Published March 8, 2023 | Version v1.0

EUPPBench postprocessing benchmark dataset - station data

  • 1. Federal Office of Meteorology and Climatology MeteoSwiss
  • 2. GeoSphere Austria
  • 3. Royal Meteorological Institute of Belgium, EUMETNET
  • 4. Meteo France, Ecole Nationale de la Meteorologie

Description

The EUMETNET EUPPBench postprocessing benchmark station data is an analysis-ready dataset to perform benchmarks of different postprocessing methods on a common dataset.

This dataset is using the Zarr format. Please look at the Zarr documentation to see how to load and access the data.

The documentation of the dataset is available on https://eupp-benchmark.github.io/EUPPBench-doc/ .

The official way to download the dataset is through the climetlab EUMETNET postprocessing benchmark plugin.

This Zenodo repository aims to preserve the dataset by providing long-term storage.

Please read the LICENSE file for more information on the data licenses.

Installation procedure

Download the the dataset in a given folder, and on a Linux (or mac OS) terminal, and still in this folder, enter the following command

unzip EUPPBench-stations.zip
rm EUPPBench-stations.zip

This will unpack the dataset. You need at least 35Gb of free space on your disk to perform this operation.

 

Citation

If you use this dataset for a publication, please cite the dataset article:

Demaeyer, J., Bhend, J., Lerch, S., Primo, C., Van Schaeybroeck, B., Atencia, A., Ben Bouallègue, Z., Chen, J., Dabernig, M., Evans, G., Faganeli Pucer, J., Hooper, B., Horat, N., Jobst, D., Merše, J., Mlakar, P., Möller, A., Mestre, O., Taillardat, M., and Vannitsem, S.: The EUPPBench postprocessing benchmark dataset v1.0, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2022-465, in review, 2023.

 

Remark

You might also be interested by the gridded data part of this dataset also available on Zenodo here: https://doi.org/10.5281/zenodo.7429236 .

Files

EUPPBench-stations.zip

Files (18.3 GB)

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md5:e409457279b3494d18f2dfb41f3f449b
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md5:b82e16afa33c93fdc5fc5a6af62eb3e3
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