Hail Forecast and Estimation of Its Maximum Size on the Output Data of the Global Atmospheric Model with Tree-Day Lead Time

Introduction. Global warming causes an increase in the frequency and intensity of dangerous weather events. Therefore, their forecast becomes relevant, which is in demand by the anti-hail services, as well as other sectors of the national economy. This is facilitated by 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). In this article the possibility of hail predicting with a lead time of up to three days using discriminant analysis and estimating its size using a regression equation is considered. The success of the hail forecast is assessed by the criteria of forecast quality. The quality of the regression model according to the indicators characterizing the statistical significance and practical applicability of the regression equation meets the accepted criteria.
Materials and methods of research. The research materials were the output data of the global atmospheric model GFS NCEP with a lead time of up to three days. The forecast was carried out by discriminant functions. To assess the success of the hail forecast, a conjugacy table was compiled for the phenomena «hail» and «not hail», according to which the criteria for the quality of forecasts were calculated. To estimate the maximum size of the hail, a regression equation was compiled. The indicators characterizing the statistical significance and practical applicability of the equation were calculated.The observation data on the fallout of hail and its size were provided by paramilitary services for active impact on meteorological and other geophysical processes located within the radius of the representativeness of the actual data of aerological sounding at the «MineralnyeVody» station.
The results of the study and  their discussion. The results of the calculations showed that the hail forecast meets all the criteria for the quality of forecasts. The success rates of the forecast turned out to be good. Thus, the justifiability of the hail forecast was ≈70%.All the indicators characterizing the statistical significance and practical applicability of regression equations have shown that the proposed hail model can adequately estimate the maximum diameter of the hail.
Conclusion. Studies have shown that the proposed approach to hail forecasting and estimating its maximum size according to the global atmospheric model, with an increase in the lead time to three days, does not lead to a noticeable decrease in the quality of forecasts and the regression equation.

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