This short course introduces participants to the Analysis-Ready Cloud-Optimised (ARCO) Zarr datasets available through the Copernicus Climate Change Service (C3S) and Copernicus Atmosphere Monitoring Service (CAMS) datastores; the Climate Data Store (CDS) and Atmosphere Data Store (ADS), both operated by ECMWF.
An increasing range of the C3S and CAMS datasets are being made available in ARCO-Zarr format, including the ERA5 family of reanalyses products, SEAS5 seasonal forecasts, AgERA5 and a collection of satellite Essential Climate Variable (ECV) datasets. ARCO-Zarr enables users to access and process only the data they need, often avoiding the need to download large datasets in advance and making many analyses substantially more efficient.
The course will demonstrate how to discover and explore available datasets, access them programmatically using Datastore credentials, and build Python workflows that stream data directly from the cloud to analysis and visualisation tools. Participants will work through hands-on Jupyter Notebooks using real Copernicus datasets and learn practical approaches for efficient data access, processing and visualisation.
The course is aimed at PhD students, researchers and technical users working in Earth-system, climate and environmental sciences. Participants should have basic familiarity with Python; no prior knowledge of Zarr or cloud-based data access is required.