Identification of Wind Gusts during a Squall from the DMRL-C Network and Numerical Modeling Data

The study considers experimental methods for identifying squalls in three intensity gradations according to the DMRL-C network data and refining the speed of gusts during a squall using numerical modeling. Particular attention is paid to the identification of severe squalls. The series of severe squalls on July 29, 2023 in the Middle Volga region is analyzed. The results of the verification of squalls using observational data from weather stations and the data on wind gust velocities recorded by automatic weather stations are presented.

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Publication Details

Journal
Russian Meteorology and Hydrology
Published
2025-11-01
DOI
https://doi.org/10.3103/s1068373925130060
Primary Topic
Ocean Waves and Remote Sensing
Type
article
Field-Weighted Citation Impact
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article

Identification of Wind Gusts during a Squall from the DMRL-C Network and Numerical Modeling Data

V. M. Bukharov, A. A. Alekseeva
Russian Meteorology and Hydrology
Ocean Waves and Remote Sensing
article

Identification of Wind Gusts during a Squall from the DMRL-C Network and Numerical Modeling Data

V. M. Bukharov, A. A. Alekseeva
article en

Abstract

The study considers experimental methods for identifying squalls in three intensity gradations according to the DMRL-C network data and refining the speed of gusts during a squall using numerical modeling. Particular attention is paid to the identification of severe squalls. The series of severe squalls on July 29, 2023 in the Middle Volga region is analyzed. The results of the verification of squalls using observational data from weather stations and the data on wind gust velocities recorded by automatic weather stations are presented.

Russian Meteorology and HydrologyVol. 50(S1)
Hydrometeorological Research Centre of Russian Federation (RU)
Openalex Percentile: Top 65%
Ocean Waves and Remote Sensing
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Identification of Wind Gusts during a Squall from the DMRL-C Network and Numerical Modeling Data — V. M. Bukharov, A. A. Alekseeva · Russian Meteorology and Hydrology (2025) | TGRS Research Map | TGRS