ИСТИНА

The health of the urban population is influenced by many factors, among which there are meteorological parameters. Moreover, the impact is not expressed in individual indicators, but in their totality, which is displayed by thermal comfort indices [1]. Basically, they are identified empirically and are presented in the format of the outdoor temperature for ease of perception of information. Due to the heterogeneity of urban development in the Moscow region, thermal comfort conditions at different points in the same territory will differ noticeably with the same meteorological parameters. Thus, it is necessary to study the parameters of comfort at the microscale. Therefore, within the framework of this study, in order to inform the public about the negative impact of the weather, and further to minimize the consequences on the human body, an attempt was made to develop an operational system for predicting dangerous conditions of thermal comfort. Climate comfort is an indicator that is a reflection of a set of parameters such as temperature, humidity, and rainfall on a person’s sensation of being favorable to being outdoors or indoors. By now, more than 100 indices have been developed in world practice to determine the bioclimatic comfort of human life [2]. Such a huge number of indexes developed up to this point is due to the fact that there is no universal indicator due to very different weather conditions in different parts of the planet. Indices that give a more accurate value of cold stress and are based on experiments in a frosty environment are called cold ones. Accordingly, those that better determine heat stress and are based on experiments in a hot environment are called thermal ones. Also special models have been developed for taking into account the individual characteristics of a person when calculating thermal conditions. Heat balance models take into account many aspects of the heat transfer mechanism. We used 3 most popular comfort indexes: PET, UTCI, mPET. In order to collect climate statistics, climate data were calculated for comfort conditions for the MSU campus using the RayMan model. Therefore, it is possible to analyze the changes in biometric conditions in recent years and track trends in various locations. Since the input parameters for the RayMan diagnostic model, which processes only text documents, serve as predictive data for the Canadian GEM global meteorological parameters in grib2 format, a program for converting files using Command.exe and a computer language were created to create an online module for predicting biometric indices. Fortran 90. Then a scripting method was developed, which allows combining various computational algorithms and creating a single module for online prediction of com of mortality with the help of GhostMouse autoclicker. For the convenience of perception of information, the results of calculations are visualized on the basis of Yandex maps. Thus, the main idea of the work was that any user with the minimum expenditure of his time resource and without knowledge of the model’s work could launch the program and receive an individual forecast of comfort conditions for the next hours in a visually understandable format. Online forecasting is a new direction in biometeorology and, quite possibly, will continue to be of particular importance for the functioning of urban infrastructure.