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. Erosive rainfall varies pronouncedly in time and space.Severe events are often restricted to a few square kilometers. Radar raindata with high spatiotemporal resolution enable this pattern of erosivityto be portrayed with high detail. We used radar data with a spatialresolution of 1 km 2 over 452 503 km 2 to derivea new erosivity map for Germany and to analyze the seasonal distribution oferosivity. The expected long-term regional pattern was extracted from thescattered pattern of events by several steps of smoothing. This includedaveraging erosivity from 2001 to 2017 and smoothing in time and space. Thepattern of the resulting map was predominantly shaped by orography. Itgenerally agrees well with the erosivity map currently used in Germany(Sauerborn map), which is based on regressions using rain gauge data(mainly from the 1960s to 1980s). In some regions the patterns of both mapsdeviate because the regressions of the Sauerborn map were weak. Mostimportantly, the new map shows that erosivity is about 66 % larger thanin the Sauerborn map. This increase in erosivity was confirmed by long-termdata from rain gauge stations that were used for the Sauerborn map and whichare still in operation. The change was thus not caused by using a differentmethodology but by climate change since the 1970s. Furthermore, the seasonaldistribution of erosivity shows a slight shift towards the winter periodwhen soil cover by plants is usually poor. This shift in addition to theincrease in erosivity may have caused an increase in erosion for many crops.For example, predicted soil erosion for winter wheat is now about 4 timeslarger than in the 1970s. These highly resolved topical erosivity data willthus have definite consequences for agricultural advisory services,landscape planning and even political decisions.

Rain erosivity map for Germany derived from contiguous radar rain data