{"title":"Numerical Simulation of the Time Series of Bioclimatic Indices in the Russian Arctic Based on a Stochastic Weather Generator","authors":"M. S. Akenteva, N. A. Kargapolova","doi":"10.3103/s1068373924030063","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The paper proposes an approach to the numerical stochastic modeling of the time series of the wind chill index and equivalent effective temperature at weather stations located in the Arctic zone of the Russian Federation. The approach is based on the use of a specially designed stochastic weather generator. It is shown that the approach allows developing the models of the time series of bioclimatic indices that very accurately reproduce various statistical properties of real processes related, in particular, to their daily variations and specific features of the study area.</p>","PeriodicalId":49581,"journal":{"name":"Russian Meteorology and Hydrology","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Meteorology and Hydrology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.3103/s1068373924030063","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The paper proposes an approach to the numerical stochastic modeling of the time series of the wind chill index and equivalent effective temperature at weather stations located in the Arctic zone of the Russian Federation. The approach is based on the use of a specially designed stochastic weather generator. It is shown that the approach allows developing the models of the time series of bioclimatic indices that very accurately reproduce various statistical properties of real processes related, in particular, to their daily variations and specific features of the study area.
期刊介绍：
Russian Meteorology and Hydrology is a peer reviewed journal that covers topical issues of hydrometeorological science and practice: methods of forecasting weather and hydrological phenomena, climate monitoring issues, environmental pollution, space hydrometeorology, agrometeorology.
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