befb5e-99ec-4bda-aa47-303641a66320",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "storage_options=dict(verify_ssl=False)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "093ceaf2-1bda-40c7-9df5-7cbe8cf9dc66",
+ "metadata": {},
+ "source": [
+ "### Xarray"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "878d421a-c4a4-4999-9f7e-e101d6b58082",
+ "metadata": {},
+ "source": [
+ "Our example dataset is available via its name and the following `zarr_url`:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "73527b45-950c-4546-9a7e-5f1877cff132",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "https://l40348.lvt.dkrz.de:9000/datasets/example/zarr\n"
+ ]
+ }
+ ],
+ "source": [
+ "dsname=\"example\"\n",
+ "zarr_url='/'.join([hosturl,\"datasets\",dsname,\"zarr\"])\n",
+ "print(zarr_url)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "482f8b5c-0186-494f-91b0-e5a03c370004",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "import xarray as xr\n",
+ "ds=xr.open_zarr(\n",
+ " zarr_url,\n",
+ " consolidated=True,\n",
+ " storage_options=storage_options\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2887ced5-7341-49e0-b0f0-511d68f55c74",
+ "metadata": {},
+ "source": [
+ "### Intake\n",
+ "\n",
+ "**All** datasets available through the app are collected in an intake catalog:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "5fb665bb-fdd1-47be-81ce-51d71506533c",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "https://l40348.lvt.dkrz.de:9000/intake.yaml\n"
+ ]
+ }
+ ],
+ "source": [
+ "intake_url='/'.join([hosturl,\"intake.yaml\"])\n",
+ "print(intake_url)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "54d805e3-6e73-46bd-838e-b8d61ecec2d6",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['example']"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import intake\n",
+ "cat=intake.open_catalog(\n",
+ " intake_url,\n",
+ " storage_options=storage_options\n",
+ ")\n",
+ "list(cat)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "62eb5ed4-9635-4e0d-822d-38ca5aad386f",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/work/bm0021/conda-envs/cloudify/lib/python3.11/site-packages/intake_xarray/base.py:21: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
+ " 'dims': dict(self._ds.dims),\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
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+ "\n",
+ ":root {\n",
+ " --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
+ " --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
+ " --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
+ " --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
+ " --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
+ " --xr-background-color: var(--jp-layout-color0, white);\n",
+ " --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
+ " --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
+ "}\n",
+ "\n",
+ "html[theme=dark],\n",
+ "html[data-theme=dark],\n",
+ "body[data-theme=dark],\n",
+ "body.vscode-dark {\n",
+ " --xr-font-color0: rgba(255, 255, 255, 1);\n",
+ " --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
+ " --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
+ " --xr-border-color: #1F1F1F;\n",
+ " --xr-disabled-color: #515151;\n",
+ " --xr-background-color: #111111;\n",
+ " --xr-background-color-row-even: #111111;\n",
+ " --xr-background-color-row-odd: #313131;\n",
+ "}\n",
+ "\n",
+ ".xr-wrap {\n",
+ " display: block !important;\n",
+ " min-width: 300px;\n",
+ " max-width: 700px;\n",
+ "}\n",
+ "\n",
+ ".xr-text-repr-fallback {\n",
+ " /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ ".xr-header {\n",
+ " padding-top: 6px;\n",
+ " padding-bottom: 6px;\n",
+ " margin-bottom: 4px;\n",
+ " border-bottom: solid 1px var(--xr-border-color);\n",
+ "}\n",
+ "\n",
+ ".xr-header > div,\n",
+ ".xr-header > ul {\n",
+ " display: inline;\n",
+ " margin-top: 0;\n",
+ " margin-bottom: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-obj-type,\n",
+ ".xr-array-name {\n",
+ " margin-left: 2px;\n",
+ " margin-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-obj-type {\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-sections {\n",
+ " padding-left: 0 !important;\n",
+ " display: grid;\n",
+ " grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+ "}\n",
+ "\n",
+ ".xr-section-item {\n",
+ " display: contents;\n",
+ "}\n",
+ "\n",
+ ".xr-section-item input {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ ".xr-section-item input + label {\n",
+ " color: var(--xr-disabled-color);\n",
+ "}\n",
+ "\n",
+ ".xr-section-item input:enabled + label {\n",
+ " cursor: pointer;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-section-item input:enabled + label:hover {\n",
+ " color: var(--xr-font-color0);\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary {\n",
+ " grid-column: 1;\n",
+ " color: var(--xr-font-color2);\n",
+ " font-weight: 500;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary > span {\n",
+ " display: inline-block;\n",
+ " padding-left: 0.5em;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:disabled + label {\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in + label:before {\n",
+ " display: inline-block;\n",
+ " content: 'â–º';\n",
+ " font-size: 11px;\n",
+ " width: 15px;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:disabled + label:before {\n",
+ " color: var(--xr-disabled-color);\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:checked + label:before {\n",
+ " content: 'â–¼';\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:checked + label > span {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary,\n",
+ ".xr-section-inline-details {\n",
+ " padding-top: 4px;\n",
+ " padding-bottom: 4px;\n",
+ "}\n",
+ "\n",
+ ".xr-section-inline-details {\n",
+ " grid-column: 2 / -1;\n",
+ "}\n",
+ "\n",
+ ".xr-section-details {\n",
+ " display: none;\n",
+ " grid-column: 1 / -1;\n",
+ " margin-bottom: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+ " display: contents;\n",
+ "}\n",
+ "\n",
+ ".xr-array-wrap {\n",
+ " grid-column: 1 / -1;\n",
+ " display: grid;\n",
+ " grid-template-columns: 20px auto;\n",
+ "}\n",
+ "\n",
+ ".xr-array-wrap > label {\n",
+ " grid-column: 1;\n",
+ " vertical-align: top;\n",
+ "}\n",
+ "\n",
+ ".xr-preview {\n",
+ " color: var(--xr-font-color3);\n",
+ "}\n",
+ "\n",
+ ".xr-array-preview,\n",
+ ".xr-array-data {\n",
+ " padding: 0 5px !important;\n",
+ " grid-column: 2;\n",
+ "}\n",
+ "\n",
+ ".xr-array-data,\n",
+ ".xr-array-in:checked ~ .xr-array-preview {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ ".xr-array-in:checked ~ .xr-array-data,\n",
+ ".xr-array-preview {\n",
+ " display: inline-block;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list {\n",
+ " display: inline-block !important;\n",
+ " list-style: none;\n",
+ " padding: 0 !important;\n",
+ " margin: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list li {\n",
+ " display: inline-block;\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list:before {\n",
+ " content: '(';\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list:after {\n",
+ " content: ')';\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list li:not(:last-child):after {\n",
+ " content: ',';\n",
+ " padding-right: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-has-index {\n",
+ " font-weight: bold;\n",
+ "}\n",
+ "\n",
+ ".xr-var-list,\n",
+ ".xr-var-item {\n",
+ " display: contents;\n",
+ "}\n",
+ "\n",
+ ".xr-var-item > div,\n",
+ ".xr-var-item label,\n",
+ ".xr-var-item > .xr-var-name span {\n",
+ " background-color: var(--xr-background-color-row-even);\n",
+ " margin-bottom: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-var-item > .xr-var-name:hover span {\n",
+ " padding-right: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-var-list > li:nth-child(odd) > div,\n",
+ ".xr-var-list > li:nth-child(odd) > label,\n",
+ ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+ " background-color: var(--xr-background-color-row-odd);\n",
+ "}\n",
+ "\n",
+ ".xr-var-name {\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-var-dims {\n",
+ " grid-column: 2;\n",
+ "}\n",
+ "\n",
+ ".xr-var-dtype {\n",
+ " grid-column: 3;\n",
+ " text-align: right;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-var-preview {\n",
+ " grid-column: 4;\n",
+ "}\n",
+ "\n",
+ ".xr-index-preview {\n",
+ " grid-column: 2 / 5;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-var-name,\n",
+ ".xr-var-dims,\n",
+ ".xr-var-dtype,\n",
+ ".xr-preview,\n",
+ ".xr-attrs dt {\n",
+ " white-space: nowrap;\n",
+ " overflow: hidden;\n",
+ " text-overflow: ellipsis;\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name:hover,\n",
+ ".xr-var-dims:hover,\n",
+ ".xr-var-dtype:hover,\n",
+ ".xr-attrs dt:hover {\n",
+ " overflow: visible;\n",
+ " width: auto;\n",
+ " z-index: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-var-attrs,\n",
+ ".xr-var-data,\n",
+ ".xr-index-data {\n",
+ " display: none;\n",
+ " background-color: var(--xr-background-color) !important;\n",
+ " padding-bottom: 5px !important;\n",
+ "}\n",
+ "\n",
+ ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+ ".xr-var-data-in:checked ~ .xr-var-data,\n",
+ ".xr-index-data-in:checked ~ .xr-index-data {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ ".xr-var-data > table {\n",
+ " float: right;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name span,\n",
+ ".xr-var-data,\n",
+ ".xr-index-name div,\n",
+ ".xr-index-data,\n",
+ ".xr-attrs {\n",
+ " padding-left: 25px !important;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs,\n",
+ ".xr-var-attrs,\n",
+ ".xr-var-data,\n",
+ ".xr-index-data {\n",
+ " grid-column: 1 / -1;\n",
+ "}\n",
+ "\n",
+ "dl.xr-attrs {\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ " display: grid;\n",
+ " grid-template-columns: 125px auto;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt,\n",
+ ".xr-attrs dd {\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ " float: left;\n",
+ " padding-right: 10px;\n",
+ " width: auto;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt {\n",
+ " font-weight: normal;\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt:hover span {\n",
+ " display: inline-block;\n",
+ " background: var(--xr-background-color);\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dd {\n",
+ " grid-column: 2;\n",
+ " white-space: pre-wrap;\n",
+ " word-break: break-all;\n",
+ "}\n",
+ "\n",
+ ".xr-icon-database,\n",
+ ".xr-icon-file-text2,\n",
+ ".xr-no-icon {\n",
+ " display: inline-block;\n",
+ " vertical-align: middle;\n",
+ " width: 1em;\n",
+ " height: 1.5em !important;\n",
+ " stroke-width: 0;\n",
+ " stroke: currentColor;\n",
+ " fill: currentColor;\n",
+ "}\n",
+ "</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 314MB\n",
+ "Dimensions: (lat: 192, time: 1032, bnds: 2, lon: 384)\n",
+ "Coordinates:\n",
+ " height float64 8B ...\n",
+ " * lat (lat) float64 2kB -89.28 -88.36 -87.42 ... 87.42 88.36 89.28\n",
+ " * lon (lon) float64 3kB 0.0 0.9375 1.875 2.812 ... 357.2 358.1 359.1\n",
+ " * time (time) datetime64[ns] 8kB 2015-01-16T12:00:00 ... 2100-12-16T1...\n",
+ "Dimensions without coordinates: bnds\n",
+ "Data variables:\n",
+ " lat_bnds (time, lat, bnds) float64 3MB dask.array<chunksize=(60, 192, 2), meta=np.ndarray>\n",
+ " lon_bnds (time, lon, bnds) float64 6MB dask.array<chunksize=(60, 384, 2), meta=np.ndarray>\n",
+ " tas (time, lat, lon) float32 304MB dask.array<chunksize=(1, 192, 384), meta=np.ndarray>\n",
+ " time_bnds (time, bnds) datetime64[ns] 17kB dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
+ "Attributes: (12/47)\n",
+ " Conventions: CF-1.7 CMIP-6.2\n",
+ " activity_id: ScenarioMIP AerChemMIP\n",
+ " branch_method: standard\n",
+ " branch_time_in_child: 60265.0\n",
+ " branch_time_in_parent: 60265.0\n",
+ " contact: cmip6-mpi-esm@dkrz.de\n",
+ " ... ...\n",
+ " title: MPI-ESM1-2-HR output prepared for CMIP6\n",
+ " variable_id: tas\n",
+ " variant_label: r1i1p1f1\n",
+ " license: CMIP6 model data produced by DKRZ is licensed und...\n",
+ " cmor_version: 3.4.0\n",
+ " tracking_id: hdl:21.14100/d6f0f6b2-b4c2-460b-bc5e-f1c72f932399</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f0abbb17-9f5b-4b96-90a3-a6a6f212ff4e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f0abbb17-9f5b-4b96-90a3-a6a6f212ff4e' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 192</li><li><span class='xr-has-index'>time</span>: 1032</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 384</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-0a1e8a90-cae1-441f-ac6c-5f36fd64e1b8' class='xr-section-summary-in' type='checkbox' checked><label for='section-0a1e8a90-cae1-441f-ac6c-5f36fd64e1b8' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bb28c820-b523-4bc1-b7df-b95dc82a5a86' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb28c820-b523-4bc1-b7df-b95dc82a5a86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-842683b3-bcd6-40e5-b203-f35e34c949dd' class='xr-var-data-in' type='checkbox'><label for='data-842683b3-bcd6-40e5-b203-f35e34c949dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.28 -88.36 ... 88.36 89.28</div><input id='attrs-c976f1c5-8506-4cff-bb43-7477bc30a929' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c976f1c5-8506-4cff-bb43-7477bc30a929' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3c66e88-1dfb-4ad4-b7a0-e3df20f21064' class='xr-var-data-in' type='checkbox'><label for='data-a3c66e88-1dfb-4ad4-b7a0-e3df20f21064' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.284228, -88.357004, -87.424304, -86.490367, -85.55596 , -84.621327,\n",
+ " -83.686567, -82.751728, -81.816839, -80.881913, -79.946962, -79.011992,\n",
+ " -78.077007, -77.142011, -76.207005, -75.271992, -74.336973, -73.401949,\n",
+ " -72.466921, -71.531889, -70.596854, -69.661816, -68.726776, -67.791734,\n",
+ " -66.856691, -65.921645, -64.986599, -64.051551, -63.116502, -62.181452,\n",
+ " -61.246401, -60.311349, -59.376297, -58.441244, -57.50619 , -56.571136,\n",
+ " -55.636081, -54.701026, -53.76597 , -52.830914, -51.895857, -50.960801,\n",
+ " -50.025743, -49.090686, -48.155628, -47.22057 , -46.285512, -45.350454,\n",
+ " -44.415395, -43.480336, -42.545277, -41.610218, -40.675159, -39.740099,\n",
+ " -38.805039, -37.86998 , -36.93492 , -35.99986 , -35.064799, -34.129739,\n",
+ " -33.194679, -32.259618, -31.324558, -30.389497, -29.454436, -28.519375,\n",
+ " -27.584315, -26.649254, -25.714193, -24.779132, -23.84407 , -22.909009,\n",
+ " -21.973948, -21.038887, -20.103825, -19.168764, -18.233703, -17.298641,\n",
+ " -16.36358 , -15.428518, -14.493457, -13.558395, -12.623333, -11.688272,\n",
+ " -10.75321 , -9.818148, -8.883087, -7.948025, -7.012963, -6.077901,\n",
+ " -5.14284 , -4.207778, -3.272716, -2.337654, -1.402593, -0.467531,\n",
+ " 0.467531, 1.402593, 2.337654, 3.272716, 4.207778, 5.14284 ,\n",
+ " 6.077901, 7.012963, 7.948025, 8.883087, 9.818148, 10.75321 ,\n",
+ " 11.688272, 12.623333, 13.558395, 14.493457, 15.428518, 16.36358 ,\n",
+ " 17.298641, 18.233703, 19.168764, 20.103825, 21.038887, 21.973948,\n",
+ " 22.909009, 23.84407 , 24.779132, 25.714193, 26.649254, 27.584315,\n",
+ " 28.519375, 29.454436, 30.389497, 31.324558, 32.259618, 33.194679,\n",
+ " 34.129739, 35.064799, 35.99986 , 36.93492 , 37.86998 , 38.805039,\n",
+ " 39.740099, 40.675159, 41.610218, 42.545277, 43.480336, 44.415395,\n",
+ " 45.350454, 46.285512, 47.22057 , 48.155628, 49.090686, 50.025743,\n",
+ " 50.960801, 51.895857, 52.830914, 53.76597 , 54.701026, 55.636081,\n",
+ " 56.571136, 57.50619 , 58.441244, 59.376297, 60.311349, 61.246401,\n",
+ " 62.181452, 63.116502, 64.051551, 64.986599, 65.921645, 66.856691,\n",
+ " 67.791734, 68.726776, 69.661816, 70.596854, 71.531889, 72.466921,\n",
+ " 73.401949, 74.336973, 75.271992, 76.207005, 77.142011, 78.077007,\n",
+ " 79.011992, 79.946962, 80.881913, 81.816839, 82.751728, 83.686567,\n",
+ " 84.621327, 85.55596 , 86.490367, 87.424304, 88.357004, 89.284228])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.9375 1.875 ... 358.1 359.1</div><input id='attrs-31b0e98e-137b-4983-a447-e7433da277a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31b0e98e-137b-4983-a447-e7433da277a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60a3e67f-10cf-46c7-a165-3accf9ce5aa3' class='xr-var-data-in' type='checkbox'><label for='data-60a3e67f-10cf-46c7-a165-3accf9ce5aa3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0. , 0.9375, 1.875 , ..., 357.1875, 358.125 , 359.0625])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2015-01-16T12:00:00 ... 2100-12-...</div><input id='attrs-0e4321e8-ff4a-442f-9ccb-d7136f611c8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e4321e8-ff4a-442f-9ccb-d7136f611c8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e61a662f-e0e5-4141-b243-d432627f4e58' class='xr-var-data-in' type='checkbox'><label for='data-e61a662f-e0e5-4141-b243-d432627f4e58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(['2015-01-16T12:00:00.000000000', '2015-02-15T00:00:00.000000000',\n",
+ " '2015-03-16T12:00:00.000000000', ..., '2100-10-16T12:00:00.000000000',\n",
+ " '2100-11-16T00:00:00.000000000', '2100-12-16T12:00:00.000000000'],\n",
+ " dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-87b655dd-b1af-4db3-b2cc-7f1929ca4388' class='xr-section-summary-in' type='checkbox' checked><label for='section-87b655dd-b1af-4db3-b2cc-7f1929ca4388' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(time, lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(60, 192, 2), meta=np.ndarray></div><input id='attrs-874f0904-839a-475e-a33e-e87c46f126a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-874f0904-839a-475e-a33e-e87c46f126a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c490da1a-4291-49a8-aa73-2a95390ed5d3' class='xr-var-data-in' type='checkbox'><label for='data-c490da1a-4291-49a8-aa73-2a95390ed5d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 3.02 MiB </td>\n",
+ " <td> 180.00 kiB </td>\n",
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+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1032, 192, 2) </td>\n",
+ " <td> (60, 192, 2) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 18 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(time, lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(60, 384, 2), meta=np.ndarray></div><input id='attrs-21eac356-7db1-48d3-9dc9-83b838f87dbd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-21eac356-7db1-48d3-9dc9-83b838f87dbd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b76b943-e9dd-468b-891c-71f6702c50e3' class='xr-var-data-in' type='checkbox'><label for='data-8b76b943-e9dd-468b-891c-71f6702c50e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
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+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
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+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 6.05 MiB </td>\n",
+ " <td> 360.00 kiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1032, 384, 2) </td>\n",
+ " <td> (60, 384, 2) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 18 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 192, 384), meta=np.ndarray></div><input id='attrs-54c2deb8-280f-44fd-88ab-09238684ba63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54c2deb8-280f-44fd-88ab-09238684ba63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fabc2b4e-ef6b-423b-87c0-6a9f2c963f64' class='xr-var-data-in' type='checkbox'><label for='data-fabc2b4e-ef6b-423b-87c0-6a9f2c963f64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2019-07-20T13:41:51Z altered by CMOR: Treated scalar dimension: 'height'. 2019-07-20T13:41:51Z altered by CMOR: replaced missing value flag (-9e+33) with standard missing value (1e+20). 2019-07-20T13:41:51Z altered by CMOR: Converted type from 'd' to 'f'. 2019-07-20T13:41:52Z altered by CMOR: Inverted axis: lat.</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 290.25 MiB </td>\n",
+ " <td> 288.00 kiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1032, 192, 384) </td>\n",
+ " <td> (1, 192, 384) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 1032 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
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+ "</svg>\n",
+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 2), meta=np.ndarray></div><input id='attrs-0ffdca79-16a7-415d-b8a7-1977eb0a151f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0ffdca79-16a7-415d-b8a7-1977eb0a151f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d2791d7-5322-44fd-858f-d912e4a692a7' class='xr-var-data-in' type='checkbox'><label for='data-5d2791d7-5322-44fd-858f-d912e4a692a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 16.12 kiB </td>\n",
+ " <td> 16 B </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1032, 2) </td>\n",
+ " <td> (1, 2) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 1032 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
+ " <td>\n",
+ " <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+ "\n",
+ " <!-- Horizontal lines -->\n",
+ " <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+ "\n",
+ " <!-- Vertical lines -->\n",
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+ "\n",
+ " <!-- Colored Rectangle -->\n",
+ " <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+ "\n",
+ " <!-- Text -->\n",
+ " <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+ " <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1032</text>\n",
+ "</svg>\n",
+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-752d0000-8648-44b9-a4de-a0611796f4a0' class='xr-section-summary-in' type='checkbox' ><label for='section-752d0000-8648-44b9-a4de-a0611796f4a0' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d0e8bdbd-dc68-4233-9380-62cedfc9e541' class='xr-index-data-in' type='checkbox'/><label for='index-d0e8bdbd-dc68-4233-9380-62cedfc9e541' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.28422753251364, -88.35700351866494, -87.42430374606988,\n",
+ " -86.49036676628116, -85.55596048489265, -84.6213271076488,\n",
+ " -83.68656681656385, -82.75172847343066, -81.81683872860319,\n",
+ " -80.8819133467975,\n",
+ " ...\n",
+ " 80.8819133467975, 81.81683872860319, 82.75172847343066,\n",
+ " 83.68656681656385, 84.6213271076488, 85.55596048489265,\n",
+ " 86.49036676628116, 87.42430374606988, 88.35700351866494,\n",
+ " 89.28422753251364],\n",
+ " dtype='float64', name='lat', length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6e327aba-4058-4dd2-b1ec-148788cf01b2' class='xr-index-data-in' type='checkbox'/><label for='index-6e327aba-4058-4dd2-b1ec-148788cf01b2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.0, 0.9375, 1.875, 2.8125, 3.75, 4.6875, 5.625,\n",
+ " 6.5625, 7.5, 8.4375,\n",
+ " ...\n",
+ " 350.625, 351.5625, 352.5, 353.4375, 354.375, 355.3125, 356.25,\n",
+ " 357.1875, 358.125, 359.0625],\n",
+ " dtype='float64', name='lon', length=384))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cb062a4a-ca61-465b-84bc-9952e69bc6f7' class='xr-index-data-in' type='checkbox'/><label for='index-cb062a4a-ca61-465b-84bc-9952e69bc6f7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2015-01-16 12:00:00', '2015-02-15 00:00:00',\n",
+ " '2015-03-16 12:00:00', '2015-04-16 00:00:00',\n",
+ " '2015-05-16 12:00:00', '2015-06-16 00:00:00',\n",
+ " '2015-07-16 12:00:00', '2015-08-16 12:00:00',\n",
+ " '2015-09-16 00:00:00', '2015-10-16 12:00:00',\n",
+ " ...\n",
+ " '2100-03-16 12:00:00', '2100-04-16 00:00:00',\n",
+ " '2100-05-16 12:00:00', '2100-06-16 00:00:00',\n",
+ " '2100-07-16 12:00:00', '2100-08-16 12:00:00',\n",
+ " '2100-09-16 00:00:00', '2100-10-16 12:00:00',\n",
+ " '2100-11-16 00:00:00', '2100-12-16 12:00:00'],\n",
+ " dtype='datetime64[ns]', name='time', length=1032, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-299f76e5-483d-42ac-80d9-1e2937d5835b' class='xr-section-summary-in' type='checkbox' ><label for='section-299f76e5-483d-42ac-80d9-1e2937d5835b' class='xr-section-summary' >Attributes: <span>(47)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>ScenarioMIP AerChemMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>60265.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>60265.0</dd><dt><span>contact :</span></dt><dd>cmip6-mpi-esm@dkrz.de</dd><dt><span>creation_date :</span></dt><dd>2019-07-20T13:41:51Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>gap-filling scenario reaching 7.0 based on SSP3</dd><dt><span>experiment_id :</span></dt><dd>ssp370</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.DKRZ.MPI-ESM1-2-HR.ssp370.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>gn</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2019-07-20T13:41:51Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Deutsches Klimarechenzentrum, Hamburg 20146, Germany</dd><dt><span>institution_id :</span></dt><dd>DKRZ</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>historical</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>MPI-ESM1-2-HR</dd><dt><span>parent_time_units :</span></dt><dd>days since 1850-1-1 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>project_id :</span></dt><dd>CMIP6</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>references :</span></dt><dd>MPI-ESM: Mauritsen, T. et al. (2019), Developments in the MPIâ€M Earth System Model version 1.2 (MPIâ€ESM1.2) and Its Response to Increasing CO2, J. Adv. Model. Earth Syst.,11, 998-1038, doi:10.1029/2018MS001400,\n",
+ "Mueller, W.A. et al. (2018): A highâ€resolution version of the Max Planck Institute Earth System Model MPIâ€ESM1.2â€HR. J. Adv. Model. EarthSyst.,10,1383–1413, doi:10.1029/2017MS001217</dd><dt><span>source :</span></dt><dd>MPI-ESM1.2-HR (2017): \n",
+ "aerosol: none, prescribed MACv2-SP\n",
+ "atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa)\n",
+ "atmosChem: none\n",
+ "land: JSBACH3.20\n",
+ "landIce: none/prescribed\n",
+ "ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 longitude/latitude; 40 levels; top grid cell 0-12 m)\n",
+ "ocnBgchem: HAMOCC6\n",
+ "seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model)</dd><dt><span>source_id :</span></dt><dd>MPI-ESM1-2-HR</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(09 May 2019) MD5:e6ef8ececc8f338646ebfb3aeed36bfc</dd><dt><span>title :</span></dt><dd>MPI-ESM1-2-HR output prepared for CMIP6</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by DKRZ is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.4.0</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/d6f0f6b2-b4c2-460b-bc5e-f1c72f932399</dd></dl></div></li></ul></div></div>"
+ ],
+ "text/plain": [
+ "<xarray.Dataset> Size: 314MB\n",
+ "Dimensions: (lat: 192, time: 1032, bnds: 2, lon: 384)\n",
+ "Coordinates:\n",
+ " height float64 8B ...\n",
+ " * lat (lat) float64 2kB -89.28 -88.36 -87.42 ... 87.42 88.36 89.28\n",
+ " * lon (lon) float64 3kB 0.0 0.9375 1.875 2.812 ... 357.2 358.1 359.1\n",
+ " * time (time) datetime64[ns] 8kB 2015-01-16T12:00:00 ... 2100-12-16T1...\n",
+ "Dimensions without coordinates: bnds\n",
+ "Data variables:\n",
+ " lat_bnds (time, lat, bnds) float64 3MB dask.array<chunksize=(60, 192, 2), meta=np.ndarray>\n",
+ " lon_bnds (time, lon, bnds) float64 6MB dask.array<chunksize=(60, 384, 2), meta=np.ndarray>\n",
+ " tas (time, lat, lon) float32 304MB dask.array<chunksize=(1, 192, 384), meta=np.ndarray>\n",
+ " time_bnds (time, bnds) datetime64[ns] 17kB dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
+ "Attributes: (12/47)\n",
+ " Conventions: CF-1.7 CMIP-6.2\n",
+ " activity_id: ScenarioMIP AerChemMIP\n",
+ " branch_method: standard\n",
+ " branch_time_in_child: 60265.0\n",
+ " branch_time_in_parent: 60265.0\n",
+ " contact: cmip6-mpi-esm@dkrz.de\n",
+ " ... ...\n",
+ " title: MPI-ESM1-2-HR output prepared for CMIP6\n",
+ " variable_id: tas\n",
+ " variant_label: r1i1p1f1\n",
+ " license: CMIP6 model data produced by DKRZ is licensed und...\n",
+ " cmor_version: 3.4.0\n",
+ " tracking_id: hdl:21.14100/d6f0f6b2-b4c2-460b-bc5e-f1c72f932399"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "cat[dsname](method=\"zarr\",storage_options=storage_options).to_dask()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "dd3473de-9be4-4b16-aee3-b9084cbeb1d8",
+ "metadata": {},
+ "source": [
+ "### Stac\n",
+ "\n",
+ "For each dataset, a stac item is generated with enriched metadata. The URL for this API is similar to the *zarr*-URL:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "9355a45a-2f0f-4923-967c-85afacdfcab7",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "stac_url=zarr_url.replace('/zarr','/stac')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "7d4148b1-5e49-4b0b-8450-2928e823471d",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "<style>\n",
+ ".pystac-summary {\n",
+ " cursor: pointer;\n",
+ " display: list-item;\n",
+ " list-style: revert;\n",
+ " margin-bottom: 0 !important;\n",
+ "\n",
+ " .pystac-l {\n",
+ " padding-left: 0.5em;\n",
+ " color: rgb(64, 128, 128);\n",
+ " font-style: italic;\n",
+ " }\n",
+ "}\n",
+ ".pystac-row {\n",
+ " overflow-wrap: break-word;\n",
+ " padding-left: .825em;\n",
+ "\n",
+ " .pystac-k {\n",
+ " display: inline-block;\n",
+ " margin: 0px 0.5em 0px 0px;\n",
+ " }\n",
+ " .pystac-v {\n",
+ " color: rgb(186, 33, 33);\n",
+ " }\n",
+ "}\n",
+ ".pystac-k {\n",
+ " color: rgb(0, 128, 0);\n",
+ " font-weight: 700;\n",
+ "}\n",
+ "</style>\n",
+ "<div class=\"jp-RenderedJSON jp-mod-trusted jp-OutputArea-output\">\n",
+ " <div class=\"container\" style=\"line-height: normal;\">\n",
+ " <ul style=\"padding: 0px; margin: 0px; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">type</span>\n",
+ " <span class=\"pystac-v\">\"Feature\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">stac_version</span>\n",
+ " <span class=\"pystac-v\">\"1.0.0\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">stac_extensions</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"https://stac-extensions.github.io/datacube/v2.2.0/schema.json\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">1</span>\n",
+ " <span class=\"pystac-v\">\"https://stac-extensions.github.io/alternate-assets/v1.2.0/schema.json\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">id</span>\n",
+ " <span class=\"pystac-v\">\"example\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">geometry</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">type</span>\n",
+ " <span class=\"pystac-v\">\"Polygon\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">coordinates</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span><span class=\"pystac-l\">[] 5 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">-180</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">1</span>\n",
+ " <span class=\"pystac-v\">-90</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">1</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">-180</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">1</span>\n",
+ " <span class=\"pystac-v\">90</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">2</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">180</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">1</span>\n",
+ " <span class=\"pystac-v\">90</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">3</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">180</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">1</span>\n",
+ " <span class=\"pystac-v\">-90</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">4</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">-180</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">1</span>\n",
+ " <span class=\"pystac-v\">-90</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">bbox</span><span class=\"pystac-l\">[] 4 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">0.0</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">1</span>\n",
+ " <span class=\"pystac-v\">-89.28422753251364</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">2</span>\n",
+ " <span class=\"pystac-v\">359.0625</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">3</span>\n",
+ " <span class=\"pystac-v\">89.28422753251364</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">properties</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"No description\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">title</span>\n",
+ " <span class=\"pystac-v\">\"MPI-ESM1-2-HR output prepared for CMIP6\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">created</span>\n",
+ " <span class=\"pystac-v\">\"2019-07-20T13:41:51Z\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">keywords</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"example\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">providers</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">name</span>\n",
+ " <span class=\"pystac-v\">\"DKRZ\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"The data host of eerie.cloud\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">roles</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"host\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">url</span>\n",
+ " <span class=\"pystac-v\">\"https://dkrz.de\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">1</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">name</span>\n",
+ " <span class=\"pystac-v\">\"DKRZ\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"Deutsches Klimarechenzentrum, Hamburg 20146, Germany\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">roles</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"producer\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">url</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets/example/\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">datetime</span>\n",
+ " <span class=\"pystac-v\">\"2025-01-06T17:26:10.494342Z\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">cube:dimensions</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
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+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">cube:variables</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
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+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">time_bnds</span></summary>\n",
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+ " \n",
+ " \n",
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+ " <li class=\"pystac-row\">\n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
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+ " \n",
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+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"time\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
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+ " <span class=\"pystac-v\">\"bnds\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">unit</span>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
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+ " \n",
+ " <li><details>\n",
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+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
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+ " \n",
+ " \n",
+ " \n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">lat_bnds</span></summary>\n",
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+ " \n",
+ " \n",
+ " \n",
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+ " \n",
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+ " <li><details>\n",
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+ " \n",
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+ " \n",
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+ " \n",
+ " \n",
+ " \n",
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+ " \n",
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+ " \n",
+ " <li class=\"pystac-row\">\n",
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+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
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+ " <span class=\"pystac-v\">\"bnds\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
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+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">unit</span>\n",
+ " <span class=\"pystac-v\">\"Not set\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"lat_bnds\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">attrs</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">lon_bnds</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">dimensions</span><span class=\"pystac-l\">[] 3 items</span></summary>\n",
+ " \n",
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+ " \n",
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+ " \n",
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+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
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+ " \n",
+ " <li class=\"pystac-row\">\n",
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+ " <span class=\"pystac-v\">\"lon\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
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+ " <span class=\"pystac-v\">\"bnds\"</span>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">unit</span>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"lon_bnds\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">attrs</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
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+ " \n",
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+ " \n",
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+ " \n",
+ " <li><details>\n",
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+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">type</span>\n",
+ " <span class=\"pystac-v\">\"data\"</span>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">dimensions</span><span class=\"pystac-l\">[] 3 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
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+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"time\"</span>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">1</span>\n",
+ " <span class=\"pystac-v\">\"lat\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">2</span>\n",
+ " <span class=\"pystac-v\">\"lon\"</span>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">unit</span>\n",
+ " <span class=\"pystac-v\">\"K\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"Near-Surface Air Temperature\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">attrs</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">standard_name</span>\n",
+ " <span class=\"pystac-v\">\"air_temperature\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">long_name</span>\n",
+ " <span class=\"pystac-v\">\"Near-Surface Air Temperature\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">comment</span>\n",
+ " <span class=\"pystac-v\">\"near-surface (usually, 2 meter) air temperature\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">units</span>\n",
+ " <span class=\"pystac-v\">\"K\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">cell_methods</span>\n",
+ " <span class=\"pystac-v\">\"area: time: mean\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">cell_measures</span>\n",
+ " <span class=\"pystac-v\">\"area: areacella\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">history</span>\n",
+ " <span class=\"pystac-v\">\"2019-07-20T13:41:51Z altered by CMOR: Treated scalar dimension: 'height'. 2019-07-20T13:41:51Z altered by CMOR: replaced missing value flag (-9e+33) with standard missing value (1e+20). 2019-07-20T13:41:51Z altered by CMOR: Converted type from 'd' to 'f'. 2019-07-20T13:41:52Z altered by CMOR: Inverted axis: lat.\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">Conventions</span>\n",
+ " <span class=\"pystac-v\">\"CF-1.7 CMIP-6.2\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">activity_id</span>\n",
+ " <span class=\"pystac-v\">\"ScenarioMIP AerChemMIP\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">branch_method</span>\n",
+ " <span class=\"pystac-v\">\"standard\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">contact</span>\n",
+ " <span class=\"pystac-v\">\"cmip6-mpi-esm@dkrz.de\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">creation_date</span>\n",
+ " <span class=\"pystac-v\">\"2019-07-20T13:41:51Z\"</span>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">data_specs_version</span>\n",
+ " <span class=\"pystac-v\">\"01.00.30\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">experiment</span>\n",
+ " <span class=\"pystac-v\">\"gap-filling scenario reaching 7.0 based on SSP3\"</span>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">experiment_id</span>\n",
+ " <span class=\"pystac-v\">\"ssp370\"</span>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">external_variables</span>\n",
+ " <span class=\"pystac-v\">\"areacella\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">forcing_index</span>\n",
+ " <span class=\"pystac-v\">\"1\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">frequency</span>\n",
+ " <span class=\"pystac-v\">\"mon\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">further_info_url</span>\n",
+ " <span class=\"pystac-v\">\"https://furtherinfo.es-doc.org/CMIP6.DKRZ.MPI-ESM1-2-HR.ssp370.none.r1i1p1f1\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">grid</span>\n",
+ " <span class=\"pystac-v\">\"gn\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">grid_label</span>\n",
+ " <span class=\"pystac-v\">\"gn\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">history</span>\n",
+ " <span class=\"pystac-v\">\"2019-07-20T13:41:51Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">initialization_index</span>\n",
+ " <span class=\"pystac-v\">\"1\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">institution</span>\n",
+ " <span class=\"pystac-v\">\"Deutsches Klimarechenzentrum, Hamburg 20146, Germany\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">institution_id</span>\n",
+ " <span class=\"pystac-v\">\"DKRZ\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">mip_era</span>\n",
+ " <span class=\"pystac-v\">\"CMIP6\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">nominal_resolution</span>\n",
+ " <span class=\"pystac-v\">\"100 km\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">parent_activity_id</span>\n",
+ " <span class=\"pystac-v\">\"CMIP\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">parent_experiment_id</span>\n",
+ " <span class=\"pystac-v\">\"historical\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">parent_mip_era</span>\n",
+ " <span class=\"pystac-v\">\"CMIP6\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">parent_source_id</span>\n",
+ " <span class=\"pystac-v\">\"MPI-ESM1-2-HR\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">parent_variant_label</span>\n",
+ " <span class=\"pystac-v\">\"r1i1p1f1\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">physics_index</span>\n",
+ " <span class=\"pystac-v\">\"1\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">product</span>\n",
+ " <span class=\"pystac-v\">\"model-output\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">project_id</span>\n",
+ " <span class=\"pystac-v\">\"CMIP6\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">realization_index</span>\n",
+ " <span class=\"pystac-v\">\"1\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">realm</span>\n",
+ " <span class=\"pystac-v\">\"atmos\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">references</span>\n",
+ " <span class=\"pystac-v\">\"MPI-ESM: Mauritsen, T. et al. (2019), Developments in the MPIâ€M Earth System Model version 1.2 (MPIâ€ESM1.2) and Its Response to Increasing CO2, J. Adv. Model. Earth Syst.,11, 998-1038, doi:10.1029/2018MS001400,\n",
+ "Mueller, W.A. et al. (2018): A highâ€resolution version of the Max Planck Institute Earth System Model MPIâ€ESM1.2â€HR. J. Adv. Model. EarthSyst.,10,1383–1413, doi:10.1029/2017MS001217\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">source</span>\n",
+ " <span class=\"pystac-v\">\"MPI-ESM1.2-HR (2017): \n",
+ "aerosol: none, prescribed MACv2-SP\n",
+ "atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa)\n",
+ "atmosChem: none\n",
+ "land: JSBACH3.20\n",
+ "landIce: none/prescribed\n",
+ "ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 longitude/latitude; 40 levels; top grid cell 0-12 m)\n",
+ "ocnBgchem: HAMOCC6\n",
+ "seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model)\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">source_id</span>\n",
+ " <span class=\"pystac-v\">\"MPI-ESM1-2-HR\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">source_type</span>\n",
+ " <span class=\"pystac-v\">\"AOGCM\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">sub_experiment</span>\n",
+ " <span class=\"pystac-v\">\"none\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">sub_experiment_id</span>\n",
+ " <span class=\"pystac-v\">\"none\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">table_id</span>\n",
+ " <span class=\"pystac-v\">\"Amon\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">table_info</span>\n",
+ " <span class=\"pystac-v\">\"Creation Date:(09 May 2019) MD5:e6ef8ececc8f338646ebfb3aeed36bfc\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">variable_id</span>\n",
+ " <span class=\"pystac-v\">\"tas\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">variant_label</span>\n",
+ " <span class=\"pystac-v\">\"r1i1p1f1\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">license</span>\n",
+ " <span class=\"pystac-v\">\"CMIP6 model data produced by DKRZ is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">cmor_version</span>\n",
+ " <span class=\"pystac-v\">\"3.4.0\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">tracking_id</span>\n",
+ " <span class=\"pystac-v\">\"hdl:21.14100/d6f0f6b2-b4c2-460b-bc5e-f1c72f932399\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">_xpublish_id</span>\n",
+ " <span class=\"pystac-v\">\"example\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">links</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">rel</span>\n",
+ " <span class=\"pystac-v\">\"DOC\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">href</span>\n",
+ " <span class=\"pystac-v\">\"https://easy.gems.dkrz.de/simulations/EERIE/eerie_data-access_online.html\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">title</span>\n",
+ " <span class=\"pystac-v\">\"Usage of the eerie.cloud\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">assets</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">data</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">href</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets/example/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">type</span>\n",
+ " <span class=\"pystac-v\">\"application/vnd+zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">title</span>\n",
+ " <span class=\"pystac-v\">\"Data\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"Accessed binary data is processed on server-side\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">Volume</span>\n",
+ " <span class=\"pystac-v\">\"0 GB uncompressed\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">No of data variables</span>\n",
+ " <span class=\"pystac-v\">\"4\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">roles</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"data\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">xarray_view</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">href</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets/example/\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">type</span>\n",
+ " <span class=\"pystac-v\">\"text/html\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">title</span>\n",
+ " <span class=\"pystac-v\">\"Xarray dataset\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"HTML representation of the xarray dataset\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">roles</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"overview\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">default_var</span>\n",
+ " <span class=\"pystac-v\">\"time_bnds\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">name</span>\n",
+ " <span class=\"pystac-v\">\"MPI-ESM1-2-HR output prepared for CMIP6\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">levels</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">name</span>\n",
+ " <span class=\"pystac-v\">\"example\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">time</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"example/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">grid</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"example/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">datasources</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">time_bnds</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"example/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">lat_bnds</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"example/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">lon_bnds</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"example/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">tas</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"example/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </div>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ "<Item id=example>"
+ ]
+ },
+ "execution_count": 9,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import pystac\n",
+ "import fsspec\n",
+ "import json\n",
+ "stacitem=pystac.item.Item.from_dict(\n",
+ " json.load(fsspec.open(stac_url,**storage_options).open())\n",
+ ")\n",
+ "stacitem"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "9f7edcd1-a4ba-40e1-ae6c-2c120e8ffcdb",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{'data': <Asset href=https://eerie.cloud.dkrz.de/datasets/example/zarr>,\n",
+ " 'xarray_view': <Asset href=https://eerie.cloud.dkrz.de/datasets/example/>}"
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "stacitem.assets"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "69012881-c3a6-48d4-9bb2-faffcf4556a3",
+ "metadata": {},
+ "source": [
+ "The stac API is right now hard-coded for 'eerie.cloud'. In theory, we could get to the data with xarray and the *href* asset."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a57ceea2-af50-4c2f-a44b-dbfca9f5c495",
+ "metadata": {},
+ "source": [
+ "### cdo\n",
+ "\n",
+ "We are developing a cdo version that can read cloudified data with netcdf-zarr via http. The built netcdf is a testversion that prints some profiling warnings and hdf errors that often can be ignored. In 01/2025, it lacks port parsing which is why we cannot use it on internal apps on levante. Until this is solved, we can see how it works with the eerie.cloud:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "feacaed0-df8d-4e52-af8c-acd094cac6f4",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\u001b[0;1m File format\u001b[0m : NCZarr filter\n",
+ "\u001b[0;1m -1 : Institut Source T Steptype Levels Num Points Num Dtype : Parameter ID\u001b[0m\n",
+ " 1 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -1 \n",
+ " 2 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -2 \n",
+ " 3 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -3 \n",
+ " 4 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -4 \n",
+ " 5 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -5 \n",
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+ " 7 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -7 \n",
+ " 8 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -8 \n",
+ " 9 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -9 \n",
+ " 10 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -10 \n",
+ " 11 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -11 \n",
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+ " 13 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -13 \n",
+ " 14 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -14 \n",
+ " 15 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -15 \n",
+ " 16 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -16 \n",
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+ " 18 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -18 \n",
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+ " 20 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -20 \n",
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+ " 22 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -22 \n",
+ " 23 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -23 \n",
+ " 24 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -24 \n",
+ " 25 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -25 \n",
+ " 26 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -26 \n",
+ " 27 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -27 \n",
+ " 28 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -28 \n",
+ " 29 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -29 \n",
+ " 30 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -30 \n",
+ " 31 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -31 \n",
+ " 32 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -32 \n",
+ " 33 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -33 \n",
+ " 34 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -34 \n",
+ " 35 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -35 \n",
+ " 36 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -36 \n",
+ " 37 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -37 \n",
+ " 38 : \u001b[34munknown ECMWF v instant \u001b[0m\u001b[32m 1 \u001b[0m 1 \u001b[32m 542080 \u001b[0m 1 \u001b[34m F64f \u001b[0m: -38 \n",
+ "\u001b[0;1m Grid coordinates\u001b[0m :\n",
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+ " 2023-12-31 20:00:00 2023-12-31 21:00:00 2023-12-31 22:00:00 2023-12-31 23:00:00\u001b[0m\n",
+ "\u001b[32mcdo sinfo: \u001b[0mProcessed 38 variables over 736344 timesteps [4.73s 3539MB]\n",
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+ ]
+ }
+ ],
+ "source": [
+ "cdo=\"/work/bm0021/cdo_incl_cmor/cdo-test_cmortest_gcc/bin/cdo\"\n",
+ "hosturl=\"https://eerie.cloud.dkrz.de\"\n",
+ "dsname=\"era5-dkrz.surface_analysis_hourly\"\n",
+ "#\n",
+ "zarr_url='/'.join([hosturl,\"datasets\",dsname,\"zarr\"])\n",
+ "zarr_prefix=\"\\#mode\\=zarr,s3,consolidated\"\n",
+ "infile=zarr_url+zarr_prefix\n",
+ "#\n",
+ "!{cdo} sinfo {infile}"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0fd1454b-b694-44df-b871-463cf77929b8",
+ "metadata": {},
+ "source": [
+ "When working with cdo on cloudified data, we have to select data with the **select** operator:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "649c9d80-45d2-4349-bb7d-605c666e917f",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\u001b[32mcdo(1) select: \u001b[0mProcess started\n",
+ "\u001b[0;1m -1 : Date Time Level Gridsize Miss : Minimum Mean Maximum : Parameter ID\n",
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+ "\u001b[32mcdo info: \u001b[0mProcessed 542080 values from 1 variable over 1 timestep [7.16s 3675MB]\n",
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+ "id": "13c929e7-fda2-4d71-a07f-6f5ed9043ec4",
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+}
diff --git a/workshop/3_use-cases-and-preparations.ipynb b/workshop/3_use-cases-and-preparations.ipynb
new file mode 100644
index 0000000..8a96cc3
--- /dev/null
+++ b/workshop/3_use-cases-and-preparations.ipynb
@@ -0,0 +1,1995 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "829dfcb4-afa3-4cd4-aed1-6ba58ccc6d11",
+ "metadata": {},
+ "source": [
+ "## 3. Use-cases and preparations for the petabyte scale\n",
+ "\n",
+ "**Requirement:** First run #1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "8ba97b5f-f16b-41f3-8b9d-daea07e31c5d",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "#From #2\n",
+ "import xarray as xr\n",
+ "port=9000\n",
+ "hostname=!echo $HOSTNAME\n",
+ "hosturl=\"https://\"+hostname[0]+\":\"+str(port)\n",
+ "dsname=\"example\"\n",
+ "zarr_url='/'.join([hosturl,\"datasets\",dsname,\"zarr\"])\n",
+ "storage_options=dict(verify_ssl=False)\n",
+ "ds=xr.open_zarr(\n",
+ " zarr_url,\n",
+ " consolidated=True,\n",
+ " storage_options=storage_options,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "84450da7-12cc-4d66-af1d-9c9d0e504868",
+ "metadata": {},
+ "source": [
+ "### Server-side processing\n",
+ "\n",
+ "In case bandwidth is the bottle-neck for users, we can help them with providing some server-side computing resources to e.g. further lossy compress our data. In the following, we firstly store the first 5 years on disk as provided. Secondly, we restart the app with enabled lossy compression and do the same. Afterwards, we compare speed and sizes."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "id": "ec89f56c-eb1e-4b31-a8e4-becd07d99019",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "def prepare_for_storage(ds_to_store):\n",
+ " bnds=[\"lat_bnds\",\"lon_bnds\"]\n",
+ " for a in bnds:\n",
+ " ds_to_store[a]=ds_to_store[a].isel(time=0).squeeze()\n",
+ " ds_to_store=ds_to_store.set_coords(bnds)\n",
+ " ds_to_store[\"time_bnds\"].load()\n",
+ "\n",
+ " return ds_to_store\n",
+ "\n",
+ "def store_"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "id": "2cce4ce3-fa18-42d4-8c2f-2b9a276a683a",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "ds5=ds.where(ds.time.dt.year.isin(range(2015,2020)),drop=True)\n",
+ "ds5=prepare_for_storage(ds5)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "id": "00c9a267-7420-4f66-a530-b782289f43fd",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "!rm compressed.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "id": "9c7b068e-db80-4985-9731-48b1a9c11e14",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "2.7509965896606445 seconds\n",
+ "512 -rw-r--r-- 1 k204210 bm0021 6.6M Jan 7 10:51 compressed.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "import time\n",
+ "s=time.time()\n",
+ "ds5.to_netcdf(\n",
+ " \"compressed.nc\",\n",
+ " unlimited_dims=[\"time\"],\n",
+ " encoding=dict(tas=dict(compression=\"zlib\"))\n",
+ ")\n",
+ "e=time.time()\n",
+ "print(e-s, \" seconds\")\n",
+ "!ls -lrths compressed.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "id": "e4d2fda6-7fe8-4cbb-aa79-95980e0b502d",
+ "metadata": {
+ "tags": []
+ },
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+ "Dimensions: (lat: 192, bnds: 2, lon: 384, time: 60)\n",
+ "Coordinates:\n",
+ " lat_bnds (lat, bnds) float64 3kB -89.75 -88.82 -88.82 ... 88.82 89.75\n",
+ " lon_bnds (lon, bnds) float64 6kB -0.4688 0.4688 0.4688 ... 358.6 359.5\n",
+ " height float64 8B 2.0\n",
+ " * lat (lat) float64 2kB -89.28 -88.36 -87.42 ... 87.42 88.36 89.28\n",
+ " * lon (lon) float64 3kB 0.0 0.9375 1.875 2.812 ... 357.2 358.1 359.1\n",
+ " * time (time) datetime64[ns] 480B 2015-01-16T12:00:00 ... 2019-12-16T...\n",
+ "Dimensions without coordinates: bnds\n",
+ "Data variables:\n",
+ " tas (time, lat, lon) float32 18MB 243.3 243.3 243.3 ... 251.1 251.1\n",
+ " time_bnds (time, bnds) datetime64[ns] 960B 2015-01-01 ... 2020-01-01\n",
+ "Attributes: (12/47)\n",
+ " Conventions: CF-1.7 CMIP-6.2\n",
+ " activity_id: ScenarioMIP AerChemMIP\n",
+ " branch_method: standard\n",
+ " branch_time_in_child: 60265.0\n",
+ " branch_time_in_parent: 60265.0\n",
+ " contact: cmip6-mpi-esm@dkrz.de\n",
+ " ... ...\n",
+ " title: MPI-ESM1-2-HR output prepared for CMIP6\n",
+ " variable_id: tas\n",
+ " variant_label: r1i1p1f1\n",
+ " license: CMIP6 model data produced by DKRZ is licensed und...\n",
+ " cmor_version: 3.4.0\n",
+ " tracking_id: hdl:21.14100/d6f0f6b2-b4c2-460b-bc5e-f1c72f932399</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5f0d12db-9212-4a72-b6db-e243fb1e8164' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5f0d12db-9212-4a72-b6db-e243fb1e8164' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 192</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 384</li><li><span class='xr-has-index'>time</span>: 60</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-165f6993-5677-45f4-a7b0-6dd2efc8e1f8' class='xr-section-summary-in' type='checkbox' checked><label for='section-165f6993-5677-45f4-a7b0-6dd2efc8e1f8' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.75 -88.82 ... 88.82 89.75</div><input id='attrs-c489035f-4cae-42aa-b210-8b0465807bdb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c489035f-4cae-42aa-b210-8b0465807bdb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11eebd66-0427-4b1c-930c-237f8e9724ae' class='xr-var-data-in' type='checkbox'><label for='data-11eebd66-0427-4b1c-930c-237f8e9724ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-89.74783954, -88.82061553],\n",
+ " [-88.82061553, -87.89065363],\n",
+ " [-87.89065363, -86.95733526],\n",
+ " [-86.95733526, -86.02316363],\n",
+ " [-86.02316363, -85.0886438 ],\n",
+ " [-85.0886438 , -84.15394696],\n",
+ " [-84.15394696, -83.21914764],\n",
+ " [-83.21914764, -82.2842836 ],\n",
+ " [-82.2842836 , -81.34937604],\n",
+ " [-81.34937604, -80.4144378 ],\n",
+ " [-80.4144378 , -79.47947712],\n",
+ " [-79.47947712, -78.54449952],\n",
+ " [-78.54449952, -77.60950886],\n",
+ " [-77.60950886, -76.67450789],\n",
+ " [-76.67450789, -75.73949865],\n",
+ " [-75.73949865, -74.80448268],\n",
+ " [-74.80448268, -73.86946114],\n",
+ " [-73.86946114, -72.93443496],\n",
+ " [-72.93443496, -71.99940486],\n",
+ " [-71.99940486, -71.06437142],\n",
+ "...\n",
+ " [ 71.06437142, 71.99940486],\n",
+ " [ 71.99940486, 72.93443496],\n",
+ " [ 72.93443496, 73.86946114],\n",
+ " [ 73.86946114, 74.80448268],\n",
+ " [ 74.80448268, 75.73949865],\n",
+ " [ 75.73949865, 76.67450789],\n",
+ " [ 76.67450789, 77.60950886],\n",
+ " [ 77.60950886, 78.54449952],\n",
+ " [ 78.54449952, 79.47947712],\n",
+ " [ 79.47947712, 80.4144378 ],\n",
+ " [ 80.4144378 , 81.34937604],\n",
+ " [ 81.34937604, 82.2842836 ],\n",
+ " [ 82.2842836 , 83.21914764],\n",
+ " [ 83.21914764, 84.15394696],\n",
+ " [ 84.15394696, 85.0886438 ],\n",
+ " [ 85.0886438 , 86.02316363],\n",
+ " [ 86.02316363, 86.95733526],\n",
+ " [ 86.95733526, 87.89065363],\n",
+ " [ 87.89065363, 88.82061553],\n",
+ " [ 88.82061553, 89.74783954]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.4688 0.4688 ... 358.6 359.5</div><input id='attrs-5e0bcaf4-19c8-47b8-9b41-004296611b64' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5e0bcaf4-19c8-47b8-9b41-004296611b64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7e4e043-c8d2-4dd2-922a-4b0b4b12fc87' class='xr-var-data-in' type='checkbox'><label for='data-d7e4e043-c8d2-4dd2-922a-4b0b4b12fc87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ -0.46875, 0.46875],\n",
+ " [ 0.46875, 1.40625],\n",
+ " [ 1.40625, 2.34375],\n",
+ " [ 2.34375, 3.28125],\n",
+ " [ 3.28125, 4.21875],\n",
+ " [ 4.21875, 5.15625],\n",
+ " [ 5.15625, 6.09375],\n",
+ " [ 6.09375, 7.03125],\n",
+ " [ 7.03125, 7.96875],\n",
+ " [ 7.96875, 8.90625],\n",
+ " [ 8.90625, 9.84375],\n",
+ " [ 9.84375, 10.78125],\n",
+ " [ 10.78125, 11.71875],\n",
+ " [ 11.71875, 12.65625],\n",
+ " [ 12.65625, 13.59375],\n",
+ " [ 13.59375, 14.53125],\n",
+ " [ 14.53125, 15.46875],\n",
+ " [ 15.46875, 16.40625],\n",
+ " [ 16.40625, 17.34375],\n",
+ " [ 17.34375, 18.28125],\n",
+ "...\n",
+ " [340.78125, 341.71875],\n",
+ " [341.71875, 342.65625],\n",
+ " [342.65625, 343.59375],\n",
+ " [343.59375, 344.53125],\n",
+ " [344.53125, 345.46875],\n",
+ " [345.46875, 346.40625],\n",
+ " [346.40625, 347.34375],\n",
+ " [347.34375, 348.28125],\n",
+ " [348.28125, 349.21875],\n",
+ " [349.21875, 350.15625],\n",
+ " [350.15625, 351.09375],\n",
+ " [351.09375, 352.03125],\n",
+ " [352.03125, 352.96875],\n",
+ " [352.96875, 353.90625],\n",
+ " [353.90625, 354.84375],\n",
+ " [354.84375, 355.78125],\n",
+ " [355.78125, 356.71875],\n",
+ " [356.71875, 357.65625],\n",
+ " [357.65625, 358.59375],\n",
+ " [358.59375, 359.53125]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-69b86a25-b051-4b4c-9815-ffb6548eb59a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69b86a25-b051-4b4c-9815-ffb6548eb59a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef5b93ce-adc7-49ea-895b-9aa95d51aac0' class='xr-var-data-in' type='checkbox'><label for='data-ef5b93ce-adc7-49ea-895b-9aa95d51aac0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.28 -88.36 ... 88.36 89.28</div><input id='attrs-ab1c59b5-38f8-4e43-8f51-0bcdadc83d1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab1c59b5-38f8-4e43-8f51-0bcdadc83d1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd19e8a7-0f05-4a90-ad32-4c87a68e984a' class='xr-var-data-in' type='checkbox'><label for='data-cd19e8a7-0f05-4a90-ad32-4c87a68e984a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.284228, -88.357004, -87.424304, -86.490367, -85.55596 , -84.621327,\n",
+ " -83.686567, -82.751728, -81.816839, -80.881913, -79.946962, -79.011992,\n",
+ " -78.077007, -77.142011, -76.207005, -75.271992, -74.336973, -73.401949,\n",
+ " -72.466921, -71.531889, -70.596854, -69.661816, -68.726776, -67.791734,\n",
+ " -66.856691, -65.921645, -64.986599, -64.051551, -63.116502, -62.181452,\n",
+ " -61.246401, -60.311349, -59.376297, -58.441244, -57.50619 , -56.571136,\n",
+ " -55.636081, -54.701026, -53.76597 , -52.830914, -51.895857, -50.960801,\n",
+ " -50.025743, -49.090686, -48.155628, -47.22057 , -46.285512, -45.350454,\n",
+ " -44.415395, -43.480336, -42.545277, -41.610218, -40.675159, -39.740099,\n",
+ " -38.805039, -37.86998 , -36.93492 , -35.99986 , -35.064799, -34.129739,\n",
+ " -33.194679, -32.259618, -31.324558, -30.389497, -29.454436, -28.519375,\n",
+ " -27.584315, -26.649254, -25.714193, -24.779132, -23.84407 , -22.909009,\n",
+ " -21.973948, -21.038887, -20.103825, -19.168764, -18.233703, -17.298641,\n",
+ " -16.36358 , -15.428518, -14.493457, -13.558395, -12.623333, -11.688272,\n",
+ " -10.75321 , -9.818148, -8.883087, -7.948025, -7.012963, -6.077901,\n",
+ " -5.14284 , -4.207778, -3.272716, -2.337654, -1.402593, -0.467531,\n",
+ " 0.467531, 1.402593, 2.337654, 3.272716, 4.207778, 5.14284 ,\n",
+ " 6.077901, 7.012963, 7.948025, 8.883087, 9.818148, 10.75321 ,\n",
+ " 11.688272, 12.623333, 13.558395, 14.493457, 15.428518, 16.36358 ,\n",
+ " 17.298641, 18.233703, 19.168764, 20.103825, 21.038887, 21.973948,\n",
+ " 22.909009, 23.84407 , 24.779132, 25.714193, 26.649254, 27.584315,\n",
+ " 28.519375, 29.454436, 30.389497, 31.324558, 32.259618, 33.194679,\n",
+ " 34.129739, 35.064799, 35.99986 , 36.93492 , 37.86998 , 38.805039,\n",
+ " 39.740099, 40.675159, 41.610218, 42.545277, 43.480336, 44.415395,\n",
+ " 45.350454, 46.285512, 47.22057 , 48.155628, 49.090686, 50.025743,\n",
+ " 50.960801, 51.895857, 52.830914, 53.76597 , 54.701026, 55.636081,\n",
+ " 56.571136, 57.50619 , 58.441244, 59.376297, 60.311349, 61.246401,\n",
+ " 62.181452, 63.116502, 64.051551, 64.986599, 65.921645, 66.856691,\n",
+ " 67.791734, 68.726776, 69.661816, 70.596854, 71.531889, 72.466921,\n",
+ " 73.401949, 74.336973, 75.271992, 76.207005, 77.142011, 78.077007,\n",
+ " 79.011992, 79.946962, 80.881913, 81.816839, 82.751728, 83.686567,\n",
+ " 84.621327, 85.55596 , 86.490367, 87.424304, 88.357004, 89.284228])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.9375 1.875 ... 358.1 359.1</div><input id='attrs-62403abb-31d4-4ec5-aa53-dd1d6a04a4b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62403abb-31d4-4ec5-aa53-dd1d6a04a4b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1340886b-f960-48de-8a0a-f4c7ec3fd3de' class='xr-var-data-in' type='checkbox'><label for='data-1340886b-f960-48de-8a0a-f4c7ec3fd3de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0. , 0.9375, 1.875 , ..., 357.1875, 358.125 , 359.0625])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2015-01-16T12:00:00 ... 2019-12-...</div><input id='attrs-eb6a84d2-3d3c-42f7-9d41-055687988e43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb6a84d2-3d3c-42f7-9d41-055687988e43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59125298-d784-49c2-b07b-b42a1c06a1c6' class='xr-var-data-in' type='checkbox'><label for='data-59125298-d784-49c2-b07b-b42a1c06a1c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(['2015-01-16T12:00:00.000000000', '2015-02-15T00:00:00.000000000',\n",
+ " '2015-03-16T12:00:00.000000000', '2015-04-16T00:00:00.000000000',\n",
+ " '2015-05-16T12:00:00.000000000', '2015-06-16T00:00:00.000000000',\n",
+ " '2015-07-16T12:00:00.000000000', '2015-08-16T12:00:00.000000000',\n",
+ " '2015-09-16T00:00:00.000000000', '2015-10-16T12:00:00.000000000',\n",
+ " '2015-11-16T00:00:00.000000000', '2015-12-16T12:00:00.000000000',\n",
+ " '2016-01-16T12:00:00.000000000', '2016-02-15T12:00:00.000000000',\n",
+ " '2016-03-16T12:00:00.000000000', '2016-04-16T00:00:00.000000000',\n",
+ " '2016-05-16T12:00:00.000000000', '2016-06-16T00:00:00.000000000',\n",
+ " '2016-07-16T12:00:00.000000000', '2016-08-16T12:00:00.000000000',\n",
+ " '2016-09-16T00:00:00.000000000', '2016-10-16T12:00:00.000000000',\n",
+ " '2016-11-16T00:00:00.000000000', '2016-12-16T12:00:00.000000000',\n",
+ " '2017-01-16T12:00:00.000000000', '2017-02-15T00:00:00.000000000',\n",
+ " '2017-03-16T12:00:00.000000000', '2017-04-16T00:00:00.000000000',\n",
+ " '2017-05-16T12:00:00.000000000', '2017-06-16T00:00:00.000000000',\n",
+ " '2017-07-16T12:00:00.000000000', '2017-08-16T12:00:00.000000000',\n",
+ " '2017-09-16T00:00:00.000000000', '2017-10-16T12:00:00.000000000',\n",
+ " '2017-11-16T00:00:00.000000000', '2017-12-16T12:00:00.000000000',\n",
+ " '2018-01-16T12:00:00.000000000', '2018-02-15T00:00:00.000000000',\n",
+ " '2018-03-16T12:00:00.000000000', '2018-04-16T00:00:00.000000000',\n",
+ " '2018-05-16T12:00:00.000000000', '2018-06-16T00:00:00.000000000',\n",
+ " '2018-07-16T12:00:00.000000000', '2018-08-16T12:00:00.000000000',\n",
+ " '2018-09-16T00:00:00.000000000', '2018-10-16T12:00:00.000000000',\n",
+ " '2018-11-16T00:00:00.000000000', '2018-12-16T12:00:00.000000000',\n",
+ " '2019-01-16T12:00:00.000000000', '2019-02-15T00:00:00.000000000',\n",
+ " '2019-03-16T12:00:00.000000000', '2019-04-16T00:00:00.000000000',\n",
+ " '2019-05-16T12:00:00.000000000', '2019-06-16T00:00:00.000000000',\n",
+ " '2019-07-16T12:00:00.000000000', '2019-08-16T12:00:00.000000000',\n",
+ " '2019-09-16T00:00:00.000000000', '2019-10-16T12:00:00.000000000',\n",
+ " '2019-11-16T00:00:00.000000000', '2019-12-16T12:00:00.000000000'],\n",
+ " dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e1db7dce-f618-48ff-a9eb-8e8a2f71e116' class='xr-section-summary-in' type='checkbox' checked><label for='section-e1db7dce-f618-48ff-a9eb-8e8a2f71e116' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>243.3 243.3 243.3 ... 251.1 251.1</div><input id='attrs-5f3840ee-57e2-44d9-bffe-d24184100ae5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f3840ee-57e2-44d9-bffe-d24184100ae5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a97771e2-cb0c-4513-8345-41ad464e215c' class='xr-var-data-in' type='checkbox'><label for='data-a97771e2-cb0c-4513-8345-41ad464e215c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2019-07-20T13:41:51Z altered by CMOR: Treated scalar dimension: 'height'. 2019-07-20T13:41:51Z altered by CMOR: replaced missing value flag (-9e+33) with standard missing value (1e+20). 2019-07-20T13:41:51Z altered by CMOR: Converted type from 'd' to 'f'. 2019-07-20T13:41:52Z altered by CMOR: Inverted axis: lat.</dd></dl></div><div class='xr-var-data'><pre>array([[[243.30435, 243.29459, 243.28091, ..., 243.29654, 243.29459,\n",
+ " 243.19107],\n",
+ " [244.38638, 244.34927, 244.28873, ..., 244.486 , 244.45865,\n",
+ " 244.42935],\n",
+ " [244.8649 , 244.78677, 244.64224, ..., 245.03287, 244.98795,\n",
+ " 244.9235 ],\n",
+ " ...,\n",
+ " [253.50748, 253.49966, 253.52896, ..., 253.38248, 253.42545,\n",
+ " 253.43912],\n",
+ " [252.84732, 252.85904, 252.861 , ..., 252.63638, 252.75748,\n",
+ " 252.80826],\n",
+ " [252.24771, 252.23404, 252.28677, ..., 252.23795, 252.23795,\n",
+ " 252.2399 ]],\n",
+ "\n",
+ " [[235.70682, 235.68729, 235.70096, ..., 235.71658, 235.70877,\n",
+ " 235.69315],\n",
+ " [236.74393, 236.70096, 236.6287 , ..., 236.90408, 236.9158 ,\n",
+ " 236.84549],\n",
+ " [237.98221, 237.96854, 237.81229, ..., 238.19315, 238.11111,\n",
+ " 238.0662 ],\n",
+ "...\n",
+ " [256.05878, 256.15448, 256.21698, ..., 255.79707, 255.90254,\n",
+ " 255.97871],\n",
+ " [255.88496, 255.91426, 255.96309, ..., 255.77168, 255.8127 ,\n",
+ " 255.84981],\n",
+ " [255.592 , 255.57832, 255.62715, ..., 255.54317, 255.58028,\n",
+ " 255.61543]],\n",
+ "\n",
+ " [[242.98508, 243.05539, 243.08664, ..., 243.00656, 243.01047,\n",
+ " 242.98508],\n",
+ " [245.07687, 245.10812, 245.0007 , ..., 245.0261 , 245.03586,\n",
+ " 245.11594],\n",
+ " [245.00656, 245.13547, 245.10226, ..., 245.2468 , 245.15695,\n",
+ " 245.0593 ],\n",
+ " ...,\n",
+ " [253.30539, 253.31516, 253.29562, ..., 253.29367, 253.32297,\n",
+ " 253.31906],\n",
+ " [252.05539, 252.05539, 252.08078, ..., 252.00266, 252.00266,\n",
+ " 252.00266],\n",
+ " [251.07687, 251.06516, 251.1257 , ..., 251.0632 , 251.0925 ,\n",
+ " 251.08273]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2015-01-01 ... 2020-01-01</div><input id='attrs-dec51311-0053-4029-a1aa-16b5a4e2aa62' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dec51311-0053-4029-a1aa-16b5a4e2aa62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6499318-1ef5-4f0e-a4d9-ae471d46722b' class='xr-var-data-in' type='checkbox'><label for='data-d6499318-1ef5-4f0e-a4d9-ae471d46722b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([['2015-01-01T00:00:00.000000000', '2015-02-01T00:00:00.000000000'],\n",
+ " ['2015-02-01T00:00:00.000000000', '2015-03-01T00:00:00.000000000'],\n",
+ " ['2015-03-01T00:00:00.000000000', '2015-04-01T00:00:00.000000000'],\n",
+ " ['2015-04-01T00:00:00.000000000', '2015-05-01T00:00:00.000000000'],\n",
+ " ['2015-05-01T00:00:00.000000000', '2015-06-01T00:00:00.000000000'],\n",
+ " ['2015-06-01T00:00:00.000000000', '2015-07-01T00:00:00.000000000'],\n",
+ " ['2015-07-01T00:00:00.000000000', '2015-08-01T00:00:00.000000000'],\n",
+ " ['2015-08-01T00:00:00.000000000', '2015-09-01T00:00:00.000000000'],\n",
+ " ['2015-09-01T00:00:00.000000000', '2015-10-01T00:00:00.000000000'],\n",
+ " ['2015-10-01T00:00:00.000000000', '2015-11-01T00:00:00.000000000'],\n",
+ " ['2015-11-01T00:00:00.000000000', '2015-12-01T00:00:00.000000000'],\n",
+ " ['2015-12-01T00:00:00.000000000', '2016-01-01T00:00:00.000000000'],\n",
+ " ['2016-01-01T00:00:00.000000000', '2016-02-01T00:00:00.000000000'],\n",
+ " ['2016-02-01T00:00:00.000000000', '2016-03-01T00:00:00.000000000'],\n",
+ " ['2016-03-01T00:00:00.000000000', '2016-04-01T00:00:00.000000000'],\n",
+ " ['2016-04-01T00:00:00.000000000', '2016-05-01T00:00:00.000000000'],\n",
+ " ['2016-05-01T00:00:00.000000000', '2016-06-01T00:00:00.000000000'],\n",
+ " ['2016-06-01T00:00:00.000000000', '2016-07-01T00:00:00.000000000'],\n",
+ " ['2016-07-01T00:00:00.000000000', '2016-08-01T00:00:00.000000000'],\n",
+ " ['2016-08-01T00:00:00.000000000', '2016-09-01T00:00:00.000000000'],\n",
+ "...\n",
+ " ['2018-06-01T00:00:00.000000000', '2018-07-01T00:00:00.000000000'],\n",
+ " ['2018-07-01T00:00:00.000000000', '2018-08-01T00:00:00.000000000'],\n",
+ " ['2018-08-01T00:00:00.000000000', '2018-09-01T00:00:00.000000000'],\n",
+ " ['2018-09-01T00:00:00.000000000', '2018-10-01T00:00:00.000000000'],\n",
+ " ['2018-10-01T00:00:00.000000000', '2018-11-01T00:00:00.000000000'],\n",
+ " ['2018-11-01T00:00:00.000000000', '2018-12-01T00:00:00.000000000'],\n",
+ " ['2018-12-01T00:00:00.000000000', '2019-01-01T00:00:00.000000000'],\n",
+ " ['2019-01-01T00:00:00.000000000', '2019-02-01T00:00:00.000000000'],\n",
+ " ['2019-02-01T00:00:00.000000000', '2019-03-01T00:00:00.000000000'],\n",
+ " ['2019-03-01T00:00:00.000000000', '2019-04-01T00:00:00.000000000'],\n",
+ " ['2019-04-01T00:00:00.000000000', '2019-05-01T00:00:00.000000000'],\n",
+ " ['2019-05-01T00:00:00.000000000', '2019-06-01T00:00:00.000000000'],\n",
+ " ['2019-06-01T00:00:00.000000000', '2019-07-01T00:00:00.000000000'],\n",
+ " ['2019-07-01T00:00:00.000000000', '2019-08-01T00:00:00.000000000'],\n",
+ " ['2019-08-01T00:00:00.000000000', '2019-09-01T00:00:00.000000000'],\n",
+ " ['2019-09-01T00:00:00.000000000', '2019-10-01T00:00:00.000000000'],\n",
+ " ['2019-10-01T00:00:00.000000000', '2019-11-01T00:00:00.000000000'],\n",
+ " ['2019-11-01T00:00:00.000000000', '2019-12-01T00:00:00.000000000'],\n",
+ " ['2019-12-01T00:00:00.000000000', '2020-01-01T00:00:00.000000000']],\n",
+ " dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4d80ff84-01c6-46d9-8030-fa8125fbc56f' class='xr-section-summary-in' type='checkbox' ><label for='section-4d80ff84-01c6-46d9-8030-fa8125fbc56f' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4560df76-5929-4d09-bb69-ddd648be8486' class='xr-index-data-in' type='checkbox'/><label for='index-4560df76-5929-4d09-bb69-ddd648be8486' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.28422753251364, -88.35700351866494, -87.42430374606988,\n",
+ " -86.49036676628116, -85.55596048489265, -84.6213271076488,\n",
+ " -83.68656681656385, -82.75172847343066, -81.81683872860319,\n",
+ " -80.8819133467975,\n",
+ " ...\n",
+ " 80.8819133467975, 81.81683872860319, 82.75172847343066,\n",
+ " 83.68656681656385, 84.6213271076488, 85.55596048489265,\n",
+ " 86.49036676628116, 87.42430374606988, 88.35700351866494,\n",
+ " 89.28422753251364],\n",
+ " dtype='float64', name='lat', length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d4da41d0-e990-422f-8987-c223b0912676' class='xr-index-data-in' type='checkbox'/><label for='index-d4da41d0-e990-422f-8987-c223b0912676' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.0, 0.9375, 1.875, 2.8125, 3.75, 4.6875, 5.625,\n",
+ " 6.5625, 7.5, 8.4375,\n",
+ " ...\n",
+ " 350.625, 351.5625, 352.5, 353.4375, 354.375, 355.3125, 356.25,\n",
+ " 357.1875, 358.125, 359.0625],\n",
+ " dtype='float64', name='lon', length=384))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-67596b54-a3b8-4098-800f-0e34b67c3ac6' class='xr-index-data-in' type='checkbox'/><label for='index-67596b54-a3b8-4098-800f-0e34b67c3ac6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2015-01-16 12:00:00', '2015-02-15 00:00:00',\n",
+ " '2015-03-16 12:00:00', '2015-04-16 00:00:00',\n",
+ " '2015-05-16 12:00:00', '2015-06-16 00:00:00',\n",
+ " '2015-07-16 12:00:00', '2015-08-16 12:00:00',\n",
+ " '2015-09-16 00:00:00', '2015-10-16 12:00:00',\n",
+ " '2015-11-16 00:00:00', '2015-12-16 12:00:00',\n",
+ " '2016-01-16 12:00:00', '2016-02-15 12:00:00',\n",
+ " '2016-03-16 12:00:00', '2016-04-16 00:00:00',\n",
+ " '2016-05-16 12:00:00', '2016-06-16 00:00:00',\n",
+ " '2016-07-16 12:00:00', '2016-08-16 12:00:00',\n",
+ " '2016-09-16 00:00:00', '2016-10-16 12:00:00',\n",
+ " '2016-11-16 00:00:00', '2016-12-16 12:00:00',\n",
+ " '2017-01-16 12:00:00', '2017-02-15 00:00:00',\n",
+ " '2017-03-16 12:00:00', '2017-04-16 00:00:00',\n",
+ " '2017-05-16 12:00:00', '2017-06-16 00:00:00',\n",
+ " '2017-07-16 12:00:00', '2017-08-16 12:00:00',\n",
+ " '2017-09-16 00:00:00', '2017-10-16 12:00:00',\n",
+ " '2017-11-16 00:00:00', '2017-12-16 12:00:00',\n",
+ " '2018-01-16 12:00:00', '2018-02-15 00:00:00',\n",
+ " '2018-03-16 12:00:00', '2018-04-16 00:00:00',\n",
+ " '2018-05-16 12:00:00', '2018-06-16 00:00:00',\n",
+ " '2018-07-16 12:00:00', '2018-08-16 12:00:00',\n",
+ " '2018-09-16 00:00:00', '2018-10-16 12:00:00',\n",
+ " '2018-11-16 00:00:00', '2018-12-16 12:00:00',\n",
+ " '2019-01-16 12:00:00', '2019-02-15 00:00:00',\n",
+ " '2019-03-16 12:00:00', '2019-04-16 00:00:00',\n",
+ " '2019-05-16 12:00:00', '2019-06-16 00:00:00',\n",
+ " '2019-07-16 12:00:00', '2019-08-16 12:00:00',\n",
+ " '2019-09-16 00:00:00', '2019-10-16 12:00:00',\n",
+ " '2019-11-16 00:00:00', '2019-12-16 12:00:00'],\n",
+ " dtype='datetime64[ns]', name='time', freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8aca4d67-9a0e-4bd3-9a78-abb05a1ab436' class='xr-section-summary-in' type='checkbox' ><label for='section-8aca4d67-9a0e-4bd3-9a78-abb05a1ab436' class='xr-section-summary' >Attributes: <span>(47)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>ScenarioMIP AerChemMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>60265.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>60265.0</dd><dt><span>contact :</span></dt><dd>cmip6-mpi-esm@dkrz.de</dd><dt><span>creation_date :</span></dt><dd>2019-07-20T13:41:51Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>gap-filling scenario reaching 7.0 based on SSP3</dd><dt><span>experiment_id :</span></dt><dd>ssp370</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.DKRZ.MPI-ESM1-2-HR.ssp370.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>gn</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2019-07-20T13:41:51Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Deutsches Klimarechenzentrum, Hamburg 20146, Germany</dd><dt><span>institution_id :</span></dt><dd>DKRZ</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>historical</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>MPI-ESM1-2-HR</dd><dt><span>parent_time_units :</span></dt><dd>days since 1850-1-1 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>project_id :</span></dt><dd>CMIP6</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>references :</span></dt><dd>MPI-ESM: Mauritsen, T. et al. (2019), Developments in the MPIâ€M Earth System Model version 1.2 (MPIâ€ESM1.2) and Its Response to Increasing CO2, J. Adv. Model. Earth Syst.,11, 998-1038, doi:10.1029/2018MS001400,\n",
+ "Mueller, W.A. et al. (2018): A highâ€resolution version of the Max Planck Institute Earth System Model MPIâ€ESM1.2â€HR. J. Adv. Model. EarthSyst.,10,1383–1413, doi:10.1029/2017MS001217</dd><dt><span>source :</span></dt><dd>MPI-ESM1.2-HR (2017): \n",
+ "aerosol: none, prescribed MACv2-SP\n",
+ "atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa)\n",
+ "atmosChem: none\n",
+ "land: JSBACH3.20\n",
+ "landIce: none/prescribed\n",
+ "ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 longitude/latitude; 40 levels; top grid cell 0-12 m)\n",
+ "ocnBgchem: HAMOCC6\n",
+ "seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model)</dd><dt><span>source_id :</span></dt><dd>MPI-ESM1-2-HR</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(09 May 2019) MD5:e6ef8ececc8f338646ebfb3aeed36bfc</dd><dt><span>title :</span></dt><dd>MPI-ESM1-2-HR output prepared for CMIP6</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by DKRZ is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.4.0</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/d6f0f6b2-b4c2-460b-bc5e-f1c72f932399</dd></dl></div></li></ul></div></div>"
+ ],
+ "text/plain": [
+ "<xarray.Dataset> Size: 18MB\n",
+ "Dimensions: (lat: 192, bnds: 2, lon: 384, time: 60)\n",
+ "Coordinates:\n",
+ " lat_bnds (lat, bnds) float64 3kB -89.75 -88.82 -88.82 ... 88.82 89.75\n",
+ " lon_bnds (lon, bnds) float64 6kB -0.4688 0.4688 0.4688 ... 358.6 359.5\n",
+ " height float64 8B 2.0\n",
+ " * lat (lat) float64 2kB -89.28 -88.36 -87.42 ... 87.42 88.36 89.28\n",
+ " * lon (lon) float64 3kB 0.0 0.9375 1.875 2.812 ... 357.2 358.1 359.1\n",
+ " * time (time) datetime64[ns] 480B 2015-01-16T12:00:00 ... 2019-12-16T...\n",
+ "Dimensions without coordinates: bnds\n",
+ "Data variables:\n",
+ " tas (time, lat, lon) float32 18MB 243.3 243.3 243.3 ... 251.1 251.1\n",
+ " time_bnds (time, bnds) datetime64[ns] 960B 2015-01-01 ... 2020-01-01\n",
+ "Attributes: (12/47)\n",
+ " Conventions: CF-1.7 CMIP-6.2\n",
+ " activity_id: ScenarioMIP AerChemMIP\n",
+ " branch_method: standard\n",
+ " branch_time_in_child: 60265.0\n",
+ " branch_time_in_parent: 60265.0\n",
+ " contact: cmip6-mpi-esm@dkrz.de\n",
+ " ... ...\n",
+ " title: MPI-ESM1-2-HR output prepared for CMIP6\n",
+ " variable_id: tas\n",
+ " variant_label: r1i1p1f1\n",
+ " license: CMIP6 model data produced by DKRZ is licensed und...\n",
+ " cmor_version: 3.4.0\n",
+ " tracking_id: hdl:21.14100/d6f0f6b2-b4c2-460b-bc5e-f1c72f932399"
+ ]
+ },
+ "execution_count": 29,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import xarray as xr\n",
+ "xr.open_dataset(\"compressed.nc\").load()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 41,
+ "id": "8dd8feff-9e4b-421b-a453-83f81e20da1a",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "k204210 1101280 1100112 0 07:33 ? 00:00:02 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-99eb3193-dfc0-45c3-9953-a1f29fb0888d.json\n",
+ "k204210 1101285 1100112 0 07:33 ? 00:00:02 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-0ac5cfbe-7cc6-4136-870a-cbac9aa18a7b.json\n",
+ "k204210 1102668 1100112 0 09:10 ? 00:00:21 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-f59a40b2-6d4d-41dd-b768-7ee9040e362a.json\n",
+ "k204210 1109706 1100112 0 10:42 ? 00:00:01 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-edc24184-27e4-4966-beb3-6f926e2d6cf0.json\n",
+ "k204210 1109938 1100112 2 10:43 ? 00:00:22 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-947ea9d3-56f0-426e-9af8-8a5be0180793.json\n",
+ "k204210 1111150 1111019 0 10:52 ? 00:00:00 /work/bm0021/conda-envs/cloudify/bin/python -c from multiprocessing.resource_tracker import main;main(26)\n",
+ "k204210 1111152 1111019 2 10:52 ? 00:00:06 /work/bm0021/conda-envs/cloudify/bin/python -c from multiprocessing.spawn import spawn_main; spawn_main(tracker_fd=27, pipe_handle=37) --multiprocessing-fork\n",
+ "k204210 1111155 1111019 2 10:52 ? 00:00:06 /work/bm0021/conda-envs/cloudify/bin/python -c from multiprocessing.spawn import spawn_main; spawn_main(tracker_fd=27, pipe_handle=37) --multiprocessing-fork\n",
+ "k204210 1111473 1109938 0 10:57 pts/3 00:00:00 /bin/bash -c ps -ef | grep cloudify\n",
+ "k204210 1111475 1111473 0 10:57 pts/3 00:00:00 grep cloudify\n"
+ ]
+ }
+ ],
+ "source": [
+ "!ps -ef | grep cloudify"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "id": "d8e827fd-5501-47ef-b2e8-8e00a0dba7cd",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "!kill 1111019"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 34,
+ "id": "42c31b41-7cd7-43f0-b65e-6223ca38c9a8",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "os.environ[\"L_LOSSY\"]=\"1\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 35,
+ "id": "13936d6b-d9af-4b0b-88ce-abc921aed6e0",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "%%bash --bg\n",
+ "\n",
+ "source activate /work/bm0021/conda-envs/cloudify\n",
+ "python xpublish_example.py \\\n",
+ " example \\\n",
+ " /work/ik1017/CMIP6/data/CMIP6/ScenarioMIP/DKRZ/MPI-ESM1-2-HR/ssp370/r1i1p1f1/Amon/tas/gn/v20190710/*.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 36,
+ "id": "d4ac3289-05b0-4d26-8d35-c9ce55fbb91c",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "dslossy=xr.open_zarr(\n",
+ " zarr_url,\n",
+ " consolidated=True,\n",
+ " storage_options=storage_options,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "id": "1e726b61-baf3-4145-864a-72ec4e925e7c",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "ds5lossy=dslossy.where(ds.time.dt.year.isin(range(2015,2020)),drop=True)\n",
+ "ds5lossy=prepare_for_storage(ds5lossy)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "id": "3fc6ce85-3bd2-48a3-8c10-df926834250e",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "rm: cannot remove 'lossy_compressed.nc': No such file or directory\n"
+ ]
+ }
+ ],
+ "source": [
+ "!rm lossy_compressed.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "id": "52799388-8c6d-4646-aae9-fa99c1ed1a10",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "2.4706828594207764 seconds\n",
+ "512 -rw-r--r-- 1 k204210 bm0021 3.5M Jan 7 10:53 lossy_compressed.nc\n"
+ ]
+ }
+ ],
+ "source": [
+ "s=time.time()\n",
+ "ds5lossy.to_netcdf(\n",
+ " \"lossy_compressed.nc\",\n",
+ " unlimited_dims=[\"time\"],\n",
+ " encoding=dict(tas=dict(compression=\"zlib\"))\n",
+ ")\n",
+ "e=time.time()\n",
+ "print(e-s, \" seconds\")\n",
+ "!ls -lrths lossy_compressed.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "id": "29f8dd36-7af2-4e0b-92b2-85a4e0cb8dae",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
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+ "</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 18MB\n",
+ "Dimensions: (lat: 192, bnds: 2, lon: 384, time: 60)\n",
+ "Coordinates:\n",
+ " lat_bnds (lat, bnds) float64 3kB -89.75 -88.82 -88.82 ... 88.82 89.75\n",
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+ " * time (time) datetime64[ns] 480B 2015-01-16T12:00:00 ... 2019-12-16T...\n",
+ "Dimensions without coordinates: bnds\n",
+ "Data variables:\n",
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+ " time_bnds (time, bnds) datetime64[ns] 960B 2015-01-01 ... 2020-01-01\n",
+ "Attributes: (12/47)\n",
+ " Conventions: CF-1.7 CMIP-6.2\n",
+ " activity_id: ScenarioMIP AerChemMIP\n",
+ " branch_method: standard\n",
+ " branch_time_in_child: 60265.0\n",
+ " branch_time_in_parent: 60265.0\n",
+ " contact: cmip6-mpi-esm@dkrz.de\n",
+ " ... ...\n",
+ " title: MPI-ESM1-2-HR output prepared for CMIP6\n",
+ " variable_id: tas\n",
+ " variant_label: r1i1p1f1\n",
+ " license: CMIP6 model data produced by DKRZ is licensed und...\n",
+ " cmor_version: 3.4.0\n",
+ " tracking_id: hdl:21.14100/d6f0f6b2-b4c2-460b-bc5e-f1c72f932399</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-62140024-f4c1-4f50-b7ea-c397f61d9942' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-62140024-f4c1-4f50-b7ea-c397f61d9942' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 192</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 384</li><li><span class='xr-has-index'>time</span>: 60</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5edc4c1a-348c-4417-9cf3-648b7ba842c9' class='xr-section-summary-in' type='checkbox' checked><label for='section-5edc4c1a-348c-4417-9cf3-648b7ba842c9' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.75 -88.82 ... 88.82 89.75</div><input id='attrs-0a62247c-090d-4902-99e1-82fee29b23f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0a62247c-090d-4902-99e1-82fee29b23f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-757eee7b-ed7f-4fbb-a8d8-7819d15c0a24' class='xr-var-data-in' type='checkbox'><label for='data-757eee7b-ed7f-4fbb-a8d8-7819d15c0a24' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-89.74783954, -88.82061553],\n",
+ " [-88.82061553, -87.89065363],\n",
+ " [-87.89065363, -86.95733526],\n",
+ " [-86.95733526, -86.02316363],\n",
+ " [-86.02316363, -85.0886438 ],\n",
+ " [-85.0886438 , -84.15394696],\n",
+ " [-84.15394696, -83.21914764],\n",
+ " [-83.21914764, -82.2842836 ],\n",
+ " [-82.2842836 , -81.34937604],\n",
+ " [-81.34937604, -80.4144378 ],\n",
+ " [-80.4144378 , -79.47947712],\n",
+ " [-79.47947712, -78.54449952],\n",
+ " [-78.54449952, -77.60950886],\n",
+ " [-77.60950886, -76.67450789],\n",
+ " [-76.67450789, -75.73949865],\n",
+ " [-75.73949865, -74.80448268],\n",
+ " [-74.80448268, -73.86946114],\n",
+ " [-73.86946114, -72.93443496],\n",
+ " [-72.93443496, -71.99940486],\n",
+ " [-71.99940486, -71.06437142],\n",
+ "...\n",
+ " [ 71.06437142, 71.99940486],\n",
+ " [ 71.99940486, 72.93443496],\n",
+ " [ 72.93443496, 73.86946114],\n",
+ " [ 73.86946114, 74.80448268],\n",
+ " [ 74.80448268, 75.73949865],\n",
+ " [ 75.73949865, 76.67450789],\n",
+ " [ 76.67450789, 77.60950886],\n",
+ " [ 77.60950886, 78.54449952],\n",
+ " [ 78.54449952, 79.47947712],\n",
+ " [ 79.47947712, 80.4144378 ],\n",
+ " [ 80.4144378 , 81.34937604],\n",
+ " [ 81.34937604, 82.2842836 ],\n",
+ " [ 82.2842836 , 83.21914764],\n",
+ " [ 83.21914764, 84.15394696],\n",
+ " [ 84.15394696, 85.0886438 ],\n",
+ " [ 85.0886438 , 86.02316363],\n",
+ " [ 86.02316363, 86.95733526],\n",
+ " [ 86.95733526, 87.89065363],\n",
+ " [ 87.89065363, 88.82061553],\n",
+ " [ 88.82061553, 89.74783954]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.4688 0.4688 ... 358.6 359.5</div><input id='attrs-8a74380e-b661-4f18-979a-f018a24da773' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a74380e-b661-4f18-979a-f018a24da773' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22377613-cef9-4366-a065-be843f56fbbd' class='xr-var-data-in' type='checkbox'><label for='data-22377613-cef9-4366-a065-be843f56fbbd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ -0.46875, 0.46875],\n",
+ " [ 0.46875, 1.40625],\n",
+ " [ 1.40625, 2.34375],\n",
+ " [ 2.34375, 3.28125],\n",
+ " [ 3.28125, 4.21875],\n",
+ " [ 4.21875, 5.15625],\n",
+ " [ 5.15625, 6.09375],\n",
+ " [ 6.09375, 7.03125],\n",
+ " [ 7.03125, 7.96875],\n",
+ " [ 7.96875, 8.90625],\n",
+ " [ 8.90625, 9.84375],\n",
+ " [ 9.84375, 10.78125],\n",
+ " [ 10.78125, 11.71875],\n",
+ " [ 11.71875, 12.65625],\n",
+ " [ 12.65625, 13.59375],\n",
+ " [ 13.59375, 14.53125],\n",
+ " [ 14.53125, 15.46875],\n",
+ " [ 15.46875, 16.40625],\n",
+ " [ 16.40625, 17.34375],\n",
+ " [ 17.34375, 18.28125],\n",
+ "...\n",
+ " [340.78125, 341.71875],\n",
+ " [341.71875, 342.65625],\n",
+ " [342.65625, 343.59375],\n",
+ " [343.59375, 344.53125],\n",
+ " [344.53125, 345.46875],\n",
+ " [345.46875, 346.40625],\n",
+ " [346.40625, 347.34375],\n",
+ " [347.34375, 348.28125],\n",
+ " [348.28125, 349.21875],\n",
+ " [349.21875, 350.15625],\n",
+ " [350.15625, 351.09375],\n",
+ " [351.09375, 352.03125],\n",
+ " [352.03125, 352.96875],\n",
+ " [352.96875, 353.90625],\n",
+ " [353.90625, 354.84375],\n",
+ " [354.84375, 355.78125],\n",
+ " [355.78125, 356.71875],\n",
+ " [356.71875, 357.65625],\n",
+ " [357.65625, 358.59375],\n",
+ " [358.59375, 359.53125]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-1ec533b3-ce9b-4a03-830c-7652d4c14266' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ec533b3-ce9b-4a03-830c-7652d4c14266' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a23c3e2f-1c8e-4e17-9853-7c407a450f97' class='xr-var-data-in' type='checkbox'><label for='data-a23c3e2f-1c8e-4e17-9853-7c407a450f97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.28 -88.36 ... 88.36 89.28</div><input id='attrs-29450a5d-e454-47a4-af4e-6a453c46cb30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29450a5d-e454-47a4-af4e-6a453c46cb30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e1729ac-17ed-40e0-8cfd-a282569b541f' class='xr-var-data-in' type='checkbox'><label for='data-8e1729ac-17ed-40e0-8cfd-a282569b541f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.284228, -88.357004, -87.424304, -86.490367, -85.55596 , -84.621327,\n",
+ " -83.686567, -82.751728, -81.816839, -80.881913, -79.946962, -79.011992,\n",
+ " -78.077007, -77.142011, -76.207005, -75.271992, -74.336973, -73.401949,\n",
+ " -72.466921, -71.531889, -70.596854, -69.661816, -68.726776, -67.791734,\n",
+ " -66.856691, -65.921645, -64.986599, -64.051551, -63.116502, -62.181452,\n",
+ " -61.246401, -60.311349, -59.376297, -58.441244, -57.50619 , -56.571136,\n",
+ " -55.636081, -54.701026, -53.76597 , -52.830914, -51.895857, -50.960801,\n",
+ " -50.025743, -49.090686, -48.155628, -47.22057 , -46.285512, -45.350454,\n",
+ " -44.415395, -43.480336, -42.545277, -41.610218, -40.675159, -39.740099,\n",
+ " -38.805039, -37.86998 , -36.93492 , -35.99986 , -35.064799, -34.129739,\n",
+ " -33.194679, -32.259618, -31.324558, -30.389497, -29.454436, -28.519375,\n",
+ " -27.584315, -26.649254, -25.714193, -24.779132, -23.84407 , -22.909009,\n",
+ " -21.973948, -21.038887, -20.103825, -19.168764, -18.233703, -17.298641,\n",
+ " -16.36358 , -15.428518, -14.493457, -13.558395, -12.623333, -11.688272,\n",
+ " -10.75321 , -9.818148, -8.883087, -7.948025, -7.012963, -6.077901,\n",
+ " -5.14284 , -4.207778, -3.272716, -2.337654, -1.402593, -0.467531,\n",
+ " 0.467531, 1.402593, 2.337654, 3.272716, 4.207778, 5.14284 ,\n",
+ " 6.077901, 7.012963, 7.948025, 8.883087, 9.818148, 10.75321 ,\n",
+ " 11.688272, 12.623333, 13.558395, 14.493457, 15.428518, 16.36358 ,\n",
+ " 17.298641, 18.233703, 19.168764, 20.103825, 21.038887, 21.973948,\n",
+ " 22.909009, 23.84407 , 24.779132, 25.714193, 26.649254, 27.584315,\n",
+ " 28.519375, 29.454436, 30.389497, 31.324558, 32.259618, 33.194679,\n",
+ " 34.129739, 35.064799, 35.99986 , 36.93492 , 37.86998 , 38.805039,\n",
+ " 39.740099, 40.675159, 41.610218, 42.545277, 43.480336, 44.415395,\n",
+ " 45.350454, 46.285512, 47.22057 , 48.155628, 49.090686, 50.025743,\n",
+ " 50.960801, 51.895857, 52.830914, 53.76597 , 54.701026, 55.636081,\n",
+ " 56.571136, 57.50619 , 58.441244, 59.376297, 60.311349, 61.246401,\n",
+ " 62.181452, 63.116502, 64.051551, 64.986599, 65.921645, 66.856691,\n",
+ " 67.791734, 68.726776, 69.661816, 70.596854, 71.531889, 72.466921,\n",
+ " 73.401949, 74.336973, 75.271992, 76.207005, 77.142011, 78.077007,\n",
+ " 79.011992, 79.946962, 80.881913, 81.816839, 82.751728, 83.686567,\n",
+ " 84.621327, 85.55596 , 86.490367, 87.424304, 88.357004, 89.284228])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.9375 1.875 ... 358.1 359.1</div><input id='attrs-57f111a1-876f-4802-8198-b9c9dd2c4f4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57f111a1-876f-4802-8198-b9c9dd2c4f4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef89ec13-0170-43d3-a021-ddc6ac4c921b' class='xr-var-data-in' type='checkbox'><label for='data-ef89ec13-0170-43d3-a021-ddc6ac4c921b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0. , 0.9375, 1.875 , ..., 357.1875, 358.125 , 359.0625])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2015-01-16T12:00:00 ... 2019-12-...</div><input id='attrs-6f029f5e-cb3a-41cc-a64d-1456eccaa7b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f029f5e-cb3a-41cc-a64d-1456eccaa7b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63960366-8701-437b-884c-c91335a8d89b' class='xr-var-data-in' type='checkbox'><label for='data-63960366-8701-437b-884c-c91335a8d89b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array(['2015-01-16T12:00:00.000000000', '2015-02-15T00:00:00.000000000',\n",
+ " '2015-03-16T12:00:00.000000000', '2015-04-16T00:00:00.000000000',\n",
+ " '2015-05-16T12:00:00.000000000', '2015-06-16T00:00:00.000000000',\n",
+ " '2015-07-16T12:00:00.000000000', '2015-08-16T12:00:00.000000000',\n",
+ " '2015-09-16T00:00:00.000000000', '2015-10-16T12:00:00.000000000',\n",
+ " '2015-11-16T00:00:00.000000000', '2015-12-16T12:00:00.000000000',\n",
+ " '2016-01-16T12:00:00.000000000', '2016-02-15T12:00:00.000000000',\n",
+ " '2016-03-16T12:00:00.000000000', '2016-04-16T00:00:00.000000000',\n",
+ " '2016-05-16T12:00:00.000000000', '2016-06-16T00:00:00.000000000',\n",
+ " '2016-07-16T12:00:00.000000000', '2016-08-16T12:00:00.000000000',\n",
+ " '2016-09-16T00:00:00.000000000', '2016-10-16T12:00:00.000000000',\n",
+ " '2016-11-16T00:00:00.000000000', '2016-12-16T12:00:00.000000000',\n",
+ " '2017-01-16T12:00:00.000000000', '2017-02-15T00:00:00.000000000',\n",
+ " '2017-03-16T12:00:00.000000000', '2017-04-16T00:00:00.000000000',\n",
+ " '2017-05-16T12:00:00.000000000', '2017-06-16T00:00:00.000000000',\n",
+ " '2017-07-16T12:00:00.000000000', '2017-08-16T12:00:00.000000000',\n",
+ " '2017-09-16T00:00:00.000000000', '2017-10-16T12:00:00.000000000',\n",
+ " '2017-11-16T00:00:00.000000000', '2017-12-16T12:00:00.000000000',\n",
+ " '2018-01-16T12:00:00.000000000', '2018-02-15T00:00:00.000000000',\n",
+ " '2018-03-16T12:00:00.000000000', '2018-04-16T00:00:00.000000000',\n",
+ " '2018-05-16T12:00:00.000000000', '2018-06-16T00:00:00.000000000',\n",
+ " '2018-07-16T12:00:00.000000000', '2018-08-16T12:00:00.000000000',\n",
+ " '2018-09-16T00:00:00.000000000', '2018-10-16T12:00:00.000000000',\n",
+ " '2018-11-16T00:00:00.000000000', '2018-12-16T12:00:00.000000000',\n",
+ " '2019-01-16T12:00:00.000000000', '2019-02-15T00:00:00.000000000',\n",
+ " '2019-03-16T12:00:00.000000000', '2019-04-16T00:00:00.000000000',\n",
+ " '2019-05-16T12:00:00.000000000', '2019-06-16T00:00:00.000000000',\n",
+ " '2019-07-16T12:00:00.000000000', '2019-08-16T12:00:00.000000000',\n",
+ " '2019-09-16T00:00:00.000000000', '2019-10-16T12:00:00.000000000',\n",
+ " '2019-11-16T00:00:00.000000000', '2019-12-16T12:00:00.000000000'],\n",
+ " dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-abd8d722-443d-4afe-a940-33bd2c4020ad' class='xr-section-summary-in' type='checkbox' checked><label for='section-abd8d722-443d-4afe-a940-33bd2c4020ad' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>243.3 243.3 243.3 ... 251.1 251.1</div><input id='attrs-a653ae84-93b3-4f93-9412-2287660bd735' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a653ae84-93b3-4f93-9412-2287660bd735' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-009e34e4-c3db-4a9e-aef7-b8275723199e' class='xr-var-data-in' type='checkbox'><label for='data-009e34e4-c3db-4a9e-aef7-b8275723199e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2019-07-20T13:41:51Z altered by CMOR: Treated scalar dimension: 'height'. 2019-07-20T13:41:51Z altered by CMOR: replaced missing value flag (-9e+33) with standard missing value (1e+20). 2019-07-20T13:41:51Z altered by CMOR: Converted type from 'd' to 'f'. 2019-07-20T13:41:52Z altered by CMOR: Inverted axis: lat.</dd></dl></div><div class='xr-var-data'><pre>array([[[243.3125 , 243.28125, 243.28125, ..., 243.28125, 243.28125,\n",
+ " 243.1875 ],\n",
+ " [244.375 , 244.34375, 244.28125, ..., 244.5 , 244.46875,\n",
+ " 244.4375 ],\n",
+ " [244.875 , 244.78125, 244.65625, ..., 245.03125, 245. ,\n",
+ " 244.9375 ],\n",
+ " ...,\n",
+ " [253.5 , 253.5 , 253.53125, ..., 253.375 , 253.4375 ,\n",
+ " 253.4375 ],\n",
+ " [252.84375, 252.84375, 252.875 , ..., 252.625 , 252.75 ,\n",
+ " 252.8125 ],\n",
+ " [252.25 , 252.21875, 252.28125, ..., 252.25 , 252.25 ,\n",
+ " 252.25 ]],\n",
+ "\n",
+ " [[235.71875, 235.6875 , 235.6875 , ..., 235.71875, 235.71875,\n",
+ " 235.6875 ],\n",
+ " [236.75 , 236.6875 , 236.625 , ..., 236.90625, 236.90625,\n",
+ " 236.84375],\n",
+ " [237.96875, 237.96875, 237.8125 , ..., 238.1875 , 238.125 ,\n",
+ " 238.0625 ],\n",
+ "...\n",
+ " [256.0625 , 256.125 , 256.1875 , ..., 255.8125 , 255.90625,\n",
+ " 255.96875],\n",
+ " [255.875 , 255.90625, 255.96875, ..., 255.78125, 255.8125 ,\n",
+ " 255.84375],\n",
+ " [255.59375, 255.59375, 255.625 , ..., 255.53125, 255.59375,\n",
+ " 255.625 ]],\n",
+ "\n",
+ " [[243. , 243.0625 , 243.09375, ..., 243. , 243. ,\n",
+ " 243. ],\n",
+ " [245.0625 , 245.09375, 245. , ..., 245.03125, 245.03125,\n",
+ " 245.125 ],\n",
+ " [245. , 245.125 , 245.09375, ..., 245.25 , 245.15625,\n",
+ " 245.0625 ],\n",
+ " ...,\n",
+ " [253.3125 , 253.3125 , 253.28125, ..., 253.28125, 253.3125 ,\n",
+ " 253.3125 ],\n",
+ " [252.0625 , 252.0625 , 252.09375, ..., 252. , 252. ,\n",
+ " 252. ],\n",
+ " [251.0625 , 251.0625 , 251.125 , ..., 251.0625 , 251.09375,\n",
+ " 251.09375]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2015-01-01 ... 2020-01-01</div><input id='attrs-327007e1-1576-41eb-92c9-e9d97e10b985' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-327007e1-1576-41eb-92c9-e9d97e10b985' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-698999cb-6204-4038-95ff-c62e97571f15' class='xr-var-data-in' type='checkbox'><label for='data-698999cb-6204-4038-95ff-c62e97571f15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([['2015-01-01T00:00:00.000000000', '2015-02-01T00:00:00.000000000'],\n",
+ " ['2015-02-01T00:00:00.000000000', '2015-03-01T00:00:00.000000000'],\n",
+ " ['2015-03-01T00:00:00.000000000', '2015-04-01T00:00:00.000000000'],\n",
+ " ['2015-04-01T00:00:00.000000000', '2015-05-01T00:00:00.000000000'],\n",
+ " ['2015-05-01T00:00:00.000000000', '2015-06-01T00:00:00.000000000'],\n",
+ " ['2015-06-01T00:00:00.000000000', '2015-07-01T00:00:00.000000000'],\n",
+ " ['2015-07-01T00:00:00.000000000', '2015-08-01T00:00:00.000000000'],\n",
+ " ['2015-08-01T00:00:00.000000000', '2015-09-01T00:00:00.000000000'],\n",
+ " ['2015-09-01T00:00:00.000000000', '2015-10-01T00:00:00.000000000'],\n",
+ " ['2015-10-01T00:00:00.000000000', '2015-11-01T00:00:00.000000000'],\n",
+ " ['2015-11-01T00:00:00.000000000', '2015-12-01T00:00:00.000000000'],\n",
+ " ['2015-12-01T00:00:00.000000000', '2016-01-01T00:00:00.000000000'],\n",
+ " ['2016-01-01T00:00:00.000000000', '2016-02-01T00:00:00.000000000'],\n",
+ " ['2016-02-01T00:00:00.000000000', '2016-03-01T00:00:00.000000000'],\n",
+ " ['2016-03-01T00:00:00.000000000', '2016-04-01T00:00:00.000000000'],\n",
+ " ['2016-04-01T00:00:00.000000000', '2016-05-01T00:00:00.000000000'],\n",
+ " ['2016-05-01T00:00:00.000000000', '2016-06-01T00:00:00.000000000'],\n",
+ " ['2016-06-01T00:00:00.000000000', '2016-07-01T00:00:00.000000000'],\n",
+ " ['2016-07-01T00:00:00.000000000', '2016-08-01T00:00:00.000000000'],\n",
+ " ['2016-08-01T00:00:00.000000000', '2016-09-01T00:00:00.000000000'],\n",
+ "...\n",
+ " ['2018-06-01T00:00:00.000000000', '2018-07-01T00:00:00.000000000'],\n",
+ " ['2018-07-01T00:00:00.000000000', '2018-08-01T00:00:00.000000000'],\n",
+ " ['2018-08-01T00:00:00.000000000', '2018-09-01T00:00:00.000000000'],\n",
+ " ['2018-09-01T00:00:00.000000000', '2018-10-01T00:00:00.000000000'],\n",
+ " ['2018-10-01T00:00:00.000000000', '2018-11-01T00:00:00.000000000'],\n",
+ " ['2018-11-01T00:00:00.000000000', '2018-12-01T00:00:00.000000000'],\n",
+ " ['2018-12-01T00:00:00.000000000', '2019-01-01T00:00:00.000000000'],\n",
+ " ['2019-01-01T00:00:00.000000000', '2019-02-01T00:00:00.000000000'],\n",
+ " ['2019-02-01T00:00:00.000000000', '2019-03-01T00:00:00.000000000'],\n",
+ " ['2019-03-01T00:00:00.000000000', '2019-04-01T00:00:00.000000000'],\n",
+ " ['2019-04-01T00:00:00.000000000', '2019-05-01T00:00:00.000000000'],\n",
+ " ['2019-05-01T00:00:00.000000000', '2019-06-01T00:00:00.000000000'],\n",
+ " ['2019-06-01T00:00:00.000000000', '2019-07-01T00:00:00.000000000'],\n",
+ " ['2019-07-01T00:00:00.000000000', '2019-08-01T00:00:00.000000000'],\n",
+ " ['2019-08-01T00:00:00.000000000', '2019-09-01T00:00:00.000000000'],\n",
+ " ['2019-09-01T00:00:00.000000000', '2019-10-01T00:00:00.000000000'],\n",
+ " ['2019-10-01T00:00:00.000000000', '2019-11-01T00:00:00.000000000'],\n",
+ " ['2019-11-01T00:00:00.000000000', '2019-12-01T00:00:00.000000000'],\n",
+ " ['2019-12-01T00:00:00.000000000', '2020-01-01T00:00:00.000000000']],\n",
+ " dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-904a63a6-8c53-4c21-b5e4-c51450e96635' class='xr-section-summary-in' type='checkbox' ><label for='section-904a63a6-8c53-4c21-b5e4-c51450e96635' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cdbda816-5bf1-4b02-add4-24b3f086808c' class='xr-index-data-in' type='checkbox'/><label for='index-cdbda816-5bf1-4b02-add4-24b3f086808c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.28422753251364, -88.35700351866494, -87.42430374606988,\n",
+ " -86.49036676628116, -85.55596048489265, -84.6213271076488,\n",
+ " -83.68656681656385, -82.75172847343066, -81.81683872860319,\n",
+ " -80.8819133467975,\n",
+ " ...\n",
+ " 80.8819133467975, 81.81683872860319, 82.75172847343066,\n",
+ " 83.68656681656385, 84.6213271076488, 85.55596048489265,\n",
+ " 86.49036676628116, 87.42430374606988, 88.35700351866494,\n",
+ " 89.28422753251364],\n",
+ " dtype='float64', name='lat', length=192))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c48bcf8a-1877-4bf6-af0a-a6bc98992d13' class='xr-index-data-in' type='checkbox'/><label for='index-c48bcf8a-1877-4bf6-af0a-a6bc98992d13' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.0, 0.9375, 1.875, 2.8125, 3.75, 4.6875, 5.625,\n",
+ " 6.5625, 7.5, 8.4375,\n",
+ " ...\n",
+ " 350.625, 351.5625, 352.5, 353.4375, 354.375, 355.3125, 356.25,\n",
+ " 357.1875, 358.125, 359.0625],\n",
+ " dtype='float64', name='lon', length=384))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9226cd1b-7299-438f-a895-c2b06c2c7af7' class='xr-index-data-in' type='checkbox'/><label for='index-9226cd1b-7299-438f-a895-c2b06c2c7af7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2015-01-16 12:00:00', '2015-02-15 00:00:00',\n",
+ " '2015-03-16 12:00:00', '2015-04-16 00:00:00',\n",
+ " '2015-05-16 12:00:00', '2015-06-16 00:00:00',\n",
+ " '2015-07-16 12:00:00', '2015-08-16 12:00:00',\n",
+ " '2015-09-16 00:00:00', '2015-10-16 12:00:00',\n",
+ " '2015-11-16 00:00:00', '2015-12-16 12:00:00',\n",
+ " '2016-01-16 12:00:00', '2016-02-15 12:00:00',\n",
+ " '2016-03-16 12:00:00', '2016-04-16 00:00:00',\n",
+ " '2016-05-16 12:00:00', '2016-06-16 00:00:00',\n",
+ " '2016-07-16 12:00:00', '2016-08-16 12:00:00',\n",
+ " '2016-09-16 00:00:00', '2016-10-16 12:00:00',\n",
+ " '2016-11-16 00:00:00', '2016-12-16 12:00:00',\n",
+ " '2017-01-16 12:00:00', '2017-02-15 00:00:00',\n",
+ " '2017-03-16 12:00:00', '2017-04-16 00:00:00',\n",
+ " '2017-05-16 12:00:00', '2017-06-16 00:00:00',\n",
+ " '2017-07-16 12:00:00', '2017-08-16 12:00:00',\n",
+ " '2017-09-16 00:00:00', '2017-10-16 12:00:00',\n",
+ " '2017-11-16 00:00:00', '2017-12-16 12:00:00',\n",
+ " '2018-01-16 12:00:00', '2018-02-15 00:00:00',\n",
+ " '2018-03-16 12:00:00', '2018-04-16 00:00:00',\n",
+ " '2018-05-16 12:00:00', '2018-06-16 00:00:00',\n",
+ " '2018-07-16 12:00:00', '2018-08-16 12:00:00',\n",
+ " '2018-09-16 00:00:00', '2018-10-16 12:00:00',\n",
+ " '2018-11-16 00:00:00', '2018-12-16 12:00:00',\n",
+ " '2019-01-16 12:00:00', '2019-02-15 00:00:00',\n",
+ " '2019-03-16 12:00:00', '2019-04-16 00:00:00',\n",
+ " '2019-05-16 12:00:00', '2019-06-16 00:00:00',\n",
+ " '2019-07-16 12:00:00', '2019-08-16 12:00:00',\n",
+ " '2019-09-16 00:00:00', '2019-10-16 12:00:00',\n",
+ " '2019-11-16 00:00:00', '2019-12-16 12:00:00'],\n",
+ " dtype='datetime64[ns]', name='time', freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d9ddc508-f8c9-4feb-bb61-45e907c319a4' class='xr-section-summary-in' type='checkbox' ><label for='section-d9ddc508-f8c9-4feb-bb61-45e907c319a4' class='xr-section-summary' >Attributes: <span>(47)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>ScenarioMIP AerChemMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>60265.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>60265.0</dd><dt><span>contact :</span></dt><dd>cmip6-mpi-esm@dkrz.de</dd><dt><span>creation_date :</span></dt><dd>2019-07-20T13:41:51Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.30</dd><dt><span>experiment :</span></dt><dd>gap-filling scenario reaching 7.0 based on SSP3</dd><dt><span>experiment_id :</span></dt><dd>ssp370</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.DKRZ.MPI-ESM1-2-HR.ssp370.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>gn</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2019-07-20T13:41:51Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>Deutsches Klimarechenzentrum, Hamburg 20146, Germany</dd><dt><span>institution_id :</span></dt><dd>DKRZ</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>historical</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>MPI-ESM1-2-HR</dd><dt><span>parent_time_units :</span></dt><dd>days since 1850-1-1 00:00:00</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>project_id :</span></dt><dd>CMIP6</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>references :</span></dt><dd>MPI-ESM: Mauritsen, T. et al. (2019), Developments in the MPIâ€M Earth System Model version 1.2 (MPIâ€ESM1.2) and Its Response to Increasing CO2, J. Adv. Model. Earth Syst.,11, 998-1038, doi:10.1029/2018MS001400,\n",
+ "Mueller, W.A. et al. (2018): A highâ€resolution version of the Max Planck Institute Earth System Model MPIâ€ESM1.2â€HR. J. Adv. Model. EarthSyst.,10,1383–1413, doi:10.1029/2017MS001217</dd><dt><span>source :</span></dt><dd>MPI-ESM1.2-HR (2017): \n",
+ "aerosol: none, prescribed MACv2-SP\n",
+ "atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa)\n",
+ "atmosChem: none\n",
+ "land: JSBACH3.20\n",
+ "landIce: none/prescribed\n",
+ "ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 longitude/latitude; 40 levels; top grid cell 0-12 m)\n",
+ "ocnBgchem: HAMOCC6\n",
+ "seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model)</dd><dt><span>source_id :</span></dt><dd>MPI-ESM1-2-HR</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(09 May 2019) MD5:e6ef8ececc8f338646ebfb3aeed36bfc</dd><dt><span>title :</span></dt><dd>MPI-ESM1-2-HR output prepared for CMIP6</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by DKRZ is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.4.0</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/d6f0f6b2-b4c2-460b-bc5e-f1c72f932399</dd></dl></div></li></ul></div></div>"
+ ],
+ "text/plain": [
+ "<xarray.Dataset> Size: 18MB\n",
+ "Dimensions: (lat: 192, bnds: 2, lon: 384, time: 60)\n",
+ "Coordinates:\n",
+ " lat_bnds (lat, bnds) float64 3kB -89.75 -88.82 -88.82 ... 88.82 89.75\n",
+ " lon_bnds (lon, bnds) float64 6kB -0.4688 0.4688 0.4688 ... 358.6 359.5\n",
+ " height float64 8B 2.0\n",
+ " * lat (lat) float64 2kB -89.28 -88.36 -87.42 ... 87.42 88.36 89.28\n",
+ " * lon (lon) float64 3kB 0.0 0.9375 1.875 2.812 ... 357.2 358.1 359.1\n",
+ " * time (time) datetime64[ns] 480B 2015-01-16T12:00:00 ... 2019-12-16T...\n",
+ "Dimensions without coordinates: bnds\n",
+ "Data variables:\n",
+ " tas (time, lat, lon) float32 18MB 243.3 243.3 243.3 ... 251.1 251.1\n",
+ " time_bnds (time, bnds) datetime64[ns] 960B 2015-01-01 ... 2020-01-01\n",
+ "Attributes: (12/47)\n",
+ " Conventions: CF-1.7 CMIP-6.2\n",
+ " activity_id: ScenarioMIP AerChemMIP\n",
+ " branch_method: standard\n",
+ " branch_time_in_child: 60265.0\n",
+ " branch_time_in_parent: 60265.0\n",
+ " contact: cmip6-mpi-esm@dkrz.de\n",
+ " ... ...\n",
+ " title: MPI-ESM1-2-HR output prepared for CMIP6\n",
+ " variable_id: tas\n",
+ " variant_label: r1i1p1f1\n",
+ " license: CMIP6 model data produced by DKRZ is licensed und...\n",
+ " cmor_version: 3.4.0\n",
+ " tracking_id: hdl:21.14100/d6f0f6b2-b4c2-460b-bc5e-f1c72f932399"
+ ]
+ },
+ "execution_count": 40,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import xarray as xr\n",
+ "xr.open_dataset(\"lossy_compressed.nc\").load()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "49a2b8a1-6533-421c-bfdd-fc814559e4d7",
+ "metadata": {},
+ "source": [
+ "We can see that\n",
+ "\n",
+ "- uncompressed data is 16MB, compressed is 6MB, lossy compressed is 4MB.\n",
+ "- the accuray is on the second decimal: 243.30435 becomes 243.3125"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "040bc746-f6ca-4a42-a867-2f4182f36fa9",
+ "metadata": {},
+ "source": [
+ "### Interest in a region of global ESM output stored in records\n",
+ "\n",
+ "A \"record\" refers to the GRIB-record where the entire global field is stored as one binary chunk. A chunk is the most fine-grained level of data access possible.\n",
+ "\n",
+ "Especially for high-resolution data, clients may not want to retrieve the full entity of a storage chunk, e.g. an entire global field or an entire month on hourly data, because this results in large data volumes. In such cases, where we know the data access *pattern*, we can adapt the chunk setting of our provided zarr data set to the use case. The cloudify service allows to provide smaller chunk sizes to clients than the orignal storage chunk sizes by providing some server-side computing resources for rechunking and acting as an intermediate layer between data and client. Although the splitting of storage chunks reduces performance on the server, the benefit of bandwidth reduction can be more important."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0ab1274e-433c-49e8-825f-6600888ad3e6",
+ "metadata": {},
+ "source": [
+ "**Chunk setting**\n",
+ "\n",
+ "Best practice is to set the chunks when opening the data. For our test zarr dataset, we split the chunks in both spatial dimensions into half of the original. In each dimension, a chunk needs to cover at least 1 increment i.e. has to be an integer > 0. \n",
+ "\n",
+ "With the `chunks` keyword in the `open_mfdataset` command, it is controlled how the dataset is chunked. These chunks are mapped to *zarr* chunks of the *zarr* API. \n",
+ "\n",
+ "In our example script, we control that chunk setting through specific environment variables:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "84fbf2ff-f626-488a-87ee-fc62492274ea",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "new_lon_chunk_size=int(len(ds[\"lon\"])/2)\n",
+ "new_lat_chunk_size=int(len(ds[\"lat\"])/2)\n",
+ "print(new_lon_chunk_size, new_lat_chunk_size)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a7ed2bfb-3254-4a13-ae99-3c3caccb0f6a",
+ "metadata": {},
+ "source": [
+ "We set these as environment variables and restart our app which finds these."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "b702311b-bde0-4587-a823-dc61d0c65d51",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "os.environ[\"XPUBLISH_LON_CHUNK_SIZE\"]=str(new_lon_chunk_size)\n",
+ "os.environ[\"XPUBLISH_LAT_CHUNK_SIZE\"]=str(new_lat_chunk_size)\n",
+ "#to get back storage chunks:\n",
+ "#del os.environ[\"XPUBLISH_LON_CHUNK_SIZE\"]\n",
+ "#del os.environ[\"XPUBLISH_LAT_CHUNK_SIZE\"]\n",
+ "\n",
+ "#kill the existing process"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a74dc51c-f9ce-439c-8217-1724ae32009c",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "!ps -ef | grep cloudify"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "7cb479a6-366b-4a5c-908b-a649a6c0f057",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "!kill 814927"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ba0e00cc-e6a3-42ac-bd50-a068d93166d2",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "%%bash --bg\n",
+ "source activate /work/bm0021/conda-envs/cloudify\n",
+ "python xpublish_example.py \\\n",
+ " example \\\n",
+ " /work/ik1017/CMIP6/data/CMIP6/ScenarioMIP/DKRZ/MPI-ESM1-2-HR/ssp370/r1i1p1f1/Amon/tas/gn/v20190710/*.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "35592ae1-4873-4d08-bdae-b28130e924b6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds2=xr.open_zarr(\n",
+ " zarr_url,\n",
+ " consolidated=True,\n",
+ " storage_options=storage_options,\n",
+ " chunks={}\n",
+ ")\n",
+ "ds2"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "46eaa475-6694-4110-a8a2-557658e658d2",
+ "metadata": {},
+ "source": [
+ "### Towards virtually, highly aggregated datasets that include multiple variables of the same kind\n",
+ "\n",
+ "Based on experience, large aggregations are beneficial for data analysis as users can skip finding and merging data sources. E.g. to train an AI model, it helps to simplify the random access within a complete experiment. With cloudify, we can realize a virtual, highly aggregated, dataset that covers the full time series of all variables that share dimensions.\n",
+ "\n",
+ "In our example, we can try to concat and merge *all* monthly atmospheric variables more variables. For that, we use a wildcard for variables in the DRS path."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "806f61be-1f47-4aa5-a029-b2d28e9bac55",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "!ps -ef | grep cloudify"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "47ce9108-5ec3-48f4-88aa-a5991b8dbe18",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "#to get back storage chunks:\n",
+ "del os.environ[\"XPUBLISH_LON_CHUNK_SIZE\"]\n",
+ "del os.environ[\"XPUBLISH_LAT_CHUNK_SIZE\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "892786b9-ca5b-40aa-8937-40be7e5c56a8",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "%%bash --bg\n",
+ "source activate /work/bm0021/conda-envs/cloudify\n",
+ "python xpublish_example.py \\\n",
+ " example \\\n",
+ " /work/ik1017/CMIP6/data/CMIP6/ScenarioMIP/DKRZ/MPI-ESM1-2-HR/ssp370/r1i1p1f1/Amon/*/gn/v20190710/*.nc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "8979a320-71d3-4c80-a7d8-f130b9de2e71",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "ds=xr.open_zarr(\n",
+ " zarr_url,\n",
+ " consolidated=True,\n",
+ " storage_options=storage_options\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a624fa43-e9e9-4c56-b697-7c8820592482",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "ds"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "fb6bc1e9-b4e6-4614-9e57-590ddcd4cdca",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "ds.nbytes/1024**3"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "feacaed0-df8d-4e52-af8c-acd094cac6f4",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "ds.isel(time=0,plev=0,lev=0).drop([\"height\",\"ap\",\"ap_bnds\",\"b\",\"b_bnds\",\"lev_bnds\"]).load()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "7ce5826a-80a3-4aea-86c4-4b6de8b229e2",
+ "metadata": {},
+ "source": [
+ "We see that\n",
+ "\n",
+ "- we host O(100GB) of data \"just like that\" because of lazy data access.\n",
+ "- the memory usage increases with the number of dask chunks to keep in memory. This is the bottle neck for our data server.\n",
+ "- the more data we aggregate into one dataset, the less endpoints we provide. Thus, the catalog of endpoints becomes small and we use the zarr datasets as the *real* catalogs.\n",
+ " - this simplifies random access which can be crucial for training of AI models"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0d0f68f0-135c-47c0-9059-e9870fb85a49",
+ "metadata": {},
+ "source": [
+ "In the next episode, we use *kerchunks* to avoid repeatedly merging these files when opening and instead use a once-*prepared* virtual dataset representation of this aggrgeation."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "5655cceb-80c1-42d7-926a-2926f2d3feba",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "cloudify",
+ "language": "python",
+ "name": "cloudify"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.0"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/workshop/4_kerchunk-input-kerchunk-api.ipynb b/workshop/4_kerchunk-input-kerchunk-api.ipynb
new file mode 100644
index 0000000..0b849a9
--- /dev/null
+++ b/workshop/4_kerchunk-input-kerchunk-api.ipynb
@@ -0,0 +1,16517 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "1bc2dd78-97d7-4b39-bf35-03dcacc767f9",
+ "metadata": {},
+ "source": [
+ "## 4. Kerchunk input data and the kerchunk API\n",
+ "\n",
+ "Within this series, we cannot explain how kerchunking works. For now, it is only important to understand that it leverages the zarr benefits of both small memory requirements for opening as well as consolidated metadata for virtual aggregation.\n",
+ "\n",
+ "We now design the script such that it \n",
+ "- opens *kerchunk* references instead of files\n",
+ "- enables access trough the kerchunk API\n",
+ "\n",
+ "With the kerchunk API, we do not necessarily need a dask cluster anymore (but without a dask cluster, the dask API will not work)."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "505d07ff-db38-4938-8b65-c18ca0391599",
+ "metadata": {},
+ "source": [
+ "**Differences to the first example**:\n",
+ "\n",
+ "- we open data through the so called *lazy reference* mapper with\n",
+ " ```python\n",
+ " fsspec.get_mapper(\n",
+ " lazy=True,\n",
+ " )\n",
+ " ```\n",
+ " which we pass to xarray afterwards. This only works for kerchunked input data.\n",
+ "- we add a *dict* of fspec mappern to the kerchunk plguin by setting `kp.mapper_dict`\n",
+ " Xpublish will recognize the"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "571a82ea-d7bc-42e3-8169-ae22ef999065",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Overwriting xpublish_references.py\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%writefile xpublish_references.py\n",
+ "\n",
+ "port=9000\n",
+ "ssl_keyfile=\"/work/bm0021/k204210/cloudify/workshop/key.pem\"\n",
+ "ssl_certfile=\"/work/bm0021/k204210/cloudify/workshop/cert.pem\"\n",
+ "\n",
+ "from cloudify.plugins.stacer import *\n",
+ "from cloudify.utils.daskhelper import *\n",
+ "from cloudify.plugins.kerchunk import *\n",
+ "import xarray as xr\n",
+ "import xpublish as xp\n",
+ "import asyncio\n",
+ "import nest_asyncio\n",
+ "import sys\n",
+ "import os\n",
+ "\n",
+ "nest_asyncio.apply()\n",
+ "\n",
+ "if __name__ == \"__main__\": # This avoids infinite subprocess creation\n",
+ " #import dask\n",
+ " #zarrcluster = asyncio.get_event_loop().run_until_complete(get_dask_cluster())\n",
+ " #os.environ[\"ZARR_ADDRESS\"]=zarrcluster.scheduler._address\n",
+ " \n",
+ " dsname=sys.argv[1]\n",
+ " glob_inp=sys.argv[2]\n",
+ "\n",
+ " dsdict={}\n",
+ " source=\"reference::/\"+glob_inp\n",
+ " fsmap = fsspec.get_mapper(\n",
+ " source,\n",
+ " remote_protocol=\"file\",\n",
+ " lazy=True,\n",
+ " cache_size=0\n",
+ " )\n",
+ " ds=xr.open_dataset(\n",
+ " fsmap,\n",
+ " engine=\"zarr\",\n",
+ " chunks=\"auto\",\n",
+ " consolidated=False \n",
+ " )\n",
+ " kp = KerchunkPass()\n",
+ " kp.mapper_dict = {source:fsmap}\n",
+ " ds=ds.drop_encoding() \n",
+ " ds.encoding[\"source\"]=source\n",
+ " dsdict[dsname]=ds\n",
+ " \n",
+ " collection = xp.Rest(dsdict)\n",
+ " collection.register_plugin(Stac())\n",
+ " collection.register_plugin(kp)\n",
+ " collection.serve(\n",
+ " host=\"0.0.0.0\",\n",
+ " port=port,\n",
+ " ssl_keyfile=ssl_keyfile,\n",
+ " ssl_certfile=ssl_certfile\n",
+ " )"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "ca64c11f-0846-4ddd-9e60-4b22dba8b32c",
+ "metadata": {},
+ "source": [
+ "We run this app with ERA5 data:\n",
+ "\n",
+ "```\n",
+ "dsname=\"era5\"\n",
+ "glob_inp=\"/work/bm1344/DKRZ/kerchunks_single/testera/E5_sf_an_1D.parquet\"\n",
+ "```\n",
+ "\n",
+ "by applying:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "5da13d6b-05f1-4b3b-aecd-1ac3bb635526",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "%%bash --bg\n",
+ "source activate /work/bm0021/conda-envs/cloudify\n",
+ "python xpublish_references.py era5 /work/bm1344/DKRZ/kerchunks_single/testera/E5_sf_an_1D.parquet"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a7ab712d-eff9-4a8e-8f66-fd603e2ab658",
+ "metadata": {},
+ "source": [
+ "If sth goes wrong, you can check for *cloudify* processes that you can *kill* by ID."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "id": "9a43c4ce-be08-4493-8dd5-a3789f8c0647",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "k204210 1753538 1752638 0 08:07 ? 00:00:26 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-16868865-4ac9-4f10-9d8e-59c1bb69e85a.json\n",
+ "k204210 1753566 1752638 0 08:07 ? 00:00:18 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-4fe110eb-67f5-471d-843b-d47538c216e2.json\n",
+ "k204210 1761151 1753566 0 15:57 pts/2 00:00:00 /bin/bash -c ps -ef | grep cloudify\n",
+ "k204210 1761153 1761151 0 15:57 pts/2 00:00:00 grep cloudify\n"
+ ]
+ }
+ ],
+ "source": [
+ "!ps -ef | grep cloudify"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "af33c134-f4ba-42f7-9687-7bb9948d5dfe",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "!kill 1539362"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "8e797fa6-8621-46c7-9dce-5b79adf714e3",
+ "metadata": {},
+ "source": [
+ "**Data access via the kerchunk API**\n",
+ "\n",
+ "You can get the host url with the hostname of the levante node you work on and the port that you used for the app:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "bd1abfca-5f10-4dfc-a71f-90f0257d10d1",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "https://l40354.lvt.dkrz.de:9000\n"
+ ]
+ }
+ ],
+ "source": [
+ "port=9000\n",
+ "hostname=!echo $HOSTNAME\n",
+ "hosturl=\"https://\"+hostname[0]+\":\"+str(port)\n",
+ "print(hosturl)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "84951ac0-8e70-4917-892a-01b236f7c0ba",
+ "metadata": {},
+ "source": [
+ "We have to tell the python programs to do not verify ssl certificates for our purposes:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "e3befb5e-99ec-4bda-aa47-303641a66320",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "storage_options=dict(verify_ssl=False)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "093ceaf2-1bda-40c7-9df5-7cbe8cf9dc66",
+ "metadata": {},
+ "source": [
+ "**Xarray**"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "878d421a-c4a4-4999-9f7e-e101d6b58082",
+ "metadata": {},
+ "source": [
+ "Our era dataset is available via both the *zarr* API **and** the *kerchunk* API.\n",
+ "They are named similar:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "id": "73527b45-950c-4546-9a7e-5f1877cff132",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "https://l40354.lvt.dkrz.de:9000/datasets/era5/kerchunk\n"
+ ]
+ }
+ ],
+ "source": [
+ "dsname=\"era5\"\n",
+ "zarr_url='/'.join([hosturl,\"datasets\",dsname,\"zarr\"])\n",
+ "kerchunk_url='/'.join([hosturl,\"datasets\",dsname,\"kerchunk\"])\n",
+ "print(kerchunk_url)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "482f8b5c-0186-494f-91b0-e5a03c370004",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "import xarray as xr\n",
+ "ds=xr.open_zarr(\n",
+ " kerchunk_url,\n",
+ " consolidated=True,\n",
+ " storage_options=storage_options\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "3b7405e3-1957-46ef-b564-942850fec433",
+ "metadata": {
+ "collapsed": true,
+ "jupyter": {
+ "outputs_hidden": true
+ },
+ "tags": []
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
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+ "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+ ".xr-attrs dt {\n",
+ " font-weight: normal;\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt:hover span {\n",
+ " display: inline-block;\n",
+ " background: var(--xr-background-color);\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dd {\n",
+ " grid-column: 2;\n",
+ " white-space: pre-wrap;\n",
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+ "}\n",
+ "\n",
+ ".xr-icon-database,\n",
+ ".xr-icon-file-text2,\n",
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+ " display: inline-block;\n",
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+ " stroke-width: 0;\n",
+ " stroke: currentColor;\n",
+ " fill: currentColor;\n",
+ "}\n",
+ "</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 5TB\n",
+ "Dimensions: (time: 30955, cell: 542080)\n",
+ "Coordinates:\n",
+ " lat (cell) float64 4MB dask.array<chunksize=(542080,), meta=np.ndarray>\n",
+ " lon (cell) float64 4MB dask.array<chunksize=(542080,), meta=np.ndarray>\n",
+ " * time (time) datetime64[ns] 248kB 1940-01-01T11:30:00 ... 2024-09-30T1...\n",
+ "Dimensions without coordinates: cell\n",
+ "Data variables: (12/40)\n",
+ " 100u (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " 100v (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " 10u (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " 10v (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " 2d (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " 2t (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " ... ...\n",
+ " swvl4 (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " tcc (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " tco3 (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " tcw (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " tcwv (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " tsn (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ "Attributes: (12/22)\n",
+ " project: ECMWF Re-Analysis\n",
+ " project_id: ERA\n",
+ " institution_id: ECMWF-DKRZ\n",
+ " institution: Data from European Centre for Medium-Range Weather ...\n",
+ " source_id: IFS\n",
+ " source: ECMWF Integrated Forecast System (IFS) CY41R2\n",
+ " ... ...\n",
+ " format: kerchunk\n",
+ " product: reanalysis\n",
+ " responsible_persons: Angelika Heil, Fabian Wachsmann\n",
+ " title: The DKRZ ERA5 data pool. Generated using Copernicus...\n",
+ " license: The ERA5 data are published with the Copernicus Pro...\n",
+ " references: Hersbach, H., Bell, B., Berrisford, P., Hirahara, S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-30d57a25-4280-4806-ae88-0a49da554150' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-30d57a25-4280-4806-ae88-0a49da554150' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 30955</li><li><span>cell</span>: 542080</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-db3cd2e9-b36c-4f20-b22f-87a44588f51a' class='xr-section-summary-in' type='checkbox' checked><label for='section-db3cd2e9-b36c-4f20-b22f-87a44588f51a' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(542080,), meta=np.ndarray></div><input id='attrs-c9dc07d3-1483-4b75-bf98-c0b12a1d47ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9dc07d3-1483-4b75-bf98-c0b12a1d47ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8269510f-be78-48b9-a1d9-27d8c5a75ee4' class='xr-var-data-in' type='checkbox'><label for='data-8269510f-be78-48b9-a1d9-27d8c5a75ee4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>source :</span></dt><dd>../../../../../pool/data/ERA5/E5/sf/an/1M/167/E5sf00_1M_1940_167.grb</dd><dt><span>filter_by_keys :</span></dt><dd>{}</dd><dt><span>encode_cf :</span></dt><dd>['parameter', 'time', 'geography', 'vertical']</dd><dt><span>original_shape :</span></dt><dd>[542080]</dd><dt><span>dtype :</span></dt><dd>float64</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 4.14 MiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (542080,) </td>\n",
+ " <td> (542080,) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
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+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(542080,), meta=np.ndarray></div><input id='attrs-6032c26c-4ca7-4610-9de0-224e1a74642a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6032c26c-4ca7-4610-9de0-224e1a74642a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67edb082-0b19-48fe-b926-da7610e975fe' class='xr-var-data-in' type='checkbox'><label for='data-67edb082-0b19-48fe-b926-da7610e975fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>source :</span></dt><dd>../../../../../pool/data/ERA5/E5/sf/an/1M/167/E5sf00_1M_1940_167.grb</dd><dt><span>filter_by_keys :</span></dt><dd>{}</dd><dt><span>encode_cf :</span></dt><dd>['parameter', 'time', 'geography', 'vertical']</dd><dt><span>original_shape :</span></dt><dd>[542080]</dd><dt><span>dtype :</span></dt><dd>float64</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 4.14 MiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (542080,) </td>\n",
+ " <td> (542080,) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
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+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1940-01-01T11:30:00 ... 2024-09-...</div><input id='attrs-4e90fc37-58da-45f2-b451-371d833105df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e90fc37-58da-45f2-b451-371d833105df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb1b51bf-95b2-4f9f-b8a4-f59256154101' class='xr-var-data-in' type='checkbox'><label for='data-cb1b51bf-95b2-4f9f-b8a4-f59256154101' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>1970-01-01T00:00:00.000000000</dd></dl></div><div class='xr-var-data'><pre>array(['1940-01-01T11:30:00.000000000', '1940-01-02T11:30:00.000000000',\n",
+ " '1940-01-03T11:30:00.000000000', ..., '2024-09-28T11:30:00.000000000',\n",
+ " '2024-09-29T11:30:00.000000000', '2024-09-30T11:30:00.000000000'],\n",
+ " dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c1641abd-8556-4656-816d-2ef39531f3f6' class='xr-section-summary-in' type='checkbox' ><label for='section-c1641abd-8556-4656-816d-2ef39531f3f6' class='xr-section-summary' >Data variables: <span>(40)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>100u</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-2c857175-f9dc-491c-98d7-444144b34cfa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c857175-f9dc-491c-98d7-444144b34cfa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10065208-4a4e-48b6-8d13-ea41c3162bf9' class='xr-var-data-in' type='checkbox'><label for='data-10065208-4a4e-48b6-8d13-ea41c3162bf9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>100u</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>100 metre U wind component</dd><dt><span>cfVarName :</span></dt><dd>u100</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
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+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>100v</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-0ad41a08-5a15-43d8-82a6-654efa95630a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ad41a08-5a15-43d8-82a6-654efa95630a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-770aac4c-2864-4d4e-bd21-0300d6a27bc5' class='xr-var-data-in' type='checkbox'><label for='data-770aac4c-2864-4d4e-bd21-0300d6a27bc5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>100v</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>100 metre V wind component</dd><dt><span>cfVarName :</span></dt><dd>v100</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
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+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>10u</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-30638e3e-5442-4723-916e-8234cbb0f0a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30638e3e-5442-4723-916e-8234cbb0f0a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66e918ff-50e4-4740-a9fa-954c297803c8' class='xr-var-data-in' type='checkbox'><label for='data-66e918ff-50e4-4740-a9fa-954c297803c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>10u</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>10 metre U wind component</dd><dt><span>cfVarName :</span></dt><dd>u10</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " </tbody>\n",
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+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>10v</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-5ed218d2-809e-4162-9488-3cc743d6713b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ed218d2-809e-4162-9488-3cc743d6713b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bdf75538-c11f-41b5-84cb-5cb0137ccab6' class='xr-var-data-in' type='checkbox'><label for='data-bdf75538-c11f-41b5-84cb-5cb0137ccab6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>10v</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>10 metre V wind component</dd><dt><span>cfVarName :</span></dt><dd>v10</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
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+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>2d</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-79342d59-1ba1-4fa2-817f-7757d32998d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79342d59-1ba1-4fa2-817f-7757d32998d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4b1a94b-a518-4197-98e0-46628ac38d9e' class='xr-var-data-in' type='checkbox'><label for='data-e4b1a94b-a518-4197-98e0-46628ac38d9e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>2d</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>2 metre dewpoint temperature</dd><dt><span>cfVarName :</span></dt><dd>d2m</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
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+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
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+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
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+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <td> </td>\n",
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+ " <th> Chunk </th>\n",
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+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
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+ " <tr>\n",
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+ " <thead>\n",
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+ " <tr>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <th> Array </th>\n",
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+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
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+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
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+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " <tr>\n",
+ " <td>\n",
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+ " <thead>\n",
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+ " <tbody>\n",
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+ " <tr>\n",
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+ " <th> Shape </th>\n",
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+ " <th> Data type </th>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <th> Array </th>\n",
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+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
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+ " <td> 125.02 GiB </td>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
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+ " <tbody>\n",
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+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
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+ " <td> (1, 542080) </td>\n",
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+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " <tr>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <td> </td>\n",
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+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
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+ " <tr>\n",
+ " <th> Bytes </th>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
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+ " <tbody>\n",
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+ " <tr>\n",
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+ " <td> 125.02 GiB </td>\n",
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+ " <th> Shape </th>\n",
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+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " <tr>\n",
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+ " <tbody>\n",
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+ " <td> 125.02 GiB </td>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
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+ " <tr>\n",
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+ " <tr>\n",
+ " <th> Data type </th>\n",
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+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl2</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-8f36cd6a-4ab8-4410-8c28-845e7c70933b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f36cd6a-4ab8-4410-8c28-845e7c70933b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95e3f7ec-257e-4fbd-87c8-ffe9ec57dc98' class='xr-var-data-in' type='checkbox'><label for='data-95e3f7ec-257e-4fbd-87c8-ffe9ec57dc98' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>swvl2</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 2</dd><dt><span>cfVarName :</span></dt><dd>swvl2</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
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+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
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+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl3</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-def43d30-2d42-416d-99ae-dc2e5a2206bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-def43d30-2d42-416d-99ae-dc2e5a2206bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2eff8d7e-0b93-4120-82d3-096d5360a262' class='xr-var-data-in' type='checkbox'><label for='data-2eff8d7e-0b93-4120-82d3-096d5360a262' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>swvl3</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 3</dd><dt><span>cfVarName :</span></dt><dd>swvl3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
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+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
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+ " <tr>\n",
+ " <th> Data type </th>\n",
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+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcc</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-9402fbab-b905-4675-ab37-a4daed9a96fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9402fbab-b905-4675-ab37-a4daed9a96fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b125dd6-9998-4775-b688-3f00af47d6c3' class='xr-var-data-in' type='checkbox'><label for='data-2b125dd6-9998-4775-b688-3f00af47d6c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>tcc</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Total cloud cover</dd><dt><span>cfName :</span></dt><dd>cloud_area_fraction</dd><dt><span>cfVarName :</span></dt><dd>tcc</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
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+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tco3</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-5310a553-a5f4-4297-a383-1e1e56eaca33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5310a553-a5f4-4297-a383-1e1e56eaca33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9c0f425-7fbb-46a4-b04d-37346ffaa9ea' class='xr-var-data-in' type='checkbox'><label for='data-d9c0f425-7fbb-46a4-b04d-37346ffaa9ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>tco3</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column ozone</dd><dt><span>cfName :</span></dt><dd>atmosphere_mass_content_of_ozone</dd><dt><span>cfVarName :</span></dt><dd>tco3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcw</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-3df96e27-88df-4041-b3eb-55c8c48f2962' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3df96e27-88df-4041-b3eb-55c8c48f2962' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7599a032-1622-432c-bc4f-3f8a3f19f145' class='xr-var-data-in' type='checkbox'><label for='data-7599a032-1622-432c-bc4f-3f8a3f19f145' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>tcw</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column water</dd><dt><span>cfVarName :</span></dt><dd>tcw</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
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+ " <tr>\n",
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+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tsn</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-a6471190-2e7d-4823-9023-15e1d59fe0f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6471190-2e7d-4823-9023-15e1d59fe0f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcbb0f13-cfa0-40c4-b375-13923ce74580' class='xr-var-data-in' type='checkbox'><label for='data-fcbb0f13-cfa0-40c4-b375-13923ce74580' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>tsn</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Temperature of snow layer</dd><dt><span>cfName :</span></dt><dd>temperature_in_surface_snow</dd><dt><span>cfVarName :</span></dt><dd>tsn</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
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+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
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+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
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+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
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+ " <text x=\"60.000000\" y=\"55.312236\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >542080</text>\n",
+ " <text x=\"140.000000\" y=\"17.656118\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,17.656118)\">30955</text>\n",
+ "</svg>\n",
+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-28b2b268-8d08-4bad-b2ac-9753d6b51df0' class='xr-section-summary-in' type='checkbox' ><label for='section-28b2b268-8d08-4bad-b2ac-9753d6b51df0' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2964085f-8fe5-4c7e-a288-d7e2e9b35631' class='xr-index-data-in' type='checkbox'/><label for='index-2964085f-8fe5-4c7e-a288-d7e2e9b35631' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['1940-01-01 11:30:00', '1940-01-02 11:30:00',\n",
+ " '1940-01-03 11:30:00', '1940-01-04 11:30:00',\n",
+ " '1940-01-05 11:30:00', '1940-01-06 11:30:00',\n",
+ " '1940-01-07 11:30:00', '1940-01-08 11:30:00',\n",
+ " '1940-01-09 11:30:00', '1940-01-10 11:30:00',\n",
+ " ...\n",
+ " '2024-09-21 11:30:00', '2024-09-22 11:30:00',\n",
+ " '2024-09-23 11:30:00', '2024-09-24 11:30:00',\n",
+ " '2024-09-25 11:30:00', '2024-09-26 11:30:00',\n",
+ " '2024-09-27 11:30:00', '2024-09-28 11:30:00',\n",
+ " '2024-09-29 11:30:00', '2024-09-30 11:30:00'],\n",
+ " dtype='datetime64[ns]', name='time', length=30955, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4996dabb-5ee0-4e5d-aff0-a80d85ff8e05' class='xr-section-summary-in' type='checkbox' ><label for='section-4996dabb-5ee0-4e5d-aff0-a80d85ff8e05' class='xr-section-summary' >Attributes: <span>(22)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>project :</span></dt><dd>ECMWF Re-Analysis</dd><dt><span>project_id :</span></dt><dd>ERA</dd><dt><span>institution_id :</span></dt><dd>ECMWF-DKRZ</dd><dt><span>institution :</span></dt><dd>Data from European Centre for Medium-Range Weather Forecasts (ECMWF) distributed by the Germen Climate Computing Center (DKRZ)</dd><dt><span>source_id :</span></dt><dd>IFS</dd><dt><span>source :</span></dt><dd>ECMWF Integrated Forecast System (IFS) CY41R2</dd><dt><span>experiment_id :</span></dt><dd>ERA5</dd><dt><span>simulation_id :</span></dt><dd>ERA5</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>frequency :</span></dt><dd>daily</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>grid_id :</span></dt><dd>N320</dd><dt><span>grid_type :</span></dt><dd>gaussian_reduced</dd><dt><span>resolution :</span></dt><dd>0.28125 deg</dd><dt><span>level_type :</span></dt><dd>surface</dd><dt><span>data_type :</span></dt><dd>analysis</dd><dt><span>format :</span></dt><dd>kerchunk</dd><dt><span>product :</span></dt><dd>reanalysis</dd><dt><span>responsible_persons :</span></dt><dd>Angelika Heil, Fabian Wachsmann</dd><dt><span>title :</span></dt><dd>The DKRZ ERA5 data pool. Generated using Copernicus Climate Change Service information [2024]. Data distribution by the German Climate Computing Center (DKRZ). Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains</dd><dt><span>license :</span></dt><dd>The ERA5 data are published with the Copernicus Product License with the necessity of attribution. https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products</dd><dt><span>references :</span></dt><dd>Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñozâ€Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., Thépaut, J-N. (2017): Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service (C3S) Data Store (CDS). DOI: 10.24381/cds.143582cf</dd></dl></div></li></ul></div></div>"
+ ],
+ "text/plain": [
+ "<xarray.Dataset> Size: 5TB\n",
+ "Dimensions: (time: 30955, cell: 542080)\n",
+ "Coordinates:\n",
+ " lat (cell) float64 4MB dask.array<chunksize=(542080,), meta=np.ndarray>\n",
+ " lon (cell) float64 4MB dask.array<chunksize=(542080,), meta=np.ndarray>\n",
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+ "Dimensions without coordinates: cell\n",
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+ " tsn (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ "Attributes: (12/22)\n",
+ " project: ECMWF Re-Analysis\n",
+ " project_id: ERA\n",
+ " institution_id: ECMWF-DKRZ\n",
+ " institution: Data from European Centre for Medium-Range Weather ...\n",
+ " source_id: IFS\n",
+ " source: ECMWF Integrated Forecast System (IFS) CY41R2\n",
+ " ... ...\n",
+ " format: kerchunk\n",
+ " product: reanalysis\n",
+ " responsible_persons: Angelika Heil, Fabian Wachsmann\n",
+ " title: The DKRZ ERA5 data pool. Generated using Copernicus...\n",
+ " license: The ERA5 data are published with the Copernicus Pro...\n",
+ " references: Hersbach, H., Bell, B., Berrisford, P., Hirahara, S..."
+ ]
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
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+ "id": "e46eeffa-f2b7-4763-9d50-3866f16b2495",
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+ "}\n",
+ "\n",
+ ".xr-dim-list:after {\n",
+ " content: ')';\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list li:not(:last-child):after {\n",
+ " content: ',';\n",
+ " padding-right: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-has-index {\n",
+ " font-weight: bold;\n",
+ "}\n",
+ "\n",
+ ".xr-var-list,\n",
+ ".xr-var-item {\n",
+ " display: contents;\n",
+ "}\n",
+ "\n",
+ ".xr-var-item > div,\n",
+ ".xr-var-item label,\n",
+ ".xr-var-item > .xr-var-name span {\n",
+ " background-color: var(--xr-background-color-row-even);\n",
+ " margin-bottom: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-var-item > .xr-var-name:hover span {\n",
+ " padding-right: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-var-list > li:nth-child(odd) > div,\n",
+ ".xr-var-list > li:nth-child(odd) > label,\n",
+ ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+ " background-color: var(--xr-background-color-row-odd);\n",
+ "}\n",
+ "\n",
+ ".xr-var-name {\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-var-dims {\n",
+ " grid-column: 2;\n",
+ "}\n",
+ "\n",
+ ".xr-var-dtype {\n",
+ " grid-column: 3;\n",
+ " text-align: right;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-var-preview {\n",
+ " grid-column: 4;\n",
+ "}\n",
+ "\n",
+ ".xr-index-preview {\n",
+ " grid-column: 2 / 5;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-var-name,\n",
+ ".xr-var-dims,\n",
+ ".xr-var-dtype,\n",
+ ".xr-preview,\n",
+ ".xr-attrs dt {\n",
+ " white-space: nowrap;\n",
+ " overflow: hidden;\n",
+ " text-overflow: ellipsis;\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name:hover,\n",
+ ".xr-var-dims:hover,\n",
+ ".xr-var-dtype:hover,\n",
+ ".xr-attrs dt:hover {\n",
+ " overflow: visible;\n",
+ " width: auto;\n",
+ " z-index: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-var-attrs,\n",
+ ".xr-var-data,\n",
+ ".xr-index-data {\n",
+ " display: none;\n",
+ " background-color: var(--xr-background-color) !important;\n",
+ " padding-bottom: 5px !important;\n",
+ "}\n",
+ "\n",
+ ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+ ".xr-var-data-in:checked ~ .xr-var-data,\n",
+ ".xr-index-data-in:checked ~ .xr-index-data {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ ".xr-var-data > table {\n",
+ " float: right;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name span,\n",
+ ".xr-var-data,\n",
+ ".xr-index-name div,\n",
+ ".xr-index-data,\n",
+ ".xr-attrs {\n",
+ " padding-left: 25px !important;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs,\n",
+ ".xr-var-attrs,\n",
+ ".xr-var-data,\n",
+ ".xr-index-data {\n",
+ " grid-column: 1 / -1;\n",
+ "}\n",
+ "\n",
+ "dl.xr-attrs {\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ " display: grid;\n",
+ " grid-template-columns: 125px auto;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt,\n",
+ ".xr-attrs dd {\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ " float: left;\n",
+ " padding-right: 10px;\n",
+ " width: auto;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt {\n",
+ " font-weight: normal;\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt:hover span {\n",
+ " display: inline-block;\n",
+ " background: var(--xr-background-color);\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dd {\n",
+ " grid-column: 2;\n",
+ " white-space: pre-wrap;\n",
+ " word-break: break-all;\n",
+ "}\n",
+ "\n",
+ ".xr-icon-database,\n",
+ ".xr-icon-file-text2,\n",
+ ".xr-no-icon {\n",
+ " display: inline-block;\n",
+ " vertical-align: middle;\n",
+ " width: 1em;\n",
+ " height: 1.5em !important;\n",
+ " stroke-width: 0;\n",
+ " stroke: currentColor;\n",
+ " fill: currentColor;\n",
+ "}\n",
+ "</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 182MB\n",
+ "Dimensions: (cell: 542080)\n",
+ "Coordinates:\n",
+ " lat (cell) float64 4MB 89.78 89.78 89.78 89.78 ... -89.78 -89.78 -89.78\n",
+ " lon (cell) float64 4MB nan 20.0 40.0 60.0 ... 280.0 300.0 320.0 340.0\n",
+ " time datetime64[ns] 8B 2024-09-30T11:30:00\n",
+ "Dimensions without coordinates: cell\n",
+ "Data variables: (12/40)\n",
+ " 100u (cell) float64 4MB 5.838 2.636 -0.8782 ... -8.296 -6.063 -2.922\n",
+ " 100v (cell) float64 4MB -8.215 -9.827 -10.22 ... -6.401 -8.995 -10.81\n",
+ " 10u (cell) float64 4MB 4.36 2.381 0.09148 ... -5.739 -4.711 -3.002\n",
+ " 10v (cell) float64 4MB -4.953 -6.245 -6.762 ... -3.089 -4.959 -6.483\n",
+ " 2d (cell) float64 4MB 259.5 259.7 259.9 260.1 ... 219.4 219.4 219.4\n",
+ " 2t (cell) float64 4MB 261.9 262.1 262.3 262.5 ... 223.3 223.4 223.5\n",
+ " ... ...\n",
+ " swvl4 (cell) float64 4MB 0.0 0.0 0.0 0.0 ... 0.1602 0.1602 0.1602 0.1602\n",
+ " tcc (cell) float64 4MB 0.9721 0.9683 0.9667 ... 0.9813 0.9838 0.9871\n",
+ " tco3 (cell) float64 4MB 0.006883 0.006877 0.006873 ... 0.002953 0.002952\n",
+ " tcw (cell) float64 4MB 5.733 5.772 5.815 5.877 ... 0.4126 0.4126 0.4126\n",
+ " tcwv (cell) float64 4MB 5.655 5.692 5.733 5.793 ... 0.3989 0.4008 0.4008\n",
+ " tsn (cell) float64 4MB 261.7 261.9 262.1 262.4 ... 221.2 221.3 221.3\n",
+ "Attributes: (12/22)\n",
+ " project: ECMWF Re-Analysis\n",
+ " project_id: ERA\n",
+ " institution_id: ECMWF-DKRZ\n",
+ " institution: Data from European Centre for Medium-Range Weather ...\n",
+ " source_id: IFS\n",
+ " source: ECMWF Integrated Forecast System (IFS) CY41R2\n",
+ " ... ...\n",
+ " format: kerchunk\n",
+ " product: reanalysis\n",
+ " responsible_persons: Angelika Heil, Fabian Wachsmann\n",
+ " title: The DKRZ ERA5 data pool. Generated using Copernicus...\n",
+ " license: The ERA5 data are published with the Copernicus Pro...\n",
+ " references: Hersbach, H., Bell, B., Berrisford, P., Hirahara, S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5f761ad2-e3c6-456d-b01b-3f4b326bf92c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5f761ad2-e3c6-456d-b01b-3f4b326bf92c' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>cell</span>: 542080</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-55dbee0e-fc22-4041-b700-da2af24fd573' class='xr-section-summary-in' type='checkbox' checked><label for='section-55dbee0e-fc22-4041-b700-da2af24fd573' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>89.78 89.78 89.78 ... -89.78 -89.78</div><input id='attrs-d15a15a8-e279-4b4f-b8e5-a6e60d13bb71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d15a15a8-e279-4b4f-b8e5-a6e60d13bb71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4af8eb66-0587-4914-ba1f-540e24cd0aa6' class='xr-var-data-in' type='checkbox'><label for='data-4af8eb66-0587-4914-ba1f-540e24cd0aa6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>source :</span></dt><dd>../../../../../pool/data/ERA5/E5/sf/an/1M/167/E5sf00_1M_1940_167.grb</dd><dt><span>filter_by_keys :</span></dt><dd>{}</dd><dt><span>encode_cf :</span></dt><dd>['parameter', 'time', 'geography', 'vertical']</dd><dt><span>original_shape :</span></dt><dd>[542080]</dd><dt><span>dtype :</span></dt><dd>float64</dd></dl></div><div class='xr-var-data'><pre>array([ 89.78487691, 89.78487691, 89.78487691, ..., -89.78487691,\n",
+ " -89.78487691, -89.78487691])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 20.0 40.0 ... 300.0 320.0 340.0</div><input id='attrs-bd8c52f4-67ae-46d2-a2d5-3c3ecd4aa5e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd8c52f4-67ae-46d2-a2d5-3c3ecd4aa5e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6000e5f-a256-45f2-91ba-94c7de37cf55' class='xr-var-data-in' type='checkbox'><label for='data-e6000e5f-a256-45f2-91ba-94c7de37cf55' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>source :</span></dt><dd>../../../../../pool/data/ERA5/E5/sf/an/1M/167/E5sf00_1M_1940_167.grb</dd><dt><span>filter_by_keys :</span></dt><dd>{}</dd><dt><span>encode_cf :</span></dt><dd>['parameter', 'time', 'geography', 'vertical']</dd><dt><span>original_shape :</span></dt><dd>[542080]</dd><dt><span>dtype :</span></dt><dd>float64</dd></dl></div><div class='xr-var-data'><pre>array([ nan, 20., 40., ..., 300., 320., 340.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2024-09-30T11:30:00</div><input id='attrs-67ddccf7-1eca-4a48-93a5-44e5589346c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67ddccf7-1eca-4a48-93a5-44e5589346c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f1bee63-0e9d-4f36-95ea-183d9c287b3c' class='xr-var-data-in' type='checkbox'><label for='data-4f1bee63-0e9d-4f36-95ea-183d9c287b3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>1970-01-01T00:00:00.000000000</dd></dl></div><div class='xr-var-data'><pre>array('2024-09-30T11:30:00.000000000', dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-17bef983-5c63-4eee-a5a0-76020693a63f' class='xr-section-summary-in' type='checkbox' ><label for='section-17bef983-5c63-4eee-a5a0-76020693a63f' class='xr-section-summary' >Data variables: <span>(40)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>100u</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.838 2.636 ... -6.063 -2.922</div><input id='attrs-0fbe7baf-6460-4f3b-a18d-e1578b7d6a02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0fbe7baf-6460-4f3b-a18d-e1578b7d6a02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-379f5f39-b1a5-489b-bd6e-f42805fe3ac2' class='xr-var-data-in' type='checkbox'><label for='data-379f5f39-b1a5-489b-bd6e-f42805fe3ac2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>100u</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>100 metre U wind component</dd><dt><span>cfVarName :</span></dt><dd>u100</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([ 5.83758545, 2.63641357, -0.87823486, ..., -8.29620361,\n",
+ " -6.06280518, -2.92218018])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>100v</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-8.215 -9.827 ... -8.995 -10.81</div><input id='attrs-f44360a9-0f87-4ea7-a688-f31989b185db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f44360a9-0f87-4ea7-a688-f31989b185db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-869c9eb3-9c5a-490d-bf37-6368f6ca29b9' class='xr-var-data-in' type='checkbox'><label for='data-869c9eb3-9c5a-490d-bf37-6368f6ca29b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>100v</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>100 metre V wind component</dd><dt><span>cfVarName :</span></dt><dd>v100</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([ -8.21508789, -9.82739258, -10.22387695, ..., -6.40063477,\n",
+ " -8.99536133, -10.8059082 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>10u</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.36 2.381 ... -4.711 -3.002</div><input id='attrs-7ca71285-5ad7-409a-9242-848451ba66f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ca71285-5ad7-409a-9242-848451ba66f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2736ba09-8b16-41dd-8ea5-4cf7e0067ced' class='xr-var-data-in' type='checkbox'><label for='data-2736ba09-8b16-41dd-8ea5-4cf7e0067ced' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>10u</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>10 metre U wind component</dd><dt><span>cfVarName :</span></dt><dd>u10</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([ 4.36003113, 2.38053894, 0.09147644, ..., -5.73860168,\n",
+ " -4.71125793, -3.00227356])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>10v</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.953 -6.245 ... -4.959 -6.483</div><input id='attrs-caf5ee4e-a287-414a-aee3-79d7c16dde94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-caf5ee4e-a287-414a-aee3-79d7c16dde94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1e0506a-276d-4326-bcd7-6ec9a85eb534' class='xr-var-data-in' type='checkbox'><label for='data-d1e0506a-276d-4326-bcd7-6ec9a85eb534' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>10v</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>10 metre V wind component</dd><dt><span>cfVarName :</span></dt><dd>v10</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([-4.95269585, -6.24468803, -6.76226616, ..., -3.0894146 ,\n",
+ " -4.95855522, -6.48296928])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>2d</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>259.5 259.7 259.9 ... 219.4 219.4</div><input id='attrs-bfd4d588-2625-4e08-a595-cc06a6b7b765' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfd4d588-2625-4e08-a595-cc06a6b7b765' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccb613bf-270c-43d5-9225-11c5f8ea2abd' class='xr-var-data-in' type='checkbox'><label for='data-ccb613bf-270c-43d5-9225-11c5f8ea2abd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>2d</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>2 metre dewpoint temperature</dd><dt><span>cfVarName :</span></dt><dd>d2m</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([259.50054932, 259.68609619, 259.87750244, ..., 219.35797119,\n",
+ " 219.38922119, 219.42242432])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>2t</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>261.9 262.1 262.3 ... 223.4 223.5</div><input id='attrs-94653477-1bb1-406a-a8d3-5bc3333592b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94653477-1bb1-406a-a8d3-5bc3333592b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d40289c0-db4c-4f82-886e-0f5e1da6637a' class='xr-var-data-in' type='checkbox'><label for='data-d40289c0-db4c-4f82-886e-0f5e1da6637a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>2t</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>2 metre temperature</dd><dt><span>cfVarName :</span></dt><dd>t2m</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([261.93292236, 262.12628174, 262.30987549, ..., 223.32745361,\n",
+ " 223.41534424, 223.49542236])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>asn</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.88 0.88 0.88 ... 0.85 0.85 0.85</div><input id='attrs-4428bc6b-173a-4385-9464-0a93be9ecbc1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4428bc6b-173a-4385-9464-0a93be9ecbc1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8bb2513f-13fb-4be4-bfe2-b909f0f0f6b4' class='xr-var-data-in' type='checkbox'><label for='data-8bb2513f-13fb-4be4-bfe2-b909f0f0f6b4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>asn</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Snow albedo</dd><dt><span>cfVarName :</span></dt><dd>asn</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([0.88000059, 0.88000059, 0.88000059, ..., 0.85000181, 0.85000181,\n",
+ " 0.85000181])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>blh</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>212.9 220.9 229.4 ... 147.6 150.0</div><input id='attrs-305bfd1f-9e91-4ef0-b1a6-fff776a9d8eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-305bfd1f-9e91-4ef0-b1a6-fff776a9d8eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-854ee329-cc44-4a43-95d2-9e2d7e1d8074' class='xr-var-data-in' type='checkbox'><label for='data-854ee329-cc44-4a43-95d2-9e2d7e1d8074' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>blh</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>name :</span></dt><dd>Boundary layer height</dd><dt><span>cfVarName :</span></dt><dd>blh</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([212.86473846, 220.92723846, 229.42723846, ..., 145.61473846,\n",
+ " 147.55223846, 149.98973846])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ci</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9867 0.9805 ... 9.999e+03</div><input id='attrs-6dedb7b3-977a-44d0-8ad1-850e25beeb1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6dedb7b3-977a-44d0-8ad1-850e25beeb1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-baf9502f-33a7-4c81-9a3e-59e6d5a27cd1' class='xr-var-data-in' type='checkbox'><label for='data-baf9502f-33a7-4c81-9a3e-59e6d5a27cd1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>ci</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Sea ice area fraction</dd><dt><span>cfName :</span></dt><dd>sea_ice_area_fraction</dd><dt><span>cfVarName :</span></dt><dd>siconc</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([9.86663818e-01, 9.80499268e-01, 9.71282959e-01, ...,\n",
+ " 9.99900000e+03, 9.99900000e+03, 9.99900000e+03])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fal</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.7554 0.751 0.7448 ... 0.85 0.85</div><input id='attrs-7ac70018-8e81-4812-a029-0b31ac377a9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ac70018-8e81-4812-a029-0b31ac377a9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-498a5ea0-b4a3-48c2-8c5d-1621b13ecb69' class='xr-var-data-in' type='checkbox'><label for='data-498a5ea0-b4a3-48c2-8c5d-1621b13ecb69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>fal</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Forecast albedo</dd><dt><span>cfVarName :</span></dt><dd>fal</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([0.7554478 , 0.75103801, 0.74481243, ..., 0.85000652, 0.85000652,\n",
+ " 0.85000652])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flsr</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-6.94 -6.954 ... -8.948 -8.948</div><input id='attrs-876a5fab-3a1d-451a-9f81-f36642b8a095' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-876a5fab-3a1d-451a-9f81-f36642b8a095' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae3e742c-26ae-401a-b5ba-8212e00adc56' class='xr-var-data-in' type='checkbox'><label for='data-ae3e742c-26ae-401a-b5ba-8212e00adc56' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>flsr</dd><dt><span>units :</span></dt><dd>~</dd><dt><span>name :</span></dt><dd>Forecast logarithm of surface roughness for heat</dd><dt><span>cfVarName :</span></dt><dd>flsr</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([-6.94027901, -6.95443916, -6.97494698, ..., -8.94784737,\n",
+ " -8.94784737, -8.94784737])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fsr</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0009742 0.0009633 ... 0.0013</div><input id='attrs-8f257fa7-c831-4374-96e5-91547bb86272' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f257fa7-c831-4374-96e5-91547bb86272' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2f38a91-788a-4510-a2e5-4191058ab25a' class='xr-var-data-in' type='checkbox'><label for='data-b2f38a91-788a-4510-a2e5-4191058ab25a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>fsr</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>name :</span></dt><dd>Forecast surface roughness</dd><dt><span>cfVarName :</span></dt><dd>fsr</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([0.00097416, 0.00096331, 0.00094829, ..., 0.00129996, 0.00129996,\n",
+ " 0.00129996])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hcc</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6475 0.6383 ... 0.7783 0.7842</div><input id='attrs-1433d022-34a7-441e-a707-a4f9270261fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1433d022-34a7-441e-a707-a4f9270261fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb079a4d-03e7-4bbe-8d1f-ce40a5569ddc' class='xr-var-data-in' type='checkbox'><label for='data-fb079a4d-03e7-4bbe-8d1f-ce40a5569ddc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>hcc</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>High cloud cover</dd><dt><span>cfVarName :</span></dt><dd>hcc</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([0.64749146, 0.63833618, 0.63415527, ..., 0.78167725, 0.77832031,\n",
+ " 0.78417969])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ie</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-8.075e-07 -9.192e-07 ... 1.536e-07</div><input id='attrs-e8adf1a6-7058-4300-9c10-1a44a7bce38d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8adf1a6-7058-4300-9c10-1a44a7bce38d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-466ce036-b8fa-4258-9612-82b98f4d82f8' class='xr-var-data-in' type='checkbox'><label for='data-466ce036-b8fa-4258-9612-82b98f4d82f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>ie</dd><dt><span>units :</span></dt><dd>kg m**-2 s**-1</dd><dt><span>name :</span></dt><dd>Instantaneous moisture flux</dd><dt><span>cfVarName :</span></dt><dd>ie</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([-8.07485776e-07, -9.19244485e-07, -7.85134034e-07, ...,\n",
+ " 1.38737960e-07, 1.46188540e-07, 1.53639121e-07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>istl1</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>261.6 261.7 261.8 ... 271.5 271.5</div><input id='attrs-ede0d88f-5b67-406b-b4a5-1d08b3dc741f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ede0d88f-5b67-406b-b4a5-1d08b3dc741f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70a47e28-51c3-472d-8693-9ec0b106ecd6' class='xr-var-data-in' type='checkbox'><label for='data-70a47e28-51c3-472d-8693-9ec0b106ecd6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>istl1</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Ice temperature layer 1</dd><dt><span>cfVarName :</span></dt><dd>istl1</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([261.5629425 , 261.71577454, 261.80366516, ..., 271.45991516,\n",
+ " 271.45991516, 271.45991516])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>istl2</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>262.6 262.7 262.8 ... 271.5 271.5</div><input id='attrs-c98dd799-da84-47dd-9e09-fbac796e1748' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c98dd799-da84-47dd-9e09-fbac796e1748' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c89add8a-a7ef-417a-af56-392298400ef6' class='xr-var-data-in' type='checkbox'><label for='data-c89add8a-a7ef-417a-af56-392298400ef6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>istl2</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Ice temperature layer 2</dd><dt><span>cfVarName :</span></dt><dd>istl2</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([262.56436157, 262.68643188, 262.77432251, ..., 271.45986938,\n",
+ " 271.45986938, 271.45986938])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>istl3</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>266.1 266.2 266.2 ... 271.5 271.5</div><input id='attrs-b1fe7730-a227-4126-abba-6d82a200b218' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1fe7730-a227-4126-abba-6d82a200b218' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b215f15b-7e14-4984-b3ec-d7ee0fac6bee' class='xr-var-data-in' type='checkbox'><label for='data-b215f15b-7e14-4984-b3ec-d7ee0fac6bee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>istl3</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Ice temperature layer 3</dd><dt><span>cfVarName :</span></dt><dd>istl3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([266.10595703, 266.16308594, 266.20361328, ..., 271.45996094,\n",
+ " 271.45996094, 271.45996094])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>istl4</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>269.2 269.3 269.3 ... 271.5 271.5</div><input id='attrs-905faf5f-512b-4429-9132-cfa3eb4820ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-905faf5f-512b-4429-9132-cfa3eb4820ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4df6739-c3e3-4841-a9e3-79e974ebfd60' class='xr-var-data-in' type='checkbox'><label for='data-f4df6739-c3e3-4841-a9e3-79e974ebfd60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>istl4</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Ice temperature layer 4</dd><dt><span>cfVarName :</span></dt><dd>istl4</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([269.24951172, 269.27514648, 269.28955078, ..., 271.45996094,\n",
+ " 271.45996094, 271.45996094])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lcc</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4417 0.4375 ... 0.9775 0.9871</div><input id='attrs-f67951a7-312f-467c-8a37-1987c76c2c15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f67951a7-312f-467c-8a37-1987c76c2c15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db120bda-2728-43c3-84e2-f5c6a13234cc' class='xr-var-data-in' type='checkbox'><label for='data-db120bda-2728-43c3-84e2-f5c6a13234cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>lcc</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Low cloud cover</dd><dt><span>cfVarName :</span></dt><dd>lcc</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([0.44168091, 0.4375 , 0.4354248 , ..., 0.94833374, 0.97750854,\n",
+ " 0.98709106])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mcc</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.8592 0.8417 ... 0.7696 0.7604</div><input id='attrs-4dd0c0b0-444f-4b26-92e2-a35a319e47c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dd0c0b0-444f-4b26-92e2-a35a319e47c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1df84c82-75b2-4c0f-98a4-97e904a88b85' class='xr-var-data-in' type='checkbox'><label for='data-1df84c82-75b2-4c0f-98a4-97e904a88b85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>mcc</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Medium cloud cover</dd><dt><span>cfVarName :</span></dt><dd>mcc</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([0.85916138, 0.8416748 , 0.85043335, ..., 0.78167725, 0.76959229,\n",
+ " 0.76040649])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>msl</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.018e+05 1.018e+05 ... 1.022e+05</div><input id='attrs-c658a773-fdb2-4fe4-82f7-fec4dd498f3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c658a773-fdb2-4fe4-82f7-fec4dd498f3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-539c5bb3-9460-4ec5-a118-357e99cbc843' class='xr-var-data-in' type='checkbox'><label for='data-539c5bb3-9460-4ec5-a118-357e99cbc843' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>msl</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>name :</span></dt><dd>Mean sea level pressure</dd><dt><span>cfName :</span></dt><dd>air_pressure_at_mean_sea_level</dd><dt><span>cfVarName :</span></dt><dd>msl</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([101790.5 , 101774.5 , 101757.75, ..., 102205.5 , 102192. ,\n",
+ " 102179. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rsn</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>100.0 100.0 100.0 ... 300.0 300.0</div><input id='attrs-98bbd866-70d6-4a9e-a9d6-fffce805fba9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98bbd866-70d6-4a9e-a9d6-fffce805fba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d67c4608-d65b-45ea-8140-a8782601c955' class='xr-var-data-in' type='checkbox'><label for='data-d67c4608-d65b-45ea-8140-a8782601c955' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>rsn</dd><dt><span>units :</span></dt><dd>kg m**-3</dd><dt><span>name :</span></dt><dd>Snow density</dd><dt><span>cfVarName :</span></dt><dd>rsn</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([100., 100., 100., ..., 300., 300., 300.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sd</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 10.0 10.0 10.0</div><input id='attrs-5aa8c4b7-3246-4f9c-b765-cb01b3fb1529' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5aa8c4b7-3246-4f9c-b765-cb01b3fb1529' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-092461bd-57c2-4462-8f54-5c1fcc87e8f7' class='xr-var-data-in' type='checkbox'><label for='data-092461bd-57c2-4462-8f54-5c1fcc87e8f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>sd</dd><dt><span>units :</span></dt><dd>m of water equivalent</dd><dt><span>name :</span></dt><dd>Snow depth</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_surface_snow_amount</dd><dt><span>cfVarName :</span></dt><dd>sd</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([ 0., 0., 0., ..., 10., 10., 10.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>skt</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>261.4 261.7 261.9 ... 221.9 222.0</div><input id='attrs-8ffdcef5-93e0-4856-93c9-ffb7f6576301' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ffdcef5-93e0-4856-93c9-ffb7f6576301' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-046d99b2-ee05-4d11-80d3-29cfca5b43a1' class='xr-var-data-in' type='checkbox'><label for='data-046d99b2-ee05-4d11-80d3-29cfca5b43a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>skt</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Skin temperature</dd><dt><span>cfVarName :</span></dt><dd>skt</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([261.41456604, 261.70753479, 261.90480042, ..., 221.98878479,\n",
+ " 221.93800354, 222.04542542])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sp</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.018e+05 1.018e+05 ... 6.936e+04</div><input id='attrs-bd81a580-d8a9-47a0-8649-eb08e4278c1b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd81a580-d8a9-47a0-8649-eb08e4278c1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-231d93d6-c1ca-4684-8276-0c52f8e576a0' class='xr-var-data-in' type='checkbox'><label for='data-231d93d6-c1ca-4684-8276-0c52f8e576a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>sp</dd><dt><span>units :</span></dt><dd>Pa</dd><dt><span>name :</span></dt><dd>Surface pressure</dd><dt><span>cfName :</span></dt><dd>surface_air_pressure</dd><dt><span>cfVarName :</span></dt><dd>sp</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([101783.453125, 101765.453125, 101750.453125, ..., 69445.453125,\n",
+ " 69429.453125, 69359.453125])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>src</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-95706b4c-f0af-4a69-9f94-c22dcc7db0a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95706b4c-f0af-4a69-9f94-c22dcc7db0a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b24e59b-d35e-4f86-8fe0-9efe0501c7c9' class='xr-var-data-in' type='checkbox'><label for='data-9b24e59b-d35e-4f86-8fe0-9efe0501c7c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>src</dd><dt><span>units :</span></dt><dd>m of water equivalent</dd><dt><span>name :</span></dt><dd>Skin reservoir content</dd><dt><span>cfVarName :</span></dt><dd>src</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>271.5 271.5 ... 9.999e+03 9.999e+03</div><input id='attrs-3e9544dd-e817-42c8-80da-706f5cab573c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e9544dd-e817-42c8-80da-706f5cab573c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afbf202c-5985-4f7d-8c03-9836406927e1' class='xr-var-data-in' type='checkbox'><label for='data-afbf202c-5985-4f7d-8c03-9836406927e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>sst</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Sea surface temperature</dd><dt><span>cfVarName :</span></dt><dd>sst</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([ 271.45996094, 271.45996094, 271.45996094, ..., 9999. ,\n",
+ " 9999. , 9999. ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stl1</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>261.7 261.9 262.1 ... 224.0 224.1</div><input id='attrs-0a836345-59a7-48da-97e5-9e56640cd286' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a836345-59a7-48da-97e5-9e56640cd286' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c12d26d7-4ed7-4e81-b9e6-6befc9612fc7' class='xr-var-data-in' type='checkbox'><label for='data-c12d26d7-4ed7-4e81-b9e6-6befc9612fc7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>stl1</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Soil temperature level 1</dd><dt><span>cfName :</span></dt><dd>surface_temperature</dd><dt><span>cfVarName :</span></dt><dd>stl1</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([261.69343567, 261.90437317, 262.08015442, ..., 223.81452942,\n",
+ " 224.02937317, 224.13288879])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stl2</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>262.7 262.9 263.0 ... 224.2 224.3</div><input id='attrs-2a0aa986-eff7-45a3-999e-df8773068b56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a0aa986-eff7-45a3-999e-df8773068b56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4cf0ca4f-8ae2-4933-a978-c2a4c6af677e' class='xr-var-data-in' type='checkbox'><label for='data-4cf0ca4f-8ae2-4933-a978-c2a4c6af677e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>stl2</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Soil temperature level 2</dd><dt><span>cfVarName :</span></dt><dd>stl2</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([262.69242859, 262.86820984, 263.03031921, ..., 223.94047546,\n",
+ " 224.15531921, 224.26664734])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stl3</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>266.2 266.3 266.4 ... 224.6 224.7</div><input id='attrs-f39779eb-0e9d-486b-909e-6d5c5862b52c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f39779eb-0e9d-486b-909e-6d5c5862b52c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5016325-dc75-463a-b8d9-1b0f29f36510' class='xr-var-data-in' type='checkbox'><label for='data-e5016325-dc75-463a-b8d9-1b0f29f36510' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>stl3</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Soil temperature level 3</dd><dt><span>cfVarName :</span></dt><dd>stl3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([266.18309021, 266.27293396, 266.35887146, ..., 224.39207458,\n",
+ " 224.59715271, 224.72410583])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stl4</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>261.6 261.9 262.1 ... 225.8 225.9</div><input id='attrs-39ac685d-07c9-42a4-b7f5-31f9594132dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39ac685d-07c9-42a4-b7f5-31f9594132dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e2bd2bf-3c98-4a8a-aab5-4277e87fdc19' class='xr-var-data-in' type='checkbox'><label for='data-2e2bd2bf-3c98-4a8a-aab5-4277e87fdc19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>stl4</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Soil temperature level 4</dd><dt><span>cfVarName :</span></dt><dd>stl4</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([261.64779663, 261.92123413, 262.11068726, ..., 225.63021851,\n",
+ " 225.80404663, 225.93295288])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl1</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.89e-06 7.89e-06 ... 0.3186 0.292</div><input id='attrs-298f9b44-7092-42aa-9c1e-719964926f27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-298f9b44-7092-42aa-9c1e-719964926f27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8848e0f1-ca96-4fb6-8e3b-65bdb162c25e' class='xr-var-data-in' type='checkbox'><label for='data-8848e0f1-ca96-4fb6-8e3b-65bdb162c25e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>swvl1</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 1</dd><dt><span>cfVarName :</span></dt><dd>swvl1</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([7.89016485e-06, 7.89016485e-06, 7.89016485e-06, ...,\n",
+ " 2.73140214e-01, 3.18626665e-01, 2.92000078e-01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl2</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.562e-06 2.562e-06 ... 0.2096</div><input id='attrs-3a1d1b55-0ab0-468f-92ea-67c100bc8f93' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a1d1b55-0ab0-468f-92ea-67c100bc8f93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-225f43e6-55bb-438a-8f87-1ebc2e3322a3' class='xr-var-data-in' type='checkbox'><label for='data-225f43e6-55bb-438a-8f87-1ebc2e3322a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>swvl2</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 2</dd><dt><span>cfVarName :</span></dt><dd>swvl2</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([2.56160274e-06, 2.56160274e-06, 2.56160274e-06, ...,\n",
+ " 2.35308348e-01, 2.52566038e-01, 2.09566771e-01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl3</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.257e-06 -3.257e-06 ... 0.2521</div><input id='attrs-89f85fac-cae8-4b62-9754-f3674d5185ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89f85fac-cae8-4b62-9754-f3674d5185ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5dc8086-47eb-4bb1-8643-1cc14e1322c7' class='xr-var-data-in' type='checkbox'><label for='data-a5dc8086-47eb-4bb1-8643-1cc14e1322c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>swvl3</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 3</dd><dt><span>cfVarName :</span></dt><dd>swvl3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([-3.25660221e-06, -3.25660221e-06, -3.25660221e-06, ...,\n",
+ " 3.07873330e-01, 3.05462442e-01, 2.52056680e-01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl4</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 0.1602 0.1602</div><input id='attrs-e7e7b608-a250-48da-ae4d-cd7662c07d08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7e7b608-a250-48da-ae4d-cd7662c07d08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51f3db2d-5872-47c9-a6ad-612ac9754a8a' class='xr-var-data-in' type='checkbox'><label for='data-51f3db2d-5872-47c9-a6ad-612ac9754a8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>swvl4</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 4</dd><dt><span>cfVarName :</span></dt><dd>swvl4</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([0. , 0. , 0. , ..., 0.16020203, 0.16020203,\n",
+ " 0.16020203])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcc</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9721 0.9683 ... 0.9838 0.9871</div><input id='attrs-0a4450e8-8d5f-445d-b18f-5f63d284a3df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a4450e8-8d5f-445d-b18f-5f63d284a3df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcca6fa4-3eef-4f04-b57a-eef390cbb6b2' class='xr-var-data-in' type='checkbox'><label for='data-bcca6fa4-3eef-4f04-b57a-eef390cbb6b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>tcc</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Total cloud cover</dd><dt><span>cfName :</span></dt><dd>cloud_area_fraction</dd><dt><span>cfVarName :</span></dt><dd>tcc</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([0.97207642, 0.96832275, 0.9666748 , ..., 0.98126221, 0.98376465,\n",
+ " 0.98709106])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tco3</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.006883 0.006877 ... 0.002952</div><input id='attrs-90219dfc-8cb4-43df-b2a3-d2f0bf291229' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90219dfc-8cb4-43df-b2a3-d2f0bf291229' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41dd6ea3-ba7f-493c-8329-1df926805054' class='xr-var-data-in' type='checkbox'><label for='data-41dd6ea3-ba7f-493c-8329-1df926805054' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>tco3</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column ozone</dd><dt><span>cfName :</span></dt><dd>atmosphere_mass_content_of_ozone</dd><dt><span>cfVarName :</span></dt><dd>tco3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([0.00688299, 0.00687715, 0.00687333, ..., 0.00295564, 0.0029529 ,\n",
+ " 0.00295159])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcw</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.733 5.772 5.815 ... 0.4126 0.4126</div><input id='attrs-35a13720-83a3-4ede-a95b-6ba4394174d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35a13720-83a3-4ede-a95b-6ba4394174d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-374f400d-6aaa-43f2-9a4d-168733c25216' class='xr-var-data-in' type='checkbox'><label for='data-374f400d-6aaa-43f2-9a4d-168733c25216' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>tcw</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column water</dd><dt><span>cfVarName :</span></dt><dd>tcw</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([5.73287004, 5.77193254, 5.81490129, ..., 0.41255754, 0.41255754,\n",
+ " 0.41255754])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcwv</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.655 5.692 5.733 ... 0.4008 0.4008</div><input id='attrs-a38b85ef-1011-4aec-85f9-c34e256685bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a38b85ef-1011-4aec-85f9-c34e256685bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-139af807-6cae-45c1-8b72-27d323763bc1' class='xr-var-data-in' type='checkbox'><label for='data-139af807-6cae-45c1-8b72-27d323763bc1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>tcwv</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column vertically-integrated water vapour</dd><dt><span>cfName :</span></dt><dd>lwe_thickness_of_atmosphere_mass_content_of_water_vapor</dd><dt><span>cfVarName :</span></dt><dd>tcwv</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([5.65474206, 5.69185144, 5.73286706, ..., 0.39888269, 0.40083581,\n",
+ " 0.40083581])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tsn</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>261.7 261.9 262.1 ... 221.3 221.3</div><input id='attrs-0cf642d6-c3e1-434f-bd7a-cfae406ffe51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0cf642d6-c3e1-434f-bd7a-cfae406ffe51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3d76dfa-214c-4489-bb26-2df937d49097' class='xr-var-data-in' type='checkbox'><label for='data-e3d76dfa-214c-4489-bb26-2df937d49097' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>tsn</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Temperature of snow layer</dd><dt><span>cfName :</span></dt><dd>temperature_in_surface_snow</dd><dt><span>cfVarName :</span></dt><dd>tsn</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><pre>array([261.6950531 , 261.90403748, 262.07981873, ..., 221.15013123,\n",
+ " 221.2809906 , 221.2888031 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-834d07b8-2ae3-4857-ab6c-24811d888956' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-834d07b8-2ae3-4857-ab6c-24811d888956' class='xr-section-summary' title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-efb524ff-4fa5-4084-8c34-64352f92a98c' class='xr-section-summary-in' type='checkbox' ><label for='section-efb524ff-4fa5-4084-8c34-64352f92a98c' class='xr-section-summary' >Attributes: <span>(22)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>project :</span></dt><dd>ECMWF Re-Analysis</dd><dt><span>project_id :</span></dt><dd>ERA</dd><dt><span>institution_id :</span></dt><dd>ECMWF-DKRZ</dd><dt><span>institution :</span></dt><dd>Data from European Centre for Medium-Range Weather Forecasts (ECMWF) distributed by the Germen Climate Computing Center (DKRZ)</dd><dt><span>source_id :</span></dt><dd>IFS</dd><dt><span>source :</span></dt><dd>ECMWF Integrated Forecast System (IFS) CY41R2</dd><dt><span>experiment_id :</span></dt><dd>ERA5</dd><dt><span>simulation_id :</span></dt><dd>ERA5</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>frequency :</span></dt><dd>daily</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>grid_id :</span></dt><dd>N320</dd><dt><span>grid_type :</span></dt><dd>gaussian_reduced</dd><dt><span>resolution :</span></dt><dd>0.28125 deg</dd><dt><span>level_type :</span></dt><dd>surface</dd><dt><span>data_type :</span></dt><dd>analysis</dd><dt><span>format :</span></dt><dd>kerchunk</dd><dt><span>product :</span></dt><dd>reanalysis</dd><dt><span>responsible_persons :</span></dt><dd>Angelika Heil, Fabian Wachsmann</dd><dt><span>title :</span></dt><dd>The DKRZ ERA5 data pool. Generated using Copernicus Climate Change Service information [2024]. Data distribution by the German Climate Computing Center (DKRZ). Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains</dd><dt><span>license :</span></dt><dd>The ERA5 data are published with the Copernicus Product License with the necessity of attribution. https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products</dd><dt><span>references :</span></dt><dd>Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñozâ€Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., Thépaut, J-N. (2017): Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service (C3S) Data Store (CDS). DOI: 10.24381/cds.143582cf</dd></dl></div></li></ul></div></div>"
+ ],
+ "text/plain": [
+ "<xarray.Dataset> Size: 182MB\n",
+ "Dimensions: (cell: 542080)\n",
+ "Coordinates:\n",
+ " lat (cell) float64 4MB 89.78 89.78 89.78 89.78 ... -89.78 -89.78 -89.78\n",
+ " lon (cell) float64 4MB nan 20.0 40.0 60.0 ... 280.0 300.0 320.0 340.0\n",
+ " time datetime64[ns] 8B 2024-09-30T11:30:00\n",
+ "Dimensions without coordinates: cell\n",
+ "Data variables: (12/40)\n",
+ " 100u (cell) float64 4MB 5.838 2.636 -0.8782 ... -8.296 -6.063 -2.922\n",
+ " 100v (cell) float64 4MB -8.215 -9.827 -10.22 ... -6.401 -8.995 -10.81\n",
+ " 10u (cell) float64 4MB 4.36 2.381 0.09148 ... -5.739 -4.711 -3.002\n",
+ " 10v (cell) float64 4MB -4.953 -6.245 -6.762 ... -3.089 -4.959 -6.483\n",
+ " 2d (cell) float64 4MB 259.5 259.7 259.9 260.1 ... 219.4 219.4 219.4\n",
+ " 2t (cell) float64 4MB 261.9 262.1 262.3 262.5 ... 223.3 223.4 223.5\n",
+ " ... ...\n",
+ " swvl4 (cell) float64 4MB 0.0 0.0 0.0 0.0 ... 0.1602 0.1602 0.1602 0.1602\n",
+ " tcc (cell) float64 4MB 0.9721 0.9683 0.9667 ... 0.9813 0.9838 0.9871\n",
+ " tco3 (cell) float64 4MB 0.006883 0.006877 0.006873 ... 0.002953 0.002952\n",
+ " tcw (cell) float64 4MB 5.733 5.772 5.815 5.877 ... 0.4126 0.4126 0.4126\n",
+ " tcwv (cell) float64 4MB 5.655 5.692 5.733 5.793 ... 0.3989 0.4008 0.4008\n",
+ " tsn (cell) float64 4MB 261.7 261.9 262.1 262.4 ... 221.2 221.3 221.3\n",
+ "Attributes: (12/22)\n",
+ " project: ECMWF Re-Analysis\n",
+ " project_id: ERA\n",
+ " institution_id: ECMWF-DKRZ\n",
+ " institution: Data from European Centre for Medium-Range Weather ...\n",
+ " source_id: IFS\n",
+ " source: ECMWF Integrated Forecast System (IFS) CY41R2\n",
+ " ... ...\n",
+ " format: kerchunk\n",
+ " product: reanalysis\n",
+ " responsible_persons: Angelika Heil, Fabian Wachsmann\n",
+ " title: The DKRZ ERA5 data pool. Generated using Copernicus...\n",
+ " license: The ERA5 data are published with the Copernicus Pro...\n",
+ " references: Hersbach, H., Bell, B., Berrisford, P., Hirahara, S..."
+ ]
+ },
+ "execution_count": 50,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "ds.isel(time=-1).load()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2887ced5-7341-49e0-b0f0-511d68f55c74",
+ "metadata": {},
+ "source": [
+ "**Intake**\n",
+ "\n",
+ "The default **method** for intake datasets is *kerchunk* i.e. the datasets are loaded through the kerchunk API per default."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "5fb665bb-fdd1-47be-81ce-51d71506533c",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "https://l40354.lvt.dkrz.de:9000/intake.yaml\n"
+ ]
+ }
+ ],
+ "source": [
+ "intake_url='/'.join([hosturl,\"intake.yaml\"])\n",
+ "print(intake_url)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 53,
+ "id": "54d805e3-6e73-46bd-838e-b8d61ecec2d6",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['era5']"
+ ]
+ },
+ "execution_count": 53,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import intake\n",
+ "cat=intake.open_catalog(\n",
+ " intake_url,\n",
+ " storage_options=storage_options\n",
+ ")\n",
+ "list(cat)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 54,
+ "id": "62eb5ed4-9635-4e0d-822d-38ca5aad386f",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/work/bm0021/conda-envs/cloudify/lib/python3.11/site-packages/intake_xarray/base.py:21: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
+ " 'dims': dict(self._ds.dims),\n"
+ ]
+ },
+ {
+ "data": {
+ "text/html": [
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+ " --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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+ "}\n",
+ "\n",
+ ".xr-header > div,\n",
+ ".xr-header > ul {\n",
+ " display: inline;\n",
+ " margin-top: 0;\n",
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+ ".xr-section-item input:enabled + label {\n",
+ " cursor: pointer;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-section-item input:enabled + label:hover {\n",
+ " color: var(--xr-font-color0);\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary {\n",
+ " grid-column: 1;\n",
+ " color: var(--xr-font-color2);\n",
+ " font-weight: 500;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary > span {\n",
+ " display: inline-block;\n",
+ " padding-left: 0.5em;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:disabled + label {\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in + label:before {\n",
+ " display: inline-block;\n",
+ " content: 'â–º';\n",
+ " font-size: 11px;\n",
+ " width: 15px;\n",
+ " text-align: center;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:disabled + label:before {\n",
+ " color: var(--xr-disabled-color);\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:checked + label:before {\n",
+ " content: 'â–¼';\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:checked + label > span {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary,\n",
+ ".xr-section-inline-details {\n",
+ " padding-top: 4px;\n",
+ " padding-bottom: 4px;\n",
+ "}\n",
+ "\n",
+ ".xr-section-inline-details {\n",
+ " grid-column: 2 / -1;\n",
+ "}\n",
+ "\n",
+ ".xr-section-details {\n",
+ " display: none;\n",
+ " grid-column: 1 / -1;\n",
+ " margin-bottom: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+ " display: contents;\n",
+ "}\n",
+ "\n",
+ ".xr-array-wrap {\n",
+ " grid-column: 1 / -1;\n",
+ " display: grid;\n",
+ " grid-template-columns: 20px auto;\n",
+ "}\n",
+ "\n",
+ ".xr-array-wrap > label {\n",
+ " grid-column: 1;\n",
+ " vertical-align: top;\n",
+ "}\n",
+ "\n",
+ ".xr-preview {\n",
+ " color: var(--xr-font-color3);\n",
+ "}\n",
+ "\n",
+ ".xr-array-preview,\n",
+ ".xr-array-data {\n",
+ " padding: 0 5px !important;\n",
+ " grid-column: 2;\n",
+ "}\n",
+ "\n",
+ ".xr-array-data,\n",
+ ".xr-array-in:checked ~ .xr-array-preview {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ ".xr-array-in:checked ~ .xr-array-data,\n",
+ ".xr-array-preview {\n",
+ " display: inline-block;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list {\n",
+ " display: inline-block !important;\n",
+ " list-style: none;\n",
+ " padding: 0 !important;\n",
+ " margin: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list li {\n",
+ " display: inline-block;\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list:before {\n",
+ " content: '(';\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list:after {\n",
+ " content: ')';\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list li:not(:last-child):after {\n",
+ " content: ',';\n",
+ " padding-right: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-has-index {\n",
+ " font-weight: bold;\n",
+ "}\n",
+ "\n",
+ ".xr-var-list,\n",
+ ".xr-var-item {\n",
+ " display: contents;\n",
+ "}\n",
+ "\n",
+ ".xr-var-item > div,\n",
+ ".xr-var-item label,\n",
+ ".xr-var-item > .xr-var-name span {\n",
+ " background-color: var(--xr-background-color-row-even);\n",
+ " margin-bottom: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-var-item > .xr-var-name:hover span {\n",
+ " padding-right: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-var-list > li:nth-child(odd) > div,\n",
+ ".xr-var-list > li:nth-child(odd) > label,\n",
+ ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+ " background-color: var(--xr-background-color-row-odd);\n",
+ "}\n",
+ "\n",
+ ".xr-var-name {\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-var-dims {\n",
+ " grid-column: 2;\n",
+ "}\n",
+ "\n",
+ ".xr-var-dtype {\n",
+ " grid-column: 3;\n",
+ " text-align: right;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-var-preview {\n",
+ " grid-column: 4;\n",
+ "}\n",
+ "\n",
+ ".xr-index-preview {\n",
+ " grid-column: 2 / 5;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-var-name,\n",
+ ".xr-var-dims,\n",
+ ".xr-var-dtype,\n",
+ ".xr-preview,\n",
+ ".xr-attrs dt {\n",
+ " white-space: nowrap;\n",
+ " overflow: hidden;\n",
+ " text-overflow: ellipsis;\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name:hover,\n",
+ ".xr-var-dims:hover,\n",
+ ".xr-var-dtype:hover,\n",
+ ".xr-attrs dt:hover {\n",
+ " overflow: visible;\n",
+ " width: auto;\n",
+ " z-index: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-var-attrs,\n",
+ ".xr-var-data,\n",
+ ".xr-index-data {\n",
+ " display: none;\n",
+ " background-color: var(--xr-background-color) !important;\n",
+ " padding-bottom: 5px !important;\n",
+ "}\n",
+ "\n",
+ ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+ ".xr-var-data-in:checked ~ .xr-var-data,\n",
+ ".xr-index-data-in:checked ~ .xr-index-data {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ ".xr-var-data > table {\n",
+ " float: right;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name span,\n",
+ ".xr-var-data,\n",
+ ".xr-index-name div,\n",
+ ".xr-index-data,\n",
+ ".xr-attrs {\n",
+ " padding-left: 25px !important;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs,\n",
+ ".xr-var-attrs,\n",
+ ".xr-var-data,\n",
+ ".xr-index-data {\n",
+ " grid-column: 1 / -1;\n",
+ "}\n",
+ "\n",
+ "dl.xr-attrs {\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ " display: grid;\n",
+ " grid-template-columns: 125px auto;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt,\n",
+ ".xr-attrs dd {\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ " float: left;\n",
+ " padding-right: 10px;\n",
+ " width: auto;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt {\n",
+ " font-weight: normal;\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt:hover span {\n",
+ " display: inline-block;\n",
+ " background: var(--xr-background-color);\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dd {\n",
+ " grid-column: 2;\n",
+ " white-space: pre-wrap;\n",
+ " word-break: break-all;\n",
+ "}\n",
+ "\n",
+ ".xr-icon-database,\n",
+ ".xr-icon-file-text2,\n",
+ ".xr-no-icon {\n",
+ " display: inline-block;\n",
+ " vertical-align: middle;\n",
+ " width: 1em;\n",
+ " height: 1.5em !important;\n",
+ " stroke-width: 0;\n",
+ " stroke: currentColor;\n",
+ " fill: currentColor;\n",
+ "}\n",
+ "</style><pre class='xr-text-repr-fallback'><xarray.Dataset> Size: 5TB\n",
+ "Dimensions: (time: 30955, cell: 542080)\n",
+ "Coordinates:\n",
+ " lat (cell) float64 4MB dask.array<chunksize=(542080,), meta=np.ndarray>\n",
+ " lon (cell) float64 4MB dask.array<chunksize=(542080,), meta=np.ndarray>\n",
+ " * time (time) datetime64[ns] 248kB 1940-01-01T11:30:00 ... 2024-09-30T1...\n",
+ "Dimensions without coordinates: cell\n",
+ "Data variables: (12/40)\n",
+ " 100u (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " 100v (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " 10u (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " 10v (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " 2d (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " 2t (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " ... ...\n",
+ " swvl4 (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " tcc (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " tco3 (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " tcw (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " tcwv (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ " tsn (time, cell) float64 134GB dask.array<chunksize=(1, 542080), meta=np.ndarray>\n",
+ "Attributes: (12/22)\n",
+ " project: ECMWF Re-Analysis\n",
+ " project_id: ERA\n",
+ " institution_id: ECMWF-DKRZ\n",
+ " institution: Data from European Centre for Medium-Range Weather ...\n",
+ " source_id: IFS\n",
+ " source: ECMWF Integrated Forecast System (IFS) CY41R2\n",
+ " ... ...\n",
+ " format: kerchunk\n",
+ " product: reanalysis\n",
+ " responsible_persons: Angelika Heil, Fabian Wachsmann\n",
+ " title: The DKRZ ERA5 data pool. Generated using Copernicus...\n",
+ " license: The ERA5 data are published with the Copernicus Pro...\n",
+ " references: Hersbach, H., Bell, B., Berrisford, P., Hirahara, S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4d6df1b0-bdb1-4b16-ac72-0694895e65af' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4d6df1b0-bdb1-4b16-ac72-0694895e65af' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 30955</li><li><span>cell</span>: 542080</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-dad35c42-21ba-4f77-ba4f-0dc2745729db' class='xr-section-summary-in' type='checkbox' checked><label for='section-dad35c42-21ba-4f77-ba4f-0dc2745729db' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(542080,), meta=np.ndarray></div><input id='attrs-77190960-0ebf-4d56-ae54-3252a6e292fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77190960-0ebf-4d56-ae54-3252a6e292fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5cbae670-2022-4a61-b7e4-bdd983e1567a' class='xr-var-data-in' type='checkbox'><label for='data-5cbae670-2022-4a61-b7e4-bdd983e1567a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>source :</span></dt><dd>../../../../../pool/data/ERA5/E5/sf/an/1M/167/E5sf00_1M_1940_167.grb</dd><dt><span>filter_by_keys :</span></dt><dd>{}</dd><dt><span>encode_cf :</span></dt><dd>['parameter', 'time', 'geography', 'vertical']</dd><dt><span>original_shape :</span></dt><dd>[542080]</dd><dt><span>dtype :</span></dt><dd>float64</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 4.14 MiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (542080,) </td>\n",
+ " <td> (542080,) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
+ " <td>\n",
+ " <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+ "\n",
+ " <!-- Horizontal lines -->\n",
+ " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+ " <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ "\n",
+ " <!-- Vertical lines -->\n",
+ " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ "\n",
+ " <!-- Colored Rectangle -->\n",
+ " <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+ "\n",
+ " <!-- Text -->\n",
+ " <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >542080</text>\n",
+ " <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+ "</svg>\n",
+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(542080,), meta=np.ndarray></div><input id='attrs-bc48fa7d-f6bd-4485-a417-24e2b5b670c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc48fa7d-f6bd-4485-a417-24e2b5b670c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a56c47f8-32c0-4274-a551-a2651c7f0bb3' class='xr-var-data-in' type='checkbox'><label for='data-a56c47f8-32c0-4274-a551-a2651c7f0bb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>source :</span></dt><dd>../../../../../pool/data/ERA5/E5/sf/an/1M/167/E5sf00_1M_1940_167.grb</dd><dt><span>filter_by_keys :</span></dt><dd>{}</dd><dt><span>encode_cf :</span></dt><dd>['parameter', 'time', 'geography', 'vertical']</dd><dt><span>original_shape :</span></dt><dd>[542080]</dd><dt><span>dtype :</span></dt><dd>float64</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 4.14 MiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (542080,) </td>\n",
+ " <td> (542080,) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
+ " <td>\n",
+ " <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+ "\n",
+ " <!-- Horizontal lines -->\n",
+ " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+ " <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ "\n",
+ " <!-- Vertical lines -->\n",
+ " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ "\n",
+ " <!-- Colored Rectangle -->\n",
+ " <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+ "\n",
+ " <!-- Text -->\n",
+ " <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >542080</text>\n",
+ " <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+ "</svg>\n",
+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1940-01-01T11:30:00 ... 2024-09-...</div><input id='attrs-06e88351-dd81-4ab9-bc9a-7aa94295d409' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06e88351-dd81-4ab9-bc9a-7aa94295d409' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f6beee6-9fc3-4fae-a8ba-ebd4d4631d49' class='xr-var-data-in' type='checkbox'><label for='data-0f6beee6-9fc3-4fae-a8ba-ebd4d4631d49' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_FillValue :</span></dt><dd>1970-01-01T00:00:00.000000000</dd></dl></div><div class='xr-var-data'><pre>array(['1940-01-01T11:30:00.000000000', '1940-01-02T11:30:00.000000000',\n",
+ " '1940-01-03T11:30:00.000000000', ..., '2024-09-28T11:30:00.000000000',\n",
+ " '2024-09-29T11:30:00.000000000', '2024-09-30T11:30:00.000000000'],\n",
+ " dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e7d4e979-e5e1-46d4-b0e5-5bf2e4b3ccfe' class='xr-section-summary-in' type='checkbox' ><label for='section-e7d4e979-e5e1-46d4-b0e5-5bf2e4b3ccfe' class='xr-section-summary' >Data variables: <span>(40)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>100u</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-9de938ed-7eba-45d7-97c0-f1122f78f0b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9de938ed-7eba-45d7-97c0-f1122f78f0b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2572bc1b-9cf8-4d25-968f-453d06fd810b' class='xr-var-data-in' type='checkbox'><label for='data-2572bc1b-9cf8-4d25-968f-453d06fd810b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>100u</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>100 metre U wind component</dd><dt><span>cfVarName :</span></dt><dd>u100</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
+ " <td>\n",
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+ "</svg>\n",
+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>100v</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-d0cb97d5-f914-41e1-8849-a17e5c43b3d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0cb97d5-f914-41e1-8849-a17e5c43b3d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-859c348e-aed3-4233-9879-92d7d1f76d8c' class='xr-var-data-in' type='checkbox'><label for='data-859c348e-aed3-4233-9879-92d7d1f76d8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>100v</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>100 metre V wind component</dd><dt><span>cfVarName :</span></dt><dd>v100</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
+ " <td>\n",
+ " <svg width=\"170\" height=\"85\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+ "\n",
+ " <!-- Horizontal lines -->\n",
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+ " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"35\" style=\"stroke-width:2\" />\n",
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+ "</svg>\n",
+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>10u</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-e64830f8-b455-441e-b74a-c242a8ccf5c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e64830f8-b455-441e-b74a-c242a8ccf5c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccc3b53b-4e55-4089-bdfb-644f65ee5087' class='xr-var-data-in' type='checkbox'><label for='data-ccc3b53b-4e55-4089-bdfb-644f65ee5087' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>10u</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>10 metre U wind component</dd><dt><span>cfVarName :</span></dt><dd>u10</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
+ " <td>\n",
+ " <svg width=\"170\" height=\"85\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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+ "</svg>\n",
+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>10v</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-310c557a-b878-4782-879e-58497580732e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-310c557a-b878-4782-879e-58497580732e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a17524c1-c777-4df4-b144-487779a36801' class='xr-var-data-in' type='checkbox'><label for='data-a17524c1-c777-4df4-b144-487779a36801' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>10v</dd><dt><span>units :</span></dt><dd>m s**-1</dd><dt><span>name :</span></dt><dd>10 metre V wind component</dd><dt><span>cfVarName :</span></dt><dd>v10</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
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+ " <tbody>\n",
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+ " <td> 125.02 GiB </td>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
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+ " <td> 125.02 GiB </td>\n",
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+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " <tr>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
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+ " <tr>\n",
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+ " <td> 125.02 GiB </td>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
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+ " <th> Chunk </th>\n",
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+ " <tbody>\n",
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+ " <tr>\n",
+ " <th> Bytes </th>\n",
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+ " <th> Data type </th>\n",
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+ " <tr>\n",
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+ " <table style=\"border-collapse: collapse;\">\n",
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+ " <th> Shape </th>\n",
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+ " <tr>\n",
+ " <td>\n",
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+ " <tr>\n",
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+ " <table style=\"border-collapse: collapse;\">\n",
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+ " <tbody>\n",
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+ " <tr>\n",
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+ " <tr>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
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+ " <tr>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
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+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
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+ " <th> Shape </th>\n",
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+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " <tr>\n",
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+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl2</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-55f23e51-2354-4b5c-8c69-7e15f40c9829' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55f23e51-2354-4b5c-8c69-7e15f40c9829' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-477f3005-081a-4db4-b54a-267b29220581' class='xr-var-data-in' type='checkbox'><label for='data-477f3005-081a-4db4-b54a-267b29220581' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>swvl2</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 2</dd><dt><span>cfVarName :</span></dt><dd>swvl2</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
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+ " \n",
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+ " <tr>\n",
+ " <th> Dask graph </th>\n",
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+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl3</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-7c51d3c4-e649-4da1-89d4-fb7c73fa06d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c51d3c4-e649-4da1-89d4-fb7c73fa06d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7087326c-2266-450c-8a7a-9054bf4e1c54' class='xr-var-data-in' type='checkbox'><label for='data-7087326c-2266-450c-8a7a-9054bf4e1c54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>swvl3</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 3</dd><dt><span>cfVarName :</span></dt><dd>swvl3</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
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+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
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+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>swvl4</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-78933681-a927-4401-a87d-8516d856e6e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78933681-a927-4401-a87d-8516d856e6e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aff9e77e-7fd2-4a31-83f0-e31480abc78d' class='xr-var-data-in' type='checkbox'><label for='data-aff9e77e-7fd2-4a31-83f0-e31480abc78d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>depthBelowLandLayer</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>swvl4</dd><dt><span>units :</span></dt><dd>m**3 m**-3</dd><dt><span>name :</span></dt><dd>Volumetric soil water layer 4</dd><dt><span>cfVarName :</span></dt><dd>swvl4</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
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+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
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+ " <tr>\n",
+ " <th> Shape </th>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
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+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 30955 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tcw</span></div><div class='xr-var-dims'>(time, cell)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 542080), meta=np.ndarray></div><input id='attrs-50d1137f-868b-4b89-b7a5-95c19ba8a5f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50d1137f-868b-4b89-b7a5-95c19ba8a5f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8ff652d-1697-43cb-849b-f489a41e9542' class='xr-var-data-in' type='checkbox'><label for='data-a8ff652d-1697-43cb-849b-f489a41e9542' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>typeOfLevel :</span></dt><dd>surface</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>tcw</dd><dt><span>units :</span></dt><dd>kg m**-2</dd><dt><span>name :</span></dt><dd>Total column water</dd><dt><span>cfVarName :</span></dt><dd>tcw</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 125.02 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
+ " <td> (1, 542080) </td>\n",
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+ " <tr>\n",
+ " <th> Dask graph </th>\n",
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+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " </table>\n",
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+ " <tr>\n",
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+ " <th> Chunk </th>\n",
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+ " <td> 125.02 GiB </td>\n",
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+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (30955, 542080) </td>\n",
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+ " <th> Dask graph </th>\n",
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+ " <th> Data type </th>\n",
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+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-c3b722f2-7057-49cd-bb88-0b940a9fd0bb' class='xr-section-summary-in' type='checkbox' ><label for='section-c3b722f2-7057-49cd-bb88-0b940a9fd0bb' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bd4f8239-6a72-42f3-9ba1-0b4ae3ccc598' class='xr-index-data-in' type='checkbox'/><label for='index-bd4f8239-6a72-42f3-9ba1-0b4ae3ccc598' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['1940-01-01 11:30:00', '1940-01-02 11:30:00',\n",
+ " '1940-01-03 11:30:00', '1940-01-04 11:30:00',\n",
+ " '1940-01-05 11:30:00', '1940-01-06 11:30:00',\n",
+ " '1940-01-07 11:30:00', '1940-01-08 11:30:00',\n",
+ " '1940-01-09 11:30:00', '1940-01-10 11:30:00',\n",
+ " ...\n",
+ " '2024-09-21 11:30:00', '2024-09-22 11:30:00',\n",
+ " '2024-09-23 11:30:00', '2024-09-24 11:30:00',\n",
+ " '2024-09-25 11:30:00', '2024-09-26 11:30:00',\n",
+ " '2024-09-27 11:30:00', '2024-09-28 11:30:00',\n",
+ " '2024-09-29 11:30:00', '2024-09-30 11:30:00'],\n",
+ " dtype='datetime64[ns]', name='time', length=30955, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-156b0a0d-1ab3-4d43-8f77-4a0a3f6b8037' class='xr-section-summary-in' type='checkbox' ><label for='section-156b0a0d-1ab3-4d43-8f77-4a0a3f6b8037' class='xr-section-summary' >Attributes: <span>(22)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>project :</span></dt><dd>ECMWF Re-Analysis</dd><dt><span>project_id :</span></dt><dd>ERA</dd><dt><span>institution_id :</span></dt><dd>ECMWF-DKRZ</dd><dt><span>institution :</span></dt><dd>Data from European Centre for Medium-Range Weather Forecasts (ECMWF) distributed by the Germen Climate Computing Center (DKRZ)</dd><dt><span>source_id :</span></dt><dd>IFS</dd><dt><span>source :</span></dt><dd>ECMWF Integrated Forecast System (IFS) CY41R2</dd><dt><span>experiment_id :</span></dt><dd>ERA5</dd><dt><span>simulation_id :</span></dt><dd>ERA5</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>frequency :</span></dt><dd>daily</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>grid_id :</span></dt><dd>N320</dd><dt><span>grid_type :</span></dt><dd>gaussian_reduced</dd><dt><span>resolution :</span></dt><dd>0.28125 deg</dd><dt><span>level_type :</span></dt><dd>surface</dd><dt><span>data_type :</span></dt><dd>analysis</dd><dt><span>format :</span></dt><dd>kerchunk</dd><dt><span>product :</span></dt><dd>reanalysis</dd><dt><span>responsible_persons :</span></dt><dd>Angelika Heil, Fabian Wachsmann</dd><dt><span>title :</span></dt><dd>The DKRZ ERA5 data pool. Generated using Copernicus Climate Change Service information [2024]. Data distribution by the German Climate Computing Center (DKRZ). Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains</dd><dt><span>license :</span></dt><dd>The ERA5 data are published with the Copernicus Product License with the necessity of attribution. https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products</dd><dt><span>references :</span></dt><dd>Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñozâ€Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., Thépaut, J-N. (2017): Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service (C3S) Data Store (CDS). DOI: 10.24381/cds.143582cf</dd></dl></div></li></ul></div></div>"
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+ "Attributes: (12/22)\n",
+ " project: ECMWF Re-Analysis\n",
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+ " responsible_persons: Angelika Heil, Fabian Wachsmann\n",
+ " title: The DKRZ ERA5 data pool. Generated using Copernicus...\n",
+ " license: The ERA5 data are published with the Copernicus Pro...\n",
+ " references: Hersbach, H., Bell, B., Berrisford, P., Hirahara, S..."
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+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"No description\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">title</span>\n",
+ " <span class=\"pystac-v\">\"The DKRZ ERA5 data pool. Generated using Copernicus Climate Change Service information [2024]. Data distribution by the German Climate Computing Center (DKRZ). Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">created</span>\n",
+ " <span class=\"pystac-v\">\"2025-01-06T16:01:17.800784\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">keywords</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"era5\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">providers</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">name</span>\n",
+ " <span class=\"pystac-v\">\"DKRZ\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"The data host of eerie.cloud\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">roles</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"host\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">url</span>\n",
+ " <span class=\"pystac-v\">\"https://dkrz.de\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">1</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">name</span>\n",
+ " <span class=\"pystac-v\">\"ECMWF-DKRZ\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"Data from European Centre for Medium-Range Weather Forecasts (ECMWF) distributed by the Germen Climate Computing Center (DKRZ)\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">roles</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"producer\"</span>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">url</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets/era5/\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
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+ " \n",
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+ " <span class=\"pystac-k\">datetime</span>\n",
+ " <span class=\"pystac-v\">\"2025-01-06T16:01:17.800784Z\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
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+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">dimensions</span><span class=\"pystac-l\">[] 2 items</span></summary>\n",
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+ " \n",
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+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">source_id</span>\n",
+ " <span class=\"pystac-v\">\"IFS\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">source</span>\n",
+ " <span class=\"pystac-v\">\"ECMWF Integrated Forecast System (IFS) CY41R2\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">experiment_id</span>\n",
+ " <span class=\"pystac-v\">\"ERA5\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">simulation_id</span>\n",
+ " <span class=\"pystac-v\">\"ERA5\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">realm</span>\n",
+ " <span class=\"pystac-v\">\"atmos\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">frequency</span>\n",
+ " <span class=\"pystac-v\">\"daily\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">grid_label</span>\n",
+ " <span class=\"pystac-v\">\"gn\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">grid_id</span>\n",
+ " <span class=\"pystac-v\">\"N320\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">grid_type</span>\n",
+ " <span class=\"pystac-v\">\"gaussian_reduced\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">resolution</span>\n",
+ " <span class=\"pystac-v\">\"0.28125 deg\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">level_type</span>\n",
+ " <span class=\"pystac-v\">\"surface\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">data_type</span>\n",
+ " <span class=\"pystac-v\">\"analysis\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">format</span>\n",
+ " <span class=\"pystac-v\">\"kerchunk\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">product</span>\n",
+ " <span class=\"pystac-v\">\"reanalysis\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">responsible_persons</span>\n",
+ " <span class=\"pystac-v\">\"Angelika Heil, Fabian Wachsmann\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">license</span>\n",
+ " <span class=\"pystac-v\">\"The ERA5 data are published with the Copernicus Product License with the necessity of attribution. https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">references</span>\n",
+ " <span class=\"pystac-v\">\"Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñozâ€Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., Thépaut, J-N. (2017): Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service (C3S) Data Store (CDS). DOI: 10.24381/cds.143582cf\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">_xpublish_id</span>\n",
+ " <span class=\"pystac-v\">\"era5\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">links</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">rel</span>\n",
+ " <span class=\"pystac-v\">\"DOC\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">href</span>\n",
+ " <span class=\"pystac-v\">\"https://easy.gems.dkrz.de/simulations/EERIE/eerie_data-access_online.html\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">title</span>\n",
+ " <span class=\"pystac-v\">\"Usage of the eerie.cloud\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">assets</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">data</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">href</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets/era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">type</span>\n",
+ " <span class=\"pystac-v\">\"application/vnd+zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">title</span>\n",
+ " <span class=\"pystac-v\">\"Data\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"Accessed binary data is processed on server-side\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">Volume</span>\n",
+ " <span class=\"pystac-v\">\"5000 GB uncompressed\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">No of data variables</span>\n",
+ " <span class=\"pystac-v\">\"40\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">alternate</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">kerchunk</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">name</span>\n",
+ " <span class=\"pystac-v\">\"Raw data\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"Accessed binary data is as stored on disk via kerchunk\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">href</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets/era5/kerchunk\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">roles</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"data\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">xarray_view</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">href</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets/era5/\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">type</span>\n",
+ " <span class=\"pystac-v\">\"text/html\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">title</span>\n",
+ " <span class=\"pystac-v\">\"Xarray dataset\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">description</span>\n",
+ " <span class=\"pystac-v\">\"HTML representation of the xarray dataset\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">roles</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">0</span>\n",
+ " <span class=\"pystac-v\">\"overview\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">default_var</span>\n",
+ " <span class=\"pystac-v\">\"100u\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">name</span>\n",
+ " <span class=\"pystac-v\">\"The DKRZ ERA5 data pool. Generated using Copernicus Climate Change Service information [2024]. Data distribution by the German Climate Computing Center (DKRZ). Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">levels</span><span class=\"pystac-l\">[] 1 items</span></summary>\n",
+ " \n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">0</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">name</span>\n",
+ " <span class=\"pystac-v\">\"era5\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">time</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">grid</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">datasources</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">100u</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">100v</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">10u</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">10v</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">2d</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">2t</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">asn</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">blh</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">ci</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">fal</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">flsr</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">fsr</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">hcc</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">ie</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">istl1</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">istl2</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">istl3</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">istl4</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">lcc</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">mcc</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">msl</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">rsn</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
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+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">sd</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">skt</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">sp</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">src</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">sst</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">stl1</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">stl2</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">stl3</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">stl4</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">swvl1</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">swvl2</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">swvl3</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">swvl4</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">tcc</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">tco3</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">tcw</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">tcwv</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li><details>\n",
+ " <summary class=\"pystac-summary\"><span class=\"pystac-k\">tsn</span></summary>\n",
+ " <ul style=\"margin: 0px; padding: 0px 0px 0px 1.75em; list-style: none; display: block;\">\n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">store</span>\n",
+ " <span class=\"pystac-v\">\"https://eerie.cloud.dkrz.de/datasets\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " <li class=\"pystac-row\">\n",
+ " <span class=\"pystac-k\">dataset</span>\n",
+ " <span class=\"pystac-v\">\"era5/zarr\"</span>\n",
+ " </li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " \n",
+ " </details></li>\n",
+ " \n",
+ " \n",
+ " </ul>\n",
+ " </div>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ "<Item id=era5>"
+ ]
+ },
+ "execution_count": 26,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import pystac\n",
+ "import fsspec\n",
+ "import json\n",
+ "pystac.item.Item.from_dict(\n",
+ " json.load(fsspec.open(stac_url,**storage_options).open())\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "9f7edcd1-a4ba-40e1-ae6c-2c120e8ffcdb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "!cdo=/work/bm0021/cdo_incl_cmor/cdo-test_cmortest_gcc/bin/cdo"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "cloudify",
+ "language": "python",
+ "name": "cloudify"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.0"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/workshop/5_catalog-input.ipynb b/workshop/5_catalog-input.ipynb
new file mode 100644
index 0000000..6305a99
--- /dev/null
+++ b/workshop/5_catalog-input.ipynb
@@ -0,0 +1,3695 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "1bc2dd78-97d7-4b39-bf35-03dcacc767f9",
+ "metadata": {},
+ "source": [
+ "## 5. Single Point of Input\n",
+ "\n",
+ "We now design the script such that uses an intake catalog with only kerchunked datasets as input."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "571a82ea-d7bc-42e3-8169-ae22ef999065",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Writing xpublish_spoi.py\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%writefile xpublish_spoi.py\n",
+ "\n",
+ "port=9000\n",
+ "ssl_keyfile=\"/work/bm0021/k204210/cloudify/workshop/key.pem\"\n",
+ "ssl_certfile=\"/work/bm0021/k204210/cloudify/workshop/cert.pem\"\n",
+ "\n",
+ "from cloudify.plugins.stacer import *\n",
+ "from cloudify.utils.daskhelper import *\n",
+ "from cloudify.plugins.kerchunk import *\n",
+ "import xarray as xr\n",
+ "import xpublish as xp\n",
+ "import asyncio\n",
+ "import nest_asyncio\n",
+ "import sys\n",
+ "import os\n",
+ "import intake\n",
+ "\n",
+ "nest_asyncio.apply()\n",
+ "STORAGE_OPTIONS=dict(\n",
+ " cache_size=0\n",
+ ")\n",
+ "\n",
+ "def get_options(desc):\n",
+ " options = dict(storage_options=desc[\"args\"].get(\"storage_options\", {}))\n",
+ " options[\"storage_options\"].update(STORAGE_OPTIONS)\n",
+ " return options\n",
+ "\n",
+ "if __name__ == \"__main__\": # This avoids infinite subprocess creation\n",
+ " import dask\n",
+ " zarrcluster = asyncio.get_event_loop().run_until_complete(get_dask_cluster())\n",
+ " os.environ[\"ZARR_ADDRESS\"]=zarrcluster.scheduler._address\n",
+ " \n",
+ " caturi=sys.argv[1]\n",
+ " cat = intake.open_catalog(caturi)\n",
+ "\n",
+ " dsdict={}\n",
+ " mapper_dict={}\n",
+ " for dsname in list(cat):\n",
+ " desc = cat[dsname].describe()\n",
+ " testurl = desc[\"args\"][\"urlpath\"]\n",
+ " if type(testurl)!=str:\n",
+ " continue\n",
+ " elif not testurl.startswith(\"reference::\"):\n",
+ " continue\n",
+ " options=get_options(desc)\n",
+ " ds=cat[dsname](**options).to_dask()\n",
+ "\n",
+ " sp = ds.encoding[\"source\"]\n",
+ " ds=ds.drop_encoding() \n",
+ " ds.encoding[\"source\"] = sp\n",
+ " \n",
+ " mapper_dict[sp] = fsspec.get_mapper(sp, **options)\n",
+ " dsdict[dsname]=ds\n",
+ " \n",
+ " kp = KerchunkPass()\n",
+ " kp.mapper_dict = mapper_dict\n",
+ "\n",
+ " collection = xp.Rest(dsdict)\n",
+ " collection.register_plugin(Stac())\n",
+ " collection.register_plugin(kp)\n",
+ " collection.serve(\n",
+ " host=\"0.0.0.0\",\n",
+ " port=port,\n",
+ " ssl_keyfile=ssl_keyfile,\n",
+ " ssl_certfile=ssl_certfile\n",
+ " )"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "ca64c11f-0846-4ddd-9e60-4b22dba8b32c",
+ "metadata": {},
+ "source": [
+ "We run this app with an intake catalog for all [kerchunked ERA5 data](://gitlab.dkrz.de/data-infrastructure-services/era5-kerchunks/-/raw/main/main.yaml)."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "5da13d6b-05f1-4b3b-aecd-1ac3bb635526",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "%%bash --bg\n",
+ "source activate /work/bm0021/conda-envs/cloudify\n",
+ "python xpublish_spoi.py https://gitlab.dkrz.de/data-infrastructure-services/era5-kerchunks/-/raw/main/main.yaml"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a7ab712d-eff9-4a8e-8f66-fd603e2ab658",
+ "metadata": {},
+ "source": [
+ "If sth goes wrong, you can check for *cloudify* processes that you can *kill* by ID."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "id": "9a43c4ce-be08-4493-8dd5-a3789f8c0647",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "k204210 1101263 1100112 0 07:33 ? 00:00:02 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-edc24184-27e4-4966-beb3-6f926e2d6cf0.json\n",
+ "k204210 1101280 1100112 0 07:33 ? 00:00:02 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-99eb3193-dfc0-45c3-9953-a1f29fb0888d.json\n",
+ "k204210 1101285 1100112 0 07:33 ? 00:00:02 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-0ac5cfbe-7cc6-4136-870a-cbac9aa18a7b.json\n",
+ "k204210 1101286 1100112 0 07:33 ? 00:00:02 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-947ea9d3-56f0-426e-9af8-8a5be0180793.json\n",
+ "k204210 1102668 1100112 0 09:10 ? 00:00:21 /work/bm0021/conda-envs/cloudify/bin/python -Xfrozen_modules=off -m ipykernel_launcher -f /home/k/k204210/.local/share/jupyter/runtime/kernel-f59a40b2-6d4d-41dd-b768-7ee9040e362a.json\n",
+ "k204210 1104705 1104568 0 09:55 ? 00:00:00 /work/bm0021/conda-envs/cloudify/bin/python -c from multiprocessing.resource_tracker import main;main(26)\n",
+ "k204210 1104707 1104568 1 09:55 ? 00:00:14 /work/bm0021/conda-envs/cloudify/bin/python -c from multiprocessing.spawn import spawn_main; spawn_main(tracker_fd=27, pipe_handle=37) --multiprocessing-fork\n",
+ "k204210 1104710 1104568 1 09:55 ? 00:00:13 /work/bm0021/conda-envs/cloudify/bin/python -c from multiprocessing.spawn import spawn_main; spawn_main(tracker_fd=27, pipe_handle=37) --multiprocessing-fork\n",
+ "k204210 1105119 1102668 0 10:07 pts/3 00:00:00 /bin/bash -c ps -ef | grep cloudify\n",
+ "k204210 1105121 1105119 0 10:07 pts/3 00:00:00 grep cloudify\n"
+ ]
+ }
+ ],
+ "source": [
+ "!ps -ef | grep cloudify"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "id": "2e3ff970-2706-47c8-8bc2-e9d559762672",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "!kill 1104568"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "id": "5fb665bb-fdd1-47be-81ce-51d71506533c",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "https://l40072.lvt.dkrz.de:9000/intake.yaml\n"
+ ]
+ }
+ ],
+ "source": [
+ "port=9000\n",
+ "hostname=!echo $HOSTNAME\n",
+ "hosturl=\"https://\"+hostname[0]+\":\"+str(port)\n",
+ "intake_url='/'.join([hosturl,\"intake.yaml\"])\n",
+ "print(intake_url)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "id": "54d805e3-6e73-46bd-838e-b8d61ecec2d6",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['pressure-level_analysis_daily',\n",
+ " 'pressure-level_analysis_monthly',\n",
+ " 'surface_analysis_daily',\n",
+ " 'surface_analysis_hourly',\n",
+ " 'surface_analysis_monthly',\n",
+ " 'surface_forecast_hourly',\n",
+ " 'surface_forecast_monthly']"
+ ]
+ },
+ "execution_count": 24,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "import intake\n",
+ "storage_options=dict(verify_ssl=False)\n",
+ "cat=intake.open_catalog(\n",
+ " intake_url,\n",
+ " storage_options=storage_options\n",
+ ")\n",
+ "list(cat)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "id": "62eb5ed4-9635-4e0d-822d-38ca5aad386f",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/work/bm0021/conda-envs/cloudify/lib/python3.11/site-packages/intake_xarray/base.py:21: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.\n",
+ " 'dims': dict(self._ds.dims),\n"
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+ },
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+ " institution: Data from European Centre for Medium-Range Weather ...\n",
+ " source_id: IFS\n",
+ " source: ECMWF Integrated Forecast System (IFS) CY41R2\n",
+ " ... ...\n",
+ " format: kerchunk\n",
+ " product: reanalysis\n",
+ " responsible_persons: Angelika Heil, Fabian Wachsmann\n",
+ " title: The DKRZ ERA5 data pool. Generated using Copernicus...\n",
+ " license: The ERA5 data are published with the Copernicus Pro...\n",
+ " references: Hersbach, H., Bell, B., Berrisford, P., Hirahara, S...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9490f65b-97da-4d74-8e91-eca982599c86' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9490f65b-97da-4d74-8e91-eca982599c86' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1008</li><li><span class='xr-has-index'>level</span>: 37</li><li><span>value</span>: 542080</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-63c68242-488e-42ca-af4a-ed248bdf7127' class='xr-section-summary-in' type='checkbox' checked><label for='section-63c68242-488e-42ca-af4a-ed248bdf7127' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(542080,), meta=np.ndarray></div><input id='attrs-11c6d7fa-52df-4960-83be-ddcaab0b562c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11c6d7fa-52df-4960-83be-ddcaab0b562c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef2cc14e-ad98-4802-822f-c49f616707cb' class='xr-var-data-in' type='checkbox'><label for='data-ef2cc14e-ad98-4802-822f-c49f616707cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 4.14 MiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (542080,) </td>\n",
+ " <td> (542080,) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
+ " <td>\n",
+ " <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+ "\n",
+ " <!-- Horizontal lines -->\n",
+ " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+ " <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ "\n",
+ " <!-- Vertical lines -->\n",
+ " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ "\n",
+ " <!-- Colored Rectangle -->\n",
+ " <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+ "\n",
+ " <!-- Text -->\n",
+ " <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >542080</text>\n",
+ " <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+ "</svg>\n",
+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>level</span></div><div class='xr-var-dims'>(level)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 5 7 ... 900 925 950 975 1000</div><input id='attrs-c9a4d9ae-8265-407c-ae10-d02d6234d785' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c9a4d9ae-8265-407c-ae10-d02d6234d785' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a09f80f2-26ff-45b8-80aa-71782b7e17ea' class='xr-var-data-in' type='checkbox'><label for='data-a09f80f2-26ff-45b8-80aa-71782b7e17ea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1, 2, 3, 5, 7, 10, 20, 30, 50, 70, 100, 125,\n",
+ " 150, 175, 200, 225, 250, 300, 350, 400, 450, 500, 550, 600,\n",
+ " 650, 700, 750, 775, 800, 825, 850, 875, 900, 925, 950, 975,\n",
+ " 1000])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(542080,), meta=np.ndarray></div><input id='attrs-59bb3c3e-6c36-4747-80f9-f605d795f924' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59bb3c3e-6c36-4747-80f9-f605d795f924' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b459ef7-611b-4eb6-9028-c649a3f159aa' class='xr-var-data-in' type='checkbox'><label for='data-7b459ef7-611b-4eb6-9028-c649a3f159aa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 4.14 MiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (542080,) </td>\n",
+ " <td> (542080,) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
+ " <td>\n",
+ " <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+ "\n",
+ " <!-- Horizontal lines -->\n",
+ " <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
+ " <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ "\n",
+ " <!-- Vertical lines -->\n",
+ " <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ " <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+ "\n",
+ " <!-- Colored Rectangle -->\n",
+ " <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+ "\n",
+ " <!-- Text -->\n",
+ " <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >542080</text>\n",
+ " <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+ "</svg>\n",
+ " </td>\n",
+ " </tr>\n",
+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1940-01-01T12:00:00 ... 2023-12-...</div><input id='attrs-94312652-e85e-4a2f-8520-d5ab1330b008' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-94312652-e85e-4a2f-8520-d5ab1330b008' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-523e3082-c2d8-4b21-bb08-70e3f99cc40f' class='xr-var-data-in' type='checkbox'><label for='data-523e3082-c2d8-4b21-bb08-70e3f99cc40f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(['1940-01-01T12:00:00.000000000', '1940-02-01T12:00:00.000000000',\n",
+ " '1940-03-01T12:00:00.000000000', ..., '2023-10-01T12:00:00.000000000',\n",
+ " '2023-11-01T12:00:00.000000000', '2023-12-01T12:00:00.000000000'],\n",
+ " dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b96b4455-68fe-41ab-acea-de381b21c78a' class='xr-section-summary-in' type='checkbox' ><label for='section-b96b4455-68fe-41ab-acea-de381b21c78a' class='xr-section-summary' >Data variables: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>cc</span></div><div class='xr-var-dims'>(time, level, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1, 542080), meta=np.ndarray></div><input id='attrs-37e08c83-cc1e-4886-bc1c-5b78712f805b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37e08c83-cc1e-4886-bc1c-5b78712f805b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4dbb298b-bcbe-4082-94e2-217ccd231830' class='xr-var-data-in' type='checkbox'><label for='data-4dbb298b-bcbe-4082-94e2-217ccd231830' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>248</dd><dt><span>numberOfPoints :</span></dt><dd>542080</dd><dt><span>typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>cc</dd><dt><span>units :</span></dt><dd>(0 - 1)</dd><dt><span>name :</span></dt><dd>Fraction of cloud cover</dd><dt><span>cfVarName :</span></dt><dd>cc</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1008, 37, 542080) </td>\n",
+ " <td> (1, 1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 37296 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ " </table>\n",
+ " </td>\n",
+ " <td>\n",
+ " <svg width=\"194\" height=\"90\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+ "\n",
+ " <!-- Horizontal lines -->\n",
+ " <line x1=\"10\" y1=\"0\" x2=\"24\" y2=\"14\" style=\"stroke-width:2\" />\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
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+ " <td> (1, 1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
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+ " <th> Data type </th>\n",
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+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
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+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
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+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
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+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
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+ " <td> (1, 1, 542080) </td>\n",
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+ " <th> Data type </th>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
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+ " </tr>\n",
+ " <tr>\n",
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+ " <th> Data type </th>\n",
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+ " <td>\n",
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+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
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+ " <td> (1, 1, 542080) </td>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1008, 37, 542080) </td>\n",
+ " <td> (1, 1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
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+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1008, 37, 542080) </td>\n",
+ " <td> (1, 1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 37296 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
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+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1008, 37, 542080) </td>\n",
+ " <td> (1, 1, 542080) </td>\n",
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+ " <th> Data type </th>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1008, 37, 542080) </td>\n",
+ " <td> (1, 1, 542080) </td>\n",
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+ " <tr>\n",
+ " <th> Dask graph </th>\n",
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+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " \n",
+ " <tr>\n",
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+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
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+ " <td> (1, 1, 542080) </td>\n",
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+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>t</span></div><div class='xr-var-dims'>(time, level, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1, 542080), meta=np.ndarray></div><input id='attrs-93352bb4-7d2e-4c74-8035-86308dfdc30d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93352bb4-7d2e-4c74-8035-86308dfdc30d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c416ed00-3e10-4439-a5f5-58103f48ba27' class='xr-var-data-in' type='checkbox'><label for='data-c416ed00-3e10-4439-a5f5-58103f48ba27' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>130</dd><dt><span>numberOfPoints :</span></dt><dd>542080</dd><dt><span>typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>t</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Temperature</dd><dt><span>cfName :</span></dt><dd>air_temperature</dd><dt><span>cfVarName :</span></dt><dd>t</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1008, 37, 542080) </td>\n",
+ " <td> (1, 1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 37296 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " </table>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1008, 37, 542080) </td>\n",
+ " <td> (1, 1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
+ " <td colspan=\"2\"> 37296 chunks in 2 graph layers </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Data type </th>\n",
+ " <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
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+ " </td>\n",
+ " </tr>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
+ " </tr>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1008, 37, 542080) </td>\n",
+ " <td> (1, 1, 542080) </td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th> Dask graph </th>\n",
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+ " <tr>\n",
+ " <th> Data type </th>\n",
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+ "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vo</span></div><div class='xr-var-dims'>(time, level, value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 1, 542080), meta=np.ndarray></div><input id='attrs-c1b6e9c6-cf16-4efe-a912-5e4eeff429b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1b6e9c6-cf16-4efe-a912-5e4eeff429b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75143d97-6cde-4a03-8a2a-73c16dd4c5c2' class='xr-var-data-in' type='checkbox'><label for='data-75143d97-6cde-4a03-8a2a-73c16dd4c5c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>138</dd><dt><span>numberOfPoints :</span></dt><dd>542080</dd><dt><span>typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>vo</dd><dt><span>units :</span></dt><dd>s**-1</dd><dt><span>name :</span></dt><dd>Vorticity (relative)</dd><dt><span>cfName :</span></dt><dd>atmosphere_relative_vorticity</dd><dt><span>cfVarName :</span></dt><dd>vo</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div><div class='xr-var-data'><table>\n",
+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
+ " <th> Chunk </th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
+ " <th> Bytes </th>\n",
+ " <td> 150.63 GiB </td>\n",
+ " <td> 4.14 MiB </td>\n",
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+ " \n",
+ " <tr>\n",
+ " <th> Shape </th>\n",
+ " <td> (1008, 37, 542080) </td>\n",
+ " <td> (1, 1, 542080) </td>\n",
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+ " <th> Data type </th>\n",
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+ " <tr>\n",
+ " <td>\n",
+ " <table style=\"border-collapse: collapse;\">\n",
+ " <thead>\n",
+ " <tr>\n",
+ " <td> </td>\n",
+ " <th> Array </th>\n",
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+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " \n",
+ " <tr>\n",
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+ " <th> Shape </th>\n",
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+ " </tr>\n",
+ " <tr>\n",
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+ " <th> Data type </th>\n",
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+ " <td>\n",
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+ " <th> Bytes </th>\n",
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+ " <td> 4.14 MiB </td>\n",
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+ " 150, 175, 200, 225, 250, 300, 350, 400, 450, 500, 550, 600,\n",
+ " 650, 700, 750, 775, 800, 825, 850, 875, 900, 925, 950, 975,\n",
+ " 1000],\n",
+ " dtype='int64', name='level'))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bd7ba577-64e9-4a80-a91f-41c8c9b7422b' class='xr-index-data-in' type='checkbox'/><label for='index-bd7ba577-64e9-4a80-a91f-41c8c9b7422b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['1940-01-01 12:00:00', '1940-02-01 12:00:00',\n",
+ " '1940-03-01 12:00:00', '1940-04-01 12:00:00',\n",
+ " '1940-05-01 12:00:00', '1940-06-01 12:00:00',\n",
+ " '1940-07-01 12:00:00', '1940-08-01 12:00:00',\n",
+ " '1940-09-01 12:00:00', '1940-10-01 12:00:00',\n",
+ " ...\n",
+ " '2023-03-01 12:00:00', '2023-04-01 12:00:00',\n",
+ " '2023-05-01 12:00:00', '2023-06-01 12:00:00',\n",
+ " '2023-07-01 12:00:00', '2023-08-01 12:00:00',\n",
+ " '2023-09-01 12:00:00', '2023-10-01 12:00:00',\n",
+ " '2023-11-01 12:00:00', '2023-12-01 12:00:00'],\n",
+ " dtype='datetime64[ns]', name='time', length=1008, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4acbbc99-fa52-4964-81f2-323a9deeabea' class='xr-section-summary-in' type='checkbox' ><label for='section-4acbbc99-fa52-4964-81f2-323a9deeabea' class='xr-section-summary' >Attributes: <span>(22)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>project :</span></dt><dd>ECMWF Re-Analysis</dd><dt><span>project_id :</span></dt><dd>ERA</dd><dt><span>institution_id :</span></dt><dd>ECMWF-DKRZ</dd><dt><span>institution :</span></dt><dd>Data from European Centre for Medium-Range Weather Forecasts (ECMWF) distributed by the Germen Climate Computing Center (DKRZ)</dd><dt><span>source_id :</span></dt><dd>IFS</dd><dt><span>source :</span></dt><dd>ECMWF Integrated Forecast System (IFS) CY41R2</dd><dt><span>experiment_id :</span></dt><dd>ERA5</dd><dt><span>simulation_id :</span></dt><dd>ERA5</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>frequency :</span></dt><dd>monthly</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>grid_id :</span></dt><dd>N320</dd><dt><span>grid_type :</span></dt><dd>gaussian_reduced</dd><dt><span>resolution :</span></dt><dd>0.28125 deg</dd><dt><span>level_type :</span></dt><dd>pressure-level</dd><dt><span>data_type :</span></dt><dd>analysis</dd><dt><span>format :</span></dt><dd>kerchunk</dd><dt><span>product :</span></dt><dd>reanalysis</dd><dt><span>responsible_persons :</span></dt><dd>Angelika Heil, Fabian Wachsmann</dd><dt><span>title :</span></dt><dd>The DKRZ ERA5 data pool. Generated using Copernicus Climate Change Service information [2024]. Data distribution by the German Climate Computing Center (DKRZ). Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains</dd><dt><span>license :</span></dt><dd>The ERA5 data are published with the Copernicus Product License with the necessity of attribution. https://cds.climate.copernicus.eu/cdsapp/#!/terms/licence-to-use-copernicus-products</dd><dt><span>references :</span></dt><dd>Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñozâ€Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., Thépaut, J-N. (2017): Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate. Copernicus Climate Change Service (C3S) Data Store (CDS). DOI: 10.24381/cds.143582cf</dd></dl></div></li></ul></div></div>"
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+ ".xr-preview {\n",
+ " color: var(--xr-font-color3);\n",
+ "}\n",
+ "\n",
+ ".xr-array-preview,\n",
+ ".xr-array-data {\n",
+ " padding: 0 5px !important;\n",
+ " grid-column: 2;\n",
+ "}\n",
+ "\n",
+ ".xr-array-data,\n",
+ ".xr-array-in:checked ~ .xr-array-preview {\n",
+ " display: none;\n",
+ "}\n",
+ "\n",
+ ".xr-array-in:checked ~ .xr-array-data,\n",
+ ".xr-array-preview {\n",
+ " display: inline-block;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list {\n",
+ " display: inline-block !important;\n",
+ " list-style: none;\n",
+ " padding: 0 !important;\n",
+ " margin: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list li {\n",
+ " display: inline-block;\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list:before {\n",
+ " content: '(';\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list:after {\n",
+ " content: ')';\n",
+ "}\n",
+ "\n",
+ ".xr-dim-list li:not(:last-child):after {\n",
+ " content: ',';\n",
+ " padding-right: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-has-index {\n",
+ " font-weight: bold;\n",
+ "}\n",
+ "\n",
+ ".xr-var-list,\n",
+ ".xr-var-item {\n",
+ " display: contents;\n",
+ "}\n",
+ "\n",
+ ".xr-var-item > div,\n",
+ ".xr-var-item label,\n",
+ ".xr-var-item > .xr-var-name span {\n",
+ " background-color: var(--xr-background-color-row-even);\n",
+ " margin-bottom: 0;\n",
+ "}\n",
+ "\n",
+ ".xr-var-item > .xr-var-name:hover span {\n",
+ " padding-right: 5px;\n",
+ "}\n",
+ "\n",
+ ".xr-var-list > li:nth-child(odd) > div,\n",
+ ".xr-var-list > li:nth-child(odd) > label,\n",
+ ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+ " background-color: var(--xr-background-color-row-odd);\n",
+ "}\n",
+ "\n",
+ ".xr-var-name {\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-var-dims {\n",
+ " grid-column: 2;\n",
+ "}\n",
+ "\n",
+ ".xr-var-dtype {\n",
+ " grid-column: 3;\n",
+ " text-align: right;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-var-preview {\n",
+ " grid-column: 4;\n",
+ "}\n",
+ "\n",
+ ".xr-index-preview {\n",
+ " grid-column: 2 / 5;\n",
+ " color: var(--xr-font-color2);\n",
+ "}\n",
+ "\n",
+ ".xr-var-name,\n",
+ ".xr-var-dims,\n",
+ ".xr-var-dtype,\n",
+ ".xr-preview,\n",
+ ".xr-attrs dt {\n",
+ " white-space: nowrap;\n",
+ " overflow: hidden;\n",
+ " text-overflow: ellipsis;\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name:hover,\n",
+ ".xr-var-dims:hover,\n",
+ ".xr-var-dtype:hover,\n",
+ ".xr-attrs dt:hover {\n",
+ " overflow: visible;\n",
+ " width: auto;\n",
+ " z-index: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-var-attrs,\n",
+ ".xr-var-data,\n",
+ ".xr-index-data {\n",
+ " display: none;\n",
+ " background-color: var(--xr-background-color) !important;\n",
+ " padding-bottom: 5px !important;\n",
+ "}\n",
+ "\n",
+ ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+ ".xr-var-data-in:checked ~ .xr-var-data,\n",
+ ".xr-index-data-in:checked ~ .xr-index-data {\n",
+ " display: block;\n",
+ "}\n",
+ "\n",
+ ".xr-var-data > table {\n",
+ " float: right;\n",
+ "}\n",
+ "\n",
+ ".xr-var-name span,\n",
+ ".xr-var-data,\n",
+ ".xr-index-name div,\n",
+ ".xr-index-data,\n",
+ ".xr-attrs {\n",
+ " padding-left: 25px !important;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs,\n",
+ ".xr-var-attrs,\n",
+ ".xr-var-data,\n",
+ ".xr-index-data {\n",
+ " grid-column: 1 / -1;\n",
+ "}\n",
+ "\n",
+ "dl.xr-attrs {\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ " display: grid;\n",
+ " grid-template-columns: 125px auto;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt,\n",
+ ".xr-attrs dd {\n",
+ " padding: 0;\n",
+ " margin: 0;\n",
+ " float: left;\n",
+ " padding-right: 10px;\n",
+ " width: auto;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt {\n",
+ " font-weight: normal;\n",
+ " grid-column: 1;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dt:hover span {\n",
+ " display: inline-block;\n",
+ " background: var(--xr-background-color);\n",
+ " padding-right: 10px;\n",
+ "}\n",
+ "\n",
+ ".xr-attrs dd {\n",
+ " grid-column: 2;\n",
+ " white-space: pre-wrap;\n",
+ " word-break: break-all;\n",
+ "}\n",
+ "\n",
+ ".xr-icon-database,\n",
+ ".xr-icon-file-text2,\n",
+ ".xr-no-icon {\n",
+ " display: inline-block;\n",
+ " vertical-align: middle;\n",
+ " width: 1em;\n",
+ " height: 1.5em !important;\n",
+ " stroke-width: 0;\n",
+ " stroke: currentColor;\n",
+ " fill: currentColor;\n",
+ "}\n",
+ "</style><pre class='xr-text-repr-fallback'><xarray.DataArray 't' (value: 542080)> Size: 4MB\n",
+ "array([251.69160461, 251.71504211, 251.71113586, ..., 244.89863586,\n",
+ " 245.12324524, 245.40840149])\n",
+ "Coordinates:\n",
+ " lat (value) float64 4MB 89.78 89.78 89.78 ... -89.78 -89.78 -89.78\n",
+ " level int64 8B 975\n",
+ " lon (value) float64 4MB 0.0 20.0 40.0 60.0 ... 280.0 300.0 320.0 340.0\n",
+ " time datetime64[ns] 8B 1976-03-01T12:00:00\n",
+ "Dimensions without coordinates: value\n",
+ "Attributes: (12/14)\n",
+ " paramId: 130\n",
+ " numberOfPoints: 542080\n",
+ " typeOfLevel: isobaricInhPa\n",
+ " stepUnits: 1\n",
+ " stepType: avg\n",
+ " gridType: reduced_gg\n",
+ " ... ...\n",
+ " name: Temperature\n",
+ " cfName: air_temperature\n",
+ " cfVarName: t\n",
+ " missingValue: 9999\n",
+ " NV: 0\n",
+ " gridDefinitionDescription: Gaussian Latitude/Longitude Grid</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'t'</div><ul class='xr-dim-list'><li><span>value</span>: 542080</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-87a22320-42e1-4957-a33c-098c743d2f6e' class='xr-array-in' type='checkbox' checked><label for='section-87a22320-42e1-4957-a33c-098c743d2f6e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>251.7 251.7 251.7 251.7 251.7 251.6 ... 244.7 244.8 244.9 245.1 245.4</span></div><div class='xr-array-data'><pre>array([251.69160461, 251.71504211, 251.71113586, ..., 244.89863586,\n",
+ " 245.12324524, 245.40840149])</pre></div></div></li><li class='xr-section-item'><input id='section-d42b97ce-4753-492a-ac69-edfc19c40c9b' class='xr-section-summary-in' type='checkbox' checked><label for='section-d42b97ce-4753-492a-ac69-edfc19c40c9b' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>89.78 89.78 89.78 ... -89.78 -89.78</div><input id='attrs-5562d7ba-c73f-41ce-815f-360424416ec3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5562d7ba-c73f-41ce-815f-360424416ec3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db8444ee-5542-4c6c-8ca5-a48f5a71ed2d' class='xr-var-data-in' type='checkbox'><label for='data-db8444ee-5542-4c6c-8ca5-a48f5a71ed2d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([ 89.78487691, 89.78487691, 89.78487691, ..., -89.78487691,\n",
+ " -89.78487691, -89.78487691])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>975</div><input id='attrs-797e8ddb-babd-47ce-b3fc-ed9b26c8e89b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-797e8ddb-babd-47ce-b3fc-ed9b26c8e89b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-581190b1-1699-4d14-80ae-c3d04b43d326' class='xr-var-data-in' type='checkbox'><label for='data-581190b1-1699-4d14-80ae-c3d04b43d326' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(975)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(value)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 20.0 40.0 ... 300.0 320.0 340.0</div><input id='attrs-b3fd3cef-1416-4298-a462-e25e3c0ee7ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3fd3cef-1416-4298-a462-e25e3c0ee7ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2742df8c-3d26-4d60-9f45-745b40bffd20' class='xr-var-data-in' type='checkbox'><label for='data-2742df8c-3d26-4d60-9f45-745b40bffd20' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([ 0., 20., 40., ..., 300., 320., 340.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1976-03-01T12:00:00</div><input id='attrs-07225d33-9d26-4301-a7d3-1508dfd78fd9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07225d33-9d26-4301-a7d3-1508dfd78fd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5efb95c-7d4d-4286-8d7b-0b99b2a9b2ef' class='xr-var-data-in' type='checkbox'><label for='data-a5efb95c-7d4d-4286-8d7b-0b99b2a9b2ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array('1976-03-01T12:00:00.000000000', dtype='datetime64[ns]')</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cc37df7e-ef8c-4015-8469-7c91df96c8f5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cc37df7e-ef8c-4015-8469-7c91df96c8f5' class='xr-section-summary' title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-f7bc3395-12ea-400f-acfc-91aa2181c441' class='xr-section-summary-in' type='checkbox' ><label for='section-f7bc3395-12ea-400f-acfc-91aa2181c441' class='xr-section-summary' >Attributes: <span>(14)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>paramId :</span></dt><dd>130</dd><dt><span>numberOfPoints :</span></dt><dd>542080</dd><dt><span>typeOfLevel :</span></dt><dd>isobaricInhPa</dd><dt><span>stepUnits :</span></dt><dd>1</dd><dt><span>stepType :</span></dt><dd>avg</dd><dt><span>gridType :</span></dt><dd>reduced_gg</dd><dt><span>shortName :</span></dt><dd>t</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>name :</span></dt><dd>Temperature</dd><dt><span>cfName :</span></dt><dd>air_temperature</dd><dt><span>cfVarName :</span></dt><dd>t</dd><dt><span>missingValue :</span></dt><dd>9999</dd><dt><span>NV :</span></dt><dd>0</dd><dt><span>gridDefinitionDescription :</span></dt><dd>Gaussian Latitude/Longitude Grid</dd></dl></div></li></ul></div></div>"
+ ],
+ "text/plain": [
+ "<xarray.DataArray 't' (value: 542080)> Size: 4MB\n",
+ "array([251.69160461, 251.71504211, 251.71113586, ..., 244.89863586,\n",
+ " 245.12324524, 245.40840149])\n",
+ "Coordinates:\n",
+ " lat (value) float64 4MB 89.78 89.78 89.78 ... -89.78 -89.78 -89.78\n",
+ " level int64 8B 975\n",
+ " lon (value) float64 4MB 0.0 20.0 40.0 60.0 ... 280.0 300.0 320.0 340.0\n",
+ " time datetime64[ns] 8B 1976-03-01T12:00:00\n",
+ "Dimensions without coordinates: value\n",
+ "Attributes: (12/14)\n",
+ " paramId: 130\n",
+ " numberOfPoints: 542080\n",
+ " typeOfLevel: isobaricInhPa\n",
+ " stepUnits: 1\n",
+ " stepType: avg\n",
+ " gridType: reduced_gg\n",
+ " ... ...\n",
+ " name: Temperature\n",
+ " cfName: air_temperature\n",
+ " cfVarName: t\n",
+ " missingValue: 9999\n",
+ " NV: 0\n",
+ " gridDefinitionDescription: Gaussian Latitude/Longitude Grid"
+ ]
+ },
+ "execution_count": 29,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "ds[\"t\"].isel(time=434,level=35).load()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3b5053d7-8541-4dd9-b71b-88744c1fc92e",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "cloudify",
+ "language": "python",
+ "name": "cloudify"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.11.0"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
--
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