Homogeneity analysis of Turkish meteorological data set

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dc.authorid0000-0002-7662-3250
dc.authorscopusid36005636900
dc.authorscopusid6603624190
dc.authorwosidSahin, Sinan/ABA-6198-2020
dc.contributor.authorŞahin, Sinan
dc.contributor.authorCığızoğlu, H. Kerem
dc.date.accessioned2022-05-11T14:26:36Z
dc.date.available2022-05-11T14:26:36Z
dc.date.issued2010
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü
dc.description.abstractThe missing value interpolation and homogeneity analysis were performed on the meteorological data of Turkey. The data set has the observations of six variables: the maximum air temperature, the minimum air temperature, the mean air temperature, the total precipitation, the relative humidity and the local pressure of 232 stations for the period 1974-2002. The missing values on the monthly data set were estimated using two methods: the linear regression (LR) and the expectation maximization ( EM) algorithm. Because of higher correlations between test and reference series, EM algorithm results were preferred. The homogeneity analysis was performed on the annual data using a relative test and four absolute homogeneity tests were used for the stations where non-testable series were found due to the low correlation coefficients between the test and the reference series. A comparison was accomplished by the graphics where relative and absolute tests provided different outcomes. Absolute tests failed to detect the inhomogeneities in the precipitation series at the significance level 1%. Interestingly, most of the inhomogeneities detected on the temperature variables existed in the Aegean region of Turkey. It is considered that theseinhomogeneities were mostly caused by non-natural effects such as relocation. Because of changes at topography at short distance in this region intensify non-random characteristics of the temperature series when relocation occurs even in small distances. The marine effect, which causes artifical cooling effect due to sea breezes has important impact on temperature series and the orograhpy allows this impact go through the inner parts in this region. Copyright (C) 2010 John Wiley & Sons, Ltd.
dc.identifier.doi10.1002/hyp.7534
dc.identifier.endpage992
dc.identifier.issn0885-6087
dc.identifier.issn1099-1085
dc.identifier.issue8en_US
dc.identifier.scopus2-s2.0-77951683894
dc.identifier.scopusqualityQ1
dc.identifier.startpage981
dc.identifier.urihttps://doi.org/10.1002/hyp.7534
dc.identifier.urihttps://hdl.handle.net/20.500.11776/6504
dc.identifier.volume24
dc.identifier.wosWOS:000276161600003
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorŞahin, Sinan
dc.language.isoen
dc.publisherWiley
dc.relation.ispartofHydrological Processes
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectTurkey
dc.subjectmissing value estimation
dc.subjecthomogeneity
dc.subjectmeteorological data set
dc.subjecttemperature
dc.subjectQuality-Control
dc.subjectDetecting Inhomogeneities
dc.subjectMinimum Temperatures
dc.subjectBivariate Test
dc.subjectTime-Series
dc.subjectPrecipitation
dc.subjectTrends
dc.subjectMaximum
dc.subjectTurkey
dc.subjectShift
dc.titleHomogeneity analysis of Turkish meteorological data set
dc.typeArticle

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