Baroclinic Wave Simulation Ensemble: a Machine Learning ready dataset

Description

A large ensemble of 6,500 different baroclinic wave simulations have been run, processed and provided to study extra tropical cyclones and mid-latitudes dynamics. The data were generated using OpenIFS@home, an open science climateprediction.net project allowing the distribution of the computation of the ensemble with the OpenIFS 43R3v2 model. For each simulation, the cyclones were tracked and 89 features -including 16 intensity measures- were extracted. The presented dataset is composed of the raw output of the OpenIFS model for 6,388 of the 6,500 members of the ensemble and the extracted features of the tracked cyclones. The computational failure of the missing 112 ensemble members is statistically assessed and explained. The distribution of the minimum mean sea level pressure and the maximum relative vorticity at 850 hPa is plotted to assess the realistic likelihood of the developing cyclones. The dataset and all the associated code is available and easily accessible. To manipulate the OpenIFS 43R3v2 outputs, plotting scripts are available in this Zenodo repository: https://zenodo.org/records/10592587 All the code used to produce this dataset can be found in this GitLab repository: https://version.helsinki.fi/dynamic-meteorology-public/Baroclinic-Wave-Simulation-Ensemble-repository
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Year of publication

2025

Type of data

Authors

Matemaattis-luonnontieteellinen tiedekunta

Clément Bouvier Orcid -palvelun logo - Curator, Publisher, Contributor, Creator

Victoria Sinclair Orcid -palvelun logo - Curator, Contributor, Creator

Antti Toropainen Orcid -palvelun logo - Creator

Joona Cornér Orcid -palvelun logo - Creator

University of Oxford

Andy Bowery Orcid -palvelun logo - Creator

David Wallom Orcid -palvelun logo - Creator

Glenn Carver Orcid -palvelun logo - Creator

Sarah Sparrow Orcid -palvelun logo - Creator

Project

Other information

Fields of science

Geosciences

Language

English

Open access

Open

License

Creative Commons Attribution 4.0 International (CC BY 4.0)

Keywords

machine learning, Baroclinic Wave Simulation, Extratropical cyclone

Subject headings

Temporal coverage

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