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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/npg-2019-64
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-2019-64
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 20 Jan 2020

Submitted as: research article | 20 Jan 2020

Review status
This preprint is currently under review for the journal NPG.

Statistical Postprocessing of Ensemble Forecasts for Severe Weather at Deutscher Wetterdienst

Reinhold Hess Reinhold Hess
  • Deutscher Wetterdienst

Abstract. Forecasts of the ensemble systems COSMO-D2-EPS and ECMWF-ENS are statistically optimised and calibrated by Ensemble-MOS with a focus on severe weather in order to support warning decision management at Deutscher Wetterdienst (DWD). Ensemble mean and spread are used as predictors for linear and logistic multiple regressions to correct for conditional biases. The predictands are derived from synoptic observations and include temperature, precipitation amounts, wind gusts and many more, and are statistically estimated in a comprehensive model output statistics (MOS) approach.

This paper gives an overview of DWD's postprocessing system called Ensemble-MOS together with its motivation and the design consequences for probabilistic forecasts of extreme events based on ensemble data. Long time series and collections of stations are used for significant training data that capture sufficient number of cases with observed events, as required for robust statistical modelling. Logistic regression is applied for threshold probabilities and details of its implementation including the selection of predictors with testing for significance are presented.

For probabilities of severe wind gusts global logistic parameterisations are developed that depend on local estimations of wind speed. In this way robust probability forecasts for extreme events are obtained while local characteristics are preserved.

Caveats of Ensemble-MOS, such as model changes and requirements for consistency, are addressed that are known from DWD's operational MOS systems.

Reinhold Hess

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Reinhold Hess

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Latest update: 23 Feb 2020
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Short summary
Forecasts of ensemble systems are statistically aligned to synoptic observations at DWD in order to provide support for warning decision management. Motivation and design consequences for extreme and rare meteorological events are presented. Especially for probabilities of severe wind gusts global logistic parameterisations are developed that generate robust statistical forecasts for extreme events, while local characteristics are preserved.
Forecasts of ensemble systems are statistically aligned to synoptic observations at DWD in order...
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