Determination of Precipitation Return Values in Complex Terrain and Their Evaluation

Barbara Früh Institute for Meteorology and Climate Research, KIT Karlsruhe, Karlsruhe, Germany

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Hendrik Feldmann Institute for Meteorology and Climate Research, KIT Karlsruhe, Karlsruhe, Germany

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Hans-Jürgen Panitz Institute for Meteorology and Climate Research, KIT Karlsruhe, Karlsruhe, Germany

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Gerd Schädler Institute for Meteorology and Climate Research, KIT Karlsruhe, Karlsruhe, Germany

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Daniela Jacob Max Planck Institute for Meteorology, Hamburg, Germany

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Philip Lorenz Max Planck Institute for Meteorology, Hamburg, Germany

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Klaus Keuler Department of Environmental Meteorology, Brandenburg University of Technology, Cottbus, Brandenburg, Germany

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Abstract

To determine return values at various return periods for extreme daily precipitation events over complex orography, an appropriate threshold value and distribution function are required. The return values are calculated using the peak-over-threshold approach in which only a reduced sample of precipitation events exceeding a predefined threshold is analyzed. To fit the distribution function to the sample, the L-moment method is used. It is found that the deviation between the fitted return values and the plotting positions of the ranked precipitation events is smaller for the kappa distribution than for the generalized Pareto distribution.

As a second focus, the ability of regional climate models to realistically simulate extreme daily precipitation events is assessed. For this purpose the return values are derived using precipitation events exceeding the 90th percentile of the precipitation time series and a fit of a kappa distribution. The results of climate simulations with two different regional climate models are analyzed for the 30-yr period 1971–2000: the so-called consortium runs performed with the climate version of the Lokal Modell (referred to as the CLM-CR) at 18-km resolution and the Regional Model (REMO)–Umweltbundesamt (UBA) simulations at 10-km resolution. It was found that generally the return values are overestimated by both models. Averaged across the region the overestimation is higher for REMO–UBA compared to CLM-CR.

* Current affiliation: Deutscher Wetterdienst, Offenbach am Main, Germany

Corresponding author address: Barbara Früh, Deutscher Wetterdienst, Frankfurter Str. 135, D-63067 Offenbach am Main, Germany. Email: barbara.frueh@dwd.de

Abstract

To determine return values at various return periods for extreme daily precipitation events over complex orography, an appropriate threshold value and distribution function are required. The return values are calculated using the peak-over-threshold approach in which only a reduced sample of precipitation events exceeding a predefined threshold is analyzed. To fit the distribution function to the sample, the L-moment method is used. It is found that the deviation between the fitted return values and the plotting positions of the ranked precipitation events is smaller for the kappa distribution than for the generalized Pareto distribution.

As a second focus, the ability of regional climate models to realistically simulate extreme daily precipitation events is assessed. For this purpose the return values are derived using precipitation events exceeding the 90th percentile of the precipitation time series and a fit of a kappa distribution. The results of climate simulations with two different regional climate models are analyzed for the 30-yr period 1971–2000: the so-called consortium runs performed with the climate version of the Lokal Modell (referred to as the CLM-CR) at 18-km resolution and the Regional Model (REMO)–Umweltbundesamt (UBA) simulations at 10-km resolution. It was found that generally the return values are overestimated by both models. Averaged across the region the overestimation is higher for REMO–UBA compared to CLM-CR.

* Current affiliation: Deutscher Wetterdienst, Offenbach am Main, Germany

Corresponding author address: Barbara Früh, Deutscher Wetterdienst, Frankfurter Str. 135, D-63067 Offenbach am Main, Germany. Email: barbara.frueh@dwd.de

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