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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/gmd-2020-250
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-250
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model experiment description paper 16 Nov 2020

Submitted as: model experiment description paper | 16 Nov 2020

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This preprint is currently under review for the journal GMD.

Recalculation of error growth models’ parameters for the ECMWF forecast system

Hynek Bednář, Aleš Raidl, and Jiří Mikšovský Hynek Bednář et al.
  • Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, 180 00, Czech Republic

Abstract. This article provides a new estimate of error growth models’ parameters approximating predictability curves and their differentials, calculated from data of the ECMWF forecast system over the 1986 to 2011 period. Estimates of the largest Lyapunov exponent are also provided, along with model error and the limit value of the predictability curve. The proposed correction is based on the ability of the Lorenz's (2005) system to simulate predictability curve of the ECMWF forecasting system and on comparing the parameters estimated for both these systems, as well as on comparison with the largest Lyapunov exponent (λ = 0.35 day−1) and limit value of the predictability curve (E = 8.2) of the Lorenz's system. Parameters are calculated from the Quadratic model with and without model error, as well as by the Logarithmic and General models and by the hyperbolic tangent model. The average value of the largest Lyapunov exponent is estimated to be in the < 0.32; 0.41 > day−1 range for the ECMWF forecasting system, limit values of the predictability curves are estimated with lower theoretically derived values and new approach of calculation of model error based on comparison of models is presented.

Hynek Bednář et al.

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Hynek Bednář et al.

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Recalculation of error growth models’ parameters for the ECMWF forecast system Hynek Bednář, Aleš Raidl, and Jiří Mikšovský https://doi.org/10.17605/OSF.IO/CEK32

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Recalculation of error growth models’ parameters for the ECMWF forecast system Hynek Bednář, Aleš Raidl, and Jiří Mikšovský https://doi.org/10.17605/OSF.IO/CEK32

Hynek Bednář et al.

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Latest update: 01 Dec 2020
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Short summary
Forecast errors in numerical weather prediction systems grow in time. To quantify the impacts of this growth, parametric error growth models may be employed. This study recalculates and newly defines parameters for several statistic models approximating error growth in the ECMWF forecasting system. Accurate values of parameters are important because they are used to evaluate improvements of the forecasting systems or to estimate predictability.
Forecast errors in numerical weather prediction systems grow in time. To quantify the impacts of...
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