Проведена оценка степени совпадения прогностических значений стратификации атмосферы с нарастающей заблаговременностью 24 часа, полученных из глобальной модели атмосферы GFS NCEP (Global Forecast System National Centers for Environmental Prediction) с фактическими данными аэрологического зондирования на основе корреляционного анализа. Актуальность работы заключается в том, что в настоящее время количество опасных природных явлений продолжает увеличиваться, в том числе и загрязнение атмосферы примесями, приводящими к глобальному потеплению. При прогнозировании опасных явлений для экологии входными данными являются значения полей метеопараметров по фактическим данным аэрологического зондирования атмосферы. Такие данные доступны только на отдельных метеостанциях, расположенных достаточно далеко друг от друга, что усложняет проведение исследований. Между тем инструменты для анализа и оценки распространения и рассеивания загрязняющих веществ в атмосфере в настоящее время получили значительное развитие. Сдерживающим фактором их более широкого применения заинтересованными структурами по прогнозированию качества воздуха, аварийно-спасательными службами, представителями авиации, государственными учреждениями и сообществом исследователей атмосферы является недостаток информации о текущем состоянии атмосферы, а также получение прогностических метеопараметров. Для решения этой проблемы предлагаются использовать данные глобальной модели атмосферы GFS NCEP. Целью исследования является определить правомерность замены фактических данных аэрологического зондирования атмосферы на прогностические поля стратифицированных метеопараметров из глобальной модели атмосферы. Методом исследования является один из методов статистического анализа данных - корреляционный анализ. В результате исследований получено, что коэффициенты корреляции между прогностическими и фактическими значениями температуры воздуха, температуры точки росы, скорости и направления ветра имеют высокие значения. Это делает возможными использование данных глобальной модели при математическом моделировании распространения загрязнения в атмосфере, а также прогнозе опасных стихийных явлений, таких как паводок, сильный ливень, град, сель, приводящих к нарушению природных экологических систем. The degree of matching of the predictive values of atmosphere stratification with an increasing lead time of 24 hours obtained from the global atmosphere model GFS NCEP (Global Forecast System National Centers for Environmental Prediction) and the actual data of aerological sounding based on correlation analysis was assessed. The relevance of the work lies in the fact that at present the number of natural hazards continues to increase, including atmospheric pollution with impurities leading to global warming. When predicting dangerous phenomena for the environment, the input data are the values of the fields of meteorological parameters based on the actual data of the aerological sounding of the atmosphere. Such data is available only at individual weather stations located far enough apart from each other, which complicates the research. Meanwhile, tools for analyzing and assessing the spread and dispersion of pollutants in the atmosphere have now received significant development. A limiting factor in their wider use by interested structures for predicting air quality, emergency services, aviation representatives, government agencies and the community of atmosphere researchers is the lack of information about the current state of the atmosphere, as well as obtaining predictive meteorological parameters. To solve this problem, data from the global atmosphere model GFS NCEP are proposed. The aim of the study is to determine the validity of replacing the actual data of the aerological sounding of the atmosphere with the predictive fields of stratified meteorological parameters from the global atmosphere model. The research method is correlation analysis, one of the methods of statistical data analysis. As a result of the research, it was found that the correlation coefficients between the predictive and actual values of air temperature, dew point temperature, wind speed and direction have high values. This makes it possible to use the data of the global model in mathematical modeling of atmospheric pollution, as well as the forecast of dangerous natural phenomena, such as floods, heavy rain, hail, mudslides, leading to disruption of natural ecological systems.
This paper describes the calculation of electrical parameters in a three-dimensional mathematical model of a convective cloud with detailed consideration of thermodynamic, microphysical and electrical processes. The formation of electric charges occurs due to freezing of droplets and accretion processes of liquid and solid particles. The calculated values of volume charges are used to determine the potential of the electric field. A three-dimensional Poisson equation is solved for this purpose - at each step of numerical integration of the model’s system of equations. The values of the electric field strength in discrete cloud cells at each time step are also taken into account when adjusting the coefficients of gravitational coagulation of cloud particles using appropriate multipliers. Some results of calculations of microstructural parameters of the cloud at different stages of development are presented with and without taking into account the electrical coagulation of cloud particles.
The paper presents a three-dimensional numerical model developed by the authors, which describes the change over time of thermodynamic and microphysical characteristics of the atmosphere in the computational domain, the distribution of impurities on a local scale (up to 50 km) from various sources, taking into account the actual or forecast fields of meteorological parameters. The model differs in that it takes into account the microphysical processes of interaction of impurities with the cloud environment. To obtain three-dimensional prognostic fields of meteorological parameters at the initial time (when initializing the model), a combination of data from the global forecasting system GFS and data from remote observations using Doppler meteorological radars is used. Validation of the model on various test data is carried out. Numerical experiments were performed using orography and the actual distribution of wind in the atmosphere. The use of data of instrumental measurements and forecast system allows obtaining a detailed analysis of the environmental situation in the study area.
Based on instrumental observations for the period from 2008 to 2019, regional features of the regime of daily thunderstorm activity in the North Caucasus are analyzed. Thunderstorm activity is calculated at different periods of the day. The temporal and spatial changes of thunderstorm activity are analyzed by time of day and by month. Temporary trends in thunderstorm activity are shown. The characteristic of the dominant tendency and diurnal features in long-term changes in the main characteristics of thunderstorm activity is given; the role of various factors determining these changes is estimated.
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