A simple model for predicting the statistics of spatiotemporal extremes of sub-daily precipitation

Cees de Valk, Aart Overeem

For a single site (of a rain gauge, say), the statistics of extreme precipitation are conveniently summarized by depth-duration-frequency (DDF) curves. Considering a spatial domain of some extent, one may ask: how often does it happen that the precipitation depth accumulated over 10 min exceeds 60 mm somewhere on this domain? Naturally, this frequency is higher than the frequency of exceedance of the same depth at a site; it depends on the size and shape of the domain and on the spatial dependence of extreme precipitation. In the present study, statistics of this spatial dependence are estimated from 11 years of gauge-adjusted radar-based precipitation data collected over the Netherlands, assuming spatial homogeneity. These statistics are the values of the extremal coefficient function (ECF) for selected spatial domains. From these values, a simple model is derived for predicting return periods or return values of the highest precipitation depth within an arbitrary spatial domain, based on a given DDF relation. In the model, the footprint of an individual downpour over its lifetime is simplified to a rectangular strip of fixed size ranging from 1.7 km x 12 km for a duration of 10 min to 5.1 km  x 21 km for a duration of 12 h. Confidence intervals of the predictions are estimated by bootstrapping. The model is checked for fitness for its application to the design and maintenance of the drainage of highways, and the scope for further improvement is discussed.

Bibliografische gegevens

Cees de Valk, Aart Overeem. A simple model for predicting the statistics of spatiotemporal extremes of sub-daily precipitation
Journal: Weather and Climate Extremes, Volume: 36, Year: 2022, First page: 1, Last page: 12, doi: 10.1016/j.wace.2022.100424