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WRF模式对江苏如东地区风速预报的检验分析.docx

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WRF模式对江苏如东地区风速预报的检验分析 Title:VerificationandAnalysisofWindSpeedForecastusingWRFModelinRudongArea,JiangsuProvince Abstract: Accuratewindspeedforecastingiscrucialforvarioussectors,includingenergygeneration,transportation,andagriculture.Inthisstudy,weevaluatetheperformanceoftheWeatherResearchandForecasting(WRF)modelinpredictingwindspeedsinRudong,JiangsuProvince,China.TheWRFmodeliswidelyusedinweatherpredictionduetoitsabilitytosimulatelocalatmosphericprocesses.Verificationandanalysisofwindspeedforecastsareconductedusingstatisticalmetricsandgraphicalcomparisonswithobservations. 1.Introduction Windenergyisanimportantrenewableenergysource,andaccuratewindspeedforecastsareessentialforitseffectiveutilization.Theavailabilityofaccurateandreliablewindspeedforecastsallowsforoptimalplanningandoperationsinwindfarms.TheWRFmodelhasbeenextensivelyusedinwindspeedforecastingduetoitsexcellentperformanceinsimulatingatmosphericprocesses.However,itisessentialtoverifyandassessthemodel'sperformancetoensureitsreliabilityforspecificregions. 2.DataandMethodology ThestudyutilizesobservationalwindspeeddatafrommeteorologicalstationsintheRudongarea.ThesimulationdataareobtainedfromtheWRFmodel,whichisrunonahigh-performancecomputingsystem.Themodelisconfiguredusinghigh-resolutionterrainandland-usedataforaccuraterepresentationoflocalatmosphericprocesses.Statisticalmetricssuchasrootmeansquareerror(RMSE),meanabsoluteerror(MAE),andcorrelationcoefficient(r)areemployedforperformanceevaluation.Graphicalcomparisonsofobservedandpredictedwindspeedsarealsoconducted. 3.ResultsandDiscussion Thestatisticalevaluationmetricsarecalculatedfordifferentleadtimesofforecast,rangingfromshort-termtolong-termforecasts.TheRMSE,MAE,andrvaluesareanalyzedtodeterminethemodel'sskillinpredictingwindspeedsinvariousforecastintervals.TheresultsrevealthattheWRFmodelperformswellinshort-termforecastsupto24hours,withahighcorrelationcoefficientandlowerrorvalues.However,astheforecastleadtimeincreasesbeyond24hours,themodel'sperformanceslightlydet