Ehmele, F. and Kunz, M., 2018: Flood-Related Extreme Precipitation in Southwestern Germany: Development of a Two-Dimensionla Stochastic Precipitation Model. Hydrol. Earth. Syst. Sci. Discuss., doi:10.5194/hess-2018-147.
Abstract. Various application fields, such as insurance industry risk assessments for the design of flood protection systems, require reliable precipitation statistics in high spatial resolution, including estimates for events with high return periods. Observations from point stations, however, lack of spatial representativeness, especially over complex terrain, and do not reliably represent the heavy tail of the distribution function. This paper presents a new method for stochastically simulating precipitation fields based on a linear theory of orographic precipitation and additional functions that consider synoptically driven rainfall and embedded convection in a simplified way. The model is initialized by various statistical distribution functions describing prevailing atmospheric conditions, such as wind vector, moisture content, or stability, estimated from radiosonde observations for a limited sample of the 200 strongest rainfall events observed.
The model is applied for the stochastic simulation of heavy rainfall over the complex terrain of Southwest Germany. It is shown that the model, despite its simplicity, yields reliable precipitation fields. Differences between observed and simulated rainfall statistics are small, being in the order of only ±10 % for return periods of up to 1000 years.