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Discussion papers | Copyright
https://doi.org/10.5194/hess-2018-147
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 16 Apr 2018

Research article | 16 Apr 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Flood-Related Extreme Precipitation in Southwestern Germany: Development of a Two-Dimensional Stochastic Precipitation Model

Florian Ehmele1 and Michael Kunz1,2 Florian Ehmele and Michael Kunz
  • 1Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany
  • 2Center for Disaster Management and Risk Reduction Technology (CEDIM), KIT – Karlsruhe, Germany

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.

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Florian Ehmele and Michael Kunz
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Florian Ehmele and Michael Kunz
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Latest update: 19 Jul 2018
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Short summary
The risk estimation of precipitation events with high recurrence periods is difficult due to the limited time scale with meteorological observations and homogeneous distribution of rain gauges, especially in mountainous terrain. In this study a spatially highly resolved analytical model, designed for stochastic simulations of flood-related precipitation, is developed and applied to an investigation area in Germany but transferable to other areas. High conformity with observations are found.
The risk estimation of precipitation events with high recurrence periods is difficult due to the...
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