Modified data classification for extreme values in Şen's innovative trend analysis: A comparative trend study for the Aegean and Eastern Anatolia Regions of Türkiye

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dc.contributor.authorAsikoglu, Omer Levend
dc.contributor.authorAlp, Harun
dc.contributor.authorTemel, Ibrahim
dc.date.accessioned2024-08-31T07:50:10Z
dc.date.available2024-08-31T07:50:10Z
dc.date.issued2024
dc.departmentEge Üniversitesien_US
dc.description.abstractThe increase in greenhouse gases in the atmosphere has worsened global warming, and marked changes have been observed in meteorological and climatic events, especially since the early 2000s. Trend analysis studies are important for determining changes in meteorological and climatic events over time. This study investigated the trends of maximum precipitation and minimum temperature in the Aegean Region and Eastern Anatolia Region of T & uuml;rkiye by conducting an innovative trend analysis (ITA), the Mann-Kendall (MK) test, and linear regression analysis (LRA). As a method, ITA has been used together with traditional methods in the last decade, and its advantages have been demonstrated in comparative trend studies. An important contribution of ITA is that it can categorize datasets according to their size (low, medium, and high). The classification technique of the ITA method includes dividing the sorted dataset into three equal parts and separately examining the trends of low, medium, and high data values. This approach is reasonable for datasets with low skewness (or normally distributed series). However, the normal distribution acceptance of ITA data classification is insufficient for trend analysis of data series with extreme values. Therefore, we propose a modified data classification method to rationally examine skewed datasets with the use of quartiles. Our study was performed for the trend analysis of maximum rainfall and minimum temperature data in two regions located in the west and east of T & uuml;rkiye showing different climatic characteristics. In the first part of the study in which the numerical trend analysis of ITA was evaluated, the MK and LRA methods showed similar results, whereas the ITA detected trends at a greater number of stations owing to its sensitivity feature in detecting trends. In the second part, which included data classification in trend analysis, the equal split data classification used in the ITA and the modified data classification proposed in the study were compared. The comparative results of the trend analysis of the maximum rainfall and minimum temperature data showed the superiority of the proposed data classification in examining the trend of extreme values, especially for maximum rainfall data with relatively high skewness.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkiye (TUBITAK)en_US
dc.description.sponsorshipOpen access funding provided by the Scientific and Technological Research Council of Turkiye (TUBITAK). The authors declare that no funds, grants, or other support was received during the prepara-tion of this manuscript. DAS:No datasets were generated or analysed during the current study.en_US
dc.identifier.doi10.1007/s00704-024-05129-9
dc.identifier.issn0177-798X
dc.identifier.issn1434-4483
dc.identifier.scopus2-s2.0-85200567898en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1007/s00704-024-05129-9
dc.identifier.urihttps://hdl.handle.net/11454/105117
dc.identifier.wosWOS:001285461500001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Wienen_US
dc.relation.ispartofTheoretical and Applied Climatologyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240831_Uen_US
dc.subjectPrecipitation Variabilityen_US
dc.subjectRainfallen_US
dc.subjectChinaen_US
dc.subjectTemperatureen_US
dc.subjectIdentificationen_US
dc.subjectIndexesen_US
dc.titleModified data classification for extreme values in Şen's innovative trend analysis: A comparative trend study for the Aegean and Eastern Anatolia Regions of Türkiyeen_US
dc.typeArticleen_US

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