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Stochastic perturbation of tendencies and parameters of parameterizations in the global ensemble prediction system based on the SL-AV model

  • Kseniya A. Alipova EMAIL logo , Gordey S. Goyman , Mikhail A. Tolstykh , Vasiliy G. Mizyak and Vladimir S. Rogutov
Published/Copyright: December 4, 2022

Abstract

Algorithms for stochastic perturbation of parameters and tendencies of physical parameterizations for subgrid-scale processes are implemented into the ensemble prediction system. This system is based on the global semi-Lagrangian atmospheric model SL-AV with the resolution of 0.9 × 0.72 degrees in longitude and latitude, respectively, 96 vertical levels, and our implementation of the Local Ensemble Tranform Kalman Filter (LETKF). The use of stochastically perturbed parameterizations allows to generate ensembles with a significantly larger spread compared to one obtained with the method of static parameter perturbation. An improvement in the probabilistic estimates of the ensemble forecast for different seasons is shown.

MSC 2010: 86-10; 86A10

Funding statement: The development of the generator for stochastic perturbations (Section 2) was carried out at the INM RAS with the support of the Russian Science Foundation grant No. 21-71-30023. The rest of the study was carried out at the Hydrometeorological Center of Russia with the support of the Russian Science Foundation grant No. 21-17-00254.

Acknowledgment

The authors are grateful to Rostislav Yu. Fadeev for discussing the results.

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Received: 2022-08-12
Accepted: 2022-10-03
Published Online: 2022-12-04
Published in Print: 2022-12-16

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