Statistical downscaling of monthly precipitation using NCEP/NCAR reanalysis data for tahtali river basin in Turkey

Basit Öğe Kaydı
dc.authorid8840536700
dc.authorid36802507700
dc.contributor.authorFistikoglu O.
dc.contributor.authorOkkan U.
dc.date.accessioned20.04.201910:49:12
dc.date.accessioned2019-04-20T21:44:53Z
dc.date.available20.04.201910:49:12
dc.date.available2019-04-20T21:44:53Z
dc.date.issued2010
dc.departmentBayburt Üniversitesien_US
dc.description.abstractStatistical downscaling methods describe a statistical relationship between large-scale atmospheric variables such as temperature, humidity, precipitation, etc., and local-scale meteorological variables like precipitation. This study examines the potential predictor variables selected from the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis data set for downscaling monthly precipitation in Tahtali watershed in Turkey. An approach based on the assessment of all possible regression types was used to select the predictors among the NCEP reanalysis data set, and artificial neural network (ANN)-based downscaling models were designed separately for each station in the basin. The results of the study showed that precipitation, surface and sea level pressures, air temperatures at surface, 850-, 500-, and 200-hPa pressure levels, and geopotential heights at 850- and 200-hPa pressure levels are the most explanatory NCEP/NCAR parameters for the study area. It was concluded that ANN-based downscaling models can be implemented to downscale coarse-scale atmospheric parameters to monthly precipitation at station scale by using the above parameters as inputs in the study area. © 2011 ASCE.en_US
dc.identifier.doi10.1061/(ASCE)HE.1943-5584.0000300
dc.identifier.endpage164
dc.identifier.issn1084-0699
dc.identifier.issue2
dc.identifier.scopus2-s2.0-78651485804en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage157
dc.identifier.urihttps://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000300
dc.identifier.urihttps://hdl.handle.net/20.500.12403/961
dc.identifier.volume16
dc.identifier.wosWOS:000286219200007en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Hydrologic Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectStatistical downscaling
dc.subjectAir temperature
dc.subjectArtificial Neural Network
dc.subjectAtmospheric parameters
dc.subjectAtmospheric variables
dc.subjectData sets
dc.subjectDown-scaling
dc.subjectGeopotential height
dc.subjectMeteorological variables
dc.subjectNational center for atmospheric researches
dc.subjectNational center for environmental predictions
dc.subjectNCEP reanalysis
dc.subjectNCEP/NCAR
dc.subjectPredictor variables
dc.subjectPressure level
dc.subjectReanalysis
dc.subjectRiver basins
dc.subjectSea level pressure
dc.subjectStatistical downscaling
dc.subjectStatistical relationship
dc.subjectStudy areas
dc.subjectClimatology
dc.subjectNeural networks
dc.subjectSea level
dc.subjectStatistics
dc.subjectWatersheds
dc.subjectAtmospheric humidity
dc.subjectair temperature
dc.subjectartificial neural network
dc.subjectatmospheric pressure
dc.subjectdownscaling
dc.subjectgeopotential
dc.subjectnumerical model
dc.subjectprecipitation (climatology)
dc.subjectprediction
dc.subjectregression analysis
dc.subjectsea level pressure
dc.subjectstatistical analysis
dc.subjectsurface pressure
dc.subjectwatershed
dc.subjectIzmir [Turkey]
dc.subjectTahtali Basin
dc.subjectTurkey
dc.subjectStatistical downscaling
dc.subjectAir temperature
dc.subjectArtificial Neural Network
dc.subjectAtmospheric parameters
dc.subjectAtmospheric variables
dc.subjectData sets
dc.subjectDown-scaling
dc.subjectGeopotential height
dc.subjectMeteorological variables
dc.subjectNational center for atmospheric researches
dc.subjectNational center for environmental predictions
dc.subjectNCEP reanalysis
dc.subjectNCEP/NCAR
dc.subjectPredictor variables
dc.subjectPressure level
dc.subjectReanalysis
dc.subjectRiver basins
dc.subjectSea level pressure
dc.subjectStatistical downscaling
dc.subjectStatistical relationship
dc.subjectStudy areas
dc.subjectClimatology
dc.subjectNeural networks
dc.subjectSea level
dc.subjectStatistics
dc.subjectWatersheds
dc.subjectAtmospheric humidity
dc.subjectair temperature
dc.subjectartificial neural network
dc.subjectatmospheric pressure
dc.subjectdownscaling
dc.subjectgeopotential
dc.subjectnumerical model
dc.subjectprecipitation (climatology)
dc.subjectprediction
dc.subjectregression analysis
dc.subjectsea level pressure
dc.subjectstatistical analysis
dc.subjectsurface pressure
dc.subjectwatershed
dc.subjectIzmir [Turkey]
dc.subjectTahtali Basin
dc.subjectTurkey
dc.titleStatistical downscaling of monthly precipitation using NCEP/NCAR reanalysis data for tahtali river basin in Turkeyen_US
dc.typeArticleen_US

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