Sensitivity analysis of the physical parameterizations in the WRF model on the prediction accuracy of meteorological parameters

Alexander V. Starchenko; Lubov I. Kizhner; Artem I. Svarovsky; Sergey A. Prokhanov

doi:10.1117/12.2603387

15 December 2021 Sensitivity analysis of the physical parameterizations in the WRF model on the prediction accuracy of meteorological parameters

Alexander V. Starchenko, Lubov I. Kizhner, Artem I. Svarovsky, Sergey A. Prokhanov

Author Affiliations +

Proceedings Volume 11916, 27th International Symposium on Atmospheric and Ocean Optics, Atmospheric Physics; 119166C (2021) https://doi.org/10.1117/12.2603387
Event: 27th International Symposium on Atmospheric and Ocean Optics, Atmospheric Physics, 2021, Moscow, Russian Federation

Abstract

Computational experiments were carried out using the WRF model version 4.2. The influence of different sets of parameterizations on the results of calculating the surface values of air temperature, wind speed and direction is considered. A set of parameterizations providing the best accuracy of numerical prediction (with a resolution of 1 km) of local meteorological characteristics for the conditions of Western Siberia, is selected. It was found that the set of parameterizations affects the simulation quality, but it is not the main aspect in ensuring prediction accuracy. To test the WRF model, the observations obtained using meteorological instruments of the JUC Atmosphere of the V.E. Zuev Institution of Atmospheric Optics SB RAS, the airfield information and measurement system of the Tomsk Airport, and the Tomsk weather station were employed.

Citation Download Citation

Alexander V. Starchenko, Lubov I. Kizhner, Artem I. Svarovsky, and Sergey A. Prokhanov "Sensitivity analysis of the physical parameterizations in the WRF model on the prediction accuracy of meteorological parameters", Proc. SPIE 11916, 27th International Symposium on Atmospheric and Ocean Optics, Atmospheric Physics, 119166C (15 December 2021); https://doi.org/10.1117/12.2603387

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