Python

How to create a multi-model of C3S Seasonal Forecasts with xarray and cfgrib

NOTE: this post has been updated. The previous code was based on the conversion of the GRIB files into NetCDF, which introduces unfortunately some issues. Among the data products of the Copernicus Climate Change (C3S) available through the Climate Data Store, there is a collection of seasonal forecasts, from the 13th November consisting of five different models (ECMWF, UK Met Office, Meteo-France, DWD and CMCC). One of the interesting things you can do with multiple climate models is to combine them into a multi-model ensemble.

The Copernicus toolbox and the role of software in climate services: why using Python

We can easily say that the Copernicus Climate Change (C3S) initiative is definitely shaping the field of climate services. I might have said “Climate Science” instead of “Climate Services”, but I want to focus here on the applicative side of the climate science. The Copernicus Climate Change (C3S) initiative and the CDS The best thing of the C3S is that they are trying to foster the creation of a ecosystem of data services and — not surprisingly — software (design, development, architecture) plays a critical role here.