{"title":"PREDICTION OF THUNDERSTORM OCCURRENCES IN TROPICAL AREAS USING A NUMERICAL MODEL","authors":"W. Suparta, W. S. Putro, T. K. Darmastono","doi":"10.21163/GT_2021.161.07","DOIUrl":null,"url":null,"abstract":": The prediction of thunderstorm activity is not only significant for weather forecasting but also for the standardization of risk assessment as in the aviation industry or emergency unit purposes. This paper aimed to develop a prediction of thunderstorm occurrences using a nonlinear model. For this work, the data used for a case study is one-year (1 January 2012 to 31 December 2012) located in a tropical area. The Jacobi algorithm has been employed to construct a prediction model with six combinations of input and one output (target). The predicted target is thunderstorm occurrence. The parameter input is surface pressure, air temperature, relative humidity, clouds, precipitable water vapor, and precipitation. The result obtained a better fit prediction model with four optimum parameters and estimation errors of 5.73%. May and October are the highest occurrences of thunderstorms where prediction errors were found high during the intermonsoon season.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geographia Technica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21163/GT_2021.161.07","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
引用次数: 1
Abstract
: The prediction of thunderstorm activity is not only significant for weather forecasting but also for the standardization of risk assessment as in the aviation industry or emergency unit purposes. This paper aimed to develop a prediction of thunderstorm occurrences using a nonlinear model. For this work, the data used for a case study is one-year (1 January 2012 to 31 December 2012) located in a tropical area. The Jacobi algorithm has been employed to construct a prediction model with six combinations of input and one output (target). The predicted target is thunderstorm occurrence. The parameter input is surface pressure, air temperature, relative humidity, clouds, precipitable water vapor, and precipitation. The result obtained a better fit prediction model with four optimum parameters and estimation errors of 5.73%. May and October are the highest occurrences of thunderstorms where prediction errors were found high during the intermonsoon season.
期刊介绍：
Geographia Technica is a journal devoted to the publication of all papers on all aspects of the use of technical and quantitative methods in geographical research. It aims at presenting its readers with the latest developments in G.I.S technology, mathematical methods applicable to any field of geography, territorial micro-scalar and laboratory experiments, and the latest developments induced by the measurement techniques to the geographical research. Geographia Technica is dedicated to all those who understand that nowadays every field of geography can only be described by specific numerical values, variables both oftime and space which require the sort of numerical analysis only possible with the aid of technical and quantitative methods offered by powerful computers and dedicated software. Our understanding of Geographia Technica expands the concept of technical methods applied to geography to its broadest sense and for that, papers of different interests such as: G.l.S, Spatial Analysis, Remote Sensing, Cartography or Geostatistics as well as papers which, by promoting the above mentioned directions bring a technical approach in the fields of hydrology, climatology, geomorphology, human geography territorial planning are more than welcomed provided they are of sufficient wide interest and relevance.
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