Assimilation of Screen-level Observations for Soil Moisture Analysis in the INM RAS-MSU Multilayer Soil Model Included in the SL-AV Global Atmospheric Modeling System

S. V. Travovaa, *, and M. A. Tolstykha, b

aHydrometeorological Research Center of the Russian Federation, Moscow, 123376 Russia

bMarchuk Institute of Numerical Mathematics, Russian Academy of Sciences, Moscow, 119333 Russia

email: *maknorylova@gmail.com

Received 25 March, 2022

Abstract— The implementation of the soil moisture analysis algorithm based on screen-level observations of air temperature and relative humidity for the INM RAS-MSU multilayer active soil layer model is presented. This soil model is a part of the global atmospheric model SL-AV. Methodical experiments on tuning of the simplified extended Kalman filter algorithm for considered atmospheric modeling system are carried out. It is found that the use of soil moisture analysis as initial data allows increasing the accuracy of short- and medium-range forecasts for screen-level temperature and relative humidity during summer season at the part of Asia, the European part of Russia, and the southeastern part of North America. The recommendations obtained in this work can be used for tuning the simplified extended Kalman filter algorithm to prepare initial data for long-range weather forecasts.

Keywords numerical weather prediction, global general atmospheric circulation model, soil moisture, soil moisture analysis, simplified extended Kalman filter, extended Kalman filter, simplified variational analysis of soil moisture, soil model

DOI: 10.3103/S1068373922080015