{"title":"贝加尔湖自然区南部天气参数时空联合场数值随机模型的建立","authors":"M. S. Akenteva, N. Kargapolova, V. Ogorodnikov","doi":"10.1515/rnam-2022-0006","DOIUrl":null,"url":null,"abstract":"Abstract The paper is focused on the construction of a numerical stochastic model of the joint spatio-temporal fields of air temperature, wind speed vector with three-hour resolution, and semidiurnal precipitation amounts according to observation data at a group of weather stations located in the south of the Baikal natural territory. The model also takes into account the dependence of one-dimensional distributions on temporal and spatial coordinates. The heterogeneity of the field in spatial correlations and the periodical correlation in time are also taken into account. The results of calculations for verification of the model are presented. An example of using the developed model to study the properties of time series of the wind chill index is given.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of a numerical stochastic model of joint spatio-temporal fields of weather parameters for the south part of the Baikal natural territory\",\"authors\":\"M. S. Akenteva, N. Kargapolova, V. Ogorodnikov\",\"doi\":\"10.1515/rnam-2022-0006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The paper is focused on the construction of a numerical stochastic model of the joint spatio-temporal fields of air temperature, wind speed vector with three-hour resolution, and semidiurnal precipitation amounts according to observation data at a group of weather stations located in the south of the Baikal natural territory. The model also takes into account the dependence of one-dimensional distributions on temporal and spatial coordinates. The heterogeneity of the field in spatial correlations and the periodical correlation in time are also taken into account. The results of calculations for verification of the model are presented. An example of using the developed model to study the properties of time series of the wind chill index is given.\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2022-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1515/rnam-2022-0006\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1515/rnam-2022-0006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of a numerical stochastic model of joint spatio-temporal fields of weather parameters for the south part of the Baikal natural territory
Abstract The paper is focused on the construction of a numerical stochastic model of the joint spatio-temporal fields of air temperature, wind speed vector with three-hour resolution, and semidiurnal precipitation amounts according to observation data at a group of weather stations located in the south of the Baikal natural territory. The model also takes into account the dependence of one-dimensional distributions on temporal and spatial coordinates. The heterogeneity of the field in spatial correlations and the periodical correlation in time are also taken into account. The results of calculations for verification of the model are presented. An example of using the developed model to study the properties of time series of the wind chill index is given.