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Advances in Geosciences An open-access journal for refereed proceedings and special publications
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Volume 10
Adv. Geosci., 10, 139–144, 2007
https://doi.org/10.5194/adgeo-10-139-2007
© Author(s) 2007. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.
Adv. Geosci., 10, 139–144, 2007
https://doi.org/10.5194/adgeo-10-139-2007
© Author(s) 2007. This work is licensed under
the Creative Commons Attribution-NonCommercial-ShareAlike 2.5 License.

  26 Apr 2007

26 Apr 2007

On evaluation of ensemble precipitation forecasts with observation-based ensembles

B. Ahrens1 and S. Jaun2 B. Ahrens and S. Jaun
  • 1Institute for Atmosphere and Environment, University of Frankfurt, Germany
  • 2Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland

Abstract. Spatial interpolation of precipitation data is uncertain. How important is this uncertainty and how can it be considered in evaluation of high-resolution probabilistic precipitation forecasts? These questions are discussed by experimental evaluation of the COSMO consortium's limited-area ensemble prediction system COSMO-LEPS. The applied performance measure is the often used Brier skill score (BSS). The observational references in the evaluation are (a) analyzed rain gauge data by ordinary Kriging and (b) ensembles of interpolated rain gauge data by stochastic simulation. This permits the consideration of either a deterministic reference (the event is observed or not with 100% certainty) or a probabilistic reference that makes allowance for uncertainties in spatial averaging. The evaluation experiments show that the evaluation uncertainties are substantial even for the large area (41 300 km2) of Switzerland with a mean rain gauge distance as good as 7 km: the one- to three-day precipitation forecasts have skill decreasing with forecast lead time but the one- and two-day forecast performances differ not significantly.

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