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Downloading, reading and TS conversion of ECMWF reanalysis data

Project description

Readers and converters for data from the ECMWF reanalysis models. Written in Python.

Works great in combination with pytesmo.


If you use the software in a publication then please cite it using the Zenodo DOI. Be aware that this badge links to the latest package version.

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Install required C-libraries via conda. For installation we recommend Miniconda. So please install it according to the official installation instructions. As soon as you have the conda command in your shell you can continue:

conda install -c conda-forge pandas pygrib netcdf4 pyresample xarray

The following command will download and install all the needed pip packages as well as the ecmwf-model package itself.

pip install ecmwf_models

To create a full development environment with conda, the yml files inside the folder environment/ in this repository can be used. Both environements should work. The file latest should install the newest version of most dependencies. The file pinned is a fallback option and should always work.

git clone --recursive ecmwf_models
cd ecmwf_models
conda env create -f environment/latest.yml
source activate ecmwf_models
python develop

Supported Products

At the moment this package supports

  • ERA Interim (deprecated)

  • ERA5

  • ERA5-Land

reanalysis data in grib and netcdf format (download, reading, time series creation) with a default spatial sampling of 0.75 degrees (ERA Interim), 0.25 degrees (ERA5), resp. 0.1 degrees (ERA5-Land). It should be easy to extend the package to support other ECMWF reanalysis products. This will be done as need arises.


We are happy if you want to contribute. Please raise an issue explaining what is missing or if you find a bug. Please take a look at the developers guide.

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