Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/58048
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dc.contributor.authorDikbaş, Fatih-
dc.date.accessioned2024-10-20T16:20:48Z-
dc.date.available2024-10-20T16:20:48Z-
dc.date.issued2024-
dc.identifier.issn0324-6329-
dc.identifier.urihttps://doi.org/10.28974/idojaras.2024.3.6-
dc.identifier.urihttps://hdl.handle.net/11499/58048-
dc.description.abstractIt is well known that the recent global warming intensifies the magnitude of rainfalls due to the increase in water content in the atmosphere. Therefore, the probability of exceeding the previously observed extreme precipitation values also increases with the experienced climate change, and forecasting extreme weather events is becoming more important. This paper presents a new polynomial regression approach and software (PolReg), where future extreme precipitations exceeding all previous observations are estimated for each month of year by using prediction bounds with a level of certainty at 95%. The presented method determines the degrees and coefficients of best-fitting polynomials for each precipitation station and forecasts the expected extreme value for each month of year by using the determined polynomials. The performance of the method is tested by removing and estimating a total of 792 highest observed monthly total precipitation values of 66 precipitation stations in Turkey (the highest observation for each month of year for each station). The results show that the proposed method and the provided software have a high performance and accuracy in estimating future precipitation extremes and might be applied in many disciplines dealing with forecasting probable extreme values.en_US
dc.language.isoenen_US
dc.publisherHungarian Meteorological Serviceen_US
dc.relation.ispartofIdojarasen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectforecasting extreme precipitationsen_US
dc.subjectpolynomial regressionen_US
dc.subjectdata-driven modelingen_US
dc.subjecthydrometeorologyen_US
dc.subjectTurkeyen_US
dc.subjectRiver-Basinen_US
dc.subjectRainfallen_US
dc.subjectTemperatureen_US
dc.subjectVariabilityen_US
dc.subjectTrendsen_US
dc.subjectUncertaintiesen_US
dc.subjectProbabilityen_US
dc.subjectPredictionsen_US
dc.subjectImputationen_US
dc.subjectThresholden_US
dc.titleForecasting extreme precipitations by using polynomial regressionen_US
dc.typeArticleen_US
dc.identifier.volume128en_US
dc.identifier.issue3en_US
dc.departmentPamukkale Universityen_US
dc.identifier.doi10.28974/idojaras.2024.3.6-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.authorscopusid22957038900-
dc.identifier.scopus2-s2.0-85204674146en_US
dc.identifier.wosWOS:001318982800006en_US
dc.institutionauthor-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypeArticle-
item.grantfulltextopen-
crisitem.author.dept10.02. Civil Engineering-
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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