Statistical Analysis of Space-times Dynamics of Extreme Precipitation
- Institute for Hydrology and Water Resources Management, Leibniz Universität Hannover, Hanover, Germany
Precipitation extremes are space-time phenomena and traditionally the statistical analyses on such occurrences have treated them merely as point events. Many of the consequences of such events like floods are related to the water volume, hence the spatial aspect of them cannot be neglected. This work aims to bring the areal aspect of the extreme rainfall into play by introducing the area into the Extreme Value Analysis (EVA) and providing Area-Depth-Duration-Frequency (ADDF) curves. For this purpose, different spatial rainfall products have been used and compared with each other. Processed raw radar data, a product of conditional merging of the radar and station data as well as the RADKLIM data (a product of the German Weather Service designed for climate research) have been used for the EVA. Unexpected patterns have been observed in the ADDF curves based on the processed radar data which were not in agreement with the assumptions of the classical approach of areal reduction factor. Usually, it is assumed that areal precipitation extremes increase with decreasing area, so in practice reduction factors are used to estimate areal precipitation extreme values from point observations. This behavior was observed as expected mostly for durations shorter than 2 hours in all the study locations whereas the opposite was present for longer durations, where the precipitation is increasing with increasing area, so that the ADDF curves, representing different areas, show crossings at these durations. Different hypotheses about the reason for the crossings like seasonality and spatial non-stationarity have been tested and did not explain the crossings. On the other hand, the ADDF curves of the merged rainfall product hardly showed such patterns and followed the classical assumptions. Therefore, the appearance of such crossings in the ADDF curves of a spatial rain product might be an indicator of artifacts in the radar rainfall product. It has to be investigated in further tests if these results hold and if these crossings could be used as an indicator for unplausible radar data.
How to cite: Goshtsasbpour, G., Haberlandt, U., El Hachem, A., Seidel, J., and Bárdossy, A.: Statistical Analysis of Space-times Dynamics of Extreme Precipitation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2738, https://doi.org/10.5194/egusphere-egu22-2738, 2022.