Commit 579a162b authored by Maria Moreno's avatar Maria Moreno
Browse files

add link to server-side explanation and fix typo

parent 62e3c7a1
......@@ -8,7 +8,7 @@
"\n",
"We will show here how to count the annual summer days for a particular geolocation of your choice using the results of a climate model, in particular, we can chose one of the historical or one of the shared socioeconomic pathway (ssp) experiments of the Coupled Model Intercomparison Project [CMIP6](https://pcmdi.llnl.gov/CMIP6/).\n",
"\n",
"This Jupyter notebook is meant to run in the Jupyterhub server of the German Climate Computing Center [DKRZ](https://www.dkrz.de/) which is an [ESGF](https://esgf.llnl.gov/) repository that hosts 4 petabytes of CMIP6 data. Please, choose the Python 3 unstable kernel on the Kernel tab above, it contains all the common geoscience packages. See more information on how to run Jupyter notebooks at DKRZ [here](https://www.dkrz.de/up/systems/mistral/programming/jupyter-notebook). Find there how to run this Jupyter notebook in the DKRZ server out of the Jupyterhub, which will entail that you create the environment accounting for the required package dependencies. Running this Jupyter notebook in your premise, which is also known as \"client-side computing\", will also require that you install the necessary packages on you own but it will anyway fail because you will not have direct access to the data pool, which one of the main benefits of the \"server-side data-near computing\" we demonstrate in this use case. \n",
"This Jupyter notebook is meant to run in the Jupyterhub server of the German Climate Computing Center [DKRZ](https://www.dkrz.de/) which is an [ESGF](https://esgf.llnl.gov/) repository that hosts 4 petabytes of CMIP6 data. Please, choose the Python 3 unstable kernel on the Kernel tab above, it contains all the common geoscience packages. See more information on how to run Jupyter notebooks at DKRZ [here](https://www.dkrz.de/up/systems/mistral/programming/jupyter-notebook). Find there how to run this Jupyter notebook in the DKRZ server out of the Jupyterhub, which will entail that you create the environment accounting for the required package dependencies. Running this Jupyter notebook in your premise, which is also known as [client-side](https://en.wikipedia.org/wiki/Client-side) computing, will also require that you install the necessary packages on you own but it will anyway fail because you will not have direct access to the data pool. Direct access to the data pool is one of the main benefits of the [server-side](https://en.wikipedia.org/wiki/Server-side) data-near computing we demonstrate in this use case. \n",
"\n",
"Thanks to the data and computer scientists Marco Kulüke, Fabian Wachsmann, Regina Kwee-Hinzmann, Caroline Arnold, Felix Stiehler, Maria Moreno, and Stephan Kindermann at DKRZ for their contribution to this notebook."
]
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