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Historical Winter Storm Atlas for Germany (GeWiSA)

Environmental Meteorology, Albert-Ludwigs-University of Freiburg, Werthmannstrasse 10, D-79085 Freiburg, Germany
Author to whom correspondence should be addressed.
Atmosphere 2019, 10(7), 387;
Received: 31 May 2019 / Revised: 28 June 2019 / Accepted: 8 July 2019 / Published: 11 July 2019
(This article belongs to the Section Climatology and Meteorology)
PDF [5735 KB, uploaded 11 July 2019]


Long-term gust speed (GS) measurements were used to develop a winter storm atlas of the 98 most severe winter storms in Germany in the period 1981–2018 (GeWiSa). The 25 m × 25 m storm-related GS fields were reconstructed in a two-step procedure: Firstly, the median gust speed ( G S ˜ ) of all winter storms was modeled by a least-squares boosting (LSBoost) approach. Orographic features and surface roughness were used as predictor variables. Secondly, the quotient of GS related to each winter storm to G S ˜ , which was defined as storm field factor (STF), was calculated and mapped by a thin plate spline interpolation (TPS). It was found that the mean study area-wide GS associated with the 2007 storm Kyrill is highest (29.7 m/s). In Southern Germany, the 1999 storm Lothar, with STF being up to 2.2, was the most extreme winter storm in terms of STF and GS. The results demonstrate that the variability of STF has a considerable impact on the simulated GS fields. Event-related model validation yielded a coefficient of determination (R2) of 0.786 for the test dataset. The developed GS fields can be used as input to storm damage models representing storm hazard. With the knowledge of the storm hazard, factors describing the vulnerability of storm exposed objects and structures can be better estimated, resulting in improved risk management. View Full-Text
Keywords: gust speed; roughness length; European Settlement Map; storm damage; digital elevation model gust speed; roughness length; European Settlement Map; storm damage; digital elevation model

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Jung, C.; Schindler, D. Historical Winter Storm Atlas for Germany (GeWiSA). Atmosphere 2019, 10, 387.

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