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Long-term gust speed (<i>GS</i>) measurements were used to develop a winter storm atlas of the 98 most severe winter storms in Germany in the period 1981&#8722;2018 (GeWiSa). The 25 m &#215; 25 m storm-related <i>GS</i> fields were reconstructed in a two-step procedure: Firstly, the median gust speed (<inline-formula> <math display="inline"> <semantics> <mrow> <mover accent="true"> <mrow> <mi>G</mi> <mi>S</mi> </mrow> <mo stretchy="true">&#732;</mo> </mover> </mrow> </semantics> </math> </inline-formula>) 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 <i>GS</i> related to each winter storm to <inline-formula> <math display="inline"> <semantics> <mrow> <mover accent="true"> <mrow> <mi>G</mi> <mi>S</mi> </mrow> <mo stretchy="true">&#732;</mo> </mover> </mrow> </semantics> </math> </inline-formula>, which was defined as storm field factor (<i>STF</i>), was calculated and mapped by a thin plate spline interpolation (TPS). It was found that the mean study area-wide <i>GS</i> associated with the 2007 storm Kyrill is highest (29.7 m/s). In Southern Germany, the 1999 storm Lothar, with <i>STF</i> being up to 2.2, was the most extreme winter storm in terms of <i>STF</i> and <i>GS</i>. The results demonstrate that the variability of <i>STF</i> has a considerable impact on the simulated <i>GS</i> fields. Event-related model validation yielded a coefficient of determination (<i>R</i>²) of 0.786 for the test dataset. The developed <i>GS</i> 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.