The paper considers possibilities of taking into account data from lightning networks in the procedure for lightning data assimilation in numerical models of atmospheric dynamics. A universal procedure is suggested and implemented as a code within the WRF-ARW model. According to the data from lightning detection networks, cells of a computational grid are defined, where lightnings have been recorded. Then moisture is iteratively added in these cells until the occurrence of thermodynamic instability and, hence, convection. The effect of using this procedure on the forecast of precipitation, temperature, and humidity is studied, and the suggested procedure is compared with other lightning assimilation methods. The use of data from lightning detectors makes it possible to locally improve the forecast of heavy precipitation and temperature in areas where thunderstorms were observed. The Peirce–Obukhov coefficient increases from 0.26 to 0.40 when this procedure is used for forecasting heavy precipitation.

Расширение грозопеленгационных сетей в последнее время привело к росту количества данных о грозах, которые могут использоваться для верификации прогнозов гроз и являются новым источником информации о состоянии атмосферы. Эта информация может быть учтена в численных моделях динамики атмосферы, но на данный момент применяется весьма редко. В работе предложена и реализована в виде кода в рамках модели WRF-ARWуниверсальная процедура учета данных о положении гроз. Процедура универсальна, так как не требует использования каких-либо процедур параметризации физических процессов, и благодаря этому она может быть введена в любую гидродинамическую модель. В процедуре по данным сетей грозопеленгации определяются ячейки расчетной сетки, в которых фиксировались молнии, в них итерационно добавляется влага до возникновения термодинамической неустойчивости, а значит конвекции. Исследована эффективность этой процедуры в прогнозе осадков, температуры и влажности; проведено сравнение с другими способами учета данных о грозах. Усвоение данных грозопеленгаторов позволяет локально улучшить прогноз сильных осадков и температуры в областях, где наблюдались грозы; коэффициент прогноза интенсивных осадков Пирси–Обухова при использовании предложенного метода возрастает с 0,26 до 0,40. The paper considers the possibilities of taking into account data from lightning networks in the procedure for lightning data assimilation in numerical models of atmospheric dynamics. A universal procedure is proposed and the code is implemented within the framework of the WRF-ARW model. According to the data from lightning detection networks, the cells of the computational grid are determined, in which lightning was recorded. Then moisture is iteratively added in these cells until the occurrence of thermodynamic instability and, hence, convection. The effect of using this scheme on the forecast of precipitation, temperature, and humidity is studied, and a comparison is made with other lightning assimilation methods. The use of data from lightning detectors makes it possible to locally improve the forecast of heavy precipitation and temperature in areas where thunderstorms were observed. The Piercy–Obukhov coefficient for forecasting intense precipitation using the proposed procedure increases from 0.26 to 0.40.

The population dose loads resulting from the maximum possible and least likely (hypothetical) nuclear accident on one of the nuclear icebreakers under construction at FSUE Atomflot were determined. Assessments were made of 1) the population danger of radioactive contamination of the environment by comparing the predicted data with the acceptable norms and 2) the contribution of the determining technogenic radionuclides to the effective radiation dose. Population safety-security measures are presented as a function of the 137 Cs fallout density and the population dose load.

Methods and results of numerical prediction of the maximum thickness of ice accretions are described for ten cases of glazed frost in the East European Plain and one case in Primorskii krai. Evaluations of forecasts on ice accretion thickness from calculations based on the output information of the WRF-ARW model and measurements at synoptic stations in different regions of Russia are presented.

We report an ensemble approach applied to the radiation dose modeling for a hypothetical radiation emergency with a long-term release of radioactive materials into the atmosphere. The study is aimed at improving the emergency response system in Russia and focuses on quantifying the impact of meteorological uncertainties on modeling the atmospheric dispersion and transport. Four sets of options of meteorological conditions are used: (i) classic global weather forecast (zero member), (ii) ensemble global weather forecast with 21 members, (iii) global weather analysis, and (iv) real local weather measurements. The numerical experiments have been conducted for four dates during September-October 2019 using the SOCRAT code for source term evaluation, WRF-ARW model - for weather prediction, and NOSTRADAMUS code - for atmospheric dispersion modeling and dose calculations. The comparable results have been obtained for all performed numerical experiments. The paper presents the results for a hypothetical release on 17 October 2019, but all conclusions are valid for all investigated dates. The ensemble approach has demonstrated to increase significantly the reliability of radionuclide dispersion predictions for severe accident conditions.

Refined initial data are presented for retrospective prediction and analysis of the radiation conditions in Primorskii Krai after a nuclear accident on a nuclear submarine on August 10, 1985 in Bukhta Chazhma. The initial and boundary conditions are substantiated, including sources of radioactive contamination of the environment, emission intensity of the determining dose-generating radionuclides, weather conditions, and particulars of the transport of the radioactive cloud above the ship repair yard, Dunai Peninsula, Zemlya Petra Velikogo, and Primorskii Krai territory. Substantiation is given for choosing the systems PARRAD and ROUZ for reconstruction of past events to predict the transport and spreading of radioactive substances in the atmosphere, making it possible to evaluate the radiation consequences of the accident for the population of Primor'ya and the adjoining part of China, including environmental contamination, taking into account actual data, numerical estimates, and reconstructed weather conditions for the period of the accident and on the days preceding and following it.

The results of forecasts of the WRF-ARW numerical mesoscale model with two sets of initial and boundary conditions are presented. The first set comprises the forecasts of the GFS global model (USA), and the second set, the forecasts of the SL-AV global model (Russia). The quality of the WRF-ARW forecasts is assessed by their comparison with the data of surface and upper-air meteorological observations for the European part of Russia in winter and summer. It is shown that the 72-hour forecast results are close to the results based on the GFS data if the Russian global model data are used as initial and boundary conditions.

Variations in wind speed and air temperature during blowing snow are considered in detail using data from the Canadian weather observation network with high spatiotemporal resolution. It is revealed that blowing snow considerably affects the lower atmospheric layer regime. The analysis of observational data illustrates the fact of wind speed increase during the snowstorm. The local minima of air temperature during the period of blowing snow are identified. The method is determined for calculating the threshold wind speed that provokes the onset of blowing snow. The highest skill scores were obtained for the method which takes into account air temperature and humidity.

The physical and mathematical description of the model of cumulonimbus cloud electrification is presented. The model uses the forecasts of the WRF-ARW numerical mesoscale model as inputs and allows predicting the parameters of the atmospheric electric field including those typical of thunderstorm activity. The prognostic values of electric breakdown are compared with the observed thunderstorms.

A system for predicting accidental dissemination of radionuclides into the atmosphere at operating NPP (PARRAD) is described. The methodological and functional components of the system are presented. The results of testing the system on examples of accidental emissions at the Fukushima NPP, an incident at a heavy machine building plant in Elektrostal, and emissions in the ACURATE experiment are presented.

Currently the Nuclear Safety Institute of the Russian Academy of Sciences (NSI RAS) jointly with the Hydrometcenter of Russia is developing the system for forecasting the transfer of radio-active substances in the atmosphere in case of radiation accidents at Russian nuclear power plants. The operation of the system is based on the numerical hydrodynamic model which allows forecasting meteorological parameters and is coupled with the mesoscale dispersion model of the transfer ofradioactive substances in the atmosphere. The results are presented of 85 Kr transport modeling under the conditions of the ACURATE experiment with three transport models: FLEXPART, HYSPLIT, and the model from the NOSTRADAMUS software package. It is demonstrated that all three Lagrangian models can give a qualitative description of concentration fields from the ACURATE experiment with the best value of the RANK metric (2.5) based on three statistics.

The estimates of 137Cs emissions from the accident happened in Elektrostal at the beginning of April 12, 2013 are presented. The transport of radionuclides and their dry and wet deposition on the surface are computed using the Lagrangian stochastic model of the NOSTRADAMUS software package worked out by Nuclear Safety Institute of Russian Academy of Sciences. Prognostic fields of wind (horizontal and vertical components) in the lower troposphere, precipitation, and vertical and horizontal turbulence diffusivity coefficients in the lower atmosphere (up to 4 km) were used as input data. Prognostic fields were obtained using the WRF-ARW numerical mesoscale model.

Compared are several experiments with the polar version ofthe WRF-ARW model. In one case, ice characteristics (concentration and temperature) are provided by the GFS (Global Forecasting System) center, and in the other case, are obtained using the ice model of Arctic and Antarctic Research Institute. Determined are the degree of sensitivity of the WRF-ARW regional hydrodynamic model to the different methods of ice cover description and their effects on the forecast of surface meteorological parameters in the Arctic. Presented are the skill scores of numerical forecasts obtained using different sources of data on ice surface thermophysical characteristics.

Studied are the effects that variations of meteorological parameters at different time scales in Naberezhnye Chelny city produce on people suffering from ischemic heart disease. The number of ambulance calls from 2010 to 2012, meteorological parameters, and some biometeorological indices are compared by the cross-correlation analysis. Demonstrated is the absence of statistically significant correlation between the daily series of ambulance calls due to ischemic heart disease during the period under study, on the one hand, and average daily series of major meteorological parameters and the most frequently used biometeorological indices, on the other hand. Revealed is the correlation between the number of ambulance calls and the intradaily variations of air pressure and air temperature at the time scale of 3 hours. Proposed is a parameter (biometeorological index of weather effects, IWE) taking into account the total effects of intradaily variations of air pressure and air temperature and characterized by statistically significant correlation with the number of ambulance calls made by people suffering from ischemic heart disease.

In the article there are considered the main problems of assessing public health risks of the combined effects of high temperatures and air pollution with the account taken of the consequences of abnormally hot weather observed in summer 2010 in Moscow and without equals in the history of meteorological measurements in the city. The daily average concentrations of fine suspended particles matter (PM10) in the city during peatland fires from 4 to 9 August are emphasized to be within the range of 431-906 μ/m3, being 7.2-15.1 times the Russian maximum permissible concentration (MPCs) (60 μ/m3). The anomalous heat and high levels of air pollution in this period were shown to cause a significant increase in excess mortality among the population of Moscow. There was established the relative gain in mortality from all natural causes per 10 μg/m3 increase in daily average concentrations of PM10 and ozone, which was respectively: 0.47% (95%; CI: 0.31-0.63) and 0.41% (95%; CI: 0.31-1.13). On the base of the statistical analysis of daily mortality rates, meteorological indices, the concentrations of PM10 and ozone there was developed marking scale for the risk assessment of these indices accordingly to 4 gradings--low (permissible), warning, alert, and a hazard level. There has been substantiated the importance of the introduction of the system for the early alert for hazard weather events and the unified rating scale for the hazard of high air temperatures and high levels of air pollution with PM10 and ozone, which allows to take timely measures for the protection of the public health.

Presented are the statistical estimates of 26 indices of atmospheric instability widely used in the world practice for the thunderstorm prediction. Proposed is a new index for the thunderstorm forecasting that takes account of the vertical component of wind speed. The computation of indices is based on the data of forecasts obtained with the WRF-ARW hydrodynamic mesoscale model. The verification of thunderstorm forecasts is carried out using the observational data from weather stations and the data of the World Wide Lightning Location Network.