ASSESSMENT OF CHANGES IN THE GROUND CHARACTERISTICS OF HAIL DURING ANACTIVE IMPACT ON HAIL PROCESSES

Introduction. Hailing processes cause significant damage to agriculture, lead to damage to buildings, the death of animals and human casualties. To reduce the negative consequences of hail phenomena, work is being carried out to actively influence hail processes. In this work, an assessment of changes in the spectral and energy characteristics of hail is carried out during an active action according to the data of the hail-gauge network and radiosonding of the atmosphere. Materials and research methods. In the study of the ground characteristics of hail damage, we used the data obtained on the hail-gauge network during the Comprehensive hail experiment High Mountain Geophysical Institute (1983-1997), the data of the North Caucasian paramilitary service on active impacts on hydrometeorological processes (NC PS) about hailstorm for the period 2011-2012 and data from radiosonding of the atmosphere. Using the method of cluster analysis (statistical program SPSS), all processes with active impact (AI) and without active impact (91 processes in total) were divided from 2 to 5 clusters to identify the maximum inluence of atmospheric parameters on the characteristics of hail processes and further select the optimal number of clusters. Further, a correlation analysis was carried out to identify the relationship between the terrestrial characteristics of hail and atmospheric parameters. Multiple linear regression equations were constructed for the relationship between the ground characteristics of hail (average diameter, average surface density of kinetic energy, average concentration) and atmospheric parameters. The obtained equations can be used to analyze changes in the spectral and energy characteristics of hailstorms during active exposure. Research results and discussion. Analysis of data on the ground characteristics of hail processes with and without AI showed that the samples are not equal. More powerful hail processes most likely got into the processes with AI, therefore, for their correct comparison with the processes without AI, it is necessary to divide them into clusters. To carry out the cluster analysis, we used the characteristics of the atmosphere obtained from the data of radio sounding performed at the time instant closest to the time of the hail. The results of cluster analysis, confirmed by the T-test, showed that division into 2 clusters is optimal. From the characteristics of the parameters of the atmosphere in two clusters of clusters, it follows that 1 cluster includes the parameters of the atmosphere, leading to more powerful hail processes. To investigate the relationship between the parameters characterizing the state of the atmosphere and the terrestrial characteristics of hail, the dependent and independent variables were determined. In the processes assigned to cluster 1 and cluster 2, significant correlations of the ground characteristics of hail with atmospheric parameters were selected at significance levels < 0.05 and close to it. Multiple regression analysis was carried out using the selected characteristics and regression equations for the relationship between the ground characteristics of hail and atmospheric parameters for processes 1 and 2 of the cluster were constructed. The resulting equations were used to analyze changes in the spectral and energy characteristics of hail hits as a result of active exposure. Conclusions. The analysis of changes in the spectral and energy characteristics of hailstorms as a result of active exposure using the obtained regression equations for the relationship between the ground characteristics of hail and atmospheric parameters has been carried out. The analysis showed that changes in the ground characteristics of hail precipitation as a result of AI in the processes of cluster 1, which includes more powerful hail processes, does not lead to a signiicant change in the ground characteristics of hail. For processes of cluster 2 (weak processes), active impact leads to a decrease in the values of the ground characteristics of hail precipitation.

hail processes, hail-gauge network, atmospheric parameters, active influences, cluster analysis, regression equations, ground characteristics of hail

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