Academic Journal

A local observation data assimilation in mesoscale numerical weather prediction models

Bibliographic Details
Title: A local observation data assimilation in mesoscale numerical weather prediction models
Authors: Starchenko, Alexander V., Tolstykh, Mickhail A., Mizyak, Vasiliy G., Svarovsky, Artem I., Prokhanov, Sergey A.
Source: Proceedings of SPIE. 2022. Vol. 12341 : 28th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics, 2022, Tomsk, Russia. P. 123416N-1-123416N-10
Publisher Information: SPIE, 2022.
Publication Year: 2022
Subject Terms: реальные локальные наблюдения за погодой, 13. Climate action, ассимиляция данных, объективный анализ, численный прогноз погоды, 0207 environmental engineering, мезомасштабные модели, прогноз тумана, 02 engineering and technology, Западная Сибирь, 01 natural sciences, оптимальная интерполяция, 0105 earth and related environmental sciences
Description: 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.
Document Type: Article
DOI: 10.1117/12.2644943
Access URL: https://vital.lib.tsu.ru/vital/access/manager/Repository/koha:001008847
Accession Number: edsair.doi.dedup.....32c7b46a0eaa8ac932b53f1cbab67b31
Database: OpenAIRE
Description
DOI:10.1117/12.2644943