Methods of studying and forecasting of storm winds in the territory of Russia

This review paper provides information about methods of storm wind research and forecasting. A storm wind is a dangerous hydrometeorological phenomenon that occurs on land or causes strong waves at sea. The mechanism of development of this phenomenon is associated with a powerful action of some conventional processes in the atmosphere. The importance of studying and forecasting storm-force winds is related to the damage that such winds can cause. Currently, the observation network in Russia is still insufficient for a full-scale assessment of convective phenomena. An exception is the Central Federal District, where there is a continuous coverage of the territory by observation data. Therefore, an important step in this direction is to equip the country's territories with a network of sensors for continuous recording of the meteorological situation. The most optimal device that allows determining the structure and physical characteristics of the origins of storm winds is the weather radar. Another comprehensive approach to assessing the origins and passage of storm winds is the use of remote sensing data. Methods based on the non-hydrostatic general use models WRF-NMM (Weather Research and Forecasting-Nonhydrostatic Mesoscale Model) and WRF-ARW (Weather Research and Forecasting) have made significant progress in predicting storm winds. These models have been developed in the USA. The world practice of forecasts shows that these models can reproduce the mesoscale convective processes quite well and be used in a system of early warning of the danger of strong winds. © Published under licence by IOP Publishing Ltd.

Сборник материалов конференции
Institute of Physics Publishing
Номер выпуска
  • 1 Ecology Faculty, Peoples Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation
Ключевые слова
Information systems; Information use; Meteorological radar; Remote sensing; Storms; Wind; Continuous coverage; Network of sensors; Nonhydrostatic mesoscale models; Observation data; Observation networks; Physical characteristics; Remote sensing data; Weather research and forecasting; Weather forecasting
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