The EUPP postprocessing benchmark dataset documentation
This website document the EUMETNET postprocessing benchmark datasets, an initiative to provide high-quality datasets to derive easily analysis-ready datasets that can be used to perform benchmarking tasks of weather forecast postprocessing methods.
The main tool to download and manage the data is a Python plugin. It can however convert the data to formats that can then be processed by other languages, and a few line of Python codes suffice to obtain the datasets.
Note
Climetlab plugin version: 0.2.5
EUPPBench dataset version: v1.0
Base dataset version: v1.0
Dataset status: Datasets status
Currently available datasets:
Using climetlab to access the data
A plugin for climetlab to retrieve the Eumetnet postprocessing benchmark datasets is available.
It facilitates the download of the dataset time-aligned forecasts, reforecasts (hindcasts) and observations (ERA5 reanalysis).
See the demo
notebooks
The climetlab python plugin allows users to easily access the data with a few lines of code such as:
# Uncomment the line below if climetlab and the plugin are not yet installed
#!pip install climetlab climetlab-eumetnet-postprocessing-benchmark
import climetlab as cml
ds = cml.load_dataset('eumetnet-postprocessing-benchmark-training-data-gridded-forecasts-surface', "2017-12-02", "2t", "highres")
fcs = ds.to_xarray()
which for instance download the deterministic (high-resolution) forecasts for the 2 metres temperature.