Articles | Volume 23, issue 12
https://doi.org/10.5194/nhess-23-3651-2023
https://doi.org/10.5194/nhess-23-3651-2023
Research article
 | 
29 Nov 2023
Research article |  | 29 Nov 2023

Forecasting large hail and lightning using additive logistic regression models and the ECMWF reforecasts

Francesco Battaglioli, Pieter Groenemeijer, Ivan Tsonevsky, and Tomàš Púčik

Related authors

Invited perspectives: Thunderstorm Intensification from Mountains to Plains
Jannick Fischer, Pieter Groenemeijer, Alois Holzer, Monika Feldmann, Katharina Schröer, Francesco Battaglioli, Lisa Schielicke, Tomáš Púčik, Christoph Gatzen, Bogdan Antonescu, and the TIM Partners
EGUsphere, https://doi.org/10.5194/egusphere-2024-2798,https://doi.org/10.5194/egusphere-2024-2798, 2024
Short summary

Related subject area

Atmospheric, Meteorological and Climatological Hazards
Intense rains in Israel associated with the train effect
Baruch Ziv, Uri Dayan, Lidiya Shendrik, and Elyakom Vadislavsky
Nat. Hazards Earth Syst. Sci., 24, 3267–3277, https://doi.org/10.5194/nhess-24-3267-2024,https://doi.org/10.5194/nhess-24-3267-2024, 2024
Short summary
Convection-permitting climate model representation of severe convective wind gusts and future changes in southeastern Australia
Andrew Brown, Andrew Dowdy, and Todd P. Lane
Nat. Hazards Earth Syst. Sci., 24, 3225–3243, https://doi.org/10.5194/nhess-24-3225-2024,https://doi.org/10.5194/nhess-24-3225-2024, 2024
Short summary
On the potential of using smartphone sensors for wildfire hazard estimation through citizen science
Hofit Shachaf, Colin Price, Dorita Rostkier-Edelstein, and Cliff Mass
Nat. Hazards Earth Syst. Sci., 24, 3035–3047, https://doi.org/10.5194/nhess-24-3035-2024,https://doi.org/10.5194/nhess-24-3035-2024, 2024
Short summary
Global estimates of 100-year return values of daily precipitation from ensemble weather prediction data
Florian Ruff and Stephan Pfahl
Nat. Hazards Earth Syst. Sci., 24, 2939–2952, https://doi.org/10.5194/nhess-24-2939-2024,https://doi.org/10.5194/nhess-24-2939-2024, 2024
Short summary
Exploring the sensitivity of extreme event attribution of two recent extreme weather events in Sweden using long-running meteorological observations
Erik Holmgren and Erik Kjellström
Nat. Hazards Earth Syst. Sci., 24, 2875–2893, https://doi.org/10.5194/nhess-24-2875-2024,https://doi.org/10.5194/nhess-24-2875-2024, 2024
Short summary

Cited articles

Adams-Selin, R. and Ziegler, C. L.: Forecasting Hail Using a One-Dimensional Hail Growth Model within WRF, Mon. Weather Rev., 144, 4919–4939, https://doi.org/10.1175/MWR-D-16-0027.1, 2016. 
Allen, J., Giammanco, I., Kumjian, M., 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. 
Anderson, G. and Klugmann, D.: A European lightning density analysis using 5 years of ATDnet data, Nat. Hazards Earth Syst. Sci., 14, 815–829, https://doi.org/10.5194/nhess-14-815-2014, 2014. 
Bang, S. and Cecil, D.: Constructing a Multifrequency Passive Microwave Hail Retrieval and Climatology in the GPM Domain, J. Appl. Meteorol. Clim., 58, 1889–1904, https://doi.org/10.1175/JAMC-D-19-0042.1, 2019. 
Battaglioli, F., Groenemeijer, P., Púčik, T., Taszarek, M., Ulbrich, U., and Rust, H.: Modeled Multidecadal Trends of Lightning and (Very) Large Hail in Europe and North America (1950–2021), J. Appl. Meteorol. Clim., 62, 1627–1653, https://doi.org/10.1175/JAMC-D-22-0195.1, 2023. 
Download
Short summary
Probabilistic models for lightning and large hail were developed across Europe using lightning observations and hail reports. These models accurately predict the occurrence of lightning and large hail several days in advance. In addition, the hail model was shown to perform significantly better than the state-of-the-art forecasting methods. These results suggest that the models developed in this study may help improve forecasting of convective hazards and eventually limit the associated risks.
Altmetrics
Final-revised paper
Preprint