Estimation of Design Rainfall from Weather Radar Data – a Case Study for the Hannover Area

Abstract:

The estimation of design rainfall requires long-term precipitation observations in high temporal resolution. Those data are available only with poor spatial density, which usually entails regionalization for their practical application. An alternative would be to utilize the high spatial resolution of weather radar for the estimation of design rainfall. Meanwhile the observation length of many operational radar instruments extend over a time period of 10 years, which suggests to analyze their benefits for estimating design rainfall.

In this study, 13 years of observations from the Hannover radar station located in Northern Germany are analyzed together with about 50 recording rain gauges in the observation range of the regarding their reproduction of extreme rainfall statistics. Pure radar data and radar-station merging products are analyzed for rainfall durations from 5 minutes to 6 hours and return periods from 1 year to 30 years. Partial duration series of the extremes were derived from the data and probability distributions fitted. The performance of the design rainfall estimates is assessed based on cross validations for observed station points, which are used as reference. For design rainfall estimation using the pure radar data, the pixel value at station location is taken; for the merging products, spatial interpolation methods are applied.

The results show, that pure radar data are not suitable for the estimation of extremes. They usually lead to an overestimation compared to the observations, which is opposite to the usual behavior of radar rainfall for average intensities. However, some of the merging products between radar and station data can provide a better estimate for extremes as the station data alone, especially for the longer durations. Main condition for a good performance is that the radar data are adjusted to daily observed rainfall sums prior to their application.