Publication:
Evaluation of the suitability of ncep/ncar, era-interim and, era5 reanalysis data sets for statistical downscaling in the eastern black sea basin, Turkey

dc.contributor.authorNacar, Sinan
dc.contributor.authorOkkan, Umut
dc.contributor.buuauthorKankal, Murat
dc.contributor.buuauthorKANKAL, MURAT
dc.contributor.departmentMühendislik Fakültesi
dc.contributor.departmentİnşaat Mühendisliği Bölümü
dc.contributor.orcid0000-0003-0897-4742
dc.contributor.researcheridAAZ-6851-2020
dc.date.accessioned2024-10-31T06:02:08Z
dc.date.available2024-10-31T06:02:08Z
dc.date.issued2022-04-01
dc.description.abstractClimate community frequently uses gridded reanalysis data sets in their climate change impact studies. However, these studies for a region yield more realistic results depending on the rigorous analysis of the reanalysis data sets for this region. This study aims to determine the most suitable reanalysis data set for the statistical downscaling method in the Eastern Black Sea Basin, one of Turkey's most important hydrological basins owing to the precipitation it receives throughout the year. For this purpose, the monthly mean temperature and total precipitation data measured from the 12 meteorological stations and 12 large-scale predictors of the NCEP/NCAR, ERA-Interim, and ERA5 reanalysis data sets were used. The multivariate adaptive regression splines (MARS) and conventional regression analysis with linear and exponential functions were used to create effective statistical downscaling models. For evaluating and comparing the performance of the downscaling models with three different reanalysis data set, four performance statistics (root means square error, scatter index, mean absolute error, and the Nash Sutcliffe coefficient of efficiency) were used. Besides, the relative importance of the input variables of the models was determined. The study revealed that the values obtained from the models of ERA5 were closer to the precipitation and temperature values measured from the meteorological stations. In addition, the model performances with three reanalysis data sets for the temperature variable were very close to each other. The study results have shown that the MARS method, which gives the highest performance values, can be used successfully as a statistical downscaling method in climate change impact studies.
dc.identifier.doi10.1007/s00703-022-00878-6
dc.identifier.issn0177-7971
dc.identifier.issue2
dc.identifier.urihttps://doi.org/10.1007/s00703-022-00878-6
dc.identifier.urihttps://hdl.handle.net/11452/47232
dc.identifier.volume134
dc.identifier.wos000770314900001
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherSpringer Wien
dc.relation.journalMeteorology And Atmospheric Physics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectAdaptive regression spline
dc.subjectLearning based optimization
dc.subjectClimate-change scenarios
dc.subjectSupport vector
dc.subjectRegional climate
dc.subjectTime-series
dc.subjectPrecipitation
dc.subjectModel
dc.subjectTemperature
dc.subjectCirculation
dc.subjectScience & technology
dc.subjectPhysical sciences
dc.subjectMeteorology & atmospheric sciences
dc.titleEvaluation of the suitability of ncep/ncar, era-interim and, era5 reanalysis data sets for statistical downscaling in the eastern black sea basin, Turkey
dc.typeArticle
dspace.entity.typePublication
local.contributor.departmentMühendislik Fakültesi/İnşaat Mühendisliği Bölümü
relation.isAuthorOfPublication875454d9-443c-4a31-9bce-5442b8431fdb
relation.isAuthorOfPublication.latestForDiscovery875454d9-443c-4a31-9bce-5442b8431fdb

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