Page 89 - 2022年第53卷第8期
P. 89

SpatialdownscalingofMSWEPdatasetbasedonATAK and
                                             itsinfluenceonrainfallmerging

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                                YUNZhaode,HUQingfang ,WANGYintang ,LILingjie ,
                                                          1
                                                                          1
                                              WANGLeizhi,CHENJiandong
                              (1.NanjingHydraulicResearchInstitute,StateKeyLaboratoryofHydrology - WaterResources&
                                          HydraulicEngineeringScience,Nanjing 210029,China;
                                  2.YangtzeInstituteforConservationandDevelopment,Nanjing 210098,China)
                  Abstract:Globalprecipitationdatasetsprovideanewwaytoobtainlarge - scaleprecipitationspatialdistribution,
                  butthelowspatialresolutionhasalwaysbeenoneofthemaingapsrestrictingtheirapplicationsatthebasinor
                  regionalscale.Therefore,spatialdownscalingmethodforglobalprecipitationdatasetsisofsignificantvaluebothin
                  theoryandpractice.UsingtwostatisticalmethodsincludingAreatoAreaKriging(ATAK)andInverseDistance
                  Weighted(IDW), Multi - SourceWeighted - EnsemblePrecipitation (MSWEP) gridded rainfallisspatially
                  downscaledfrom0.1° × 0.1°to0.02° × 0.02°intheHanjiangRiverBasin ,withoutconsideringthegroundrainfall
                  dataandanyauxiliaryinformation.TheresultsshowthatalthoughthemonthlyrainfallfieldsobtainedbyATAK
                  downscalingisnotratherdifferentfrom IDW intermsofstatisticalaccuracyindices,however,theyimprovethe
                  abilitytodescribethelocalvariationofmonthlyrainfallandovercomethesmoothingeffectofIDW toacertain
                  extent.Furthermore ,throughGeographicallyWeightedRegression(GWR),thedisaggregatedMSWEPdataby
                  ATAKandIDW andtherawMSWEPdatawithoutspatialdownscalingareusedasthebackgroundfieldstomerge
                  thegaugesobservedrainfallrespectively.Itisfoundthatthemonthlyfusedprecipitationobtainedusingthethree
                  differentkindsofbackgroundfieldsaregenerallysimilarinspatialpatterns ,andtheaccuracystatisticsarealso
                  quiteclose.However ,amongthethreekindsofmergedprecipitationdatasets,therearestillsomedifferencesin
                  thespatialcontinuityanddetails.Inthecaseofdensegroundrainfallgaugeswithinthestudyarea ,theinfluenceof
                  backgroundfield differenceson themergingresultsofMSWEP and gaugeobserved precipitation cannotbe
                  completelyeliminated , and even maybeamplified locally.Therefore, strengthen thecomparison ofspatial
                  downscalingmethodsforglobalprecipitationdataandchoosingtheappropriatemethodisvital.Theseconclusions
                  provideimportantreferencesforthespatialdownscalingofglobalprecipitationdatasetsandaccurateestimationof
                  rainfallfields.
                  Keywords:spatialdownscaling;rainfallmerging;MSWEP;ATAK;GWR;HanjiangRiverBasin


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