Abstract
The nature of the causes of prerequisites for flight accidents due to meteorological conditions has remained unchanged for many years. For the effective operation of aviation, it is necessary to solve the issues of the timely detection of weather hazards and the identification of their intensity. This article discusses the research into the atmospheric reflectivity and turbulence in cumulonimbus clouds using a near-field meteorological radar system. Experimental studies are carried out with the aim of obtaining estimates of statistical characteristics of the reflectivity distribution and turbulence for weather hazards. The methodology for conducting an experimental study to obtain information about the weather hazards (rain shower, thunderstorm and hail), special features of the radar reflectivity propagation and the specific rate of turbulent energy dissipation in the considered conditions for the Tver region is presented. The analysis of the obtained results has been carried out: comparisons of meteorological data derived, using the meteorological radar complex of the near airfield zone (WR BZ), with the reliable sources of meteorological observation data obtained during experimental studies. Studies of horizontal sections and vertical profiles of the weather hazards parameters under consideration, associated with the cumulonimbus area, have been carried out. A data bank has been formed. Histograms of the information parameter distribution have been constructed. The article considers the results of experimental data approximation, using the χ2 criterion for various distribution laws. It is shown that the distributions of reflectivity and turbulence can be described by the generalized Rice’s law. The results obtained can be used to correct the classification criteria of weather hazards to subsequently increase the justification and reliability of the weather hazard classification. The further development of the method to process meteorological information is also of paramount importance to more correctly interpretate experimental data processing results of remote meteorological phenomena sensing.
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