Articles | Volume 14, issue 10
https://doi.org/10.5194/gmd-14-6495-2021
https://doi.org/10.5194/gmd-14-6495-2021
Methods for assessment of models
 | 
27 Oct 2021
Methods for assessment of models |  | 27 Oct 2021

Object-based analysis of simulated thunderstorms in Switzerland: application and validation of automated thunderstorm tracking with simulation data

Timothy H. Raupach, Andrey Martynov, Luca Nisi, Alessandro Hering, Yannick Barton, and Olivia Martius

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Cited articles

Adams-Selin, R. D. 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. a, b
Allen, J. T.: Climate change and severe thunderstorms, in: Oxford Research Encyclopedia of Climate Science, Oxford University Press, https://doi.org/10.1093/acrefore/9780190228620.013.62, 2018. a, b
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Barton, Y., Sideris, I. V., Raupach, T. H., Gabella, M., Germann, U., and Martius, O.: A multi-year assessment of sub-hourly gridded precipitation for Switzerland based on a blended radar – Rain-gauge dataset, Int. J. Climatol., 40, 5208–5222, https://doi.org/10.1002/joc.6514, 2020. a
Brimelow, J. C., Reuter, G. W., and Poolman, E. R.: Modeling Maximum Hail Size in Alberta Thunderstorms, Weather Forecast., 17, 1048–1062, https://doi.org/10.1175/1520-0434(2002)017<1048:MMHSIA>2.0.CO;2, 2002. a
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Short summary
When simulated thunderstorms are compared to observations or other simulations, a match between overall storm properties is often more important than exact matches to individual storms. We tested a comparison method that uses a thunderstorm tracking algorithm to characterise simulated storms. For May 2018 in Switzerland, the method produced reasonable matches to independent observations for most storm properties, showing its feasibility for summarising simulated storms over mountainous terrain.
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