Validation the output data of the global model of the atmosphere on data of aerological sensing with increscent lead time

Introduction. To investigate dangerous weather phenomena associated with convection in the atmosphere, actual upper-air sounding data are required. However, the network of upper-air radio sounding of the atmosphere in our country cannot provide information consumers with a sufficient frequency of measurements in time and the required density of points in the country. In this work, it is proposed to use the output of the global atmospheric model GFS NCEP instead of the upper-air sounding data, which is especially important for predicting convective phenomena. The possibility of such a replacement is assessed by the methods of correlation analysis. Materials and methods of the research. The research materials are the output of the global atmospheric model GFS NCEP, which includes stratified fields of meteorological elements: air temperature, dew point temperature, wind speed and direction, with an increasing lead time of 24, 48, 60, 84 and 132 hours. The actual data were obtained from the aerological sounding at the meteostation «Mineralnye Vody» in the Central part of the North Caucasus. The degree of their coincidences was estimated by correlation analysis methods. The results of the study and their discussion. In the course of the study, the correlation coefficients were obtained between the predictive (model) and actual data of air temperature, dew point temperature, wind direction and speed. It was found that a consistent increase in the lead time of forecasting meteorological fields up to 132 hours did not lead to a noticeable decrease in the correlation coefficients between them. This indicate to the preservation of the predictive potential of the data of the global atmospheric model up to average term meteorological forecasts. Conclusions. The results obtained show the possibility of using the data of the fields of meteorological elements from the global model of the atmosphere with increasing lead time when predicting dangerous weather phenomena, modeling thunderstorm-hail clouds for operational use with an active impact on dangerous phenomena.

global atmospheric model, aerological sending, lead time, meteorological parameters, correlation coeficient, validation

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