A Simplified Extended Kalman Filter assimilation of soil moisture for the SL-AV global medium-range forecast model
- Authors: Makhnorylova S.V.1,2, Tolstykh M.A.2,3
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Affiliations:
- Siberian Regional Research Hydrometeorological Institute
- Hydrometeorological Research Center of the Russian Federation
- Institute of Numerical Mathematics
- Issue: Vol 42, No 6 (2017)
- Pages: 394-402
- Section: Article
- URL: https://journals.rcsi.science/1068-3739/article/view/230190
- DOI: https://doi.org/10.3103/S106837391706005X
- ID: 230190
Cite item
Abstract
The implementation of the Simplified Extended Kalman Filter (SEKF) for the deep soil moisture initialization in the SL-AV global atmosphere model is described. Special attention is paid to the calculation of the observation operator and analysis increment. SL-AV screen-level parameters forecasts are estimated with SEKF and optimal interpolation initialization methods. It is demonstrated that the implementation of the assimilation algorithm improves the model forecast quality for screen-level temperature and relative humidity.
About the authors
S. V. Makhnorylova
Siberian Regional Research Hydrometeorological Institute; Hydrometeorological Research Center of the Russian Federation
Author for correspondence.
Email: makhnorylova@gmail.com
Russian Federation, ul. Sovetskaya 30, Novosibirsk, 630099; Bolshoi Predtechenskii per. 11-13, Moscow, 123242
M. A. Tolstykh
Hydrometeorological Research Center of the Russian Federation; Institute of Numerical Mathematics
Email: makhnorylova@gmail.com
Russian Federation, Bolshoi Predtechenskii per. 11-13, Moscow, 123242; ul. Gubkina 8, Moscow, 119333