Articles | Volume 24, issue 3
https://doi.org/10.5194/nhess-24-847-2024
https://doi.org/10.5194/nhess-24-847-2024
Research article
 | 
11 Mar 2024
Research article |  | 11 Mar 2024

An open-source radar-based hail damage model for buildings and cars

Timo Schmid, Raphael Portmann, Leonie Villiger, Katharina Schröer, and David N. Bresch

Related authors

Modelling crop hail damage footprints with single-polarization radar: the roles of spatial resolution, hail intensity, and cropland density
Raphael Portmann, Timo Schmid, Leonie Villiger, David N. Bresch, and Pierluigi Calanca
Nat. Hazards Earth Syst. Sci., 24, 2541–2558, https://doi.org/10.5194/nhess-24-2541-2024,https://doi.org/10.5194/nhess-24-2541-2024, 2024
Short summary
Atmospheric drivers of melt-related ice speed-up events on the Russell Glacier in southwest Greenland
Timo Schmid, Valentina Radić, Andrew Tedstone, James M. Lea, Stephen Brough, and Mauro Hermann
The Cryosphere, 17, 3933–3954, https://doi.org/10.5194/tc-17-3933-2023,https://doi.org/10.5194/tc-17-3933-2023, 2023
Short summary

Related subject area

Atmospheric, Meteorological and Climatological Hazards
Verifying the relationships among the variabilities of summer rainfall extremes over Japan in the d4PDF climate ensemble, Pacific sea surface temperature, and monsoon activity
Shao-Yi Lee, Sicheng He, and Tetsuya Takemi
Nat. Hazards Earth Syst. Sci., 25, 2225–2253, https://doi.org/10.5194/nhess-25-2225-2025,https://doi.org/10.5194/nhess-25-2225-2025, 2025
Short summary
Tree fall along railway lines: modelling the impact of wind and other meteorological factors
Rike Lorenz, Nico Becker, Barry Gardiner, Uwe Ulbrich, Marc Hanewinkel, and Benjamin Schmitz
Nat. Hazards Earth Syst. Sci., 25, 2179–2196, https://doi.org/10.5194/nhess-25-2179-2025,https://doi.org/10.5194/nhess-25-2179-2025, 2025
Short summary
The probabilistic skill of extended-range heat wave forecasts over Europe
Natalia Korhonen, Otto Hyvärinen, Virpi Kollanus, Timo Lanki, Juha Jokisalo, Risto Kosonen, David S. Richardson, and Kirsti Jylhä
Nat. Hazards Earth Syst. Sci., 25, 1865–1879, https://doi.org/10.5194/nhess-25-1865-2025,https://doi.org/10.5194/nhess-25-1865-2025, 2025
Short summary
An appraisal of the value of simulated weather data for quantifying coastal flood hazard in the Netherlands
Cees de Valk and Henk van den Brink
Nat. Hazards Earth Syst. Sci., 25, 1769–1788, https://doi.org/10.5194/nhess-25-1769-2025,https://doi.org/10.5194/nhess-25-1769-2025, 2025
Short summary
Insights into thunderstorm characteristics from geostationary lightning jump and dive observations
Felix Erdmann and Dieter Roel Poelman
Nat. Hazards Earth Syst. Sci., 25, 1751–1768, https://doi.org/10.5194/nhess-25-1751-2025,https://doi.org/10.5194/nhess-25-1751-2025, 2025
Short summary

Cited articles

Ackermann, L., Soderholm, J., Protat, A., Whitley, R., Ye, L., and Ridder, N.: Radar and environment-based hail damage estimates using machine learning, Atmos. Meas. Tech., 17, 407–422, https://doi.org/10.5194/amt-17-407-2024, 2024. a
Allen, J. T., Giammanco, I. M., Kumjian, M. R., Jurgen Punge, H., Zhang, Q., Groenemeijer, P., Kunz, M., and Ortega, K.: Understanding Hail in the Earth System, Rev. Geophys., 58, e2019RG000665, https://doi.org/10.1029/2019RG000665, 2020. a
Amburn, S. A. and Wolf, P. L.: VIL Density as a Hail Indicator, Weather Forecast., 12, 473–478, https://doi.org/10.1175/1520-0434(1997)012<0473:VDAAHI>2.0.CO;2, 1997. a
Atlas, D., Harper, W. G., Ludlam, F. H., and MacKlin, W. C.: Radar scatter by large hail, Q. J. Roy. Meteor. Soc., 86, 468–482, https://doi.org/10.1002/qj.49708637004, 1960. a
Auer, A. H.: Hail Recognition through the Combined Use of Radar Reflectivity and Cloud-Top Temperatures, Mon. Weather Rev., 122, 2218–2221, https://doi.org/10.1175/1520-0493(1994)122<2218:HRTTCU>2.0.CO;2, 1994. a
Download
Short summary
Hailstorms cause severe damage to buildings and cars, which motivates a detailed risk assessment. Here, we present a new open-source hail damage model based on radar data in Switzerland. The model successfully estimates the correct order of magnitude of car and building damages for most large hail events over 20 years. However, large uncertainty remains in the geographical distribution of modelled damages, which can be improved for individual events by using crowdsourced hail reports.
Share
Altmetrics
Final-revised paper
Preprint