Ordaz et al. (2026) A climatology of hail in Europe (2014–2024) based on GPM-DPR sensor data

Identification

• Journal: Atmospheric Research
• Year: 2026
• Date: 2026-03-27
• Authors: Laura Rivero Ordaz, Eduardo García-Ortega, Andrés Navarro, Francisco J. Tapiador, José Luis Sánchez, Alejandro Corbea-Pérez, Andrés Merino
• DOI: 10.1016/j.atmosres.2026.108965

Research Groups

• Institute for Environment and Global Change (IMACG), Universidad de Le´on, Le´on, Spain
• University of Castilla-La Mancha, ICAM, Toledo, Spain

Short Summary

This study developed a continental-scale hail climatology for Europe (2014–2024) using GPM-DPR satellite data and four detection algorithms to overcome surface observation limitations. It identified the Alpine range as the primary hail epicenter, with activity extending over the Balkan peninsula and Apennines, and revealed a clear seasonal migration of hail hotspots across the continent.

Objective

• To investigate the behavior of hail in Europe during 2014–2024, using detection algorithms applied to data from the GPM Dual-frequency Precipitation Radar (DPR sensor).

Study Configuration

• Spatial Scale: Continental Europe (10.4°W to 36.2°E longitude, 36°N to 55.38°N latitude), including west-central Türkiye, analyzed on a 0.1° × 0.1° grid. DPR horizontal resolution is 5 km, with a nominal vertical resolution of 250 m.
• Temporal Scale: 11-year period from 2014 to 2024, focusing on the April–September hail season, with monthly and subregional analyses.

Methodology and Data

• Models used: Four hail detection algorithms adapted from Mroz et al. (2017):
  • Zmix Ku (Mean measured reflectivity in mixed-phase layer, Ku band)
  • Zmix KuKa (Two-variable algorithm, Ku and Ka band)
  • H40AFL Ku (40-dBZ measured reflectivity-level height above 0 °C isotherm, Ku band)
  • H30AFL Ka (30-dBZ measured reflectivity-level height above 0 °C isotherm, Ka band)
• Data sources: Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) sensor data (Ku-band at 13.6 GHz, Ka-band at 35.6 GHz), specifically the Level 2ADPR product (version V07). Extracted variables include measured Ku- and Ka-band reflectivity (dBZ), 0 °C isotherm height (m), and air temperature (°C).

Main Results

• The primary hail epicenter in Europe is located near the Alpine range, particularly the eastern Alps (southeastern Austria, Slovenia, northeast Italy), with secondary axes extending over the Balkan peninsula and Apennines.
• Orography is confirmed as the dominant influence on hail distribution.
• Hail activity exhibits a clear seasonal evolution:
  • April: Scattered foci.
  • May: Intensification and shift towards southeastern Europe.
  • June: Maximum spatial extent and heterogeneity (Carpathians, France, Türkiye).
  • July–August (summer peak): Activity consolidates over the Alpine system and northern Italy.
  • September: Shifts towards the Mediterranean Sea, driven by warm waters.
• The H40AFL Ku algorithm consistently yielded much larger maximum detection values, indicating its sensitivity to more extreme hailstorms with greater vertical development, while other algorithms (Zmix KuKa, Zmix Ku, H30AFL Ka) showed more extended distributions.
• The study processed 11,946 DPR swaths, resulting in a mean pass count of 737.73 per pixel (approximately 0.37 daily scans), ensuring statistical robustness for climatological patterns despite intermittent temporal sampling.

Contributions

• Provides the first continental-scale hail climatology for Europe (2014–2024) using homogeneous satellite radar data, addressing limitations of sparse and inhomogeneous terrestrial observations.
• Robustly validates documented hail patterns and provides new, detailed insights into continental and subregional hail hotspots and their seasonal evolution.
• Confirms the crucial role of major orographic barriers (Alps, Pyrenees, Apennines, Carpathians, and Dinaric Alps) in initiating and intensifying severe convection.
• Demonstrates the value of satellite radar (GPM-DPR) for studying extreme events, offering an independent perspective that avoids population density and observer network biases inherent in surface-based climatologies.

Funding

• Projects PID2022-138298OB-C21, PID2022-138298OB-C22, JCYL (LE035P24), PID2019-108470RB-C22, and PID2019-108470RB-C21, supported by MCIN/AEI/10.13039/501100011033.

Citation

@article{Ordaz2026climatology,
  author = {Ordaz, Laura Rivero and García-Ortega, Eduardo and Navarro, Andrés and Tapiador, Francisco J. and Sánchez, José Luis and Corbea-Pérez, Alejandro and Merino, Andrés},
  title = {A climatology of hail in Europe (2014–2024) based on GPM-DPR sensor data},
  journal = {Atmospheric Research},
  year = {2026},
  doi = {10.1016/j.atmosres.2026.108965},
  url = {https://doi.org/10.1016/j.atmosres.2026.108965}
}