Swiss Storm-Object Dataset for ML-Based Hail Detection: Polarimetric Radar Predictors and Crowdsourced Labels (2020–2024)

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Authors: Martin Aregger
Cited by: 0

Abstract

This dataset contains a set of object-based predictors derived from operational C-band polarimetric weather radar data in Switzerland, matched with ground-truth hail labels derived from crowdsourced reports. The predictors are calculated for storm cells identified and tracked by the Thunderstorms Radar Tracking (TRT) algorithm. This dataset was generated to support the development of machine learning models for hail detection and hail size estimation. The dataset covers convective storm activity over Switzerland and a 50-km buffer zone around its borders for the years 2020–2024.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
2 January 2026
Document type
Dataset