Assessing Physics Parameterizations Using Evolutionary Computation
Guerrero Calzas, Iciar (Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius)
Rossetto, Lorenzo (Mitiga Solutions S.L.)
Cortés Fité, Ana (Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius)
Hanzich, Mauricio (Mitiga Solutions S.L.)
Miró, Josep Ramon (Servei Meteorològic de Catalunya)

Imprint:	Springer Cham, 2025
Description:	15 pàg.
Abstract:	Hailstorms are intense, localized weather phenomena that can severely impact agriculture, infrastructure, and property, making precise forecasting essential for risk management. The Weather Research and Forecasting (WRF) model is widely used for numerical weather prediction, offering numerous physical parameterization options to represent atmospheric processes. However, due to the large number of possible configurations, identifying the most suitable configuration is a challenge. This research uses a genetic algorithm (GA) to systematically refine WRF physics schemes for hail prediction in Central Europe, specifically for the hail events of June 2022. Within this framework, WRF configurations are treated as individuals in a population that evolves through selection, crossover, and mutation over multiple iterations. Fitness is evaluated using the F2 score. This methodology allows to evaluate more than 2. 4 million possible setups improving the WRF model's capacity to accurately represent hailstorms. This strategy provides a robust framework for testing a wide range of setups, proving its value in refining parameterizations to better forecast impactful weather phenomena.
Grants:	Generalitat de Catalunya 2023DI00013 Agencia Estatal de Investigación PID2023-146193OB-I00 Agència de Gestió d'Ajuts Universitaris i de Recerca 2021/SGR-00574
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Language:	Anglès
Series:	Lecture Notes in Computer Science; 15904
Document:	Capítol de llibre ; recerca ; Versió acceptada per publicar
Subject:	Hail Modeling ; Genetic Algorithm ; Numerical Weather Prediction (NWP)
Published in:	Computational Science - ICCS 2025. 25th International Conference, Singapore, Singapore, July 7-9, 2025, Proceedings, Part II, 2025, p. 106-120, ISBN 978-3-031-97629-2

DOI: 10.1007/978-3-031-97629-2_8

Available from: 2026-07-31 Postprint

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