ecmwf_models
ecmwf_models copied to clipboard
Python package for downloading ECMWF reanalysis data and converting it into a time series format.
============ ecmwf_models
.. image:: https://github.com/TUW-GEO/ecmwf_models/workflows/Automated%20Tests/badge.svg?branch=master :target: https://github.com/TUW-GEO/ecmwf_models/actions
.. image:: https://coveralls.io/repos/github/TUW-GEO/ecmwf_models/badge.svg?branch=master :target: https://coveralls.io/github/TUW-GEO/ecmwf_models?branch=master
.. image:: https://badge.fury.io/py/ecmwf-models.svg :target: https://badge.fury.io/py/ecmwf-models
.. image:: https://readthedocs.org/projects/ecmwf-models/badge/?version=latest :target: https://ecmwf-models.readthedocs.io/en/latest/
Readers and converters for data from the ECMWF reanalysis models <http://apps.ecmwf.int/datasets/>
_. Written in Python.
Works great in combination with pytesmo <https://github.com/TUW-GEO/pytesmo>
_.
Citation
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.593533.svg :target: https://doi.org/10.5281/zenodo.593533
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.
Please select your specific version at https://doi.org/10.5281/zenodo.593533 to get the DOI of that version. You should normally always use the DOI for the specific version of your record in citations. This is to ensure that other researchers can access the exact research artefact you used for reproducibility.
You can find additional information regarding DOI versioning at http://help.zenodo.org/#versioning
Installation
Install required C-libraries via conda. For installation we recommend
Miniconda <http://conda.pydata.org/miniconda.html>
_. So please install it according
to the official installation instructions. As soon as you have the conda
command in your shell you can continue:
.. code::
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.
.. code::
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.
.. code::
git clone --recursive [email protected]:TUW-GEO/ecmwf_models.git ecmwf_models
cd ecmwf_models
conda env create -f environment/latest.yml
source activate ecmwf_models
python setup.py develop
pytest
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.
Contribute
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 <https://github.com/TUW-GEO/ecmwf_models/blob/master/CONTRIBUTING.rst>
_.