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Based on user and developer experience of the Climate Data Store (CDS) Toolbox; the DSS offers a JupyterHub service as online computing environment and earthkit as the supported post-processing and visualisation software. Jupyterhub sessions will be available to all DSS users (resource availability dependent) which provide fast access to data available on the various Data Stores and will allow users to perform post-processing and visualisation of this data. The sessions are considered small and not designed for very large computation (see compute resource provisions table below). For larger computation task, users should consider other JupyterHub resources, for example WEkEO.
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Once logged in, users are given a choice of environment to use for their Jupyter session session from a dropdown menu, with several additional option depending on which environment you have selected. Please note that by launching a ECMWF-DSS JupyterHub session you are agreeing the terms and conditions of use Terms of Use for the ECMWF Data Store Service JupyterHub.
Figure1: Selecting DSS from ECMWF JupyterHub launcher page
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This is the general ECMWF JupyterHub launcher, therefore it is possible that you have access to more than the Data Store option described here |
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Name | Use case | RAM | CPU | Duration |
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ECMWF Data Store Service | Some small data processing, e.g. data averaging of small files | 4 Gb | 2 cores | 5 hours |
For reference, a month for one variable in the ERA5 hourly data on single levels is roughly 1.5 Gb. Larger volumes of data could be computed if using block-wise processing of data, e.g. using dask chunks in xarray.
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Small sessions will be prioritised to ensure fair usage of the platform. These priorities are to be monitored closely and will evolve as the project develops. |
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