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Peer-reviewedCC BY 4.0Natural Hazards and Earth System Sciences

RHITA: a web tool for real-time detection of extreme weather events

  • Greta Cazzaniga
  • Anastasia Akakpo-Numado
  • Patrick Brockmann
  • Adrien Burq
  • Mathieu Vrac
  • Davide Faranda1,2,3
  1. 1Laboratoire des Sciences du Climat et de l'Environnement (Gif-sur-Yvette, France)
  2. 2Laboratoire de Météorologie Dynamique (Palaiseau, France)
  3. 3London Mathematical Laboratory (London, United Kingdom)
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Abstract

Extreme weather hazards are increasing and stakeholders need rapid, transparent information during unfolding events. We present RHITA (Real-time Hazard Identification and Tracking Algorithm), an open-source framework and web tool for near real-time detection and tracking of weather-related hazards over Europe. RHITA identifies grid cells exceeding local quantile thresholds, groups them into spatial clusters, and links clusters through time to reconstruct three-dimensional events in longitude, latitude, and time. For each event, RHITA provides intensity, extent and duration metrics and estimates rarity through return periods derived from a long historical record. RHITA is operated with ECMWF open forecasts for daily monitoring and ERA5 reanalysis for a consistent historical archive from 1950 to 2024. We target four hazards: heatwaves, cold spells, heavy precipitation and strong winds. Key spatial and temporal parameters are optimized against EM-DAT disaster records (2000 to 2023). Applying RHITA to ERA5 yields a European climatology of hazard events and reveals robust increases in heatwave frequency, intensity and affected area, a decline in cold spell frequency, and more heterogeneous signals for heavy precipitation and strong winds at the continental scale. RHITA provides open access data and an interactive interface to support rapid hazard characterization, event contextualization and downstream risk analysis.

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Cite

BibTeXRIS
BibTeX
@article{cazzaniga2026rhita,
  title = {{RHITA: a web tool for real-time detection of extreme weather events}},
  author = {Greta Cazzaniga and Anastasia Akakpo-Numado and Patrick Brockmann and Adrien Burq and Mathieu Vrac and Davide Faranda},
  journal = {Natural Hazards and Earth System Sciences},
  year = {2026},
  month = oct,
  doi = {10.5194/nhess-26-4741-2026},
  url = {https://hal.science/hal-05563119v2},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - RHITA: a web tool for real-time detection of extreme weather events
AU  - Greta Cazzaniga
AU  - Anastasia Akakpo-Numado
AU  - Patrick Brockmann
AU  - Adrien Burq
AU  - Mathieu Vrac
AU  - Davide Faranda
PY  - 2026
DA  - 2026/10/02
JO  - Natural Hazards and Earth System Sciences
DO  - 10.5194/nhess-26-4741-2026
UR  - https://hal.science/hal-05563119v2
AB  - Extreme weather hazards are increasing and stakeholders need rapid, transparent information during unfolding events. We present RHITA (Real-time Hazard Identification and Tracking Algorithm), an open-source framework and web tool for near real-time detection and tracking of weather-related hazards over Europe. RHITA identifies grid cells exceeding local quantile thresholds, groups them into spatial clusters, and links clusters through time to reconstruct three-dimensional events in longitude, latitude, and time. For each event, RHITA provides intensity, extent and duration metrics and estimates rarity through return periods derived from a long historical record. RHITA is operated with ECMWF open forecasts for daily monitoring and ERA5 reanalysis for a consistent historical archive from 1950 to 2024. We target four hazards: heatwaves, cold spells, heavy precipitation and strong winds. Key spatial and temporal parameters are optimized against EM-DAT disaster records (2000 to 2023). Applying RHITA to ERA5 yields a European climatology of hazard events and reveals robust increases in heatwave frequency, intensity and affected area, a decline in cold spell frequency, and more heterogeneous signals for heavy precipitation and strong winds at the continental scale. RHITA provides open access data and an interactive interface to support rapid hazard characterization, event contextualization and downstream risk analysis.
SN  - 1561-8633
SN  - 1684-9981
ER  -