{"title":"Intelligent Monitoring of Air Temperature by the DATA of Satellites and Meteorological Stations","authors":"M. Talakh, S. Holub, Pavlo Luchshev, Ihor Turkin","doi":"10.47839/ijc.21.1.2525","DOIUrl":null,"url":null,"abstract":"Climate models are the primary tools for investigating the response of the climate system to various forcings and for climate predictions. The combined use of the data from remote sensors and meteostations allows taking into account the spatial and temporal components of monitoring. In this study the temperature forecasting technique was improved by using the data from thermal imaging satellites and weather stations. This technique uses for this purpose the model of dependence of temperature received from satellite imagery on the temperature obtained from existing meteorological stations. During the investigation of the variables selected from the input data array, it was shown that satellite imagery data can be used in regional models of temperature prediction, and temperature traces obtained from satellite imagery and weather stations at similar points show similar dynamics. The effectiveness of the group method of data handling using multi-row algorithm for forecasting temperature for areas with no meteorological stations is shown.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":"135 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47839/ijc.21.1.2525","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 1
Abstract
Climate models are the primary tools for investigating the response of the climate system to various forcings and for climate predictions. The combined use of the data from remote sensors and meteostations allows taking into account the spatial and temporal components of monitoring. In this study the temperature forecasting technique was improved by using the data from thermal imaging satellites and weather stations. This technique uses for this purpose the model of dependence of temperature received from satellite imagery on the temperature obtained from existing meteorological stations. During the investigation of the variables selected from the input data array, it was shown that satellite imagery data can be used in regional models of temperature prediction, and temperature traces obtained from satellite imagery and weather stations at similar points show similar dynamics. The effectiveness of the group method of data handling using multi-row algorithm for forecasting temperature for areas with no meteorological stations is shown.
期刊介绍：
The International Journal of Computing Journal was established in 2002 on the base of Branch Research Laboratory for Automated Systems and Networks, since 2005 it’s renamed as Research Institute of Intelligent Computer Systems. A goal of the Journal is to publish papers with the novel results in Computing Science and Computer Engineering and Information Technologies and Software Engineering and Information Systems within the Journal topics. The official language of the Journal is English; also papers abstracts in both Ukrainian and Russian languages are published there. The issues of the Journal are published quarterly. The Editorial Board consists of about 30 recognized worldwide scientists.
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