Reliable forecasts of heavy precipitation are one of the most difficult challenges in weather forecasting. Highest precipitation rates of convective events usually realise more likely in the surrounding of rain gauges rather than exactly above their small funnels and are therefore not always detected by this observation system. Precipitation rates of more than 15 mm per hour are captured only about once a year at each rain gauge within Germany and more extreme events are even less frequent. Statistical forecasts of these point observations often underestimate maximum rain rates and result in low probabilities for the occurrence of heavy precipitation at a given location.
The spatial coverage of DWD’s radar network allows to detect local precipitation events in the vicinity of synoptic stations and increases representativity and predictive skill of statistical forecasts of heavy convection. The suggested approach derives spatial 95%-quantiles in circular surroundings of 40 km radius as an innovative forecast product in order to support forecasters to rate upcoming heavy precipative events. 95%-quantiles of rain gauge adjusted radar precipitation are chosen in order to estimate the maximum precipitation amount in the circular surroundings, whilst they are robust against spurious spikes in the radar data.
For statistical training several years of data are used in a model output statistics (MOS) approach that is based on numerical ensemble forecasts of the COSMO-DE/2-EPS of DWD. Resulting statistical forecasts are presented for different relevant precipitation scenarios. Probabilities for heavy precipitation rates show enhanced signals for upcoming convective and also stratiform events compared to corresponding statistical forecasts based on conventional synoptic observations. Verifications of raw COSMO-DE/2-EPS forecasts are likewise included.
Main focus, however, are the relevance and acceptance of the presented new radar product for forecasters and the public with regard to weather warnings of heavy precipitation.
How to cite: Hess, R.: A radar based statistical forecast product for heavy precipitation, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-705, https://doi.org/10.5194/ems2022-705, 2022.