Investigating the Spatial Extent of Extreme Precipitation

Investigation of precipitation extremes is traditionally based on point observations. Such rain gauges networks  often have an insufficient network density to  correctly capture the spatial extent of extreme events. An alternative is to use weather radar data which provide a spatially distributed rainfall field but these observations are prone to errors. To reduce the errors in the radar observations, a copula-based merging procedure is applied to combine radar and station observations with high temporal resolution. From this product, the spatial extent of extremes in investigated. This is done by extracting the connected rainfall areas from every rainfall field for several precipitation thresholds and temporal aggregations. The location, size, station data whithin these areas, areal mean precipitation value, and the areal maximum precipitation value are gathered and investigated.

This procedure was applied to the area covered by the German Weather Service (DWD) radar in Hannover with a 5 minutes temporal resolution and for the period 2000-2019. The first results of this investigation shows that station observations underestimate the true areal maxima in most of the cases. Moreover, the connected areas are categorized based on their size and the areal mean precipitation values are compared. It was found that with increasing area size the corresponding areal mean increased. This was observed until a certain area size is reached after which the areal mean almost stabilizes. A clustering of the continuous areas revealed that the occurrence of the areas is independent of the location and that extreme observation can occur anywhere within the study region.