diff --git a/Tables/era5-cmor-tables/ERA5_CV.json b/Tables/era5-cmor-tables/ERA5_CV.json
new file mode 100644
index 0000000000000000000000000000000000000000..eb0a698157f5572b21fff54c9e6db54222bfef56
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_CV.json
@@ -0,0 +1,126 @@
+{
+ "CV":{
+ "activity_id":"obs4MIPs",
+ "frequency":{
+ "frequency":{
+ "1hr":"sampled hourly",
+ "day":"daily mean samples",
+ "fx":"fixed (time invariant) field",
+ "mon":"monthly mean samples"
+ },
+ "version_metadata":{
+ "CV_collection_modified":"Fri Feb 28 14:15:44 2025 -0800",
+ "CV_collection_version":"6.2.58.77",
+ "author":"Paul J. Durack <durack1@llnl.gov>",
+ "frequency_CV_modified":"Mon May 24 13:48:15 2021 00100",
+ "frequency_CV_note":"Update description of 3hr and 6hr frequencies",
+ "institution_id":"PCMDI",
+ "previous_commit":"6e872533fd1ac9980d000aba0ba16334bc9a88dd",
+ "specs_doc":"v6.2.7 (10th September 2018; https://goo.gl/v1drZl)"
+ }
+ },
+ "grid_label":{
+ "grid_label":{
+ "gm":"global mean data",
+ "gn":"data reported on a model's native grid",
+ "gr":"regridded data reported on the data provider's preferred target grid"
+ },
+ "version_metadata":{
+ "CV_collection_modified":"Fri Feb 28 14:15:44 2025 -0800",
+ "CV_collection_version":"6.2.58.77",
+ "author":"Paul J. Durack <durack1@llnl.gov>",
+ "grid_label_CV_modified":"Fri Sep 8 18:12:00 2017 -0700",
+ "grid_label_CV_note":"Issue395 durack1 augment grid_label with description (#401)",
+ "institution_id":"PCMDI",
+ "previous_commit":"6e872533fd1ac9980d000aba0ba16334bc9a88dd",
+ "specs_doc":"v6.2.7 (10th September 2018; https://goo.gl/v1drZl)"
+ }
+ },
+ "institution_id":{
+ "ECMWF":"The European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading RG2 9AX, UK"
+ },
+ "license":"ERA5 data, which are produced as part of the EU-funded Copernicus Climate Change Service (C3S), are distributed on an open basis without any specific restrictions on their usage or distribution (see License). However, all users of Copernicus Products must provide clear and visible attribution to the Copernicus program. A detailed description can be found at https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf",
+ "nominal_resolution":{
+ "nominal_resolution":[
+ "9 km",
+ "31 km"
+ ],
+ "version_metadata":{
+ "CV_collection_modified":"Fri Feb 28 14:15:44 2025 -0800",
+ "CV_collection_version":"6.2.58.77",
+ "author":"Paul J. Durack <durack1@llnl.gov>",
+ "institution_id":"PCMDI",
+ "nominal_resolution_CV_modified":"Tues Nov 15 16:04:00 2016 -0700",
+ "nominal_resolution_CV_note":"Issue141 durack1 update grid_resolution to nominal_resolution (#143)",
+ "previous_commit":"6e872533fd1ac9980d000aba0ba16334bc9a88dd",
+ "specs_doc":"v6.2.7 (10th September 2018; https://goo.gl/v1drZl)"
+ }
+ },
+ "product":[
+ "observations",
+ ],
+ "realm":[
+ "aerosol",
+ "atmos",
+ "atmosChem",
+ "land",
+ "landIce",
+ "ocean",
+ "ocnBgchem",
+ "seaIce"
+ ],
+ "region":[
+ "global",
+ "global_land",
+ "global_ocean"
+ ],
+ "required_global_attributes":[
+ "Conventions",
+ "activity_id",
+ "contact",
+ "creation_date",
+ "data_specs_version",
+ "frequency",
+ "grid",
+ "grid_label",
+ "institution",
+ "institution_id",
+ "license",
+ "nominal_resolution",
+ "product",
+ "realm",
+ "source_id",
+ "table_id",
+ "tracking_id",
+ "variable_id",
+ "variant_label"
+ ],
+ "source_id":{
+ "ERA-5":{
+ "region":"global",
+ "source":"ECMWF-ERA-5 1.0 (2019): ECMWF - ERA5 (European ReAnalysis)",
+ "source_type":"reanalysis",
+ "source_version_number":"1.0"
+ },
+ "ERA-5Land":{
+ "region":"global",
+ "source":"ECMWF-ERA-5Land 1.0 (2019): ECMWF - ERA5Land (European ReAnalysis)",
+ "source_type":"reanalysis",
+ "source_version_number":"1.0"
+ },
+ },
+ "source_type":{
+ "reanalysis":"gridded product generated from a model reanalysis based on in-situ instruments and possibly satellite measurements"
+ },
+ "table_id":[
+ "obs4MIPs_Amon",
+ "obs4MIPs_Aday",
+ "obs4MIPs_A3hr",
+ "obs4MIPs_Lmon",
+ "obs4MIPs_Omon",
+ "obs4MIPs_SImon",
+ "obs4MIPs_fx",
+ "obs4MIPs_Ofx"
+ ]
+ }
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_frequency.json b/Tables/era5-cmor-tables/ERA5_frequency.json
new file mode 100644
index 0000000000000000000000000000000000000000..d7370a98465ef2ab7ac936a848c8ba42ac55fcda
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_frequency.json
@@ -0,0 +1,19 @@
+{
+ "frequency":{
+ "frequency":{
+ "1hr":"sampled hourly",
+ "day":"daily mean samples",
+ "mon":"monthly mean samples"
+ },
+ "version_metadata":{
+ "CV_collection_modified":"Fri Feb 28 14:15:44 2025 -0800",
+ "CV_collection_version":"6.2.58.77",
+ "author":"Paul J. Durack <durack1@llnl.gov>",
+ "frequency_CV_modified":"Mon May 24 13:48:15 2021 00100",
+ "frequency_CV_note":"Update description of 3hr and 6hr frequencies",
+ "institution_id":"PCMDI",
+ "previous_commit":"6e872533fd1ac9980d000aba0ba16334bc9a88dd",
+ "specs_doc":"v6.2.7 (10th September 2018; https://goo.gl/v1drZl)"
+ }
+ }
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_grid_label.json b/Tables/era5-cmor-tables/ERA5_grid_label.json
new file mode 100644
index 0000000000000000000000000000000000000000..d98678a19d37dfff73d0fd9456c81632edd0061d
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_grid_label.json
@@ -0,0 +1,19 @@
+{
+ "grid_label":{
+ "grid_label":{
+ "gm":"global mean data",
+ "gn":"data reported on a model's native grid",
+ "gr":"regridded data reported on the data provider's preferred target grid"
+ },
+ "version_metadata":{
+ "CV_collection_modified":"Fri Feb 28 14:15:44 2025 -0800",
+ "CV_collection_version":"6.2.58.77",
+ "author":"Paul J. Durack <durack1@llnl.gov>",
+ "grid_label_CV_modified":"Fri Sep 8 18:12:00 2017 -0700",
+ "grid_label_CV_note":"Issue395 durack1 augment grid_label with description (#401)",
+ "institution_id":"PCMDI",
+ "previous_commit":"6e872533fd1ac9980d000aba0ba16334bc9a88dd",
+ "specs_doc":"v6.2.7 (10th September 2018; https://goo.gl/v1drZl)"
+ }
+ }
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_grids.json b/Tables/era5-cmor-tables/ERA5_grids.json
new file mode 100644
index 0000000000000000000000000000000000000000..7e1f82ac031239d4341e22af86e52597787891d0
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_grids.json
@@ -0,0 +1,53 @@
+{
+ "Header":{
+ "Conventions":"CF-1.7 CMIP-6.2",
+ "cmor_version":"3.5",
+ "data_specs_version":"01.00.33",
+ "missing_value":"1e20",
+ "product":"output",
+ "table_date":"18 November 2020",
+ "table_id":"Table grids"
+ },
+ "variable_entry":{
+ "latitude":{
+ "dimensions":"longitude latitude",
+ "long_name":"latitude",
+ "out_name":"latitude",
+ "standard_name":"latitude",
+ "type":"double",
+ "units":"degrees_north",
+ "valid_max":"90.0",
+ "valid_min":"-90.0"
+ },
+ "longitude":{
+ "dimensions":"longitude latitude",
+ "long_name":"longitude",
+ "out_name":"longitude",
+ "standard_name":"longitude",
+ "type":"double",
+ "units":"degrees_east",
+ "valid_max":"360.0",
+ "valid_min":"0.0"
+ },
+ "vertices_latitude":{
+ "dimensions":"vertices longitude latitude",
+ "long_name":"",
+ "out_name":"vertices_latitude",
+ "standard_name":"",
+ "type":"double",
+ "units":"degrees_north",
+ "valid_max":"90.0",
+ "valid_min":"-90.0"
+ },
+ "vertices_longitude":{
+ "dimensions":"vertices longitude latitude",
+ "long_name":"",
+ "out_name":"vertices_longitude",
+ "standard_name":"",
+ "type":"double",
+ "units":"degrees_east",
+ "valid_max":"360.0",
+ "valid_min":"0.0"
+ }
+ }
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_institution_id.json b/Tables/era5-cmor-tables/ERA5_institution_id.json
new file mode 100644
index 0000000000000000000000000000000000000000..cbd67913153228c354ad3e06cb98cfe5b2d8ba45
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_institution_id.json
@@ -0,0 +1,5 @@
+{
+ "institution_id":{
+ "ECMWF":"The European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading RG2 9AX, UK"
+ }
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_license.json b/Tables/era5-cmor-tables/ERA5_license.json
new file mode 100644
index 0000000000000000000000000000000000000000..f1a43e225620a0baf66a2490d05d1bab57a8dcf8
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_license.json
@@ -0,0 +1,3 @@
+{
+ "license":"ERA5 data, which are produced as part of the EU-funded Copernicus Climate Change Service (C3S), are distributed on an open basis without any specific restrictions on their usage or distribution (see License). However, all users of Copernicus Products must provide clear and visible attribution to the Copernicus program. A detailed description can be found at https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf"
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_nominal_resolution.json b/Tables/era5-cmor-tables/ERA5_nominal_resolution.json
new file mode 100644
index 0000000000000000000000000000000000000000..1df799f261ab1e54ba49dcda5454bb5d78564710
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_nominal_resolution.json
@@ -0,0 +1,18 @@
+{
+ "nominal_resolution":{
+ "nominal_resolution":[
+ "9 km",
+ "31 km"
+ ],
+ "version_metadata":{
+ "CV_collection_modified":"Fri Feb 28 14:15:44 2025 -0800",
+ "CV_collection_version":"6.2.58.77",
+ "author":"Paul J. Durack <durack1@llnl.gov>",
+ "institution_id":"PCMDI",
+ "nominal_resolution_CV_modified":"Tues Nov 15 16:04:00 2016 -0700",
+ "nominal_resolution_CV_note":"Issue141 durack1 update grid_resolution to nominal_resolution (#143)",
+ "previous_commit":"6e872533fd1ac9980d000aba0ba16334bc9a88dd",
+ "specs_doc":"v6.2.7 (10th September 2018; https://goo.gl/v1drZl)"
+ }
+ }
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_product.json b/Tables/era5-cmor-tables/ERA5_product.json
new file mode 100644
index 0000000000000000000000000000000000000000..30de89f2d2618d4d1b11524d613671ad3c94f536
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_product.json
@@ -0,0 +1,5 @@
+{
+ "product":[
+ "reanalysis"
+ ]
+}
diff --git a/Tables/era5-cmor-tables/ERA5_realm.json b/Tables/era5-cmor-tables/ERA5_realm.json
new file mode 100644
index 0000000000000000000000000000000000000000..ffe16ec257859c27a7dc28b1ac503857ddd7be8b
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_realm.json
@@ -0,0 +1,12 @@
+{
+ "realm":[
+ "aerosol",
+ "atmos",
+ "atmosChem",
+ "land",
+ "landIce",
+ "ocean",
+ "ocnBgchem",
+ "seaIce"
+ ]
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_region.json b/Tables/era5-cmor-tables/ERA5_region.json
new file mode 100644
index 0000000000000000000000000000000000000000..338624d6a0d38dc655b32e7242eedddcdf89730d
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_region.json
@@ -0,0 +1,7 @@
+{
+ "region":[
+ "global",
+ "global_land",
+ "global_ocean"
+ ]
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_required_global_attributes.json b/Tables/era5-cmor-tables/ERA5_required_global_attributes.json
new file mode 100644
index 0000000000000000000000000000000000000000..1c78c5af89cb36930d1b5b10a7dbc0c36fe222fb
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_required_global_attributes.json
@@ -0,0 +1,23 @@
+{
+ "required_global_attributes":[
+ "Conventions",
+ "activity_id",
+ "contact",
+ "creation_date",
+ "data_specs_version",
+ "frequency",
+ "grid",
+ "grid_label",
+ "institution",
+ "institution_id",
+ "license",
+ "nominal_resolution",
+ "product",
+ "realm",
+ "source_id",
+ "table_id",
+ "tracking_id",
+ "variable_id",
+ "variant_label"
+ ]
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_source_id.json b/Tables/era5-cmor-tables/ERA5_source_id.json
new file mode 100644
index 0000000000000000000000000000000000000000..69d8864378aa3e039d20be33caa36eceb45f80fc
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_source_id.json
@@ -0,0 +1,49 @@
+{
+ "source_id":{
+ "ERA-5":{
+ "institution_id":"ECMWF",
+ "region":[
+ "global"
+ ],
+ "release_year":"2019",
+ "source_description":"ECMWF - ERA5 (European ReAnalysis)",
+ "source_id":"ERA-5",
+ "source_label":"ECMWF-ERA-5",
+ "source_name":"ECMWF ERA-5",
+ "source_type":"reanalysis",
+ "citation":[
+ "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 (Accessed on 15-JUN-2023). Data distribution by the German Climate Computing Center (DKRZ). (E5, ET)",
+ "Simmons, A., Soci, C., Nicolas, J., Bell, B., Berrisford, P., Dragani, R., Flemming, J., Haimberger, L., Healy, S., Hersbach, H., Horányi, A., Inness, A., Munoz-Sabater, J., Radu, R., Schepers, D. (2020): ERA5.1: Rerun of the Fifth generation of ECMWF atmospheric reanalyses of the global climate (2000-2006 only). Copernicus Climate Change Service (C3S) Data Store (CDS). DOI: 10.24381/cds.143582cf (Accessed on 02-FEB-2023). Data distribution by the German Climate Computing Center (DKRZ). (E1)"
+ ],
+ "family":["E5", "ET", "E1"],
+ "source_variables":[
+ "psl",
+ "ta",
+ "tas",
+ "ua",
+ "va",
+ "zg"
+ ],
+ "source_version_number":"1.0"
+ },
+ "ERA-5Land":{
+ "institution_id":"ECMWF",
+ "region":[
+ "global"
+ ],
+ "release_year":"2019",
+ "source_description":"ECMWF - ERA5Land (European ReAnalysis)",
+ "source_id":"ERA-5Land",
+ "source_label":"ECMWF-ERA-5Land",
+ "source_name":"ECMWF ERA-5Land",
+ "source_type":"reanalysis",
+ "citation":"Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac (Accessed on DD-MMM-YYYY). Data distribution by the German Climate Computing Center (DKRZ).",
+ "family":"EL",
+ "source_variables":[
+ "pr",
+ "tas"
+ ],
+ "source_version_number":"1.0"
+ }
+ }
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_source_type.json b/Tables/era5-cmor-tables/ERA5_source_type.json
new file mode 100644
index 0000000000000000000000000000000000000000..901f156becef05de5fa5aebf89907b124f7050da
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_source_type.json
@@ -0,0 +1,5 @@
+{
+ "source_type":{
+ "reanalysis":"gridded product generated from a model reanalysis based on in-situ instruments and possibly satellite measurements"
+ }
+}
\ No newline at end of file
diff --git a/Tables/era5-cmor-tables/ERA5_table_id.json b/Tables/era5-cmor-tables/ERA5_table_id.json
new file mode 100644
index 0000000000000000000000000000000000000000..a9991d88527c52543b712b2c175beb597ba97003
--- /dev/null
+++ b/Tables/era5-cmor-tables/ERA5_table_id.json
@@ -0,0 +1,12 @@
+{
+ "table_id":[
+ "obs4MIPs_Amon",
+ "obs4MIPs_Aday",
+ "obs4MIPs_A3hr",
+ "obs4MIPs_Lmon",
+ "obs4MIPs_Omon",
+ "obs4MIPs_SImon",
+ "obs4MIPs_fx",
+ "obs4MIPs_Ofx"
+ ]
+}
\ No newline at end of file
diff --git a/Tables/original_tables/README.md b/Tables/original_tables/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..5f41aace15297a5a1767db45a2a1cd524d3ab3ba
--- /dev/null
+++ b/Tables/original_tables/README.md
@@ -0,0 +1,44 @@
+# Revision Sep/2022 E.Lucio
+# CMOR follows https
+#
+# colnumber; col abbreviation; key meaning Attribute: Global, variable, json only, skip Global attribute
+# No 0; CCC; code numbers used in DKRZ data pool, defined in https://doi.org/10.5281/zenodo.10060933 skip No, not needed inside the file metadata since this is the DKRZ code, only "code":Â #CCC,
+# No 1; ECTABLE; ECMWF GRIB table number, defined in https://codes.ecmwf.int/grib/param-db/?filter=All grib_paramID variable N
+# No 2; ECCODE; ECMWF GRIB parameter ID, defined in https://codes.ecmwf.int/grib/param-db/?filter=All grib_table variable
+# No 3; ECPAR; original ECMWF shortName of parameter as 'cdo --eccodes showname ORIGFILE' and corresponding to shortName provided in metadata of the original GRIB file orig_short_name global? N "orig_short_name": ECPAR,
+# No 4; ECNAME; original ECMWF parameter full name orig_name global? Y "orig_name": ECNAME,
+# No 5; ECUNIT; original ECMWF parameter unit orig_units global? Y "orig_units": ECUNIT,
+# No 6; ECDESC; original ECMWF parameter description grib_description global "grib_description": DESCRIPTION,
+# No 7; LTYPE; flags to indicate the ECMWF data source (an:analysis,fc:forecast,pl:pressure level,sfc:surface level). All data are ERA5, except for flags ending with _land, which are ERA5 LAND. Possible flag values: pl_an, sfc_an, sfc_fc, sfc_an_land, sfc_fc_land level_type Y
+# No 8; DIMS; dimensionality of data CMPAR(time, level, latitude, longitude) dimensions N --> Variable dimensionality
+# No 9; TREPR; type of time representation: INST instantaneous, ACC accumulated, MIN minimum, MAX maximum, IV time-invariant "orig_grid": GRIDTYPE,
+# No 10; ECGRID; native grid on which the ERA5 data are provided. redGG is reduced Gaussian
+# No 11 CMIP mapping approach 0 no, 1 CF, 3 CF-CMIP, 5 CMIP5, 6 CMIP6 Y
+# No 12 CMPAR varname follows CMOR N "variable": CMPAR "comment": COMMENT,
+
+
+# No 9 CFNAME CF standard name N "standard_name": "land_area_fraction", CFNAME "dimensions": "longitude latitude", <--- ? NEW VARIABLE ?? "DIM"
+# No 10 CMUNIT unit follows CMOR and compatible with CF canonical units N "units": CMUNIT, "type": "real", <--- I guess that this will always be REAL
+# No 11 CMFACT factor for convertion from ECUNIT to CMUNIT Y "conversion": CMFACT, "positive": "", <--- this should be derived from the conversion factor (the sign)
+# No 12 CELL_METHODS CF cell_method attribute N "cell_methods": CELL_METHODS, "grid": GRIDTYPE,
+# No 13 CELL_MEASURES CF cell_measures attribute N "cell_measures": CELL_MEASURES, "table": "180", <---?
+# No 9 CMLNAME CF long_name attribute N "long_name": CMLNAME,
+# No 13 REALM realm of the variable (atmos, land, ocean, landice, seaice, aerosol)
+# No 10 CMTABLE name of the CMOR table for monthly averages
+# No 11 GRIDTYPE gridtype
+# No 12 GRIBVERS version of GRIB (= Version 1) GRIBx (=1,2) GRIB2 (=Version 2)
+# No 13 REALM realm of the variable (atmos, land, ocean, landice, seaice, aerosol) "modeling_realm": REALM,
+# No 19 LEVELS levels extracted
+# No 20 XCES whether the variable was already in XCES or not
+# No 21 OBS complementary information 9 10 11 13 14 15 16
+
+
+
+ "project": "reanalysis",
+ "institute": "ECMWF",
+ "model": "IFS",
+ "experiment": "ERA5, ERA5-Land",
+ "institution": "European Centre for Medium-Range Weather Forecasts",
+ "license": "ERA5 data, which are produced as part of the EU-funded Copernicus Climate Change Service (C3S), are distributed on an open basis without any specific restrictions on their usage or distribution (see License). However, all users of Copernicus Products must provide clear and visible attribution to the Copernicus program. A detailed desription can be found at https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf",
+ "citation": "Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac (Accessed on DD-MMM-YYYY). Data distribution by the German Climate Computing Center (DKRZ).",
+ "family": "provisional (ET) improved (E1) final (E5)",
diff --git a/Tables/original_tables/ct_ecmwf.rc b/Tables/original_tables/ct_ecmwf.rc
new file mode 100644
index 0000000000000000000000000000000000000000..e1a149b039a5dd0f3a677d2fba2f766874dbc976
--- /dev/null
+++ b/Tables/original_tables/ct_ecmwf.rc
@@ -0,0 +1,142 @@
+# Revision Mar/2025 Etor Lucio, Angelika Heil|Unnamed: 1|Unnamed: 2|Unnamed: 3|Unnamed: 4|Unnamed: 5|Unnamed: 6|Unnamed: 7|Unnamed: 8|Unnamed: 9|Unnamed: 10|Unnamed: 11|Unnamed: 12|Unnamed: 13|Unnamed: 14|Unnamed: 15|Unnamed: 16|Unnamed: 17|Unnamed: 18|Unnamed: 19|Unnamed: 20|Unnamed: 21
+# CMOR follows https|||||||||||||||||||||
+#|||||||||||||||||||||
+# colnumber; col abbreviation; key meaning|||||||||||Attribute|Alt_Name|obs||||||||
+# No 00; CCC; code numbers used in DKRZ data pool, defined in https://doi.org/10.5281/zenodo.10060933|||||||||||skip|"""code"":Â #CCC,"|||||||||
+# No 01; ECTABLE; ECMWF GRIB table number, defined in https://codes.ecmwf.int/grib/param-db/?filter=All|||||||||||variable|grib_paramID|||||||||
+# No 02; ECCODE; ECMWF GRIB parameter ID, defined in https://codes.ecmwf.int/grib/param-db/?filter=All|||||||||||variable|grib_table|||||||||
+# No 03; ECPAR; original ECMWF shortName of parameter as 'cdo --eccodes showname ORIGFILE' and corresponding to shortName provided in metadata of the original GRIB file|||||||||||global|"""orig_short_name"": ECPAR,"|||||||||
+# No 04; ECNAME; original ECMWF parameter full name|||||||||||global|"""orig_name"": ECNAME,"|||||||||
+# No 05; ECUNIT; original ECMWF parameter unit|||||||||||global|"""orig_units"": ECUNIT,"|||||||||
+# No 06; ECDESC; original ECMWF parameter description|||||||||||global|"""grib_description"": DESCRIPTION,"|||||||||
+# No 07; LTYPE; flags to indicate the ECMWF data source (an:analysis,fc:forecast,pl:pressure level,sfc:surface level). All data are ERA5, except for flags ending with _land, which are ERA5 LAND. Possible flag values: pl_an, sfc_an, sfc_fc, sfc_an_land, sfc_fc_land|||||||||||global|level_type|||||||||
+# No 08; TREPR; type of time representation: INST instantaneous, ACC accumulated, MIN minimum, MAX maximum, IV time-invariant|||||||||||skip||"will help derive the ""dimensions"" variable (new)"||||||||
+# No 09; ECGRID; native grid on which the ERA5 data are provided. redGG is reduced Gaussian|||||||||||global|"""orig_grid"": GRIDTYPE,"|||||||||
+# No 10; CMIP; mapping approach 0 no, 1 CF, 3 CF-CMIP, 5 CMIP5, 6 CMIP6|||||||||||global||||||||||
+# No 11; CMPAR; varname follows CMOR|||||||||||variable|"""variable"": CMPAR"|||||||||
+# No 12; CFNAME; CF standard name|||||||||||variable|"""standard_name"": ""land_area_fraction"", CFNAME"|||||||||
+# No 13; CFNAME_OBS; observations over the CFNAME|||||||||||skip||||||||||
+# No 14; CMUNIT; unit follows CMOR and compatible with CF canonical units|||||||||||variable|"""units"": CMUNIT,"|"""type"": ""real"", <--- I guess that this will always be REAL"||||||||
+# No 15; CMFACT; factor for convertion from ECUNIT to CMUNIT|||||||||||global|"""conversion"": CMFACT,"|"""positive"": """", <--- this should be derived from the conversion factor (the sign)"||||||||
+# No 16; COMMENT; additional general comments|||||||||||global|"""comment"": COMMENT,"|to be appended to the json comments||||||||
+# No 17; CMLNAME; CF long_name attribute|||||||||||variable|"""long_name"": CMLNAME,"|||||||||
+# No 18; CMTABLE; name of the CMOR table for monthly averages|||||||||||global||||||||||
+# No 19; REALM; realm of the variable (atmos, land, ocean, landice, seaice, aerosol)|||||||||||variable||||||||||
+# No 20; GRIDTYPE; gridtype|||||||||||skip||||||||||
+# No 21; LTYPE_SEL; selected level type|||||||||||skip||||||||||
+|||||||||||||||||||||
+#CCC|ECTABLE|ECCODE|ECPAR|ECNAME|ECUNIT|ECDESC|LTYPE|TREPR|ECGRID|CMIP|CMPAR|CFNAME|CFNAME_OBS|CMUNIT|CMFACT|COMMENT|CMLNAME|CMTABLE|REALM|GRIDTYPE|LTYPE_SEL
+8|128|8|sro|Surface runoff|m|Some water from rainfall, melting snow, or deep in the soil, stays stored in the soil. Otherwise, the water drains away, either over the surface (surface runoff), or under the ground (sub-surface runoff) and the sum of these two is simply called 'runoff'. This parameter is the total amount of water accumulated over a [particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations).The units of runoff are depth in metres. This is the depth the water would have if it were spread evenly over the [grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step). Care should be taken when comparing model parameters with observations, because observations are often local to a particular point rather than averaged over a grid square area. Observations are also often taken in different units, such as mm/day, rather than the accumulated metres produced here. Runoff is a measure of the availability of water in the soil, and can, for example, be used as an indicator of drought or flood. More information about how runoff is calculated is given in the [ IFS Physical Processes documentation](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#subsection.H.6.3). |sfc_fc,sfc_fc_land|ACC| redGG-N320 redGG-N1280|6|mrros|surface_runoff_flux|"alternatively: surface_runoff_amount (cell_methods = ""time: sum""); if _flux, then comment needs to be added that it's not time: point --> area: mean where land time: mean"|kg m-2 s-1|1.0/3600.0|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Surface Runoff|Lmon|land|gr|sf00
+27|128|27|cvl|Low vegetation cover|(0 - 1)|This parameter is the fraction of the [grid box](https://confluence.ecmwf.int/display/CKB/model%2bgrid%2bbox%2band%2btime%2bstep) (0-1) that is covered with vegetation that is classified as 'low'. This is one of the parameters in the model that describes land surface vegetation. 'Low vegetation' consists of crops and mixed farming, irrigated crops, short grass, tall grass, tundra, semidesert, bogs and marshes, evergreen shrubs, deciduous shrubs, and water and land mixtures. |sfc_an|INV|redGG-N320 |1|cvl|"area_fraction (cell_methods=""area: mean where low_vegetation"" or like in CMIP6 ""area: mean where land over all_area_types"")"|"cvl and cvh can only have the same CF standard name if there is a further differentiation with the cell_method. But this would require adding low_vegetation and high_vegetaiton to the official CF area type table. For example, area_fraction (cell_methods=""area: mean where low_vegetation"" or like in CMIP6 ""area: mean where land over all_area_types"").So, better no CF standard name. "|%|100||Low Vegetation Cover|mon|land|gr|sf00
+28|128|28|cvh|High vegetation cover|(0 - 1)|This parameter is the fraction of the [grid box](https://confluence.ecmwf.int/display/CKB/model%2bgrid%2bbox%2band%2btime%2bstep) (0-1) that is covered with vegetation that is classified as 'high'. This is one of the parameters in the model that describes land surface vegetation. 'High vegetation' consists of evergreen trees, deciduous trees, mixed forest/woodland, and interrupted forest. |sfc_an|INV|redGG-N320 |1|cvh|"area_fraction (cell_methods=""area: mean where high_vegetation"") BUT low_vegetation needs to be added to https://cfconventions.org/Data/area-type-table/current/build/area-type-table.html "||%|100||High Vegetation Cover|mon|land|gr|sf00
+29|128|29|tvl|Type of low vegetation|~|This parameter indicates the 10 types of low vegetation recognised by the ECMWF Integrated Forecasting System: 1 = Crops, Mixed farming 2 = Grass 7 = Tall grass 9 = Tundra 10 = Irrigated crops 11 = Semidesert 13 = Bogs and marshes 16 = Evergreen shrubs 17 = Deciduous shrubs 20 = Water and land mixtures They are used to calculate the surface energy balance and the snow albedo. The other types (3, 4, 5, 6, 18, 19 and 19) are high vegetation, or indicate no land surface vegetation (8 = Desert, 12=Ice caps and Glaciers, 14 = Inland water, 15 =Ocean). |sfc_an|INV|redGG-N320 |0|tvl|no CF standard_name exist||-|1||Type of Low Vegetation|mon|land|gr|sf00
+30|128|30|tvh|Type of high vegetation|~|This parameter indicates the 6 types of high vegetation recognised by the ECMWF Integrated Forecasting System: 3 = Evergreen needleleaf trees 4 = Deciduous needleleaf trees 5 = Deciduous broadleaf trees 6 = Evergreen broadleaf trees 18 = Mixed forest/woodland 19 = Interrupted forest They are used to calculate the surface energy balance and the snow albedo. The other types (1, 2, 7, 9, 10, 11, 13, 16, 17 and 20) are low vegetation, or indicate no land surface vegetation (8 = Desert, 12=Ice caps and Glaciers, 14 = Inland water, 15 =Ocean). |sfc_an|INV|redGG-N320 |0|tvh|no CF standard_name exist||-|1||Type of High Vegetation|mon|land|gr|sf00
+31|128|31|ci|Sea ice area fraction|(0 - 1)|This parameter is the fraction of a [grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step) which is covered by sea ice. Sea ice can only occur in a grid box which includes ocean or inland water according to the land sea mask and lake cover, at the resolution being used. This parameter can be known as sea-ice (area) fraction, sea-ice concentration and more generally as sea-ice cover. Coupled atmosphere ocean simulations of the ECMWF Integrated Forecasting System (IFS) predict the formation and melting of sea ice. Otherwise, in analyses and atmosphere only simulations, sea ice is derived from observations, but the model does take account of the way that sea ice alters the interaction between the atmosphere and ocean. Sea ice is frozen sea water which floats on the surface of the ocean. Sea ice does not include ice which forms on land such as glaciers, icebergs and ice- sheets. It also excludes ice shelves which are anchored on land, but protrude out over the surface of the ocean. These phenomena are not modelled by the IFS. Long-term monitoring of sea ice is important for understanding climate change. Sea ice also affects shipping routes through the polar regions. |sfc_an|INST|redGG-N320 |5|sic|sea_ice_area_fraction||%|100||Sea Ice Area Fraction|OImon|seaIce|gr|sf00
+32|128|32|asn|Snow albedo|(0 - 1)|This parameter is a measure of the reflectivity of the snow-covered part of the [grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step). It is the fraction of solar (shortwave) radiation reflected by snow across the solar spectrum. The [ECMWF Integrated Forecast System represents snow](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#section.H.4) as a single additional layer over the uppermost soil level. This parameter changes with snow age and also depends on vegetation height. For low vegetation, it ranges between 0.52 for old snow and 0.88 for fresh snow. For high vegetation with snow underneath, it depends on vegetation type and has values between 0.27 and 0.38. See [further information](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#section.H.4). |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |0|asn|"surface_albedo (cell_methods=""area: mean where snow"")"||%|100||Snow Albedo|mon|landIce|gr|sf00
+33|128|33|rsn|Snow density|kg m-3|This parameter is the mass of snow per cubic metre in the snow layer. The ECMWF Integrated Forecast System (IFS) model represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the[ grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step). [ See further information on snow in the IFS](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#section.H.4). |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |1|rsn|surface_snow_density||kg m-3|1||Snow Density|mon|landIce|gr|sf00
+34|128|34|sst|Sea surface temperature|K|This parameter is the temperature of sea water near the surface. This parameter is taken from various providers, who process the observational data in different ways. Each provider uses data from several different observational sources. For example, satellites measure sea surface temperature (SST) in a layer a few microns thick in the uppermost mm of the ocean, drifting buoys measure SST at a depth of about 0.2-1.5m, whereas ships sample sea water down to about 10m, while the vessel is underway. Deeper measurements are not affected by changes that occur during a day, due to the rising and setting of the Sun (diurnal variations). Sometimes this parameter is taken from a forecast made by coupling the NEMO ocean model to the ECMWF Integrated Forecasting System. In this case, the SST is the average temperature of the uppermost metre of the ocean and does exhibit diurnal variations. [ See further documentation ](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#section.H.10). This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. |sfc_an,sfc_fc|INST|redGG-N320 redGG-N320 |6|tos|sea_surface_temperature||K|1||Sea Surface Temperature|Omon|ocean|gr|sf00
+35|128|35|istl1|Ice temperature layer 1|K|This parameter is the sea-ice temperature in layer 1 (0 to 7cm). The ECMWF Integrated Forecasting System (IFS) has a four-layer sea-ice slab: Layer 1: 0-7cm Layer 2: 7-28cm Layer 3: 28-100cm Layer 4: 100-150cm The temperature of the sea-ice in each layer changes as heat is transferred between the sea-ice layers and the atmosphere above and ocean below.[ See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2016/16648-part- iv-physical-processes.pdf#section.8.9). |sfc_an|INST|redGG-N320 |1|istl1|sea_ice_temperature (vertical coordinate lev=1)|"we could merge all layers into a single netcdf
+dimensions:
+ lev = 4 ;
+float istl(time, lev, latitude, longitude);
+double LEV(LEV)"|K|1||Ice Temperature Layer 1|mon|seaIce|gr|sf00
+36|128|36|istl2|Ice temperature layer 2|K|This parameter is the sea-ice temperature in layer 2 (7 to 28 cm). The ECMWF Integrated Forecasting System (IFS) has a four-layer sea-ice slab: Layer 1: 0-7cm Layer 2: 7-28cm Layer 3: 28-100cm Layer 4: 100-150cm The temperature of the sea-ice in each layer changes as heat is transferred between the sea-ice layers and the atmosphere above and ocean below.[ See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2016/16648-part- iv-physical-processes.pdf#section.8.9). |sfc_an|INST|redGG-N320 |1|istl2|sea_ice_temperature (vertical coordinate lev=2)||K|1||Ice Temperature Layer 2|mon|seaIce|gr|sf00
+37|128|37|istl3|Ice temperature layer 3|K|This parameter is the sea-ice temperature in layer 3 (28 to 100 cm). The ECMWF Integrated Forecasting System (IFS) has a four-layer sea-ice slab: Layer 1: 0-7cm Layer 2: 7-28cm Layer 3: 28-100cm Layer 4: 100-150cm The temperature of the sea-ice in each layer changes as heat is transferred between the sea-ice layers and the atmosphere above and ocean below.[ See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2016/16648-part- iv-physical-processes.pdf#section.8.9). |sfc_an|INST|redGG-N320 |1|istl3|sea_ice_temperature (vertical coordinate lev=3)||K|1||Ice Temperature Layer 3|mon|seaIce|gr|sf00
+38|128|38|istl4|Ice temperature layer 4|K|This parameter is the sea-ice temperature in layer 4 (100 to 150 cm). The ECMWF Integrated Forecasting System (IFS) has a four-layer sea-ice slab: Layer 1: 0-7cm Layer 2: 7-28cm Layer 3: 28-100cm Layer 4: 100-150cm The temperature of the sea-ice in each layer changes as heat is transferred between the sea-ice layers and the atmosphere above and ocean below.[ See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2016/16648-part- iv-physical-processes.pdf#section.8.9). |sfc_an|INST|redGG-N320 |1|istl4|sea_ice_temperature (vertical coordinate lev=4)||K|1||Ice Temperature Layer 4|mon|seaIce|gr|sf00
+39|128|39|swvl1|Volumetric soil water layer 1|m3 m-3|This parameter is the volume of water in soil layer 1 (0 - 7cm, the surface is at 0cm). The ECMWF Integrated Forecasting System model has a four-layer representation of soil: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level. |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |1|swvl1|volume_fraction_of_condensed_water_in_soil (vertical coordinate lev=1)||m3 m-3|1||Volumetric Soil Water Layer 1|mon|land|gr|sf00
+40|128|40|swvl2|Volumetric soil water layer 2|m3 m-3|This parameter is the volume of water in soil layer 2 (7 - 28cm, the surface is at 0cm). The ECMWF Integrated Forecasting System model has a four-layer representation of soil: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level. |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |1|swvl2|volume_fraction_of_condensed_water_in_soil (vertical coordinate lev=2)||m3 m-3|1||Volumetric Soil Water Layer 2|mon|land|gr|sf00
+41|128|41|swvl3|Volumetric soil water layer 3|m3 m-3|This parameter is the volume of water in soil layer 3 (28 - 100cm, the surface is at 0cm). The ECMWF Integrated Forecasting System model has a four-layer representation of soil: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level. |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |1|swvl3|volume_fraction_of_condensed_water_in_soil (vertical coordinate lev=3)||m3 m-3|1||Volumetric Soil Water Layer 3|mon|land|gr|sf00
+42|128|42|swvl4|Volumetric soil water layer 4|m3 m-3|This parameter is the volume of water in soil layer 4 (100 - 289cm, the surface is at 0cm). The ECMWF Integrated Forecasting System model has a four-layer representation of soil: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm The volumetric soil water is associated with the soil texture (or classification), soil depth, and the underlying groundwater level. |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |1|swvl4|volume_fraction_of_condensed_water_in_soil (vertical coordinate lev=4)||m3 m-3|1||Volumetric Soil Water Layer 4|mon|land|gr|sf00
+44|128|44|es|Snow evaporation|m of water equivalent|This parameter is the accumulated amount of water that has evaporated from snow from the snow-covered area of a [grid box](https://confluence.ecmwf.int/display/CKB/ERA5%253A+What+is+the+spatial+reference) into vapour in the air above. The [ECMWF Integrated Forecast System represents snow](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#section.H.4) as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box. This parameter is the depth of water there would be if the evaporated snow (from the snow-covered area of a [grid box](https://confluence.ecmwf.int/display/CKB/ERA5%253A+What+is+the+spatial+reference) ) were liquid and were spread evenly over the whole grid box. This parameter is accumulated over a [ particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). The ECMWF Integrated Forecasting System convention is that downward fluxes are positive. Therefore, negative values indicate evaporation and positive values indicate deposition. |sfc_fc,sfc_fc_land|ACC| redGG-N320 |6|esn|no CF standard_name exist||kg m-2 s-1|1.0/3.6|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Snow Evaporation|Lmon|land|gr|sf12
+45|128|45|smlt|Snowmelt|m of water equivalent|This parameter is the accumulated amount of water that has melted from snow in the snow-covered area of a [grid box](https://confluence.ecmwf.int/display/CKB/ERA5%253A+What+is+the+spatial+reference). The [ECMWF Integrated Forecast System represents snow](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#section.H.4) as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box. This parameter is the depth of water there would be if the melted snow (from the snow-covered area of a [grid box](https://confluence.ecmwf.int/display/CKB/ERA5%253A+What+is+the+spatial+reference) ) were spread evenly over the whole grid box. For example, if half the grid box were covered in snow with a water equivalent depth of 0.02m, this parameter would have a value of 0.01m. This parameter is accumulated over a [ particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). |sfc_fc,sfc_fc_land|ACC| redGG-N320 |6|snm|no CF standard_name exist||kg m-2 s-1|1.0/3.6|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Surface Snow Melt|LImon|landIce|gr|sf12
+49|128|49|10fg|10 metre wind gust since previous post-processing|m s-1|Maximum 3 second wind at 10 m height as defined by WMO. Parametrization represents turbulence only before 01102008|sfc_fc|MAX| redGG-N320 |6|wsgsmax|wind_speed_of_gust (vertical coordinate height=10m)||m s-1|1||Maximum Wind Speed of Gust at 10m|Amon|atmos|gr|sf12
+50|128|50|lspf|Large-scale precipitation fraction|s|This parameter is the accumulation of the fraction of the grid box (0-1) that was covered by large-scale precipitation. This parameter is accumulated over a [ particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). See [further information](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#subsection.7.2.4). |sfc_fc|ACC| redGG-N320 |0|lspf|no CF standard_name exist||s|1||Large-scale Precipitation Fraction|mon|atmos|gr|sf12
+57|128|57|uvb|Downward UV radiation at the surface|J m-2|This parameter is the amount of ultraviolet (UV) radiation reaching the surface. It is the amount of radiation passing through a horizontal plane, not a plane perpendicular to the direction of the Sun. UV radiation is part of the electromagnetic spectrum emitted by the Sun that has wavelengths shorter than visible light. In the ECMWF Integrated Forecasting system it is defined as radiation with a wavelength of 0.20-0.44 µm (microns, 1 millionth of a metre). Small amounts of UV are essential for living organisms, but overexposure may result in cell damage|sfc_fc|ACC| redGG-N320 |0|uvb|no CF standard_name exist||W m-2|1.0/3600.0||Downward UV Radiation at the Surface|mon|atmos|gr|sf12
+59|128|59|cape|Convective available potential energy|J kg-1|This is an indication of the instability (or stability) of the atmosphere and can be used to assess the potential for the development of convection, which can lead to heavy rainfall, thunderstorms and other severe weather. In the ECMWF Integrated Forecasting System (IFS), CAPE is calculated by considering parcels of air departing at different model levels below the 350 hPa level. If a parcel of air is more buoyant (warmer and/or with more moisture) than its surrounding environment, it will continue to rise (cooling as it rises) until it reaches a point where it no longer has positive buoyancy. CAPE is the potential energy represented by the total excess buoyancy. The maximum CAPE produced by the different parcels is the value retained. Large positive values of CAPE indicate that an air parcel would be much warmer than its surrounding environment and therefore, very buoyant. CAPE is related to the maximum potential vertical velocity of air within an updraft|sfc_fc|INST| redGG-N320 |1|cape|atmosphere_convective_available_potential_energy_wrt_surface||J kg-1|1||Convective Available Potential Energy|mon|atmos|gr|sf12
+60|128|60|pv|Potential vorticity|K m2 kg-1 s-1|Potential vorticity is a measure of the capacity for air to rotate in the atmosphere. If we ignore the effects of heating and friction, potential vorticity is conserved following an air parcel. It is used to look for places where large wind storms are likely to originate and develop. Potential vorticity increases strongly above the tropopause and therefore, it can also be used in studies related to the stratosphere and stratosphere-troposphere exchanges. Large wind storms develop when a column of air in the atmosphere starts to rotate. Potential vorticity is calculated from the wind, temperature and pressure across a column of air in the atmosphere. |pl_an|INST| redGG-N320 |1|pv|ertel_potential_vorticity||K m2 kg-1 s-1|1||Potential Vorticity|mon|atmos|gr|pl00
+75|128|75|crwc|Specific rain water content|kg kg-1|The mass of water produced from large-scale clouds that is of raindrop size and so can fall to the surface as precipitation. Large-scale clouds are generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. See [further information](https://confluence.ecmwf.int/display/CKB/Convective%2Band%2Blarge- scale%2Bprecipitation). The quantity is expressed in kilograms per kilogram of the total mass of moist air. The 'total mass of moist air' is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow. This parameter represents the average value for a [grid box](https://confluence.ecmwf.int/display/CKB/Model%2Bgrid%2Bbox%2Band%2Btime%2Bstep). Clouds contain a continuum of different sized water droplets and ice particles. The IFS cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, phase transition and aggregation are also highly simplified in the IFS. |ml_an,pl_an|INST| redGG-N320 redGG-N320 |0|crcw|mass_fraction_of_liquid_precipitation_in_air||kg kg-1|1||Specific Rain Water Content|mon|atmos|gr|pl00
+76|128|76|cswc|Specific snow water content|kg kg-1|The mass of snow (aggregated ice crystals) produced from large-scale clouds that can fall to the surface as precipitation. Large-scale clouds are generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of a grid box or larger. See [further information](https://confluence.ecmwf.int/display/CKB/Convective%2Band%2Blarge- scale%2Bprecipitation). The mass is expressed in kilograms per kilogram of the total mass of moist air. The 'total mass of moist air' is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow. This parameter represents the average value for a [grid box](https://confluence.ecmwf.int/display/CKB/Model%2Bgrid%2Bbox%2Band%2Btime%2Bstep). Clouds contain a continuum of different sized water droplets and ice particles. The IFS cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, phase transition and aggregation are also highly simplified in the IFS. |ml_an,pl_an|INST| redGG-N320 redGG-N320 |0|cswc|mass_fraction_of_snow_in_air||kg kg-1|1||Specific Snow Water Content|mon|atmos|gr|pl00
+77|128|77|etadot|Eta-coordinate vertical velocity|s-1|This parameter is the rate of air motion in the upward or downward direction. The ECMWF Integrated Forecasting System (IFS) uses a pressure and terrain-based vertical coordinate system called eta-coordinate. Since pressure in the atmosphere decreases with height, negative values of eta-coordinate vertical velocity indicate upward motion. This parameter is used in the IFS to calculate the vertical transport, or advection, of atmospheric quantities such as moisture. |ml_an|INST| specG-T639 |0|etadot|no CF standard_name exist||s-1|1||Eta-coordinate Vertical Velocity|mon|atmos|sp|ml00
+78|128|78|tclw|Total column cloud liquid water|kg m-2|This parameter is the amount of liquid water contained within cloud droplets in a column extending from the surface of the Earth to the top of the atmosphere. Rain water droplets, which are much larger in size (and mass), are not included in this parameter. This parameter represents the area averaged value for a [model grid box](https://confluence.ecmwf.int/display/CKB/model%2bgrid%2bbox%2band%2btime%2bstep). Clouds contain a continuum of different- sized water droplets and ice particles. The ECMWF Integrated Forecasting System (IFS) cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, phase transition and aggregation are also highly simplified in the IFS. |sfc_fc|INST| redGG-N320 |6|clwvi|atmosphere_mass_content_of_cloud_liquid_water||kg m-2|1||Condensed Water Path|Amon|atmos|gr|sf12
+79|128|79|tciw|Total column cloud ice water|kg m-2|This parameter is the amount of ice contained within clouds in a column extending from the surface of the Earth to the top of the atmosphere. Snow (aggregated ice crystals) is not included in this parameter. This parameter represents the area averaged value for a [model grid box](https://confluence.ecmwf.int/display/CKB/model%2bgrid%2bbox%2band%2btime%2bstep). Clouds contain a continuum of different- sized water droplets and ice particles. The ECMWF Integrated Forecasting System (IFS) cloud scheme simplifies this to represent a number of discrete cloud droplets/particles including: cloud water droplets, raindrops, ice crystals and snow (aggregated ice crystals). The processes of droplet formation, phase transition and aggregation are also highly simplified in the IFS. |sfc_fc|INST| redGG-N320 |6|clivi|atmosphere_mass_content_of_cloud_ice||kg m-2|1||Ice Water Path|Amon|atmos|gr|sf12
+129|128|129|z|Geopotential|m2 s-2|This parameter is the gravitational potential energy of a unit mass, at a particular location, relative to mean sea level. It is also the amount of work that would have to be done, against the force of gravity, to lift a unit mass to that location from mean sea level. The geopotential height can be calculated by dividing the geopotential by the Earth's gravitational acceleration, g (=9.80665 m s-2). The geopotential height plays an important role in synoptic meteorology (analysis of weather patterns). Charts of geopotential height plotted at constant pressure levels (e.g., 300, 500 or 850 hPa) can be used to identify weather systems such as cyclones, anticyclones, troughs and ridges. At the surface of the Earth, this parameter shows the variations in geopotential (height) of the surface, and is often referred to as the orography. |sfc_an,ml_an,pl_an|INV INST| specG-T639 redGG-N320 |1|z|geopotential||m2 s-2|1||Geopotential|mon|atmos|gr|pl00
+130|128|130|t|Temperature|K|This parameter is the temperature in the atmosphere. It has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. This parameter is available on multiple levels through the atmosphere. |ml_an,pl_an|INST| specG-T639 redGG-N320 |6|ta|air_temperature||K|1||Air Temperature|Amon|atmos|gr|pl00
+131|128|131|u|U component of wind|m s-1|This parameter is the eastward component of the wind. It is the horizontal speed of air moving towards the east, in metres per second. A negative sign thus indicates air movement towards the west. This parameter can be combined with the V component of wind to give the speed and direction of the horizontal wind. |ml_an,pl_an|INST| specG-T639 redGG-N320 |6|ua|eastward_wind||m s-1|1||Eastward Wind|Amon|atmos|gr|pl00
+132|128|132|v|V component of wind|m s-1|This parameter is the northward component of the wind. It is the horizontal speed of air moving towards the north, in metres per second. A negative sign thus indicates air movement towards the south. This parameter can be combined with the U component of wind to give the speed and direction of the horizontal wind. |ml_an,pl_an|INST| specG-T639 redGG-N320 |6|va|northward_wind||m s-1|1||Northward Wind|Amon|atmos|gr|pl00
+133|128|133|q|Specific humidity|kg kg-1|This parameter is the mass of water vapour per kilogram of moist air. The total mass of moist air is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow. |ml_an,pl_an|INST| redGG-N320 redGG-N320 |6|hus|specific_humidity||1|1||Specific Humidity|Amon|atmos|gr|pl00
+134|128|134|sp|Surface pressure|Pa|This parameter is the pressure (force per unit area) of the atmosphere on the surface of land, sea and in- land water. It is a measure of the weight of all the air in a column vertically above the area of the Earth's surface represented at a fixed point. Surface pressure is often used in combination with temperature to calculate air density. The strong variation of pressure with altitude makes it difficult to see the low and high pressure systems over mountainous areas, so mean sea level pressure, rather than surface pressure, is normally used for this purpose. The units of this parameter are Pascals (Pa). Surface pressure is often measured in hPa and sometimes is presented in the old units of millibars, mb (1 hPa = 1 mb= 100 Pa). |sfc_an,sfc_fc_land|INST|redGG-N320 redGG-N1280|6|ps|surface_air_pressure||Pa|1||Surface Air Pressure|Amon|atmos|gr|sf00
+135|128|135|w|Vertical velocity|Pa s-1|This parameter is the speed of air motion in the upward or downward direction. The ECMWF Integrated Forecasting System (IFS) uses a pressure based vertical co-ordinate system and pressure decreases with height, therefore negative values of vertical velocity indicate upward motion. Vertical velocity can be useful to understand the large-scale dynamics of the atmosphere, including areas of upward motion/ascent (negative values) and downward motion/subsidence (positive values). |ml_an,pl_an|INST| specG-T639 redGG-N320 |5|wap|lagrangian_tendency_of_air_pressure||Pa s-1|1||omega (=dp/dt)|Amon|atmos|gr|pl00
+136|128|136|tcw|Total column water|kg m-2|This parameter is the sum of water vapour, liquid water, cloud ice, rain and snow in a column extending from the surface of the Earth to the top of the atmosphere. In old versions of the ECMWF model (IFS), rain and snow were not accounted for. |sfc_an|INST|redGG-N320 |1|tcw|atmosphere_mass_content_of_water||kg m-2|1||Water Path|mon|atmos|gr|sf00
+137|128|137|tcwv|Total column vertically-integrated water vapour|kg m-2|This parameter is the total amount of water vapour in a column extending from the surface of the Earth to the top of the atmosphere. This parameter represents the area averaged value for a [grid box](https://confluence.ecmwf.int/display/CKB/Model%2Bgrid%2Bbox%2Band%2Btime%2Bstep). |sfc_an,sfc_fc|INST|redGG-N320 redGG-N320 |5|prw|lwe_thickness_of_atmosphere_mass_content_of_water_vapor||kg m-2|1||Water Vapor Path|Amon|atmos|gr|sf00
+138|128|138|vo|Vorticity (relative)|s-1|This parameter is a measure of the rotation of air in the horizontal, around a vertical axis, relative to a fixed point on the surface of the Earth. On the scale of weather systems, troughs (weather features that can include rain) are associated with anticlockwise rotation (in the northern hemisphere), and ridges (weather features that bring light or still winds) are associated with clockwise rotation. Adding the rotation of the Earth, the so-called Coriolis parameter, to the relative vorticity produces the absolute vorticity. |ml_an,pl_an|INST| specG-T639 redGG-N320 |1|rv|atmosphere_relative_vorticity||s-1|1||Relative Vorticity|mon|atmos|gr|pl00
+139|128|139|stl1|Soil temperature level 1|K|This parameter is the temperature of the soil at level 1 (in the middle of layer 1). The ECMWF Integrated Forecasting System (IFS) has a four-layer representation of soil, where the surface is at 0cm: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer. This parameter has units of Kelvin (K). Temperature measured in Kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. [See further information.](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#section.H.5) |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |6|tsl1|soil_temperature-atLevel1||K|1||Temperature of Soil 1|Lmon|land|gr|sf00
+141|128|141|sd|Snow depth|m of water equivalent|This parameter is the depth of snow from the snow-covered area of a [ grid box](https://confluence.ecmwf.int/display/CKB/ERA5%3A+What+is+the+spatial+reference). Its units are metres of water equivalent, so it is the depth the water would have if the snow melted and was spread evenly over the whole grid box. The ECMWF Integrated Forecast System represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box. [ See further information](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#section.H.4). |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |6|snd|lwe_thickness_of_surface_snow_amount||m|1||Snow Depth|LImon|landIce|gr|sf00
+142|128|142|lsp|Large-scale precipitation|m|This parameter is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface and which is generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of the [grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step) or larger. Precipitation can also be generated by the convection scheme in the IFS, which represents convection at spatial scales smaller than the grid box. [See further information.](https://confluence.ecmwf.int/display/CKB/Convective+and+large- scale+precipitation) This parameter does not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This parameter is the total amount of water [accumulated over a particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). The units of this parameter are depth in metres of water equivalent. It is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box. |sfc_fc|ACC| redGG-N320 |6|prlsprof|lwe_thickness_of_stratiform_precipitation_amount||kg m-2 s-1|1.0/3.6|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Stratiform Rainfall Flux|Amon|atmos|gr|sf12
+143|128|143|cp|Convective precipitation|m|This parameter is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface and which is generated by the convection scheme in the ECMWF Integrated Forecasting System (IFS). The convection scheme represents convection at spatial scales smaller than the [grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step). Precipitation can also be generated by the cloud scheme in the IFS, which represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly at spatial scales of the grid box or larger. [See further information.](https://confluence.ecmwf.int/display/CKB/Convective+and+large- scale+precipitation) This parameter does not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This parameter is the total amount of water [accumulated over a particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). The units of this parameter are depth in metres of water equivalent. It is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box. |sfc_fc|ACC| redGG-N320 |6|prcprof|lwe_thickness_of_convective_precipitation_amount||kg m-2 s-1|1.0/3.6|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Convective Rainfall Flux|Amon|atmos|gr|sf12
+144|128|144|sf|Snowfall|m of water equivalent|This parameter is the accumulated snow that falls to the Earth's surface. It is the sum of large-scale snowfall and convective snowfall. Large-scale snowfall is generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of the [grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step) or larger. Convective snowfall is generated by the convection scheme in the IFS, which represents convection at spatial scales smaller than the grid box. [See further information.](https://confluence.ecmwf.int/display/CKB/Convective+and+large- scale+precipitation) This parameter is the total amount of water [accumulated over a particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). The units of this parameter are depth in metres of water equivalent. It is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box. |sfc_fc,sfc_fc_land|ACC| redGG-N320 |6|prsn|lwe_thickness_of_snowfall_amount||kg m-2 s-1|1.0/3.6|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Snowfall Flux|Amon|atmos|gr|sf12
+145|128|145|bld|Boundary layer dissipation|J m-2|This parameter is the amount of energy per unit area that is converted from kinetic energy, into heat, due to small-scale motion in the lower levels of the atmosphere. These small-scale motions are called eddies or turbulence. A higher value of this parameter means that more energy is being converted to heat, and so the mean flow is slowing more and the air temperature is rising by a greater amount. This parameter is accumulated over a [particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). |sfc_fc|ACC| redGG-N320 |1|bld|kinetic_energy_dissipation_in_atmosphere_boundary_layer-scaling_factor_inverse_accumulation_time||W m-2|-0.0002777777777777778||Boundary Layer Dissipation|mon|atmos|gr|sf12
+146|128|146|sshf|Surface sensible heat flux|J m-2|This parameter is the transfer of heat between the Earth's surface and the atmosphere through the effects of turbulent air motion (but excluding any heat transfer resulting from condensation or evaporation). The magnitude of the sensible heat flux is governed by the difference in temperature between the surface and the overlying atmosphere, wind speed and the surface roughness. For example, cold air overlying a warm surface would produce a sensible heat flux from the land (or ocean) into the atmosphere.[ See further documentation ](https://www.ecmwf.int/sites/default/files/elibrary/2016/16648-part-iv- physical-processes.pdf#section.3.6) This is a single level parameter and it is accumulated over a [particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations).The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc,sfc_fc_land|ACC| redGG-N320 |6|hfss|integral_wrt_time_of_surface_downward_sensible_heat_flux||W m-2|-0.0002777777777777778||Surface Upward Sensible Heat Flux|Amon|atmos|gr|sf12
+147|128|147|slhf|Surface latent heat flux|J m-2|This parameter is the transfer of latent heat (resulting from water phase changes, such as evaporation or condensation) between the Earth's surface and the atmosphere through the effects of turbulent air motion. Evaporation from the Earth's surface represents a transfer of energy from the surface to the atmosphere. [See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2016/16648-part- iv-physical-processes.pdf#section.3.6) This parameter is accumulated over a [particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations).The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc,sfc_fc_land|ACC| redGG-N320 |6|hfls|integral_wrt_time_of_surface_downward_latent_heat_flux||W m-2|-0.0002777777777777778||Surface Upward Latent Heat Flux|Amon|atmos|gr|sf12
+151|128|151|msl|Mean sea level pressure|Pa|This parameter is the pressure (force per unit area) of the atmosphere adjusted to the height of mean sea level. It is a measure of the weight that all the air in a column vertically above the area of Earth's surface would have at that point, if the point were located at the mean sea level. It is calculated over all surfaces - land, sea and in-land water. Maps of mean sea level pressure are used to identify the locations of low and high pressure systems, often referred to as cyclones and anticyclones. Contours of mean sea level pressure also indicate the strength of the wind. Tightly packed contours show stronger winds. The units of this parameter are pascals (Pa). Mean sea level pressure is often measured in hPa and sometimes is presented in the old units of millibars, mb (1 hPa = 1 mb = 100 Pa). |sfc_an|INST|redGG-N320 |6|psl|air_pressure_at_mean_sea_level||Pa|1||Sea Level Pressure|Amon|atmos|gr|sf00
+152|128|152|lnsp|Logarithm of surface pressure|~|This parameter is the natural logarithm of pressure (force per unit area) of the atmosphere on the surface of land, sea and inland water. Numerical weather prediction models often utilise the logarithm of surface pressure in their calculations. |ml_an|INST| specG-T639 |0|lnsp|no CF standard_name exist||ln(Pa)|1||Logarithm of Surface Pressure|mon|atmos|sp|ml00
+155|128|155|d|Divergence|s-1|This parameter is the horizontal divergence of velocity. It is the rate at which air is spreading out horizontally from a point, per square metre. This parameter is positive for air that is spreading out, or diverging, and negative for the opposite, for air that is concentrating, or converging (convergence). |ml_an,pl_an|INST| specG-T639 redGG-N320 |1|d|divergence_of_wind||s-1|1||Divergence|mon|atmos|gr|pl00
+156|128|156|gh|Geopotential height|gpm|"This parameter is a measure of the height of a point in the atmosphere in relation to its potential energy. It is calculated by dividing the geopotential by the Earth's mean gravitational acceleration, g (=9.80665 m s-2). The geopotential is the gravitational potential energy of a unit mass, at a particular location, relative to mean sea level. Geopotential is also the amount of work that would have to be done, against the force of gravity, to lift a unit mass to that location from mean sea level.
+
+This parameter plays an important role in synoptic meteorology (analysis of weather patterns). Charts of geopotential height plotted at constant pressure levels (e.g., 300, 500 or 850 hPa) can be used to identify weather systems such as cyclones, anticyclones, troughs and ridges. At the surface of the Earth, this parameter shows the variations in geopotential height of the surface, and is often referred to as the orography.
+
+The units of this parameter are geopotential metres. A geopotential metre is approximately 2% shorter than a geometric metre."|sfc_an,ml_an,pl_an|INV INST| specG-T639 redGG-N320 |6|zg|geopotential_height||m|1.0/9.80665|derived from Geopotential (z)|Geopotential Height|Amon|atmos|gr|pl00
+157|128|157|r|Relative humidity|%|This parameter is the water vapour pressure as a percentage of the value at which the air becomes saturated (the point at which water vapour begins to condense into liquid water or deposition into ice). For temperatures over 0°C (273.15 K) it is calculated for saturation over water. At temperatures below -23°C it is calculated for saturation over ice. Between -23°C and 0°C this parameter is calculated by interpolating between the ice and water values using a quadratic function. [See more information about the model's relative humidity calculation](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#subsection.7.4.2). |pl_an|INST| redGG-N320 |6|hur|relative_humidity||%|1||Relative Humidity|Amon|atmos|gr|pl00
+159|128|159|blh|Boundary layer height|m|This parameter is the depth of air next to the Earth's surface which is most affected by the resistance to the transfer of momentum, heat or moisture across the surface. The boundary layer height can be as low as a few tens of metres, such as in cooling air at night, or as high as several kilometres over the desert in the middle of a hot sunny day. When the boundary layer height is low, higher concentrations of pollutants (emitted from the Earth's surface) can develop. The boundary layer height calculation is based on the bulk Richardson number (a measure of the atmospheric conditions) following the conclusions of a 2012 review. [ See further information](https://www.ecmwf.int/sites/default/files/elibrary/2017/17736-part- iv-physical-processes.pdf#section.3.10). |sfc_fc|INST| redGG-N320 |6|zmla|atmosphere_boundary_layer_thickness||m|1||Height of Boundary Layer|Amon|atmos|gr|sf12
+160|128|160|sdor|Standard deviation of orography|m|This parameter is one of four parameters (the others being angle of sub-gridscale orography, slope and anisotropy) that describe the features of the orography that are too small to be resolved by [the model grid](https://confluence.ecmwf.int/display/CKB/model%2bgrid%2bbox%2band%2btime%2bstep). These four parameters are calculated for orographic features with horizontal scales comprised between 5 km and the model grid resolution, being derived from the height of valleys, hills and mountains at about 1 km resolution. They are used as input for the sub-grid orography scheme which represents low-level blocking and orographic gravity wave effects. This parameter represents the standard deviation of the height of the sub-grid valleys, hills and mountains within a grid box. |sfc_an|INV|redGG-N320 |0|sdor|no CF standard_name exist||-|1||Standard Deviation of Orography|mon|atmos|gr|sf00
+161|128|161|isor|Anisotropy of sub-gridscale orography|~|This parameter is one of four parameters (the others being standard deviation, slope and angle of sub- gridscale orography) that describe the features of the orography that are too small to be resolved by [the model grid](https://confluence.ecmwf.int/display/CKB/model%2bgrid%2bbox%2band%2btime%2bstep). These four parameters are calculated for orographic features with horizontal scales comprised between 5 km and the model grid resolution, being derived from the height of valleys, hills and mountains at about 1 km resolution. They are used as input for the sub-grid orography scheme which represents low-level blocking and orographic gravity wave effects. This parameter is a measure of how much the shape of the terrain in the horizontal plane (from a bird's-eye view) is distorted from a circle. A value of one is a circle, less than one an ellipse, and 0 is a ridge. In the case of a ridge, wind blowing parallel to it does not exert any drag on the flow, but wind blowing perpendicular to it exerts the maximum drag. |sfc_an|INV|redGG-N320 |0|isor|no CF standard_name exist||-|1||Anisotropy of Sub-gridscale Orography|mon|atmos|gr|sf00
+162|128|162|anor|Angle of sub-gridscale orography|radians|This parameter is one of four parameters (the others being standard deviation, slope and anisotropy) that describe the features of the orography that are too small to be resolved by [the model grid](https://confluence.ecmwf.int/display/CKB/model%2bgrid%2bbox%2band%2btime%2bstep). These four parameters are calculated for orographic features with horizontal scales comprised between 5 km and the model grid resolution, being derived from the height of valleys, hills and mountains at about 1 km resolution. They are used as input for the sub-grid orography scheme which represents low-level blocking and orographic gravity wave effects. The angle of the sub-grid scale orography characterises the geographical orientation of the terrain in the horizontal plane (from a bird's-eye view) relative to an eastwards axis. |sfc_an|INV|redGG-N320 |0|anor|no CF standard_name exist||radians|1||Angle of Sub-gridscale Orography|mon|atmos|gr|sf00
+163|128|163|slor|Slope of sub-gridscale orography|~|This parameter is one of four parameters (the others being standard deviation, angle and anisotropy) that describe the features of the orography that are too small to be resolved by [the model grid](https://confluence.ecmwf.int/display/CKB/model%2bgrid%2bbox%2band%2btime%2bstep). These four parameters are calculated for orographic features with horizontal scales comprised between 5 km and the model grid resolution, being derived from the height of valleys, hills and mountains at about 1 km resolution. They are used as input for the sub-grid orography scheme which represents low-level blocking and orographic gravity wave effects. This parameter represents the slope of the sub-grid valleys, hills and mountains. A flat surface has a value of 0, and a 45 degree slope has a value of 0.5. |sfc_an|INV|redGG-N320 |0|slor|no CF standard_name exist||-|1||Slope of Sub-gridscale Orography|mon|atmos|gr|sf00
+164|128|164|tcc|Total cloud cover|(0 - 1)|This parameter is the proportion of a[ grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step) covered by cloud. Total cloud cover is a single level field calculated from the cloud occurring at different model levels through the atmosphere. Assumptions are made about the degree of overlap/randomness between clouds at different heights. Cloud fractions vary from 0 to 1. |sfc_an,sfc_fc|INST|redGG-N320 redGG-N320 |6|clt|cloud_area_fraction||%|100||Total Cloud Cover Percentage|Amon|atmos|gr|sf00
+165|128|165|10u|10 metre U wind component|m s-1|This parameter is the eastward component of the 10m wind. It is the horizontal speed of air moving towards the east, at a height of ten metres above the surface of the Earth, in metres per second. Care should be taken when comparing this parameter with observations, because wind observations vary on small space and time scales and are affected by the local terrain, vegetation and buildings that are represented only on average in the ECMWF Integrated Forecasting System. This parameter can be combined with the V component of 10m wind to give the speed and direction of the horizontal 10m wind. |sfc_an,sfc_fc_land|INST|redGG-N320 redGG-N1280|6|uas|eastward_wind-at10m||m s-1|1||Eastward Near-Surface Wind|Amon|atmos|gr|sf00
+166|128|166|10v|10 metre V wind component|m s-1|This parameter is the northward component of the 10m wind. It is the horizontal speed of air moving towards the north, at a height of ten metres above the surface of the Earth, in metres per second. Care should be taken when comparing this parameter with observations, because wind observations vary on small space and time scales and are affected by the local terrain, vegetation and buildings that are represented only on average in the ECMWF Integrated Forecasting System. This parameter can be combined with the U component of 10m wind to give the speed and direction of the horizontal 10m wind. |sfc_an,sfc_fc_land|INST|redGG-N320 redGG-N1280|6|vas|eastward_wind-at10m||m s-1|1||Northward Near-Surface Wind|Amon|atmos|gr|sf00
+167|128|167|2t|2 metre temperature|K|This parameter is the temperature of air at 2m above the surface of land, sea or in-land waters. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.[ See further information ](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#subsection.3.10.3). This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. |sfc_an,sfc_fc_land|INST|redGG-N320 redGG-N1280|6|tas|air_temperature||K|1||Near-Surface Air Temperature|Amon|atmos|gr|sf00
+168|128|168|2d|2 metre dewpoint temperature|K|This parameter is the temperature to which the air, at 2 metres above the surface of the Earth, would have to be cooled for saturation to occur. It is a measure of the humidity of the air. Combined with temperature and pressure, it can be used to calculate the relative humidity. 2m dew point temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.[ See further information](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#subsection.3.10.3).This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. |sfc_an,sfc_fc_land|INST|redGG-N320 redGG-N1280|6|tdps|dew_point_temperature-at2m||K|1||2m Dewpoint Temperature|Amon|atmos|gr|sf00
+169|128|169|ssrd|Surface solar radiation downwards|J m-2|This parameter is the amount of solar radiation (also known as shortwave radiation) that reaches a horizontal plane at the surface of the Earth. This parameter comprises both direct and diffuse solar radiation. Radiation from the Sun (solar, or shortwave, radiation) is partly reflected back to space by clouds and particles in the atmosphere (aerosols) and some of it is absorbed. The rest is incident on the Earth's surface (represented by this parameter). [See further documentation.](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf) To a reasonably good approximation, this parameter is the model equivalent of what would be measured by a pyranometer (an instrument used for measuring solar radiation) at the surface. However, care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a [model grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step). This parameter is [accumulated over a particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc,sfc_fc_land|ACC| redGG-N320 |1|rsds|integral_wrt_time_of_surface_downwelling_shortwave_flux_in_air||W m-2|1.0/3600.0||Surface Solar Radiation Downwards|mon|atmos|gr|sf12
+170|128|170|stl2|Soil temperature level 2|K|This parameter is the temperature of the soil at level 2 (in the middle of layer 2). The ECMWF Integrated Forecasting System (IFS) has a four-layer representation of soil, where the surface is at 0cm: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer. This parameter has units of Kelvin (K). Temperature measured in Kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. [See further information.](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#section.H.5) |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |6|tsl2|soil_temperature-atLevel2||K|1||Temperature of Soil 2|Lmon|land|gr|sf00
+172|128|172|lsm|Land-sea mask|(0 - 1)|This parameter is the proportion of land, as opposed to ocean or inland waters (lakes, reservoirs, rivers and coastal waters), in a [grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step). This parameter has values ranging between zero and one and is dimensionless. In cycles of the ECMWF Integrated Forecasting System (IFS) from CY41R1 (introduced in May 2015) onwards, grid boxes where this parameter has a value above 0.5 can be comprised of a mixture of land and inland water but not ocean. Grid boxes with a value of 0.5 and below can only be comprised of a water surface. In the latter case, the lake cover is used to determine how much of the water surface is ocean or inland water. In cycles of the IFS before CY41R1, grid boxes where this parameter has a value above 0.5 can only be comprised of land and those grid boxes with a value of 0.5 and below can only be comprised of ocean. In these older model cycles, there is no differentiation between ocean and inland water. |sfc_an|INV|redGG-N320 redGG-N320 |6|sftlf|land_area_fraction||%|100||Percentage of the Grid Cell Occupied by Land (Including Lakes)|fx|atmos|gr|sf00
+175|128|175|strd|Surface thermal radiation downwards|J m-2|This parameter is the amount of thermal (also known as longwave or terrestrial) radiation emitted by the atmosphere and clouds that reaches a horizontal plane at the surface of the Earth. The surface of the Earth emits thermal radiation, some of which is absorbed by the atmosphere and clouds. The atmosphere and clouds likewise emit thermal radiation in all directions, some of which reaches the surface (represented by this parameter). [See further documentation.](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf) This parameter is [accumulated over a particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc,sfc_fc_land|ACC| redGG-N320 |6|rlds|integral_wrt_time_of_surface_downwelling_longwave_flux_in_air||W m-2|1.0/3600||Surface Downwelling Longwave Radiation|Amon|atmos|gr|sf12
+176|128|176|ssr|Surface net solar radiation|J m-2|This parameter is the amount of solar radiation (also known as shortwave radiation) that reaches a horizontal plane at the surface of the Earth (both direct and diffuse) minus the amount reflected by the Earth's surface (which is governed by the albedo). Radiation from the Sun (solar, or shortwave, radiation) is partly reflected back to space by clouds and particles in the atmosphere (aerosols) and some of it is absorbed. The remainder is incident on the Earth's surface, where some of it is reflected. [See further documentation.](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf) This parameter is [accumulated over a particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc,sfc_fc_land|ACC| redGG-N320 |1|rss|integral_wrt_time_of_surface_net_downward_shortwave_flux||W m-2|1.0/3600.0||Surface Net Solar Radiation|Amon|atmos|gr|sf12
+177|128|177|str|Surface net thermal radiation|J m-2|Thermal radiation (also known as longwave or terrestrial radiation) refers to radiation emitted by the atmosphere, clouds and the surface of the Earth. This parameter is the difference between downward and upward thermal radiation at the surface of the Earth. It the amount passing through a horizontal plane. The atmosphere and clouds emit thermal radiation in all directions, some of which reaches the surface as downward thermal radiation. The upward thermal radiation at the surface consists of thermal radiation emitted by the surface plus the fraction of downwards thermal radiation reflected upward by the surface. [See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf). This parameter is [accumulated over a particular time period](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations) which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc,sfc_fc_land|ACC| redGG-N320 |6|rls|integral_wrt_time_of_surface_net_downward_longwave_flux||W m-2|1.0/3600||Net Longwave Surface Radiation|Emon|atmos|gr|sf12
+178|128|178|tsr|Top net solar radiation|J m-2|This parameter is the incoming solar radiation (also known as shortwave radiation) minus the outgoing solar radiation at the top of the atmosphere. It is the amount of radiation passing through a horizontal plane. The incoming solar radiation is the amount received from the Sun. The outgoing solar radiation is the amount reflected and scattered by the Earth's atmosphere and surface. [See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf). This parameter is [accumulated over a particular time period](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations) which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc|ACC| redGG-N320 |1|rst|integral_wrt_time_of_toa_net_downward_shortwave_flux||W m-2|1.0/3600.0||TOA Net Downward Shortwave Flux|mon|atmos|gr|sf12
+179|128|179|ttr|Top net thermal radiation|J m-2|The thermal (also known as terrestrial or longwave) radiation emitted to space at the top of the atmosphere is commonly known as the Outgoing Longwave Radiation (OLR). The top net thermal radiation (this parameter) is equal to the negative of OLR. [See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf). This parameter is [accumulated over a particular time period ](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations)which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds.The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc|ACC| redGG-N320 |6|rlut|integral_wrt_time_of_toa_outgoing_longwave_flux||W m-2|-0.0002777777777777778||TOA Outgoing Longwave Radiation|Amon|atmos|gr|sf12
+180|128|180|ewss|Eastward turbulent surface stress|N m-2 s|Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is the accumulated stress on the Earth's surface in the eastward direction due to both the turbulent interactions between the atmosphere and the surface, and to turbulent orographic form drag. The turbulent interactions between the atmosphere and the surface are due to the roughness of the surface. The turbulent orographic form drag is the stress due to the valleys, hills and mountains on horizontal scales below 5km being derived from land surface data at about 1 km resolution. [See further information.](https://www.ecmwf.int/en/elibrary/17117-part-iv-physical- processes) Positive (negative) values denote stress in the eastward (westward) direction. This parameter is [accumulated over a particular time period](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations) which depends on the data extracted. |sfc_fc|ACC| redGG-N320 |6|tauu|integral_wrt_time_of_surface_downward_eastward_stress||Pa|1.0/3600||Surface Downward Eastward Wind Stress|Amon|atmos|gr|sf12
+181|128|181|nsss|Northward turbulent surface stress|N m-2 s|Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is the accumulated stress on the Earth's surface in the northward direction due to both the turbulent interactions between the atmosphere and the surface, and to turbulent orographic form drag. The turbulent interactions between the atmosphere and the surface are due to the roughness of the surface. The turbulent orographic form drag is the stress due to the valleys, hills and mountains on horizontal scales below 5km being derived from land surface data at about 1 km resolution. [See further information.](https://www.ecmwf.int/en/elibrary/17117-part-iv-physical- processes) Positive (negative) values denote stress in the northward (southward) direction. This parameter is [accumulated over a particular time period](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations) which depends on the data extracted. |sfc_fc|ACC| redGG-N320 |6|tauv|integral_wrt_time_of_surface_downward_northward_stress||Pa|1.0/3600||Surface Downward Northward Wind Stress|Amon|atmos|gr|sf12
+182|128|182|e|Evaporation|m of water equivalent|This parameter is the accumulated amount of water that has evaporated from the Earth's surface, including a simplified representation of transpiration (from vegetation), into vapour in the air above. This parameter is accumulated over a[ particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). The ECMWF Integrated Forecasting System convention is that downward fluxes are positive. Therefore, negative values indicate evaporation and positive values indicate condensation. |sfc_fc,sfc_fc_land|ACC| redGG-N320 |6|evspsbl|lwe_thickness_of_water_evaporation_amount||kg m-2 s-1|1.0/3.6|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Evaporation Including Sublimation and Transpiration|Amon|atmos|gr|sf12
+183|128|183|stl3|Soil temperature level 3|K|This parameter is the temperature of the soil at level 3 (in the middle of layer 3). The ECMWF Integrated Forecasting System (IFS) has a four-layer representation of soil, where the surface is at 0cm: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer. This parameter has units of Kelvin (K). Temperature measured in Kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. [See further information.](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#section.H.5) |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |6|tsl3|soil_temperature-atLevel3||K|1||Temperature of Soil 3|Lmon|land|gr|sf00
+186|128|186|lcc|Low cloud cover|(0 - 1)|This parameter is the proportion of a[ grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step) covered by cloud occurring in the lower levels of the troposphere. Low cloud is a single level field calculated from cloud occurring on model levels with a pressure greater than 0.8 times the surface pressure. So, if the surface pressure is 1000 hPa (hectopascal), low cloud would be calculated using levels with a pressure greater than 800 hPa (below approximately 2km (assuming a 'standard atmosphere')). The low cloud cover parameter is calculated from cloud cover for the appropriate model levels as described above. Assumptions are made about the degree of overlap/randomness between clouds in different model levels. Cloud fractions vary from 0 to 1. |sfc_an|INST|redGG-N320 |1|lcc|low_type_cloud_area_fraction||%|100||Low Cloud Cover|mon|atmos|gr|sf00
+187|128|187|mcc|Medium cloud cover|(0 - 1)|This parameter is the proportion of a[ grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step) covered by cloud occurring in the middle levels of the troposphere. Medium cloud is a single level field calculated from cloud occurring on model levels with a pressure between 0.45 and 0.8 times the surface pressure. So, if the surface pressure is 1000 hPa (hectopascal), medium cloud would be calculated using levels with a pressure of less than or equal to 800 hPa and greater than or equal to 450 hPa (between approximately 2km and 6km (assuming a 'standard atmosphere')). The medium cloud parameter is calculated from cloud cover for the appropriate model levels as described above. Assumptions are made about the degree of overlap/randomness between clouds in different model levels. Cloud fractions vary from 0 to 1. |sfc_an|INST|redGG-N320 |1|mcc|medium_type_cloud_area_fraction||%|100||Medium Cloud Cover|mon|atmos|gr|sf00
+188|128|188|hcc|High cloud cover|(0 - 1)|The proportion of a [grid box ](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step)covered by cloud occurring in the high levels of the troposphere. High cloud is a single level field calculated from cloud occurring on model levels with a pressure less than 0.45 times the surface pressure. So, if the surface pressure is 1000 hPa (hectopascal), high cloud would be calculated using levels with a pressure of less than 450 hPa (approximately 6km and above ([ assuming a `standard atmosphere`](http://glossary.ametsoc.org/wiki/Standard_atmosphere))). The high cloud cover parameter is calculated from cloud for the appropriate model levels as described above. Assumptions are made about the degree of overlap/randomness between clouds in different model levels. Cloud fractions vary from 0 to 1. |sfc_an|INST|redGG-N320 |1|hcc|high_type_cloud_area_fraction||%|100||High Cloud Cover|mon|atmos|gr|sf00
+195|128|195|lgws|Eastward gravity wave surface stress|N m-2 s|Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is the component of the surface stress, in an eastward direction, associated with low-level blocking and orographic gravity waves. It is calculated by the ECMWF Integrated Forecasting System sub-grid orography scheme. It represents surface stress due to unresolved valleys, hills and mountains with horizontal scales between 5 km and [the model grid](https://confluence.ecmwf.int/display/CKB/model%2bgrid%2bbox%2band%2btime%2bstep). (The surface stress associated with orographic features with horizontal scales smaller than 5 km is accounted for by the turbulent orographic form drag scheme). Orographic gravity waves are oscillations in the flow maintained by the buoyancy of displaced air parcels, produced when the air is deflected upwards by hills and mountains. Hills and mountains can also block the flow of air at low levels. Together these processes can create a drag or stress on the atmosphere at the Earth's surface (and at other levels in the atmosphere). This parameter is accumulated over a [particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). |sfc_fc|ACC| redGG-N320 |6|xgwdparam|atmosphere_eastward_stress_due_to_gravity_wave_drag--scaling_factor_inverse_accumulation_time||Pa|1.0/3600||Eastward Gravity Wave Drag|Amon|atmos|gr|sf12
+196|128|196|mgws|Northward gravity wave surface stress|N m-2 s|Air flowing over a surface exerts a stress that transfers momentum to the surface and slows the wind. This parameter is the component of the surface stress, in a northward direction, associated with low-level blocking and orographic gravity waves. It is calculated by the ECMWF Integrated Forecasting System sub-grid orography scheme. It represents surface stress due to unresolved valleys, hills and mountains with horizontal scales between 5 km and [the model grid](https://confluence.ecmwf.int/display/CKB/model%2bgrid%2bbox%2band%2btime%2bstep). (The surface stress associated with orographic features with horizontal scales smaller than 5 km is accounted for by the turbulent orographic form drag scheme). The stress computed in the sub-grid orography scheme is associated with low-level blocking and orographic gravity waves. Orographic gravity waves are oscillations in the flow maintained by the buoyancy of displaced air parcels, produced when the air is deflected upwards by hills and mountains. Hills and mountains can also block the flow of air at low levels. Together these processes can create a drag or stress on the atmosphere at the Earth's surface (and at other levels in the atmosphere). This parameter is accumulated over a [particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). |sfc_fc|ACC| redGG-N320 |6|ygwdparam|atmosphere_northward_stress_due_to_gravity_wave_drag--scaling_factor_inverse_accumulation_time||Pa|1.0/3600||Northward Gravity Wave Drag|Amon|atmos|gr|sf12
+197|128|197|gwd|Gravity wave dissipation|J m-2|This parameter is the amount of energy per unit area that is converted from kinetic energy in the mean flow, into heat, due to the effects of orographic gravity waves. A higher value of this parameter means that more energy is being converted to heat, and so the mean flow is slowing more and the air temperature is rising by a greater amount. Orographic gravity waves are oscillations in the flow maintained by the buoyancy of displaced air parcels, produced when the air is deflected upwards by hills and mountains. Hills and mountains can also block the flow of air at low levels. Together these processes can create a drag or stress on the atmosphere at the Earth's surface (and at other levels in the atmosphere). This parameter is accumulated over a [particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). |sfc_fc|ACC| redGG-N320 |0|gwd|no CF standard_name exist||W m-2|-0.0002777777777777778||Gravity Wave Dissipation|mon|atmos|gr|sf12
+198|128|198|src|Skin reservoir content|m of water equivalent|This parameter is the amount of water in the vegetation canopy and/or in a thin layer on the soil. It represents the amount of rain intercepted by foliage, and water from dew. The maximum amount of 'skin reservoir content' a grid box can hold depends on the type of vegetation, and may be zero. Water leaves the 'skin reservoir' by evaporation. [ See further information.](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#subsection.H.6.1) |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |0|src|lwe_thickness_of_canopy_water_amount||m|1||Skin Reservoir Content|mon|atmos|gr|sf00
+201|128|201|mx2t|Maximum temperature at 2 metres since previous post-processing|K|This parameter is the highest temperature of air at 2m above the surface of land, sea or in-land waters since the parameter was last archived in a particular forecast. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.[ See further information ](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#subsection.3.10.3). This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. |sfc_fc|MAX| redGG-N320 |6|tasmax|air_temperature||K|1||Maximum Near-Surface Air Temperature|Amon|atmos|gr|sf12
+202|128|202|mn2t|Minimum temperature at 2 metres since previous post-processing|K|This parameter is the lowest temperature of air at 2m above the surface of land, sea or in-land waters since the parameter was last archived in a particular forecast. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.[ See further information ](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#subsection.3.10.3). This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. |sfc_fc|MIN| redGG-N320 |6|tasmin|air_temperature||K|1||Minimum Near-Surface Air Temperature|Amon|atmos|gr|sf12
+203|128|203|o3|Ozone mass mixing ratio|kg kg-1|This parameter is the mass of ozone per kilogram of air. In the ECMWF Integrated Forecasting System (IFS), there is a simplified representation of ozone chemistry (including representation of the chemistry which has caused the ozone hole). Ozone is also transported around in the atmosphere through the motion of air.[ See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2016/16648-part- iv-physical-processes.pdf#chapter.10). Naturally occurring ozone in the stratosphere helps protect organisms at the surface of the Earth from the harmful effects of ultraviolet (UV) radiation from the Sun. Ozone near the surface, often produced because of pollution, is harmful to organisms. Most of the IFS chemical species are archived as mass mixing ratios [kg kg-1].[ This link](https://confluence.ecmwf.int/pages/viewpage.action?pageId=153391710) explains how to convert to concentration in terms of mass per unit volume. |ml_an,pl_an|INST| redGG-N320 redGG-N320 |1|o3|mass_fraction_of_ozone_in_air||kg kg-1|1||Ozone Mass Mixing Ratio|mon|atmos|gr|pl00
+205|128|205|ro|Runoff|m|Some water from rainfall, melting snow, or deep in the soil, stays stored in the soil. Otherwise, the water drains away, either over the surface (surface runoff), or under the ground (sub-surface runoff) and the sum of these two is simply called 'runoff'. This parameter is the total amount of water accumulated over a [particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations).The units of runoff are depth in metres. This is the depth the water would have if it were spread evenly over the [grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step). Care should be taken when comparing model parameters with observations, because observations are often local to a particular point rather than averaged over a grid square area. Observations are also often taken in different units, such as mm/day, rather than the accumulated metres produced here. Runoff is a measure of the availability of water in the soil, and can, for example, be used as an indicator of drought or flood. More information about how runoff is calculated is given in the [ IFS Physical Processes documentation](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#subsection.H.6.3). |sfc_fc,sfc_fc_land|ACC| redGG-N320 |6|mrro|runoff_amount||kg m-2 s-1|1.0/3.6|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Total Runoff|Lmon|land|gr|sf12
+206|128|206|tco3|Total column ozone|kg m-2|This parameter is the total amount of ozone in a column of air extending from the surface of the Earth to the top of the atmosphere. This parameter can also be referred to as total ozone, or vertically integrated ozone. The values are dominated by ozone within the stratosphere. In the ECMWF Integrated Forecasting System (IFS), there is a simplified representation of ozone chemistry (including representation of the chemistry which has caused the ozone hole). Ozone is also transported around in the atmosphere through the motion of air.[ See further documentation ](https://www.ecmwf.int/sites/default/files/elibrary/2016/16648-part-iv- physical-processes.pdf#chapter.10). Naturally occurring ozone in the stratosphere helps protect organisms at the surface of the Earth from the harmful effects of ultraviolet (UV) radiation from the Sun. Ozone near the surface, often produced because of pollution, is harmful to organisms. In the IFS, the units for total ozone are kilograms per square metre, but before 12/06/2001 dobson units were used. Dobson units (DU) are still used extensively for total column ozone. 1 DU = 2.1415E-5 kg m-2 |sfc_an|INST|redGG-N320 |1|tco3|atmosphere_mass_content_of_ozone||kg m-2|1||Total Column Ozone|mon|atmos|gr|sf00
+208|128|208|tsrc|Top net solar radiation, clear sky|J m-2|This parameter is the incoming solar radiation (also known as shortwave radiation) minus the outgoing solar radiation at the top of the atmosphere, assuming clear-sky (cloudless) conditions. It is the amount of radiation passing through a horizontal plane. The incoming solar radiation is the amount received from the Sun. The outgoing solar radiation is the amount reflected and scattered by the Earth's atmosphere and surface, assuming clear-sky (cloudless) conditions. [See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf). Clear-sky radiation quantities are computed for exactly the same atmospheric conditions of temperature, humidity, ozone, trace gases and aerosol as the total-sky (clouds included) quantities, but assuming that the clouds are not there. This parameter is [accumulated over a particular time period](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations) which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc|ACC| redGG-N320 |3|rstcs|toa_net_downward_shortwave_flux_assuming_clear_sky||W m-2|1.0/3600||TOA Net Downward Shortwave Flux Assuming Clear Sky|mon|atmos|gr|sf12
+209|128|209|ttrc|Top net thermal radiation, clear sky|J m-2|This parameter is the thermal (also known as terrestrial or longwave) radiation emitted to space at the top of the atmosphere, assuming clear-sky (cloudless) conditions. It is the amount passing through a horizontal plane. Note that the ECMWF convention for vertical fluxes is positive downwards, so a flux from the atmosphere to space will be negative. [See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf). Clear-sky radiation quantities are computed for exactly the same atmospheric conditions of temperature, humidity, ozone, trace gases and aerosol as total- sky quantities (clouds included), but assuming that the clouds are not there. The thermal radiation emitted to space at the top of the atmosphere is commonly known as the Outgoing Longwave Radiation (OLR) (i.e., taking a flux from the atmosphere to space as positive). Note that OLR is typically shown in units of watts per square metre (W m-2). This parameter is [accumulated over a particular time period](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations) which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. |sfc_fc|ACC| redGG-N320 |6|rlutcs|toa_net_upward_longwave_flux_assuming_clear_sky||W m-2|-0.0002777777777777778||TOA Outgoing Clear-Sky Longwave Radiation|Amon|atmos|gr|sf12
+210|128|210|ssrc|Surface net solar radiation, clear sky|J m-2|This parameter is the amount of solar (shortwave) radiation reaching the surface of the Earth (both direct and diffuse) minus the amount reflected by the Earth's surface (which is governed by the albedo), assuming clear-sky (cloudless) conditions. It is the amount of radiation passing through a horizontal plane, not a plane perpendicular to the direction of the Sun. Clear-sky radiation quantities are computed for exactly the same atmospheric conditions of temperature, humidity, ozone, trace gases and aerosol as the corresponding total-sky quantities (clouds included), but assuming that the clouds are not there. Radiation from the Sun (solar, or shortwave, radiation) is partly reflected back to space by clouds and particles in the atmosphere (aerosols) and some of it is absorbed. The rest is incident on the Earth's surface, where some of it is reflected. The difference between downward and reflected solar radiation is the surface net solar radiation. [See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf). This parameter is [accumulated over a particular time period](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations) which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc|ACC| redGG-N320 |3|rsscs|surface_net_downward_shortwave_flux_assuming_clear_sky||W m-2|1.0/3600||Surface Net Downward Shortwave Flux Assuming Clear Sky|mon|atmos|gr|sf12
+211|128|211|strc|Surface net thermal radiation, clear sky|J m-2|Thermal radiation (also known as longwave or terrestrial radiation) refers to radiation emitted by the atmosphere, clouds and the surface of the Earth. This parameter is the difference between downward and upward thermal radiation at the surface of the Earth, assuming clear-sky (cloudless) conditions. It is the amount of radiation passing through a horizontal plane. [See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf). Clear-sky radiation quantities are computed for exactly the same atmospheric conditions of temperature, humidity, ozone, trace gases and aerosol as the corresponding total-sky quantities (clouds included), but assuming that the clouds are not there. The atmosphere and clouds emit thermal radiation in all directions, some of which reaches the surface as downward thermal radiation. The upward thermal radiation at the surface consists of thermal radiation emitted by the surface plus the fraction of downwards thermal radiation reflected upward by the surface. [See further documentation](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf). This parameter is [accumulated over a particular time period](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations) which depends on the data extracted. The units are joules per square metre (J m-2). To convert to watts per square metre (W m-2), the accumulated values should be divided by the accumulation period expressed in seconds. The ECMWF convention for vertical fluxes is positive downwards. |sfc_fc|ACC| redGG-N320 |3|rlscs|surface_net_downward_longwave_flux_assuming_clear_sky||W m-2|1.0/3600||Surface Net Downward Longwave Flux Assuming Clear Sky|mon|atmos|gr|sf12
+212|128|212|tisr|TOA incident solar radiation|J m-2|Accumulated field |sfc_fc|ACC| redGG-N320 |6|rsdt|toa_incoming_shortwave_flux-scale_factor(1/86400)||W m-2|1.0/3600||TOA Incident Shortwave Radiation|Amon|atmos|gr|sf12
+228|128|228|tp|Total precipitation|m|This parameter is the accumulated liquid and frozen water, comprising rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation and convective precipitation. Large-scale precipitation is generated by the cloud scheme in the ECMWF Integrated Forecasting System (IFS). The cloud scheme represents the formation and dissipation of clouds and large-scale precipitation due to changes in atmospheric quantities (such as pressure, temperature and moisture) predicted directly by the IFS at spatial scales of the [grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step) or larger. Convective precipitation is generated by the convection scheme in the IFS, which represents convection at spatial scales smaller than the grid box. [See further information.](https://confluence.ecmwf.int/display/CKB/Convective+and+large- scale+precipitation) This parameter does not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This parameter is the total amount of water [accumulated over a particular time period which depends on the data extracted](https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation- Meanrates/fluxesandaccumulations). The units of this parameter are depth in metres of water equivalent. It is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model parameters with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box. |sfc_fc,sfc_fc_land|ACC| redGG-N320 redGG-N1280|6|pr|lwe_thickness_of_precipitation_amount||kg m-2 s-1|1.0/3.6||Precipitation|Amon|atmos|gr|sf12
+235|128|235|skt|Skin temperature|K|This parameter is the temperature of the surface of the Earth. The skin temperature is the theoretical temperature that is required to satisfy the surface energy balance. It represents the temperature of the uppermost surface layer, which has no heat capacity and so can respond instantaneously to changes in surface fluxes. Skin temperature is calculated differently over land and sea. This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. See further information about the skin temperature [over land](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#section.3.6) and [over sea](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#section.H.10). |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |0|skt|surface_temperature||K|1||Skin Temperature|mon|atmos|gr|sf00
+236|128|236|stl4|Soil temperature level 4|K|This parameter is the temperature of the soil at level 4 (in the middle of layer 4). The ECMWF Integrated Forecasting System (IFS) has a four-layer representation of soil, where the surface is at 0cm: Layer 1: 0 - 7cm Layer 2: 7 - 28cm Layer 3: 28 - 100cm Layer 4: 100 - 289cm Soil temperature is set at the middle of each layer, and heat transfer is calculated at the interfaces between them. It is assumed that there is no heat transfer out of the bottom of the lowest layer. This parameter has units of Kelvin (K). Temperature measured in Kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. [See further information.](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#section.H.5) |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |6|tsl4|soil_temperature-atLevel4||K|1||Temperature of Soil 4|Lmon|land|gr|sf00
+238|128|238|tsn|Temperature of snow layer|K|This parameter gives the temperature of the snow layer from the ground to the snow-air interface. The ECMWF Integrated Forecast System (IFS) model represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the [ grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step). [ See further information on snow in the IFS](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv- physical-processes.pdf#section.H.4). This parameter has units of kelvin (K). Temperature measured in kelvin can be converted to degrees Celsius (°C) by subtracting 273.15. |sfc_an,sfc_an_land|INST|redGG-N320 redGG-N1280 |6|tsn|temperature_in_surface_snow||K|1||Snow Internal Temperature|LImon|landIce|gr|sf00
+239|128|239|csf|Convective snowfall|m of water equivalent|Accumulated field |sfc_fc|ACC| redGG-N320 |6|prsnc|lwe_thickness_of_convective_snowfall_amount||kg m-2 s-1|1.0/3.6|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Convective Snowfall Flux|Amon|atmos|gr|sf12
+240|128|240|lsf|Large-scale snowfall|m of water equivalent|Accumulated field |sfc_fc|ACC| redGG-N320 |6|prlsns|lwe_thickness_of_stratiform_snowfall_amount||kg m-2 s-1|1.0/3.6|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Stratiform Snowfall Flux|Amon|atmos|gr|sf12
+243|128|243|fal|Forecast albedo|(0 - 1)|This parameter is a measure of the reflectivity of the Earth's surface. It is the fraction of solar (shortwave) radiation reflected by Earth's surface, across the solar spectrum, for both direct and diffuse radiation. Typically, snow and ice have high reflectivity with albedo values of 0.8 and above, land has intermediate values between about 0.1 and 0.4 and the ocean has low values of 0.1 or less. Radiation from the Sun (solar, or shortwave, radiation) is partly reflected back to space by clouds and particles in the atmosphere (aerosols) and some of it is absorbed. The rest is incident on the Earth's surface, where some of it is reflected. The portion that is reflected by the Earth's surface depends on the albedo. [See further documentation ](https://www.ecmwf.int/sites/default/files/elibrary/2015/18490-radiation- quantities-ecmwf-model-and-mars.pdf). In the ECMWF Integrated Forecasting System (IFS), a climatological background albedo (observed values averaged over a period of several years) is used, modified by the model over water, ice and snow. Albedo is often shown as a percentage (%). |sfc_an,sfc_fc,sfc_fc_land|INST|redGG-N320 redGG-N320 |0|fal|surface_albedo||%|100||Forecast Albedo|mon|atmos|gr|sf00
+244|128|244|fsr|Forecast surface roughness|m|This parameter is the aerodynamic roughness length in metres. It is a measure of the surface resistance. This parameter is used to determine the air to surface transfer of momentum. For given atmospheric conditions, a higher surface roughness causes a slower near-surface wind speed. Over the ocean, surface roughness depends on the waves. Over the land, surface roughness is derived from the vegetation type and snow cover. |sfc_an,sfc_fc|INST|redGG-N320 redGG-N320 |0|fsr|surface_roughness_length||m|1||Forecast Surface Roughness|mon|atmos|gr|sf00
+245|128|245|flsr|Forecast logarithm of surface roughness for heat|~|This parameter is the natural logarithm of the roughness length for heat. The surface roughness for heat is a measure of the surface resistance to heat transfer. This parameter is used to determine the air to surface transfer of heat. For given atmospheric conditions, a higher surface roughness for heat means that it is more difficult for the air to exchange heat with the surface. A lower surface roughness for heat that it is easier for the air to exchange heat with the surface. Over the ocean, surface roughness for heat depends on the waves. Over sea-ice, it has a constant value of 0.001 m. Over the land, it is derived from the vegetation type and snow cover. [See further information.](https://www.ecmwf.int/en/elibrary/17117-part-iv-physical- processes) |sfc_an,sfc_fc|INST|redGG-N320 redGG-N320 |0|flsr|no CF standard_name exist||-|1||Forecast Logarithm of Surface Roughness for Heat|mon|atmos|gr|sf00
+246|128|246|clwc|Specific cloud liquid water content|kg kg-1|This parameter is the mass of cloud liquid water droplets per kilogram of the total mass of moist air. The 'total mass of moist air' is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow. This parameter represents the average value for a[ grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step). Water within clouds can be liquid or ice, or a combination of the two.[ See further information about the cloud formulation](https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part- iv-physical-processes.pdf#subsection.7.2.2). |ml_an,pl_an|INST| redGG-N320 redGG-N320 |6|clw|mass_fraction_of_convective_cloud_liquid_water_in_air||1|1||Mass Fraction of Cloud Liquid Water|Amon|atmos|gr|pl00
+247|128|247|ciwc|Specific cloud ice water content|kg kg-1|This parameter is the mass of cloud ice particles per kilogram of the total mass of moist air. The 'total mass of moist air' is the sum of the dry air, water vapour, cloud liquid, cloud ice, rain and falling snow. This parameter represents the average value for a[ grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step). Water within clouds can be liquid or ice, or a combination of the two. Note that 'cloud frozen water' is the same as 'cloud ice water'. See further information about the cloud formulation. |ml_an,pl_an|INST| redGG-N320 redGG-N320 |6|cli|mass_fraction_of_cloud_ice_in_air||1|1||Mass Fraction of Cloud Ice|Amon|atmos|gr|pl00
+248|128|248|cc|Fraction of cloud cover|(0 - 1)|This parameter is the proportion of a[ grid box](https://confluence.ecmwf.int/display/CKB/Model+grid+box+and+time+step) covered by cloud (liquid or ice). This parameter is available on multiple levels through the atmosphere. |ml_an,pl_an|INST| redGG-N320 redGG-N320 |6|cl|cloud_area_fraction_in_atmosphere_layer||%|100||Percentage Cloud Cover|Amon|atmos|gr|pl00
+507|228|251|pev|Potential evaporation|m|This parameter is a measure of the extent to which near-surface atmospheric conditions are conducive to the process of evaporation. It is usually considered to be the amount of evaporation, under existing atmospheric conditions, from a surface of pure water which has the temperature of the lowest layer of the atmosphere and gives an indication of the maximum possible evaporation.<br/><br/>Potential evaporation in the current ECMWF Integrated Forecasting System is based on surface energy balance calculations with the vegetation parameters set to 'crops/mixed farming' and assuming 'no stress from soil moisture'. In other words, evaporation is computed for agricultural land as if it is well watered and assuming that the atmosphere is not affected by this artificial surface condition. The latter may not always be realistic. Although potential evaporation is meant to provide an estimate of irrigation requirements, the method can give unrealistic results in arid conditions due to too strong evaporation forced by dry air.<br/><br/>This parameter is accumulated over a <a href='https://confluence.ecmwf.int/display/CKB/ERA5%3A+data+documentation#ERA5:datadocumentation-Meanrates/fluxesandaccumulations'>particular time period which depends on the data extracted</a>.|sfc_fc,sfc_fc_land|ACC| redGG-N320 redGG-N1280|6|evspsblpot|water_potential_evaporation_flux||kg m-2 s-1|1.0/3.6|derived from the hourly accumulated quantity and assuming a constant density of water of 1 kg m-3|Potential Evapotranspiration|Emon|land|gr|sf00
+550|260|38|snowc|Snow cover|%||sfc_fc_land|INST| redGG-N1280|6|snc|surface_snow_area_fraction||%|1||Snow Area Percentage|LImon|landIce land|gr|sf00
+# last line of table|||||||||||||||||||||
diff --git a/Tables/original_tables/ct_ecmwf_original.rc b/Tables/original_tables/ct_ecmwf_original.rc
new file mode 100644
index 0000000000000000000000000000000000000000..75dfcfff1b0f24a53dc93e3362de771d528a1c77
--- /dev/null
+++ b/Tables/original_tables/ct_ecmwf_original.rc
@@ -0,0 +1,141 @@
+# Revision Sep/2022 E.Lucio
+# CMOR follows https|//github.com/PCMDI/cmip5-cmor-tables Release Date 2013-07-17
+#
+# https //apps.ecmwf.int/codes/grib/format/grib2/ctables/
+# description follows codetable 128
+# https //apps.ecmwf.int/codes/grib/param-db?&filter=grib1&table=128
+#
+# ml00-data use ECPAR and GRIB2, varname in lower case
+# pl00 and sf data differs, cdo PARDES gives the original name and varname in upper case letters
+#
+# colnumber key meaning
+# No 0 CCC codenumber follows grid table 128
+# No 1 PARDES varname follows 'cdo pardes ORIGFILE'
+# No 2 ECMWF varname follows 'cdo -t ecmwf pardes ORIGFILE'
+# No 3 ECPAR varname follows ECMWF codetable
+# No 4 ECNAME full name follows ECMWF codetable
+# No 5 ECUNIT unit follows ECMWF codetable
+# No 6 CMIP cmor name exists| 0 no, 1 CF, 3 CF-CMIP, 5 CMIP5, 6 CMIP6
+# No 7 CMPAR varname follows CMOR
+# No 8 CMNAME long name follows CMOR
+# No 9 CMUNIT unit follows CMOR
+# No 10 CMFACT factor for convertion to CMOR
+# No 11 CMOFFSET offset for conversion to CMOR
+# No 12 CMLNAME special long name
+# No 13 CMTABLE name of the CMOR table for monthly averages
+# No 14 GRIDTYPE gridtype| gr gaussian_reduced ga gaussian sp spectral
+# No 15 GRIBVERS version of GRIB (= Version 1) GRIBx (=1,2) GRIB2 (=Version 2)
+# No 16 REALM realm of the variable (atmos, land, ocean, landice, seaice, aerosol)
+# No 17 PTYPE type of processing I instantaneous, A accumulated, E extreme EI min EX max
+# No 18 LTYPE current source of the var
+# No 19 DATASET possible source(s) for the var (sf00, sf12, pl00, ml00)
+# No 20 LEVELS levels extracted| 37 Pa levels (100000 - 100), 137 model levels (137 - 1). Comma sepparated, None for surface.
+# No 21 XCES whether the variable was already in XCES or not
+# No 22 OBS complementary information
+#
+#CCC|PARDES|ECMWF|ECPAR|ECNAME|ECUNIT|CMIP|CMPAR|CMNAME|CMUNIT|CMFACT|CMOFFSET|CMLNAME|CMTABLE|GRIDTYPE|GRIBVERS|REALM|PTYPE|LTYPE|DATASET|LEVELS|XCES|OBS
+27|var27|CVL|cvl|Low vegetation cover|0..1|1|cvl|vegetation_area_fraction|%|100|0.0|Low Vegetation Cover|fx|gr|GRIB|land|I|sf00|sf00|None|1.0||
+28|var28|CVH|cvh|High vegetation cover|0..1|1|cvh|vegetation_area_fraction|%|100|0.0|High Vegetation Cover|fx|gr|GRIB|land|I|sf00|sf00|None|1.0||
+29|var29|TVL|tvl|Type of low vegetation|-|0|tvl|type_of_low_vegetation|-|1.0|0.0|Type of Low Vegetation|fx|gr|GRIB|land|I|sf00|sf00|None|1.0||
+30|var30|TVH|tvh|Type of high vegetation|-|0|tvh|type_of_high_vegetation|-|1.0|0.0|Type of High Vegetation|fx|gr|GRIB|land|I|sf00|sf00|None|1.0||
+31|var31|CI|ci|Sea ice area fraction|0..1|5|sic|sea_ice_area_fraction|%|100|0|Sea Ice Area Fraction|OImon|gr|GRIB|seaIce|I|sf00|sf00|None|1.0||
+32|var32|ASN|asn|Snow albedo|0..1|0|asn|snow_albedo|%|100|0.0|Snow Albedo|mon-era5|gr|GRIB|landIce|I|sf00|sf00|None|1.0||
+33|var33|RSN|rsn|Snow density|kg/m^3|1|rsn|snow_density|kg m-3|1.0|0.0|Snow Density|mon-cf|gr|GRIB|landIce|I|sf00|sf00|None|1.0||
+34|var34|SSTK|sst|Sea surface temperature|K|6|tos|sea_surface_temperature|K|1|0.0|Sea Surface Temperature|Omon|gr|GRIB|ocean|I|sf00|sf00,sf12|None|1.0||
+35|var35|ISTL|istl1|Ice temperature layer 1|K|1|istl1|sea_ice_temperature|K|1.0|0.0|Ice Temperature Layer 1|mon-cf|gr|GRIB|seaIce|I|sf00|sf00|None|0.0||
+36|var36|ISTL2|istl2|Ice temperature layer 2|K|1|istl2|sea_ice_temperature|K|1.0|0.0|Ice Temperature Layer 2|mon-cf|gr|GRIB|seaIce|I|sf00|sf00|None|0.0||
+37|var37|ISTL3|istl3|Ice temperature layer 3|K|1|istl3|sea_ice_temperature|K|1.0|0.0|Ice Temperature Layer 3|mon-cf|gr|GRIB|seaIce|I|sf00|sf00|None|0.0||
+38|var38|ISTL4|istl4|Ice temperature layer 4|K|1|istl4|sea_ice_temperature|K|1.0|0.0|Ice Temperature Layer 4|mon-cf|gr|GRIB|seaIce|I|sf00|sf00|None|0.0||
+39|var39|SWVL1|swvl1|Volumetric soil water layer 1|m^3/m^3|1|swvl1|volume_fraction_of_condensed_water_in_soil|m3 m-3|1.0|0.0|Volumetric Soil Water Layer 1|mon-cf|gr|GRIB|land|I|sf00|sf00|None|1.0||
+40|var40|SWVL2|swvl2|Volumetric soil water layer 2|m^3/m^3|1|swvl2|volume_fraction_of_condensed_water_in_soil|m3 m-3|1.0|0.0|Volumetric Soil Water Layer 2|mon-cf|gr|GRIB|land|I|sf00|sf00|None|1.0||
+41|var41|SWVL3|swvl3|Volumetric soil water layer 3|m^3/m^3|1|swvl3|volume_fraction_of_condensed_water_in_soil|m3 m-3|1.0|0.0|Volumetric Soil Water Layer 3|mon-cf|gr|GRIB|land|I|sf00|sf00|None|1.0||
+42|var42|SWVL4|swvl4|Volumetric soil water layer 4|m^3/m^3|1|swvl4|volume_fraction_of_condensed_water_in_soil|m3 m-3|1.0|0.0|Volumetric Soil Water Layer 4|mon-cf|gr|GRIB|land|I|sf00|sf00|None|1.0||
+44|var44|ES|es|Snow evaporation|m of water equivalent|6|esn|water_evapotranspiration_flux|kg m-2 s-1|1.0/3.6|0|Snow Evaporation|Lmon|gr|GRIB|land|A|sf12|sf12|None|1.0||
+45|var45|SMLT|smlt|Snowmelt|m of water equivalent|6|snm|surface_snow_melt_flux|kg m-2 s-1|1.0/3.6|0|Surface Snow Melt|LImon|gr|GRIB|landIce|A|sf12|sf12|None|1.0||
+49|var49|WG10|10fg|10 metre wind gust since previous post-processing|m/s|6|wsgsmax|wind_speed_of_gust|m s-1|1|0.0|Maximum Wind Speed of Gust at 10m|Amon|gr|GRIB|atmos|EX|sf12|sf12|None|1.0||
+50|var50|LSPF|lspf|Large-scale precipitation fraction|s|0|lspf|large-scale_precipitation_fraction|s|1.0|0.0|Large-scale Precipitation Fraction|mon-era5|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+57|var57|var57|uvb|Downward UV radiation at the surface|J/m^2|0|uvb|downward_uv_radiation_at_the_surface|W m-2|1.0/3600.0|0.0|Downward UV Radiation at the Surface|mon-era5|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+59|var59|var59|cape|Convective available potential energy|J/kg|1|cape|atmosphere_convective_available_potential_energy|J kg-1|1.0|0.0|Convective Available Potential Energy|mon-cf|gr|GRIB|atmos|I|sf12|sf12|None|1.0||
+60|var60|PV|pv|potential vorticity|Km^2/kg/s|1|pv|ertel_potential_vorticity|K m2 kg-1 s-1|1.0|0.0|Potential Vorticity|mon-cf|gr|GRIB|atmos|I|pl00|pl00|100000,85000,70000,50000,30000|0.0||
+75|var75|var75|crcw|Specific rain water content|kg/kg|0|crcw|specific_rain_water_content|kg kg-1|1.0|0.0|Specific Rain Water Content|mon-era5|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|0.0||
+76|var76|var76|cswc|Specific snow water content|kg/kg|0|cswc|specific_snow_water_content|kg kg-1|1.0|0.0|Specific Snow Water Content|mon-era5|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|0.0||
+77|var77|etadot|etadot|Eta-coordinate vertical velocity|1/s|0|etadot|eta-coordinate_vertical_velocity|s-1|1.0|0.0|Eta-coordinate Vertical Velocity|mon-era5|sp|GRIB2|atmos|I|ml00|ml00|137|0.0||
+78|var78|var78|tclw|Total column cloud liquid water|kg/m^2|6|clwvi|atmosphere_mass_content_of_cloud_condensed_water|kg m-2|1|0.0|Condensed Water Path|Amon|gr|GRIB|atmos|I|sf12|sf12|None|1.0||
+79|var79|var79|tciw|Total column cloud ice water|kg/m^2|6|clivi|atmosphere_mass_content_of_cloud_ice|kg m-2|1|0.0|Ice Water Path|Amon|gr|GRIB|atmos|I|sf12|sf12|None|1.0||
+129|var129|Z|z|Geopotential|m^2/s^2|1|z|geopotential|m2 s-2|1.0|0.0|Geopotential|mon-cf|gr|GRIBx|atmos|I|pl00|sf00,sf12,pl00,ml00|100000,85000,70000,50000,30000|1.0|sp (ml00)||
+130|var130|T|t|Temperature|K|6|ta|air_temperature|K|1|0.0|Air Temperature|Amon|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|1.0|sp (ml00)||
+131|var131|U|u|U component of wind|m/s|6|ua|eastward_wind|m s-1|1|0.0|Eastward Wind|Amon|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|1.0|sp (ml00)||
+132|var132|V|v|V component of wind|m/s|6|va|northward_wind|m s-1|1|0.0|Northward Wind|Amon|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|1.0|sp (ml00)||
+133|var133|Q|q|Specific humidity|kg/kg|6|hus|specific_humidity|1|1|0.0|Specific Humidity|Amon|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|0.0||
+134|var134|SP|sp|Surface pressure|Pa|6|ps|surface_air_pressure|Pa|1|0.0|Surface Air Pressure|Amon|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+135|var135|W|w|Vertical velocity|Pa/s|5|wap|lagrangian_tendency_of_air_pressure|Pa s-1|1|0.0|omega (=dp/dt)|Amon|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|0.0|sp (ml00)||
+136|var136|TCW|tcw|Total column water|kg/m^2|1|tcw|atmosphere_mass_content_of_water|kg m-2|1.0|0.0|Water Path|mon-cf|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+137|var137|TCWV|tcwv|Total column water vapour|kg/m^2|5|prw|atmosphere_water_vapor_content|kg m-2|1|0.0|Water Vapor Path|Amon|gr|GRIB|atmos|I|sf00|sf00,sf12|None|1.0||
+138|var138|VO|vo|Relative Vorticity|1/s|1|rv|atmospheric_relative_vorticity|s-1|1.0|0.0|Relative Vorticity|mon-cf|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|0.0|sp (ml00)||
+139|var139|STL1|stl1|Soil temperature level 1|K|6|tsl1|soil_temperature|K|1|0.0|Temperature of Soil 1|Lmon|gr|GRIB|land|I|sf00|sf00|None|1.0||
+141|var141|SD|sd|Snow depth|m|6|snd|surface_snow_thickness|m|1|0.0|Snow Depth|LImon|gr|GRIB|landIce|I|sf00|sf00|None|1.0||
+142|var142|LSP|lsp|Large-scale precipitation|m|6|prlsprof|stratiform_rainfall_flux|kg m-2 s-1|1.0/3.6|0|Stratiform Rainfall Flux|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+143|var143|CP|cp|Convective precipitation|m|6|prcprof|convective_rainfall_flux|kg m-2 s-1|1.0/3.6|0|Convective Rainfall Flux|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+144|var144|SF|sf|Snowfall|m of water equivalent|6|prsn|snowfall_flux|kg m-2 s-1|1.0/3.6|0|Snowfall Flux|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+145|var145|BLD|bld|Boundary layer dissipation|J/m^2|1|bld|kinetic_energy_dissipation_in_atmosphere_boundary_layer|W m-2|-1.0/3600.0|0.0|Boundary Layer Dissipation|mon-cf|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+146|var146|SSHF|sshf|Surface sensible heat flux|J/m^2|6|hfss|surface_upward_sensible_heat_flux|W m-2|-1.0/3600|0.0|Surface Upward Sensible Heat Flux|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+147|var147|SLHF|slhf|Surface latent heat flux|J/m^2|6|hfls|surface_upward_latent_heat_flux|W m-2|-1.0/3600|0.0|Surface Upward Latent Heat Flux|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+151|var151|MSL|msl|Mean sea level pressure|Pa|6|psl|air_pressure_at_mean_sea_level|Pa|1|0.0|Sea Level Pressure|Amon|gr|GRIB|atmos|I|sf00|sf00,sf12|None|1.0||
+152|var152|LNSP|lnsp|Logarithm of surface pressure|-|0|lnsp|logarithm_of_surface_pressure|ln(Pa)|1.0|0.0|Logarithm of Surface Pressure|mon-era5|sp|GRIB2|atmos|I|ml00|ml00|137|0.0||
+155|var155|D|d|Divergence|1/s|1|d|divergence_of_wind|s-1|1.0|0.0|Divergence|mon-cf|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|0.0|sp (ml00)||
+156|var129|Z|z|Geopotential|m^2/s^2|6|zg|geopotential_height|m|1.0/9.80665|0|Geopotential Height|Amon|gr|GRIBx|atmos|I|pl00|sf00,sf12,pl00,ml00|100000,85000,70000,50000,30000|0.0||
+157|var157|R|r|Relative_humidity|%|6|hur|relative_humidity|%|1|0.0|Relative Humidity|Amon|gr|GRIB|atmos|I|pl00|pl00|100000,85000,70000,50000,30000|0.0||
+159|var159|BLH|blh|Boundary layer height|m|6|zmla|atmosphere_boundary_layer_thickness|m|1|0.0|Height of Boundary Layer|Amon|gr|GRIB|atmos|I|sf12|sf12|None|1.0||
+160|var160|SDOR|sdor|Standard deviation of orography|-|0|sdor|standard_deviation_of_orography|-|1.0|0.0|Standard Deviation of Orography|mon-era5|gr|GRIB|atmos|I|sf00|sf00|None|0.0||
+161|var161|ISOR|isor|Anisotropy of sub-gridscale orography|-|0|isor|anisotropy_of_sub-gridscale_orography|-|1.0|0.0|Anisotropy of Sub-gridscale Orography|mon-era5|gr|GRIB|atmos|I|sf00|sf00|None|0.0||
+162|var162|ANOR|anor|Angle of sub-gridscale orography|radians|0|anor|angle_of_sub-gridscale_orography|radians|1.0|0.0|Angle of Sub-gridscale Orography|mon-era5|gr|GRIB|atmos|I|sf00|sf00|None|0.0||
+163|var163|SLOR|slor|Slope of sub-gridscale orography|-|0|slor|slope_of_sub-gridscale_orography|-|1.0|0.0|Slope of Sub-gridscale Orography|mon-era5|gr|GRIB|atmos|I|sf00|sf00|None|0.0||
+164|var164|TCC|tcc|Total cloud cover|0..1|6|clt|cloud_area_fraction|%|100|0|Total Cloud Cover Percentage|Amon|gr|GRIB|atmos|I|sf00|sf00,sf12|None|1.0||
+165|var165|U10M|10u|10 metre U wind component|m/s|6|uas|eastward_wind|m s-1|1|0.0|Eastward Near-Surface Wind|Amon|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+166|var166|V10M|10v|10 metre V wind component|m/s|6|vas|northward_wind|m s-1|1|0.0|Northward Near-Surface Wind|Amon|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+167|var167|T2M|2t|2 metre temperature|K|6|tas|air_temperature|K|1|0.0|Near-Surface Air Temperature|Amon|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+168|var168|D2M|2d|2 metre dewpoint temperature|K|6|tdps|dew_point_temperature|K|1|0.0|2m Dewpoint Temperature|Amon|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+169|var169|SSRD|ssrd|Surface solar radiation downwards|J/m^2|1|rsds|surface_downwelling_shortwave_flux_in_air|W m-2|1.0/3600.0|0.0|Surface Solar Radiation Downwards|mon-cf|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+170|var170|STL2|stl2|Soil temperature level 2|K|6|tsl2|soil_temperature|K|1|0.0|Temperature of Soil 2|Lmon|gr|GRIB|land|I|sf00|sf00|None|1.0||
+172|var172|LSM|lsm|Land-sea mask|0..1|6|sftlf|land_area_fraction|%|100|0|Percentage of the Grid Cell Occupied by Land (Including Lakes)|fx|gr|GRIB|atmos|I|sf00|sf00|None|0.0||
+175|var175|STRD|strd|Surface thermal radiation downwards|J/m^2|6|rlds|surface_downwelling_longwave_flux_in_air|W m-2|1.0/3600|0.0|Surface Downwelling Longwave Radiation|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+176|var176|SSR|ssr|Surface net solar radiation|J/m^2|1|rss|surface_net_downward_shortwave_flux|W m-2|1.0/3600.0|0.0|Surface Net Solar Radiation|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+177|var177|STR|str|Surface net thermal radiation|J/m^2|6|rls|surface_net_downward_longwave_flux|W m-2|1.0/3600|0.0|Net Longwave Surface Radiation|Emon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+178|var178|TSR|tsr|Top net solar radiation|J/m^2|1|rst|toa_net_downward_shortwave_flux|W m-2|1.0/3600.0|0.0|TOA Net Downward Shortwave Flux|mon-cf|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+179|var179|TTR|ttr|Top net thermal radiation|J/m^2|6|rlut|toa_outgoing_longwave_flux|W m-2|-1.0/3600|0.0|TOA Outgoing Longwave Radiation|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+180|var180|EWSS|ewss|Eastward turbulent surface stress|N/m^2s|6|tauu|surface_downward_eastward_stress|Pa|1.0/3600|0.0|Surface Downward Eastward Wind Stress|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+181|var181|NSSS|nsss|Northward turbulent surface stress|N/m^2s|6|tauv|surface_downward_northward_stress|Pa|1.0/3600|0.0|Surface Downward Northward Wind Stress|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+182|var182|E|e|Evaporation|m of water equivalent|6|evspsbl|water_evaporation_flux|kg m-2 s-1|1.0/3.6|0|Evaporation Including Sublimation and Transpiration|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+183|var183|STL3|stl3|Soil temperature level 3|K|6|tsl3|soil_temperature|K|1|0.0|Temperature of Soil 3|Lmon|gr|GRIB|land|I|sf00|sf00|None|1.0||
+186|var186|LCC|lcc|Low cloud cover|0..1|1|lcc|low_type_cloud_area_fraction|%|100|0.0|Low Cloud Cover|mon-cf|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+187|var187|MCC|mcc|Medium cloud cover|0..1|1|mcc|medium_type_cloud_area_fraction|%|100|0.0|Medium Cloud Cover|mon-cf|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+188|var188|HCC|hcc|High cloud cover|0..1|1|hcc|high_type_cloud_area_fraction|%|100|0.0|High Cloud Cover|mon-cf|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+195|var195|LGWS|lgws|Eastward gravity wave surface stress|N/m^2s|6|xgwdparam|atmosphere_eastward_stress_due_to_gravity_wave_drag|Pa|1.0/3600|0.0|Eastward Gravity Wave Drag|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+196|var196|MGWS|mgws|Northward gravity wave surface stress|N/m^2s|6|ygwdparam|atmosphere_northward_stress_due_to_gravity_wave_drag|Pa|1.0/3600|0.0|Northward Gravity Wave Drag|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+197|var197|GWD|gwd|Gravity wave dissipation|J/m^2|0|gwd|gravity_wave_dissipation|W m-2|-1.0/3600.0|0.0|Gravity Wave Dissipation|mon-era5|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+198|var198|SRC|src|Skin reservoir content|m of water equivalent|0|src|skin_reservoir_content|m|1.0|0.0|Skin Reservoir Content|mon-era5|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+201|var201|MX2T|mx2t|Maximum temperature at 2 metres since previous post-processing|K|6|tasmax|air_temperature|K|1|0.0|Maximum Near-Surface Air Temperature|Amon|gr|GRIB|atmos|EX|sf12|sf12|None|1.0||
+202|var202|MN2T|mn2t|Minimum temperature at 2 metres since previous post-processing|K|6|tasmin|air_temperature|K|1|0.0|Minimum Near-Surface Air Temperature|Amon|gr|GRIB|atmos|EI|sf12|sf12|None|1.0||
+203|var203|O3|o3|Ozone mass mixing ratio|kg/kg|1|o3|mass_fraction_of_ozone_in_air|kg kg-1|1.0|0.0|Ozone Mass Mixing Ratio|mon-cf|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|0.0||
+205|var205|RO|ro|Runoff|m|6|mrro|runoff_flux|kg m-2 s-1|1.0/3.6|0|Total Runoff|Lmon|gr|GRIB|land|A|sf12|sf12|None|1.0||
+206|var206|TCO3|tco3|Total column ozone|kg/m^2|1|tco3|atmosphere_mass_content_of_ozone|kg m-2|1.0|0.0|Total Column Ozone|mon-cf|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+208|var208|TSRC|tsrc|Top net solar radiation, clear sky|J/m^2|3|rstcs|toa_net_downward_shortwave_flux_assuming_clear_sky|W m-2|1.0/3600|0.0|TOA Net Downward Shortwave Flux Assuming Clear Sky|mon-cf|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+209|var209|TTRC|ttrc|Top net thermal radiation, clear sky|J/m^2|6|rlutcs|toa_outgoing_longwave_flux_assuming_clear_sky|W m-2|-1.0/3600|0.0|TOA Outgoing Clear-Sky Longwave Radiation|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+210|var210|SSRC|ssrc|Surface net solar radiation, clear sky|J/m^2|3|rsscs|surface_net_downward_shortwave_flux_assuming_clear_sky|W m-2|1.0/3600|0.0|Surface Net Downward Shortwave Flux Assuming Clear Sky|mon-cf|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+211|var211|STRC|strc|Surface net thermal radiation, clear sky|J/m^2|3|rlscs|surface_net_downward_longwave_flux_assuming_clear_sky|W m-2|1.0/3600|0.0|Surface Net Downward Longwave Flux Assuming Clear Sky|mon-cf|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+212|var212|SI|tisr|TOA incident solar radiation|J/m^2|6|rsdt|toa_incoming_shortwave_flux|W m-2|1.0/3600|0.0|TOA Incident Shortwave Radiation|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+228|var228|TP|tp|Total precipitation|m|6|pr|precipitation_flux|kg m-2 s-1|1.0/3.6|0|Precipitation|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+235|var235|SKT|skt|Skin temperature|K|0|skt|skin_temperature|K|1.0|0.0|Skin Temperature|mon-era5|gr|GRIB|atmos|I|sf00|sf00|None|1.0||
+236|var236|STL4|stl4|Soil temperature level 4|K|6|tsl4|soil_temperature|K|1|0.0|Temperature of Soil 4|Lmon|gr|GRIB|land|I|sf00|sf00|None|1.0||
+238|var238|TSN|tsn|Temperature of snow layer|K|6|tsn|temperature_in_surface_snow|K|1|0.0|Snow Internal Temperature|LImon|gr|GRIB|landIce|I|sf00|sf00|None|1.0||
+239|var239|CSF|csf|Convective snowfall|m of water equivalent|6|prsnc|convective_snowfall_flux|kg m-2 s-1|1.0/3.6|0|Convective Snowfall Flux|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+240|var240|LSF|lsf|Large-scale snowfall|m of water equivalent|6|prlsns|stratiform_snowfall_flux|kg m-2 s-1|1.0/3.6|0|Stratiform Snowfall Flux|Amon|gr|GRIB|atmos|A|sf12|sf12|None|1.0||
+243|var243|FAL|fal|Forecast albedo|0..1|0|fal|forecast_albedo|%|100|0.0|Forecast Albedo|mon-era5|gr|GRIB|atmos|I|sf00|sf00,sf12|None|1.0||
+244|var244|FSR|fsr|Forecast surface roughness|m|0|fsr|forecast_surface_roughness|m|1.0|0.0|Forecast Surface Roughness|mon-era5|gr|GRIB|atmos|I|sf00|sf00,sf12|None|1.0||
+245|var245|FLSR|flsr|Forecast logarithm of surface roughness for heat|-|0|flsr|forecast_logarithm_of_surface_roughness_for_heat|-|1.0|0.0|Forecast Logarithm of Surface Roughness for Heat|mon-era5|gr|GRIB|atmos|I|sf00|sf00,sf12|None|1.0||
+246|var246|CLWC|clwc|Specific cloud liquid water content|kg/kg|6|clw|mass_fraction_of_cloud_liquid_water_in_air|1|1|0.0|Mass Fraction of Cloud Liquid Water|Amon|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|0.0||
+247|var247|CIWC|ciwc|Specific cloud ice water content|kg/kg|6|cli|mass_fraction_of_cloud_ice_in_air|1|1|0.0|Mass Fraction of Cloud Ice|Amon|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|0.0||
+248|var248|CC|cc|Fraction of cloud cover|0..1|6|cl|cloud_area_fraction_in_atmosphere_layer|%|100|0|Percentage Cloud Cover|Amon|gr|GRIBx|atmos|I|pl00|ml00,pl00|100000,85000,70000,50000,30000|0.0||
+507|var251|PEV|pev|Potential evaporation|m|0|evspsblpot|water_potential_evaporation_flux|kg m-2 s-1|1.0/3.6|0|Water Potential Evaporation Flux|Amon|gr|GRIB|atmos|A|sf12|sf12|None|0.0||
+999|var129|Z|z|Geopotential|m^2/s^2|6|orog|surface_altitude|m|1.0/9.80665|0|Surface Altitude|fx|gr|GRIBx|land|I|sf00|sf00,sf12,pl00,ml00|None|0.0||
+# last line of table
diff --git a/tables/CSV/ct_ecmwf.rc b/tables/CSV/ct_ecmwf.rc
new file mode 100644
index 0000000000000000000000000000000000000000..8459a853456424c971b8715681af4b0eff1004be
--- /dev/null
+++ b/tables/CSV/ct_ecmwf.rc
@@ -0,0 +1,139 @@
+# Revision Sep/2022 E.Lucio
+# CMOR follows https://github.com/PCMDI/cmip5-cmor-tables Release Date 2013-07-17
+#
+# https //apps.ecmwf.int/codes/grib/format/grib2/ctables/
+# description follows codetable 128
+# https //apps.ecmwf.int/codes/grib/param-db?&filter=grib1&table=128
+#
+# ml00-data use ECPAR and GRIB2, varname in lower case
+# pl00 and sf data differs, cdo PARDES gives the original name and varname in upper case letters
+#
+# colnumber key meaning
+# No 0 CCC codenumber follows grid table 128
+# No 1 PARDES varname follows 'cdo pardes ORIGFILE'
+# No 2 ECMWF varname follows 'cdo -t ecmwf pardes ORIGFILE'
+# No 3 ECPAR varname follows ECMWF codetable
+# No 4 ECNAME full name follows ECMWF codetable
+# No 5 ECUNIT unit follows ECMWF codetable
+# No 6 CMIP cmor name exists: 0 no, 1 CF, 3 CF-CMIP, 5 CMIP5, 6 CMIP6
+# No 7 CMPAR varname follows CMOR
+# No 8 CMNAME long name follows CMOR
+# No 9 CMUNIT unit follows CMOR
+# No 10 CMFACT factor for convertion to CMOR
+# No 11 CMOFFSET offset for conversion to CMOR
+# No 12 CMLNAME special long name
+# No 13 CMTABLE name of the CMOR table for monthly averages
+# No 14 GRIDTYPE gridtype: gr gaussian_reduced ga gaussian sp spectral
+# No 15 GRIBVERS version of GRIB (= Version 1) GRIBx (=1,2) GRIB2 (=Version 2)
+# No 16 REALM realm of the variable (atmos, land, ocean, landice, seaice, aerosol)
+# No 17 PTYPE type of processing I instantaneous, A accumulated, E extreme EI min EX max
+# No 18 LTYPE current source of the var
+# No 19 DATASET possible source(s) for the var (sf00, sf12, pl00, ml00)
+# No 20 LEVELS levels extracted: 37 Pa levels (100000 - 100), 137 model levels (137 - 1). Comma sepparated, None for surface.
+# No 21 XCES whether the variable was already in XCES or not
+# No 22 OBS complementary information
+#
+#CCC:PARDES:ECMWF:ECPAR:ECNAME:ECUNIT:CMIP:CMPAR:CMNAME:CMUNIT:CMFACT:CMOFFSET:CMLNAME:CMTABLE:GRIDTYPE:GRIBVERS:REALM:PTYPE:LTYPE:DATASET:LEVELS:XCES:OBS
+27:var27:CVL:cvl:Low vegetation cover:0..1:1:cvl:vegetation_area_fraction:%:100:0.0:Low Vegetation Cover:mon-cf:gr:GRIB:land:I:sf00:sf00:None:1.0::
+28:var28:CVH:cvh:High vegetation cover:0..1:1:cvh:vegetation_area_fraction:%:100:0.0:High Vegetation Cover:mon-cf:gr:GRIB:land:I:sf00:sf00:None:1.0::
+29:var29:TVL:tvl:Type of low vegetation:-:0:tvl:type_of_low_vegetation:-:1.0:0.0:Type of Low Vegetation:mon-era5:gr:GRIB:land:I:sf00:sf00:None:1.0::
+30:var30:TVH:tvh:Type of high vegetation:-:0:tvh:type_of_high_vegetation:-:1.0:0.0:Type of High Vegetation:mon-era5:gr:GRIB:land:I:sf00:sf00:None:1.0::
+31:var31:CI:ci:Sea ice area fraction:0..1:5:sic:sea_ice_area_fraction:%:100:0:Sea Ice Area Fraction:OImon:gr:GRIB:seaIce:I:sf00:sf00:None:1.0::
+32:var32:ASN:asn:Snow albedo:0..1:0:asn:snow_albedo:%:100:0.0:Snow Albedo:mon-era5:gr:GRIB:landIce:I:sf00:sf00:None:1.0::
+33:var33:RSN:rsn:Snow density:kg/m^3:1:rsn:snow_density:kg m-3:1.0:0.0:Snow Density:mon-cf:gr:GRIB:landIce:I:sf00:sf00:None:1.0::
+34:var34:SSTK:sst:Sea surface temperature:K:6:tos:sea_surface_temperature:K:1:0.0:Sea Surface Temperature:Omon:gr:GRIB:ocean:I:sf00:sf00,sf12:None:1.0::
+35:var35:ISTL:istl1:Ice temperature layer 1:K:1:istl1:sea_ice_temperature:K:1.0:0.0:Ice Temperature Layer 1:mon-cf:gr:GRIB:seaIce:I:sf00:sf00:None:0.0::
+36:var36:ISTL2:istl2:Ice temperature layer 2:K:1:istl2:sea_ice_temperature:K:1.0:0.0:Ice Temperature Layer 2:mon-cf:gr:GRIB:seaIce:I:sf00:sf00:None:0.0::
+37:var37:ISTL3:istl3:Ice temperature layer 3:K:1:istl3:sea_ice_temperature:K:1.0:0.0:Ice Temperature Layer 3:mon-cf:gr:GRIB:seaIce:I:sf00:sf00:None:0.0::
+38:var38:ISTL4:istl4:Ice temperature layer 4:K:1:istl4:sea_ice_temperature:K:1.0:0.0:Ice Temperature Layer 4:mon-cf:gr:GRIB:seaIce:I:sf00:sf00:None:0.0::
+39:var39:SWVL1:swvl1:Volumetric soil water layer 1:m^3/m^3:1:swvl1:volume_fraction_of_condensed_water_in_soil:m3 m-3:1.0:0.0:Volumetric Soil Water Layer 1:mon-cf:gr:GRIB:land:I:sf00:sf00:None:1.0::
+40:var40:SWVL2:swvl2:Volumetric soil water layer 2:m^3/m^3:1:swvl2:volume_fraction_of_condensed_water_in_soil:m3 m-3:1.0:0.0:Volumetric Soil Water Layer 2:mon-cf:gr:GRIB:land:I:sf00:sf00:None:1.0::
+41:var41:SWVL3:swvl3:Volumetric soil water layer 3:m^3/m^3:1:swvl3:volume_fraction_of_condensed_water_in_soil:m3 m-3:1.0:0.0:Volumetric Soil Water Layer 3:mon-cf:gr:GRIB:land:I:sf00:sf00:None:1.0::
+42:var42:SWVL4:swvl4:Volumetric soil water layer 4:m^3/m^3:1:swvl4:volume_fraction_of_condensed_water_in_soil:m3 m-3:1.0:0.0:Volumetric Soil Water Layer 4:mon-cf:gr:GRIB:land:I:sf00:sf00:None:1.0::
+44:var44:ES:es:Snow evaporation:m of water equivalent:6:esn:water_evapotranspiration_flux:kg m-2 s-1:1.0/3.6:0:Snow Evaporation:Lmon:gr:GRIB:land:A:sf12:sf12:None:1.0::
+45:var45:SMLT:smlt:Snowmelt:m of water equivalent:6:snm:surface_snow_melt_flux:kg m-2 s-1:1.0/3.6:0:Surface Snow Melt:LImon:gr:GRIB:landIce:A:sf12:sf12:None:1.0::
+49:var49:WG10:10fg:10 metre wind gust since previous post-processing:m/s:6:wsgsmax:wind_speed_of_gust:m s-1:1:0.0:Maximum Wind Speed of Gust at 10m:Amon:gr:GRIB:atmos:EX:sf12:sf12:None:1.0::
+50:var50:LSPF:lspf:Large-scale precipitation fraction:s:0:lspf:large-scale_precipitation_fraction:s:1.0:0.0:Large-scale Precipitation Fraction:mon-era5:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+57:var57:var57:uvb:Downward UV radiation at the surface:J/m^2:0:uvb:downward_uv_radiation_at_the_surface:W m-2:1.0/3600.0:0.0:Downward UV Radiation at the Surface:mon-era5:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+59:var59:var59:cape:Convective available potential energy:J/kg:1:cape:atmosphere_convective_available_potential_energy:J kg-1:1.0:0.0:Convective Available Potential Energy:mon-cf:gr:GRIB:atmos:I:sf12:sf12:None:1.0::
+60:var60:PV:pv:potential vorticity:Km^2/kg/s:1:pv:ertel_potential_vorticity:K m2 kg-1 s-1:1.0:0.0:Potential Vorticity:mon-cf:gr:GRIB:atmos:I:pl00:pl00:85000,50000,25000:0.0::
+75:var75:var75:crcw:Specific rain water content:kg/kg:0:crcw:specific_rain_water_content:kg kg-1:1.0:0.0:Specific Rain Water Content:mon-era5:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:0.0::
+76:var76:var76:cswc:Specific snow water content:kg/kg:0:cswc:specific_snow_water_content:kg kg-1:1.0:0.0:Specific Snow Water Content:mon-era5:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:0.0::
+77:var77:etadot:etadot:Eta-coordinate vertical velocity:1/s:0:etadot:eta-coordinate_vertical_velocity:s-1:1.0:0.0:Eta-coordinate Vertical Velocity:mon-era5:sp:GRIB2:atmos:I:ml00:ml00:137:0.0::
+78:var78:var78:tclw:Total column cloud liquid water:kg/m^2:6:clwvi:atmosphere_mass_content_of_cloud_condensed_water:kg m-2:1:0.0:Condensed Water Path:Amon:gr:GRIB:atmos:I:sf12:sf12:None:1.0::
+79:var79:var79:tciw:Total column cloud ice water:kg/m^2:6:clivi:atmosphere_mass_content_of_cloud_ice:kg m-2:1:0.0:Ice Water Path:Amon:gr:GRIB:atmos:I:sf12:sf12:None:1.0::
+129:var129:Z:z:Geopotential:m^2/s^2:1:z:geopotential:m2 s-2:1.0:0.0:Geopotential:mon-cf:gr:GRIBx:atmos:I:pl00:sf00,sf12,pl00,ml00:85000,50000,25000:1.0:sp (ml00)::
+130:var130:T:t:Temperature:K:6:ta:air_temperature:K:1:0.0:Air Temperature:Amon:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:1.0:sp (ml00)::
+131:var131:U:u:U component of wind:m/s:6:ua:eastward_wind:m s-1:1:0.0:Eastward Wind:Amon:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:1.0:sp (ml00)::
+132:var132:V:v:V component of wind:m/s:6:va:northward_wind:m s-1:1:0.0:Northward Wind:Amon:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:1.0:sp (ml00)::
+133:var133:Q:q:Specific humidity:kg/kg:6:hus:specific_humidity:1:1:0.0:Specific Humidity:Amon:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:0.0::
+134:var134:SP:sp:Surface pressure:Pa:6:ps:surface_air_pressure:Pa:1:0.0:Surface Air Pressure:Amon:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+135:var135:W:w:Vertical velocity:Pa/s:5:wap:lagrangian_tendency_of_air_pressure:Pa s-1:1:0.0:omega (=dp/dt):Amon:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:0.0:sp (ml00)::
+136:var136:TCW:tcw:Total column water:kg/m^2:1:tcw:atmosphere_mass_content_of_water:kg m-2:1.0:0.0:Water Path:mon-cf:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+137:var137:TCWV:tcwv:Total column water vapour:kg/m^2:5:prw:atmosphere_water_vapor_content:kg m-2:1:0.0:Water Vapor Path:Amon:gr:GRIB:atmos:I:sf00:sf00,sf12:None:1.0::
+138:var138:VO:vo:Relative Vorticity:1/s:1:rv:atmospheric_relative_vorticity:s-1:1.0:0.0:Relative Vorticity:mon-cf:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:0.0:sp (ml00)::
+139:var139:STL1:stl1:Soil temperature level 1:K:6:tsl1:soil_temperature:K:1:0.0:Temperature of Soil 1:Lmon:gr:GRIB:land:I:sf00:sf00:None:1.0::
+141:var141:SD:sd:Snow depth:m:6:snd:surface_snow_thickness:m:1:0.0:Snow Depth:LImon:gr:GRIB:landIce:I:sf00:sf00:None:1.0::
+142:var142:LSP:lsp:Large-scale precipitation:m:6:prlsprof:stratiform_rainfall_flux:kg m-2 s-1:1.0/3.6:0:Stratiform Rainfall Flux:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+143:var143:CP:cp:Convective precipitation:m:6:prcprof:convective_rainfall_flux:kg m-2 s-1:1.0/3.6:0:Convective Rainfall Flux:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+144:var144:SF:sf:Snowfall:m of water equivalent:6:prsn:snowfall_flux:kg m-2 s-1:1.0/3.6:0:Snowfall Flux:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+145:var145:BLD:bld:Boundary layer dissipation:J/m^2:1:bld:kinetic_energy_dissipation_in_atmosphere_boundary_layer:W m-2:-1.0/3600.0:0.0:Boundary Layer Dissipation:mon-cf:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+146:var146:SSHF:sshf:Surface sensible heat flux:J/m^2:6:hfss:surface_upward_sensible_heat_flux:W m-2:-1.0/3600:0.0:Surface Upward Sensible Heat Flux:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+147:var147:SLHF:slhf:Surface latent heat flux:J/m^2:6:hfls:surface_upward_latent_heat_flux:W m-2:-1.0/3600:0.0:Surface Upward Latent Heat Flux:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+151:var151:MSL:msl:Mean sea level pressure:Pa:6:psl:air_pressure_at_mean_sea_level:Pa:1:0.0:Sea Level Pressure:Amon:gr:GRIB:atmos:I:sf00:sf00,sf12:None:1.0::
+152:var152:LNSP:lnsp:Logarithm of surface pressure:-:0:lnsp:logarithm_of_surface_pressure:ln(Pa):1.0:0.0:Logarithm of Surface Pressure:mon-era5:sp:GRIB2:atmos:I:ml00:ml00:137:0.0::
+155:var155:D:d:Divergence:1/s:1:d:divergence_of_wind:s-1:1.0:0.0:Divergence:mon-cf:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:0.0:sp (ml00)::
+156:var129:Z:z:Geopotential:m^2/s^2:6:zg:geopotential_height:m:1.0/9.80665:0:Geopotential Height:Amon:gr:GRIBx:atmos:I:pl00:sf00,sf12,pl00,ml00:85000,50000,25000:0.0::
+157:var157:R:r:Relative_humidity:%:6:hur:relative_humidity:%:1:0.0:Relative Humidity:Amon:gr:GRIB:atmos:I:pl00:pl00:85000,50000,25000:0.0::
+159:var159:BLH:blh:Boundary layer height:m:6:zmla:atmosphere_boundary_layer_thickness:m:1:0.0:Height of Boundary Layer:Amon:gr:GRIB:atmos:I:sf12:sf12:None:1.0::
+160:var160:SDOR:sdor:Standard deviation of orography:-:0:sdor:standard_deviation_of_orography:-:1.0:0.0:Standard Deviation of Orography:mon-era5:gr:GRIB:atmos:I:sf00:sf00:None:0.0::
+161:var161:ISOR:isor:Anisotropy of sub-gridscale orography:-:0:isor:anisotropy_of_sub-gridscale_orography:-:1.0:0.0:Anisotropy of Sub-gridscale Orography:mon-era5:gr:GRIB:atmos:I:sf00:sf00:None:0.0::
+162:var162:ANOR:anor:Angle of sub-gridscale orography:radians:0:anor:angle_of_sub-gridscale_orography:radians:1.0:0.0:Angle of Sub-gridscale Orography:mon-era5:gr:GRIB:atmos:I:sf00:sf00:None:0.0::
+163:var163:SLOR:slor:Slope of sub-gridscale orography:-:0:slor:slope_of_sub-gridscale_orography:-:1.0:0.0:Slope of Sub-gridscale Orography:mon-era5:gr:GRIB:atmos:I:sf00:sf00:None:0.0::
+164:var164:TCC:tcc:Total cloud cover:0..1:6:clt:cloud_area_fraction:%:100:0:Total Cloud Cover Percentage:Amon:gr:GRIB:atmos:I:sf00:sf00,sf12:None:1.0::
+165:var165:U10M:10u:10 metre U wind component:m/s:6:uas:eastward_wind:m s-1:1:0.0:Eastward Near-Surface Wind:Amon:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+166:var166:V10M:10v:10 metre V wind component:m/s:6:vas:northward_wind:m s-1:1:0.0:Northward Near-Surface Wind:Amon:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+167:var167:T2M:2t:2 metre temperature:K:6:tas:air_temperature:K:1:0.0:Near-Surface Air Temperature:Amon:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+168:var168:D2M:2d:2 metre dewpoint temperature:K:6:tdps:dew_point_temperature:K:1:0.0:2m Dewpoint Temperature:Amon:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+169:var169:SSRD:ssrd:Surface solar radiation downwards:J/m^2:1:rsds:surface_downwelling_shortwave_flux_in_air:W m-2:1.0/3600.0:0.0:Surface Solar Radiation Downwards:mon-cf:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+170:var170:STL2:stl2:Soil temperature level 2:K:6:tsl2:soil_temperature:K:1:0.0:Temperature of Soil 2:Lmon:gr:GRIB:land:I:sf00:sf00:None:1.0::
+172:var172:LSM:lsm:Land-sea mask:0..1:6:sftlf:land_area_fraction:%:100:0:Percentage of the Grid Cell Occupied by Land (Including Lakes):fx:gr:GRIB:atmos:I:sf00:sf00:None:0.0::
+175:var175:STRD:strd:Surface thermal radiation downwards:J/m^2:6:rlds:surface_downwelling_longwave_flux_in_air:W m-2:1.0/3600:0.0:Surface Downwelling Longwave Radiation:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+176:var176:SSR:ssr:Surface net solar radiation:J/m^2:1:rss:surface_net_downward_shortwave_flux:W m-2:1.0/3600.0:0.0:Surface Net Solar Radiation:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+177:var177:STR:str:Surface net thermal radiation:J/m^2:6:rls:surface_net_downward_longwave_flux:W m-2:1.0/3600:0.0:Net Longwave Surface Radiation:Emon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+178:var178:TSR:tsr:Top net solar radiation:J/m^2:1:rst:toa_net_downward_shortwave_flux:W m-2:1.0/3600.0:0.0:TOA Net Downward Shortwave Flux:mon-cf:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+179:var179:TTR:ttr:Top net thermal radiation:J/m^2:6:rlut:toa_outgoing_longwave_flux:W m-2:-1.0/3600:0.0:TOA Outgoing Longwave Radiation:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+180:var180:EWSS:ewss:Eastward turbulent surface stress:N/m^2s:6:tauu:surface_downward_eastward_stress:Pa:1.0/3600:0.0:Surface Downward Eastward Wind Stress:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+181:var181:NSSS:nsss:Northward turbulent surface stress:N/m^2s:6:tauv:surface_downward_northward_stress:Pa:1.0/3600:0.0:Surface Downward Northward Wind Stress:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+182:var182:E:e:Evaporation:m of water equivalent:6:evspsbl:water_evaporation_flux:kg m-2 s-1:1.0/3.6:0:Evaporation Including Sublimation and Transpiration:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+183:var183:STL3:stl3:Soil temperature level 3:K:6:tsl3:soil_temperature:K:1:0.0:Temperature of Soil 3:Lmon:gr:GRIB:land:I:sf00:sf00:None:1.0::
+186:var186:LCC:lcc:Low cloud cover:0..1:1:lcc:low_type_cloud_area_fraction:%:100:0.0:Low Cloud Cover:mon-cf:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+187:var187:MCC:mcc:Medium cloud cover:0..1:1:mcc:medium_type_cloud_area_fraction:%:100:0.0:Medium Cloud Cover:mon-cf:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+188:var188:HCC:hcc:High cloud cover:0..1:1:hcc:high_type_cloud_area_fraction:%:100:0.0:High Cloud Cover:mon-cf:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+195:var195:LGWS:lgws:Eastward gravity wave surface stress:N/m^2s:6:xgwdparam:atmosphere_eastward_stress_due_to_gravity_wave_drag:Pa:1.0/3600:0.0:Eastward Gravity Wave Drag:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+196:var196:MGWS:mgws:Northward gravity wave surface stress:N/m^2s:6:ygwdparam:atmosphere_northward_stress_due_to_gravity_wave_drag:Pa:1.0/3600:0.0:Northward Gravity Wave Drag:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+197:var197:GWD:gwd:Gravity wave dissipation:J/m^2:0:gwd:gravity_wave_dissipation:W m-2:-1.0/3600.0:0.0:Gravity Wave Dissipation:mon-era5:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+198:var198:SRC:src:Skin reservoir content:m of water equivalent:0:src:skin_reservoir_content:m:1.0:0.0:Skin Reservoir Content:mon-era5:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+201:var201:MX2T:mx2t:Maximum temperature at 2 metres since previous post-processing:K:6:tasmax:air_temperature:K:1:0.0:Maximum Near-Surface Air Temperature:Amon:gr:GRIB:atmos:EX:sf12:sf12:None:1.0::
+202:var202:MN2T:mn2t:Minimum temperature at 2 metres since previous post-processing:K:6:tasmin:air_temperature:K:1:0.0:Minimum Near-Surface Air Temperature:Amon:gr:GRIB:atmos:EI:sf12:sf12:None:1.0::
+203:var203:O3:o3:Ozone mass mixing ratio:kg/kg:1:o3:mass_fraction_of_ozone_in_air:kg kg-1:1.0:0.0:Ozone Mass Mixing Ratio:mon-cf:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:0.0::
+205:var205:RO:ro:Runoff:m:6:mrro:runoff_flux:kg m-2 s-1:1.0/3.6:0:Total Runoff:Lmon:gr:GRIB:land:A:sf12:sf12:None:1.0::
+206:var206:TCO3:tco3:Total column ozone:kg/m^2:1:tco3:atmosphere_mass_content_of_ozone:kg m-2:1.0:0.0:Total Column Ozone:mon-cf:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+208:var208:TSRC:tsrc:Top net solar radiation, clear sky:J/m^2:3:rstcs:toa_net_downward_shortwave_flux_assuming_clear_sky:W m-2:1.0/3600:0.0:TOA Net Downward Shortwave Flux Assuming Clear Sky:mon-cf:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+209:var209:TTRC:ttrc:Top net thermal radiation, clear sky:J/m^2:6:rlutcs:toa_outgoing_longwave_flux_assuming_clear_sky:W m-2:-1.0/3600:0.0:TOA Outgoing Clear-Sky Longwave Radiation:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+210:var210:SSRC:ssrc:Surface net solar radiation, clear sky:J/m^2:3:rsscs:surface_net_downward_shortwave_flux_assuming_clear_sky:W m-2:1.0/3600:0.0:Surface Net Downward Shortwave Flux Assuming Clear Sky:mon-cf:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+211:var211:STRC:strc:Surface net thermal radiation, clear sky:J/m^2:3:rlscs:surface_net_downward_longwave_flux_assuming_clear_sky:W m-2:1.0/3600:0.0:Surface Net Downward Longwave Flux Assuming Clear Sky:mon-cf:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+212:var212:SI:tisr:TOA incident solar radiation:J/m^2:6:rsdt:toa_incoming_shortwave_flux:W m-2:1.0/3600:0.0:TOA Incident Shortwave Radiation:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+228:var228:TP:tp:Total precipitation:m:6:pr:precipitation_flux:kg m-2 s-1:1.0/3.6:0:Precipitation:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+235:var235:SKT:skt:Skin temperature:K:0:skt:skin_temperature:K:1.0:0.0:Skin Temperature:mon-era5:gr:GRIB:atmos:I:sf00:sf00:None:1.0::
+236:var236:STL4:stl4:Soil temperature level 4:K:6:tsl4:soil_temperature:K:1:0.0:Temperature of Soil 4:Lmon:gr:GRIB:land:I:sf00:sf00:None:1.0::
+238:var238:TSN:tsn:Temperature of snow layer:K:6:tsn:temperature_in_surface_snow:K:1:0.0:Snow Internal Temperature:LImon:gr:GRIB:landIce:I:sf00:sf00:None:1.0::
+239:var239:CSF:csf:Convective snowfall:m of water equivalent:6:prsnc:convective_snowfall_flux:kg m-2 s-1:1.0/3.6:0:Convective Snowfall Flux:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+240:var240:LSF:lsf:Large-scale snowfall:m of water equivalent:6:prlsns:stratiform_snowfall_flux:kg m-2 s-1:1.0/3.6:0:Stratiform Snowfall Flux:Amon:gr:GRIB:atmos:A:sf12:sf12:None:1.0::
+243:var243:FAL:fal:Forecast albedo:0..1:0:fal:forecast_albedo:%:100:0.0:Forecast Albedo:mon-era5:gr:GRIB:atmos:I:sf00:sf00,sf12:None:1.0::
+244:var244:FSR:fsr:Forecast surface roughness:m:0:fsr:forecast_surface_roughness:m:1.0:0.0:Forecast Surface Roughness:mon-era5:gr:GRIB:atmos:I:sf00:sf00,sf12:None:1.0::
+245:var245:FLSR:flsr:Forecast logarithm of surface roughness for heat:-:0:flsr:forecast_logarithm_of_surface_roughness_for_heat:-:1.0:0.0:Forecast Logarithm of Surface Roughness for Heat:mon-era5:gr:GRIB:atmos:I:sf00:sf00,sf12:None:1.0::
+246:var246:CLWC:clwc:Specific cloud liquid water content:kg/kg:6:clw:mass_fraction_of_cloud_liquid_water_in_air:1:1:0.0:Mass Fraction of Cloud Liquid Water:Amon:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:0.0::
+247:var247:CIWC:ciwc:Specific cloud ice water content:kg/kg:6:cli:mass_fraction_of_cloud_ice_in_air:1:1:0.0:Mass Fraction of Cloud Ice:Amon:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:0.0::
+248:var248:CC:cc:Fraction of cloud cover:0..1:6:cl:cloud_area_fraction_in_atmosphere_layer:%:100:0:Percentage Cloud Cover:Amon:gr:GRIBx:atmos:I:pl00:ml00,pl00:85000,50000,25000:0.0::
+# last line of table
diff --git a/tables/ERA5Land/EL_1hr.json b/tables/ERA5Land/EL_1hr.json
new file mode 100644
index 0000000000000000000000000000000000000000..d3146714e937853b1443010177e362fe8a7e6989
--- /dev/null
+++ b/tables/ERA5Land/EL_1hr.json
@@ -0,0 +1,39 @@
+{
+ "Header": {
+ "data_specs_version": "01.01.00",
+ "cmor_version": "3.6",
+ "table_id": "Table 1hr",
+ "realm": "atmos land landIce",
+ "table_date": "19 Dec 2023",
+ "missing_value": "1e20",
+ "int_missing_value": "-999",
+ "product": "reanalysis",
+ "approx_interval": "",
+ "generic_levels": "",
+ "project": "reanalysis",
+ "Conventions": "CF-1.7",
+ "institution": "European Centre for Medium-Range Weather Forecasts",
+ "license": "ERA5 data, which are produced as part of the EU-funded Copernicus Climate Change Service (C3S), are distributed on an open basis without any specific restrictions on their usage or distribution (see License). However, all users of Copernicus Products must provide clear and visible attribution to the Copernicus program. A detailed desription can be found at https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf",
+ "citation": "Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac (Accessed on DD-MMM-YYYY). Data distribution by the German Climate Computing Center (DKRZ)."
+ },
+ "variable_entry": {
+ "rsn": {
+ "frequency": "1hr",
+ "modeling_realm": "landIce",
+ "standard_name": "snow_density",
+ "units": "kg m-3",
+ "cell_methods": "area: time: point",
+ "cell_measures": "area: areacella",
+ "long_name": "Snow Density",
+ "comment": "This parameter is the mass of snow per cubic metre in the snow layer. The ECMWF Integrated Forecast System (IFS) model represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box.",
+ "dimensions": "longitude latitude time",
+ "out_name": "rsn",
+ "type": "real",
+ "positive": "",
+ "table": "128",
+ "code": "33",
+ "short_name": "rsn",
+ "conversion": "1"
+ },
+ }
+}
diff --git a/tables/ERA5Land/EL_CV.json b/tables/ERA5Land/EL_CV.json
new file mode 100644
index 0000000000000000000000000000000000000000..bab74ad9ee0afc3fb6ec53b38d1da8bad5c184ce
--- /dev/null
+++ b/tables/ERA5Land/EL_CV.json
@@ -0,0 +1,239 @@
+{
+ "CV":{
+ "required_global_attributes":[
+ "Conventions",
+ "activity_id",
+ "creation_date",
+ "CORDEX_domain",
+ "driving_experiment_name",
+ "driving_experiment",
+ "driving_model_ensemble_member",
+ "driving_model_id",
+ "rcm_version_id",
+ "experiment",
+ "experiment_id",
+ "forcing_index",
+ "frequency",
+ "grid",
+ "grid_label",
+ "initialization_index",
+ "institution",
+ "institution_id",
+ "license",
+ "model_id",
+ "physics_index",
+ "product",
+ "realization_index",
+ "realm",
+ "source",
+ "source_id",
+ "source_type",
+ "sub_experiment",
+ "sub_experiment_id",
+ "table_id",
+ "variable_id",
+ "variant_label"
+ ],
+ "version_metadata":{
+ "CV_collection_modified":"Fri January 27 20:00:00 2023 -0700",
+ "CV_collection_version":"1.0.0.0",
+ "author":"Martin Schupfner <schupfner@dkrz.de>",
+ "institution_id":"DKRZ"
+ },
+ "activity_id":{
+ "OcMod":"Observations closer to Model Data"
+ },
+ "institution_id":{
+ "DKRZ":"Deutsches Klimarechenzentrum, Hamburg 20146, Germany",
+ "DWD":"Deutscher Wetterdienst, Offenbach am Main 63067, Germany",
+ "MPI-M":"Max Planck Institute for Meteorology, Hamburg 20146, Germany",
+ "UHH":"Universität Hamburg, Hamburg 20148, Germany",
+ "ECMWF":"European Centre for Medium-Range Weather Forecasts, 53175 Bonn, Germany"
+ },
+ "source_id":{
+ "COSMO":{
+ "activity_participation":[
+ "OcMod"
+ ],
+ "cohort":[
+ "Registered"
+ ],
+ "institution_id":[
+ "DWD"
+ ],
+ "source_id":"",
+ "source":"COSMO v4.25 (2012): \naerosol: none/prescribed\natmos: COnsortium for Small-Scale MOdelling (COSMO) limited-area model (LAM) version 4.25 (Arakawa-C/Lorenz Grid; 848 x 824 longitude/latitude; 40 levels; top level 40 hPa)\natmosChem: none\nland: TERRA-ML\nlandIce: none/prescribed\nocean: none/prescribed\nocnBgchem: none\nseaIce: none/prescribed\nsolidLand: none/prescribed"
+ }
+ },
+ "source_type":{
+ "AER":"aerosol treatment in an atmospheric model where concentrations are calculated based on emissions, transformation, and removal processes (rather than being prescribed or omitted entirely)",
+ "AGCM":"atmospheric general circulation model run with prescribed ocean surface conditions and usually a model of the land surface",
+ "AOGCM":"coupled atmosphere-ocean global climate model, additionally including explicit representation of at least the land and sea ice",
+ "BGC":"biogeochemistry model component that at the very least accounts for carbon reservoirs and fluxes in the atmosphere, terrestrial biosphere, and ocean",
+ "CHEM":"chemistry treatment in an atmospheric model that calculates atmospheric oxidant concentrations (including at least ozone), rather than prescribing them",
+ "ISM":"ice-sheet model that includes ice-flow",
+ "LAND":"land model run uncoupled from the atmosphere",
+ "OGCM":"ocean general circulation model run uncoupled from an AGCM but, usually including a sea-ice model",
+ "RAD":"radiation component of an atmospheric model run 'offline'",
+ "SLAB":"slab-ocean used with an AGCM in representing the atmosphere-ocean coupled system",
+ "SLM":"solid land/earth model"
+ },
+ "frequency":{
+ "1hr":"sampled hourly",
+ "1hrCM":"monthly-mean diurnal cycle resolving each day into 1-hour means",
+ "1hrPt":"sampled hourly, at specified time point within an hour",
+ "3hr":"sampled every 3 hours",
+ "3hrPt":"sampled 3 hourly, at specified time point within the time period",
+ "6hr":"sampled every 6 hours",
+ "6hrPt":"sampled 6 hourly, at specified time point within the time period",
+ "day":"daily mean samples",
+ "dec":"decadal mean samples",
+ "fx":"fixed (time invariant) field",
+ "mon":"monthly mean samples",
+ "monC":"monthly climatology computed from monthly mean samples",
+ "monPt":"sampled monthly, at specified time point within the time period",
+ "subhrPt":"sampled sub-hourly, at specified time point within an hour",
+ "yr":"annual mean samples",
+ "yrPt":"sampled yearly, at specified time point within the time period"
+ },
+ "grid_label":{
+ "gm":"global mean data",
+ "gn":"data reported on a model's native grid",
+ "gna":"data reported on a native grid in the region of Antarctica",
+ "gng":"data reported on a native grid in the region of Greenland",
+ "gnz":"zonal mean data reported on a model's native latitude grid",
+ "gr":"regridded data reported on the data provider's preferred target grid",
+ "gr1":"regridded data reported on a grid other than the native grid and other than the preferred target grid",
+ "gr1a":"regridded data reported in the region of Antarctica on a grid other than the native grid and other than the preferred target grid",
+ "gr1g":"regridded data reported in the region of Greenland on a grid other than the native grid and other than the preferred target grid",
+ "gr1z":"regridded zonal mean data reported on a grid other than the native latitude grid and other than the preferred latitude target grid",
+ "gr2":"regridded data reported on a grid other than the native grid and other than the preferred target grid",
+ "gr2a":"regridded data reported in the region of Antarctica on a grid other than the native grid and other than the preferred target grid",
+ "gr2g":"regridded data reported in the region of Greenland on a grid other than the native grid and other than the preferred target grid",
+ "gr2z":"regridded zonal mean data reported on a grid other than the native latitude grid and other than the preferred latitude target grid",
+ "gr3":"regridded data reported on a grid other than the native grid and other than the preferred target grid",
+ "gr3a":"regridded data reported in the region of Antarctica on a grid other than the native grid and other than the preferred target grid",
+ "gr3g":"regridded data reported in the region of Greenland on a grid other than the native grid and other than the preferred target grid",
+ "gr3z":"regridded zonal mean data reported on a grid other than the native latitude grid and other than the preferred latitude target grid",
+ "gr4":"regridded data reported on a grid other than the native grid and other than the preferred target grid",
+ "gr4a":"regridded data reported in the region of Antarctica on a grid other than the native grid and other than the preferred target grid",
+ "gr4g":"regridded data reported in the region of Greenland on a grid other than the native grid and other than the preferred target grid",
+ "gr4z":"regridded zonal mean data reported on a grid other than the native latitude grid and other than the preferred latitude target grid",
+ "gr5":"regridded data reported on a grid other than the native grid and other than the preferred target grid",
+ "gr5a":"regridded data reported in the region of Antarctica on a grid other than the native grid and other than the preferred target grid",
+ "gr5g":"regridded data reported in the region of Greenland on a grid other than the native grid and other than the preferred target grid",
+ "gr5z":"regridded zonal mean data reported on a grid other than the native latitude grid and other than the preferred latitude target grid",
+ "gr6":"regridded data reported on a grid other than the native grid and other than the preferred target grid",
+ "gr6a":"regridded data reported in the region of Antarctica on a grid other than the native grid and other than the preferred target grid",
+ "gr6g":"regridded data reported in the region of Greenland on a grid other than the native grid and other than the preferred target grid",
+ "gr6z":"regridded zonal mean data reported on a grid other than the native latitude grid and other than the preferred latitude target grid",
+ "gr7":"regridded data reported on a grid other than the native grid and other than the preferred target grid",
+ "gr7a":"regridded data reported in the region of Antarctica on a grid other than the native grid and other than the preferred target grid",
+ "gr7g":"regridded data reported in the region of Greenland on a grid other than the native grid and other than the preferred target grid",
+ "gr7z":"regridded zonal mean data reported on a grid other than the native latitude grid and other than the preferred latitude target grid",
+ "gr8":"regridded data reported on a grid other than the native grid and other than the preferred target grid",
+ "gr8a":"regridded data reported in the region of Antarctica on a grid other than the native grid and other than the preferred target grid",
+ "gr8g":"regridded data reported in the region of Greenland on a grid other than the native grid and other than the preferred target grid",
+ "gr8z":"regridded zonal mean data reported on a grid other than the native latitude grid and other than the preferred latitude target grid",
+ "gr9":"regridded data reported on a grid other than the native grid and other than the preferred target grid",
+ "gr9a":"regridded data reported in the region of Antarctica on a grid other than the native grid and other than the preferred target grid",
+ "gr9g":"regridded data reported in the region of Greenland on a grid other than the native grid and other than the preferred target grid",
+ "gr9z":"regridded zonal mean data reported on a grid other than the native latitude grid and other than the preferred latitude target grid",
+ "gra":"regridded data in the region of Antarctica reported on the data provider's preferred target grid",
+ "grg":"regridded data in the region of Greenland reported on the data provider's preferred target grid",
+ "grz":"regridded zonal mean data reported on the data provider's preferred latitude target grid"
+ },
+ "nominal_resolution":[
+ "0.5 km",
+ "1 km",
+ "10 km",
+ "100 km",
+ "1000 km",
+ "10000 km",
+ "1x1 degree",
+ "2.5 km",
+ "25 km",
+ "250 km",
+ "2500 km",
+ "5 km",
+ "50 km",
+ "500 km",
+ "5000 km"
+ ],
+ "realm":{
+ "aerosol":"Aerosol",
+ "atmos":"Atmosphere",
+ "atmosChem":"Atmospheric Chemistry",
+ "land":"Land Surface",
+ "landIce":"Land Ice",
+ "ocean":"Ocean",
+ "ocnBgchem":"Ocean Biogeochemistry",
+ "seaIce":"Sea Ice"
+ },
+ "table_id":[
+ "mon",
+ "day",
+ "6hr",
+ "1hr",
+ "1hrPt",
+ "fx"
+ ],
+ "license":[
+ "^All data in the freely accessible area are part of the DWD's open data and are protected by copyright\\. Re-use of data is granted without any restrictions provided that the source reference is indicated, as laid down in the GeoNutzV ordinance ('Verordnung zur Festlegung der Nutzungsbestimmungen für die Bereitstellung von Geodaten des Bundes' = Ordinance to Determine the Conditions for Use for the Provision of Spatial Data of the Federation)\\. See also 'https://opendata\\.dwd\\.de/climate_environment/REA/Terms_of_use_REA.txt'\\.$"
+ ],
+ "sub_experiment_id":{
+ "none":"none"
+ },
+ "experiment_id":{
+ "REA6":{
+ "activity_id":[
+ "OcMod"
+ ],
+ "additional_allowed_model_components":[
+ "AER",
+ "BGC"
+ ],
+ "experiment":"regional reanalysis",
+ "experiment_id":"REA6",
+ "parent_activity_id":[
+ "None"
+ ],
+ "parent_experiment_id":[
+ "None"
+ ],
+ "required_model_components":[
+ "AGCM"
+ ],
+ "sub_experiment_id":[
+ "none"
+ ]
+ }
+ },
+ "product":[
+ "model-output",
+ "reanalysis"
+ ],
+ "tracking_id":[
+ "hdl:21.14105/.*"
+ ],
+
+ "realization_index":[
+ "^\\[\\{0,\\}[[:digit:]]\\{1,\\}\\]\\{0,\\}$"
+ ],
+ "variant_label":[
+ "r[[:digit:]]\\{1,\\}i[[:digit:]]\\{1,\\}p[[:digit:]]\\{1,\\}f[[:digit:]]\\{1,\\}$"
+ ],
+ "Conventions":[
+ "^CF-1.7\\( UGRID-1.0\\)\\{0,\\}$"
+ ],
+ "forcing_index":[
+ "^\\[\\{0,\\}[[:digit:]]\\{1,\\}\\]\\{0,\\}$"
+ ],
+ "initialization_index":[
+ "^\\[\\{0,\\}[[:digit:]]\\{1,\\}\\]\\{0,\\}$"
+ ],
+ "physics_index":[
+ "^\\[\\{0,\\}[[:digit:]]\\{1,\\}\\]\\{0,\\}$"
+ ]
+ }
+}
diff --git a/tables/ERA5Land/EL_day.json b/tables/ERA5Land/EL_day.json
new file mode 100644
index 0000000000000000000000000000000000000000..1c79d1d3f1d6ce750dc2a8bcfb9021677d8806e2
--- /dev/null
+++ b/tables/ERA5Land/EL_day.json
@@ -0,0 +1,39 @@
+{
+ "Header": {
+ "data_specs_version": "01.01.00",
+ "cmor_version": "3.6",
+ "table_id": "Table day",
+ "realm": "atmos land landIce",
+ "table_date": "19 Dec 2023",
+ "missing_value": "1e20",
+ "int_missing_value": "-999",
+ "product": "reanalysis",
+ "approx_interval": "0.041667",
+ "generic_levels": "sfc",
+ "project": "reanalysis",
+ "Conventions": "CF-1.7",
+ "institution": "European Centre for Medium-Range Weather Forecasts",
+ "license": "ERA5 data, which are produced as part of the EU-funded Copernicus Climate Change Service (C3S), are distributed on an open basis without any specific restrictions on their usage or distribution (see License). However, all users of Copernicus Products must provide clear and visible attribution to the Copernicus program. A detailed desription can be found at https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf",
+ "citation": "Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac (Accessed on DD-MMM-YYYY). Data distribution by the German Climate Computing Center (DKRZ)."
+ },
+ "variable_entry": {
+ "rsn": {
+ "frequency": "day",
+ "modeling_realm": "landIce",
+ "standard_name": "snow_density",
+ "units": "kg m-3",
+ "cell_methods": "area: time: mean",
+ "cell_measures": "area: areacella",
+ "long_name": "Snow Density",
+ "comment": "This parameter is the mass of snow per cubic metre in the snow layer. The ECMWF Integrated Forecast System (IFS) model represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box.",
+ "dimensions": "longitude latitude time",
+ "out_name": "rsn",
+ "type": "real",
+ "positive": "",
+ "table": "128",
+ "code": "33",
+ "short_name": "rsn",
+ "conversion": "1"
+ },
+ }
+}
diff --git a/tables/ERA5Land/EL_fx.json b/tables/ERA5Land/EL_fx.json
new file mode 100644
index 0000000000000000000000000000000000000000..41686e9ba60ce7de8341e234bd73f60c5be4c88c
--- /dev/null
+++ b/tables/ERA5Land/EL_fx.json
@@ -0,0 +1,51 @@
+{
+ "Header": {
+ "data_specs_version": "01.01.00",
+ "cmor_version": "3.6",
+ "table_id": "Table fx",
+ "realm": "land",
+ "table_date": "19 Dec 2023",
+ "missing_value": "1e20",
+ "int_missing_value": "-999",
+ "product": "reanalysis",
+ "approx_interval": "",
+ "generic_levels": "",
+ "Conventions": "CF-1.7",
+ "project": "reanalysis",
+ "institute": "ECMWF",
+ "model": "IFS",
+ "experiment": "ERA5, ERA5-Land",
+ "institution": "European Centre for Medium-Range Weather Forecasts",
+ "license": "ERA5 data, which are produced as part of the EU-funded Copernicus Climate Change Service (C3S), are distributed on an open basis without any specific restrictions on their usage or distribution (see License). However, all users of Copernicus Products must provide clear and visible attribution to the Copernicus program. A detailed desription can be found at https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf",
+ "citation": "Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac (Accessed on DD-MMM-YYYY). Data distribution by the German Climate Computing Center (DKRZ).",
+ "family": "provisional (ET) improved (E1) final (E5)",
+
+
+ },
+ "variable_entry": {
+ "sftlf": {
+ "frequency": "fx",
+ "modeling_realm": "land",
+ "standard_name": "land_area_fraction",
+ "units": "%",
+ "cell_methods": "area: mean",
+ "cell_measures": "area: areacella",
+ "long_name": "Percentage of the Grid Cell Occupied by Land (Including Lakes)",
+ "comment": "Percentage of horizontal area occupied by land.",
+ "dimensions": "longitude latitude",
+ "type": "real",
+ "positive": "",
+ "conversion": "100",
+ "grid": "regular gaussian",
+ "table": "180",
+ "code": "172",
+ "orig_short_name": "lsm",
+ "orig_name": "Land-sea mask",
+ "grib_description": "This parameter is the proportion of land, as opposed to ocean or inland waters (lakes, reservoirs, rivers and coastal waters), in a grid box. This parameter has values ranging between zero and one and is dimensionless. In cycles of the ECMWF Integrated Forecasting System (IFS) from CY41R1 (introduced in May 2015) onwards, grid boxes where this parameter has a value above 0.5 can be comprised of a mixture of land and inland water but not ocean. Grid boxes with a value of 0.5 and below can only be comprised of a water surface. In the latter case, the lake cover is used to determine how much of the water surface is ocean or inland water. In cycles of the IFS before CY41R1, grid boxes where this parameter has a value above 0.5 can only be comprised of land and those grid boxes with a value of 0.5 and below can only be comprised of ocean. In these older model cycles, there is no differentiation between ocean and inland water. https://codes.ecmwf.int/grib/param-db/?id=172",
+ "orig_units": "(0..1)",
+ "orig_grid": "gaussian reduced, spectral",
+ "level_type": "pl_an, ml_an, sfc_an, sfc_fc",
+ "mapping": "CMIP6"
+ }
+ }
+}
diff --git a/tables/ERA5Land/EL_mon.json b/tables/ERA5Land/EL_mon.json
new file mode 100644
index 0000000000000000000000000000000000000000..bd737ed485fb317eede4d59d5d48d1ca6fc76149
--- /dev/null
+++ b/tables/ERA5Land/EL_mon.json
@@ -0,0 +1,38 @@
+{
+ "Header": {
+ "data_specs_version": "01.01.00",
+ "cmor_version": "3.6",
+ "table_id": "Table mon",
+ "realm": "atmos land landIce",
+ "table_date": "19 Dec 2023",
+ "missing_value": "1e20",
+ "int_missing_value": "-999",
+ "product": "reanalysis",
+ "generic_levels": "sfc",
+ "project": "reanalysis",
+ "Conventions": "CF-1.7",
+ "institution": "European Centre for Medium-Range Weather Forecasts",
+ "license": "ERA5 data, which are produced as part of the EU-funded Copernicus Climate Change Service (C3S), are distributed on an open basis without any specific restrictions on their usage or distribution (see License). However, all users of Copernicus Products must provide clear and visible attribution to the Copernicus program. A detailed desription can be found at https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf",
+ "citation": "Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac (Accessed on DD-MMM-YYYY). Data distribution by the German Climate Computing Center (DKRZ)."
+ },
+ "variable_entry": {
+ "rsn": {
+ "frequency": "mon",
+ "modeling_realm": "landIce",
+ "standard_name": "snow_density",
+ "units": "kg m-3",
+ "cell_methods": "area: time: mean",
+ "cell_measures": "area: areacella",
+ "long_name": "Snow Density",
+ "comment": "This parameter is the mass of snow per cubic metre in the snow layer. The ECMWF Integrated Forecast System (IFS) model represents snow as a single additional layer over the uppermost soil level. The snow may cover all or part of the grid box.",
+ "dimensions": "longitude latitude time",
+ "out_name": "rsn",
+ "type": "real",
+ "positive": "",
+ "table": "128",
+ "code": "33",
+ "short_name": "rsn",
+ "conversion": "1"
+ },
+ }
+}
diff --git a/tables/template/template.json b/tables/template/template.json
new file mode 100644
index 0000000000000000000000000000000000000000..27a6ded6b5b8418e7e2aa7d2b7f60d7908d61cba
--- /dev/null
+++ b/tables/template/template.json
@@ -0,0 +1,51 @@
+{
+ "Header": {
+ // "data_specs_version": "01.01.00", # --> WHAT IS THE MEANING OF THIS. AND HOW DO YOU DEFINE IT? --> ASK MARTIN
+ // "cmor_version": "3.6", # --> NOT NEED
+ "table_id": "Table fx",
+ "realm": "land",
+ // "table_date": "19 Dec 2023",
+ // "missing_value": "1e20",
+ // "int_missing_value": "-999",
+ "product": "reanalysis",
+ "approx_interval": "",
+ "generic_levels": "",
+ "Conventions": "CF-1.7", #### ----> we should make it to CF-1.8 at least
+ "project": "reanalysis",
+ "institute": "ECMWF",
+ "model": "IFS",
+ "experiment": "ERA5, ERA5-Land",
+ "institution": "European Centre for Medium-Range Weather Forecasts",
+ "license": "ERA5 data, which are produced as part of the EU-funded Copernicus Climate Change Service (C3S), are distributed on an open basis without any specific restrictions on their usage or distribution (see License). However, all users of Copernicus Products must provide clear and visible attribution to the Copernicus program. A detailed desription can be found at https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf",
+ "citation": "Muñoz Sabater, J. (2019): ERA5-Land hourly data from 1950 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). DOI: 10.24381/cds.e2161bac (Accessed on DD-MMM-YYYY). Data distribution by the German Climate Computing Center (DKRZ).",
+ "family": "provisional (ET) improved (E1) final (E5)",
+
+
+ },
+ "variable_entry": {
+ "sftlf": {
+ "frequency": "fx",
+ "modeling_realm": "land",
+ "standard_name": "land_area_fraction",
+ "units": "%",
+ "cell_methods": "area: mean",
+ "cell_measures": "area: areacella",
+ "long_name": "Percentage of the Grid Cell Occupied by Land (Including Lakes)",
+ "comment": "Percentage of horizontal area occupied by land.",
+ "dimensions": "longitude latitude",
+ "type": "real",
+ "positive": "",
+ "conversion": "100",
+ "grid": "regular gaussian",
+ "table": "180",
+ "code": "172",
+ "orig_short_name": "lsm",
+ "orig_name": "Land-sea mask",
+ "grib_description": "This parameter is the proportion of land, as opposed to ocean or inland waters (lakes, reservoirs, rivers and coastal waters), in a grid box. This parameter has values ranging between zero and one and is dimensionless. In cycles of the ECMWF Integrated Forecasting System (IFS) from CY41R1 (introduced in May 2015) onwards, grid boxes where this parameter has a value above 0.5 can be comprised of a mixture of land and inland water but not ocean. Grid boxes with a value of 0.5 and below can only be comprised of a water surface. In the latter case, the lake cover is used to determine how much of the water surface is ocean or inland water. In cycles of the IFS before CY41R1, grid boxes where this parameter has a value above 0.5 can only be comprised of land and those grid boxes with a value of 0.5 and below can only be comprised of ocean. In these older model cycles, there is no differentiation between ocean and inland water. https://codes.ecmwf.int/grib/param-db/?id=172",
+ "orig_units": "(0..1)",
+ "orig_grid": "gaussian reduced, spectral",
+ "level_type": "pl_an, ml_an, sfc_an, sfc_fc",
+ "mapping": "CMIP6"
+ }
+ }
+}