статья в журнале

En

Physical Oceanography

ISSN:1573160

2024

Purpose. The purpose of the study is to describe comprehensively the extreme storm in the Black Sea in November 2023 in terms of wind and wave field characteristics, based on model calculations, satellite data and field measurements. Methods and results. The atmospheric fields are calculated using the WRF model, and the wave fields – using the SWAN model. The wind and wave fields, as well as their development during the storm are described in detail. The phenomenon of wave shadowing by the Crimean Peninsula is studied. Using the data available for the storm period, the calculation results are compared to the data from satellite altimeters, the CFOSAT SWIM wave scatterometer and synthetic aperture radars. The data of in situ measurements carried out during the storm with the standard equipment of the oceanographic platform in the coastal zone of the Southern Coast of Crimea are presented. The wave characteristics near the oceanographic platform are calculated using the nested grid method. Conclusions. It was found that during the storm in the Black Sea in November 2023, the maximum wave heights and the maximum wave periods exceeded 9 m and 13 s, respectively. A large amount of satellite data confirmed the calculation results. The results of wave modelling near the oceanographic platform are consistent with in situ measurements. Since the applied configuration of models permitted calculation of the fields of wave physical characteristics with a high degree of reliability, they can be used for an authentic forecast of extreme storms in the Black Sea. The shadowing of waves by the Crimean Peninsula has led to a decrease by a factor of ~ 2 or more in the heights of extreme waves in the coastal waters from the southern tip of the peninsula to Cape Chauda (35.8°E). © 2024, V. A. Dulov, M. V. Yurovskaya, V. V. Fomin, M. V. Shokurov, Yu. Yu. Yurovsky, V. S. Barabanov, A. V. Garmashov and 2024, Physical Oceanography.

Black Sea, CFOSAT SWIM wave scatterometer, extreme storm, marine in situ data, natural disasters

2024-07-31 14:48:34