Evaluating the effect of the statistical downscaling method on monthly precipitation estimates of global climate models

Basit Öğe Kaydı
dc.authoridIRVEM, AHMET/0000-0002-3838-1924
dc.contributor.authorOzbuldu, M.
dc.contributor.authorIrvem, A.
dc.date.accessioned2024-09-18T20:25:18Z
dc.date.available2024-09-18T20:25:18Z
dc.date.issued2021
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractResearches to foresee the possible effects of climate change on the environment and living beings for taking necessary precautions on time have increased in recent years. In the improvement of these studies, especially the reduction of estimation errors by downscaling the outputs of global climate models played an important role. In this study, the effect of the statistical downscaling method on improving the prediction accuracy of global climate models (GCM) was investigated. For this purpose, a statistical downscaling method based on multiple linear regression was applied to improve monthly precipitation estimates of 3 different GCM (CanESM2, GISS-E2H, and CSIRO Mk 3-6-0) used in future climate predictions. The effect of this method on improving GCM prediction accuracy was determined by comparing the results obtained as a result of scale reduction with the results obtained from the observation station. The predictive parameters for global climate models were determined using downscaling methods by applying correlation analysis for the study area. As a result of this analysis, it was seen that the air temperature and specific humidity values at the pressure level of 925 hPa and the geopotential height value at the 300 hPa pressure level had the best correlation for the years 1970-2005. The usability of three different global climate models for the forecast of future precipitation in the Antakya district of Hatay province was investigated using multiple linear regression analysis, one of the downscaling methods. As a result of the statistical analysis, it was seen that the use of the downscaling method increased the accuracy of all prediction models.en_US
dc.identifier.doi10.30955/gnj.003458
dc.identifier.endpage240en_US
dc.identifier.issn1790-7632
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-85120165021en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage232en_US
dc.identifier.urihttps://doi.org/10.30955/gnj.003458
dc.identifier.urihttps://hdl.handle.net/20.500.12483/10229
dc.identifier.volume23en_US
dc.identifier.wosWOS:000709770400009en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherGlobal Network Environmental Science & Technologyen_US
dc.relation.ispartofGlobal Nest Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectGCMen_US
dc.subjectstatistical downscalingen_US
dc.subjectpredictor selectionen_US
dc.subjectreanalysis dataen_US
dc.subjecthatayen_US
dc.titleEvaluating the effect of the statistical downscaling method on monthly precipitation estimates of global climate modelsen_US
dc.typeArticleen_US

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
Tam Metin / Full Text
Boyut:
738.68 KB
Biçim:
Adobe Portable Document Format
İndir

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu