Articles | Volume 4, issue 4
https://doi.org/10.5194/wcd-4-981-2023
https://doi.org/10.5194/wcd-4-981-2023
Research article
 | 
20 Nov 2023
Research article |  | 20 Nov 2023

Identification of high-wind features within extratropical cyclones using a probabilistic random forest – Part 2: Climatology over Europe

Lea Eisenstein, Benedikt Schulz, Joaquim G. Pinto, and Peter Knippertz

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Cited articles

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Born, K., Ludwig, P., and Pinto, J. G.: Wind gust estimation for Mid-European winter storms: Towards a probabilistic view, Tellus A, 64, 17471, https://doi.org/10.3402/tellusa.v64i0.17471, 2012. a, b
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Mesoscale high-wind features within extratropical cyclones can cause immense damage. In Part 1 of this work, we introduced RAMEFI (RAndom-forest-based MEsoscale wind Feature Identification), an objective, flexible identification tool for these wind features based on a probabilistic random forest. Here, we use RAMEFI to compile a climatology of the features over 19 extended winter seasons over western and central Europe, focusing on relative occurrence, affected areas and further characteristics.