Paper
7 December 2022 A local observation data assimilation in mesoscale numerical weather prediction models
Alexander V. Starchenko, Mickhail A. Tolstykh, Vasiliy G. Mizyak, Artem I. Svarovsky, Sergey A. Prokhanov
Author Affiliations +
Proceedings Volume 12341, 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics; 123416N (2022) https://doi.org/10.1117/12.2644943
Event: 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 2022, Tomsk, Russia
Abstract
This paper presents the results of applying an optimal interpolation method to assimilate meteorological observation data obtained by using ground-based weather stations and temperature profilers of the Atmosphere JUC (Joint Use Center) at the Institute of Atmospheric Optics SB RAS to calculate a numerical prediction with high horizontal resolution (1km) of the parameters of the atmospheric boundary layer for the next 24 hours.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexander V. Starchenko, Mickhail A. Tolstykh, Vasiliy G. Mizyak, Artem I. Svarovsky, and Sergey A. Prokhanov "A local observation data assimilation in mesoscale numerical weather prediction models", Proc. SPIE 12341, 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 123416N (7 December 2022); https://doi.org/10.1117/12.2644943
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KEYWORDS
Data modeling

Atmospheric modeling

Environmental sensing

Visibility

Fiber optic gyroscopes

Temperature metrology

Visibility through fog

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