MEDIUM-RANGE HAIL FORECAST BASED ON GLOBAL ATMOSPHERIC MODEL OUTPUT DATA

Introduction. The forecast of dangerous weather phenomena, including hail, is becoming more and more popular not only for services to combat hail, but also for other sectors of the national economy. This is facilitated by the intensification of weather processes due to climate warming and the operat...

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Main Authors: A. K. Kagermazov, L. M. Fedchenko, L. T. Sozaeva, M. M. Zhaboeva
Format: Article
Language:Russian
Published: North-Caucasus Federal University 2022-07-01
Series:Наука. Инновации. Технологии
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Online Access:https://scienceit.elpub.ru/jour/article/view/136
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author A. K. Kagermazov
L. M. Fedchenko
L. T. Sozaeva
M. M. Zhaboeva
author_facet A. K. Kagermazov
L. M. Fedchenko
L. T. Sozaeva
M. M. Zhaboeva
author_sort A. K. Kagermazov
collection DOAJ
description Introduction. The forecast of dangerous weather phenomena, including hail, is becoming more and more popular not only for services to combat hail, but also for other sectors of the national economy. This is facilitated by the intensification of weather processes due to climate warming and the operational availability of the results of modeling the Earth's atmosphere, in particular, the values of stratification according to the global model (GFS NCEP). This paper discusses the possibility of predicting hail with a lead time of 132 hours using discriminant analysis. The success of the hail forecast is assessed by the criteria of the forecast quality. Materials and methods of research. The research materials were the output data of the global atmospheric model GFS NCEP with a lead time of 132 hours. Discriminant functions were used to predict the phenomenon of «hail» and «non-hail». The results of the forecast were compared with the data of observations on the fall of hail provided by the paramilitary services for active influence on meteorological and other geophysical processes, located within the radius of representativeness of the actual data of the aerological sounding at the Mineralnye Vody station. To assess the success of the hail forecast, the conjugacy table is compiled and the forecast quality criteria are calculated. Research results and their discussion. The results of the calculations showed that the hail forecast with a lead time of 132 hours meets all the criteria for the quality of forecasts. The forecast success rates were good. Thus, the accuracy of the hail forecast was ~ 70 %. Conclusion. Studies have shown that the proposed approach to forecasting hail from the data of the global atmospheric model does not lead to a noticeable decrease in the quality of forecasts when the lead time is increased to five days.
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spelling doaj-art-172c0fb03ae148c58234809d7a447f4e2025-08-20T03:42:25ZrusNorth-Caucasus Federal UniversityНаука. Инновации. Технологии2308-47582022-07-01029110810.37493/2308-4758.2021.2.6135MEDIUM-RANGE HAIL FORECAST BASED ON GLOBAL ATMOSPHERIC MODEL OUTPUT DATAA. K. Kagermazov0L. M. Fedchenko1L. T. Sozaeva2M. M. Zhaboeva3High-Mountain Geophysical InstituteHigh-Mountain Geophysical InstituteHigh-Mountain Geophysical InstituteHigh-Mountain Geophysical InstituteIntroduction. The forecast of dangerous weather phenomena, including hail, is becoming more and more popular not only for services to combat hail, but also for other sectors of the national economy. This is facilitated by the intensification of weather processes due to climate warming and the operational availability of the results of modeling the Earth's atmosphere, in particular, the values of stratification according to the global model (GFS NCEP). This paper discusses the possibility of predicting hail with a lead time of 132 hours using discriminant analysis. The success of the hail forecast is assessed by the criteria of the forecast quality. Materials and methods of research. The research materials were the output data of the global atmospheric model GFS NCEP with a lead time of 132 hours. Discriminant functions were used to predict the phenomenon of «hail» and «non-hail». The results of the forecast were compared with the data of observations on the fall of hail provided by the paramilitary services for active influence on meteorological and other geophysical processes, located within the radius of representativeness of the actual data of the aerological sounding at the Mineralnye Vody station. To assess the success of the hail forecast, the conjugacy table is compiled and the forecast quality criteria are calculated. Research results and their discussion. The results of the calculations showed that the hail forecast with a lead time of 132 hours meets all the criteria for the quality of forecasts. The forecast success rates were good. Thus, the accuracy of the hail forecast was ~ 70 %. Conclusion. Studies have shown that the proposed approach to forecasting hail from the data of the global atmospheric model does not lead to a noticeable decrease in the quality of forecasts when the lead time is increased to five days.https://scienceit.elpub.ru/jour/article/view/136global model of the atmosphereaerological soundinglead timemeteorological parametersdiscriminant analysisforecast of hazardous phenomena
spellingShingle A. K. Kagermazov
L. M. Fedchenko
L. T. Sozaeva
M. M. Zhaboeva
MEDIUM-RANGE HAIL FORECAST BASED ON GLOBAL ATMOSPHERIC MODEL OUTPUT DATA
Наука. Инновации. Технологии
global model of the atmosphere
aerological sounding
lead time
meteorological parameters
discriminant analysis
forecast of hazardous phenomena
title MEDIUM-RANGE HAIL FORECAST BASED ON GLOBAL ATMOSPHERIC MODEL OUTPUT DATA
title_full MEDIUM-RANGE HAIL FORECAST BASED ON GLOBAL ATMOSPHERIC MODEL OUTPUT DATA
title_fullStr MEDIUM-RANGE HAIL FORECAST BASED ON GLOBAL ATMOSPHERIC MODEL OUTPUT DATA
title_full_unstemmed MEDIUM-RANGE HAIL FORECAST BASED ON GLOBAL ATMOSPHERIC MODEL OUTPUT DATA
title_short MEDIUM-RANGE HAIL FORECAST BASED ON GLOBAL ATMOSPHERIC MODEL OUTPUT DATA
title_sort medium range hail forecast based on global atmospheric model output data
topic global model of the atmosphere
aerological sounding
lead time
meteorological parameters
discriminant analysis
forecast of hazardous phenomena
url https://scienceit.elpub.ru/jour/article/view/136
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AT lmfedchenko mediumrangehailforecastbasedonglobalatmosphericmodeloutputdata
AT ltsozaeva mediumrangehailforecastbasedonglobalatmosphericmodeloutputdata
AT mmzhaboeva mediumrangehailforecastbasedonglobalatmosphericmodeloutputdata