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简介：一个数字实验被执行使用天气研究并且预报(WRF)分析惯性严肃的产生和繁殖的模型在在2014年8月17日发生在四川区域的山论的暴风雨期间挥手。为了检验惯性严肃波浪的空间、时间的结构并且识别波浪，打字，三wavenumber频率光谱分析方法(Fourier分析，跨spectral分析，和小浪跨光谱的分析)被使用。在暴风雨期间，惯性严肃波浪出现在10-14km的高度，与80-100min的时期和40-50km的波长。这些波浪在一座山上被产生并且宣传以15-20ms1的平均速度东方。同时，在波浪和积累的降水在那里显示出的重建的惯性严肃之间的比较是在他们之间的一个相互的提升过程。理查森数字和得分者参数被用来证明东方动人的惯性严肃波浪与有利反射镜和批评水平条件在一个有效大气的ducting地区被套住，它是波浪的长寿的主要原因。最后，测试敏感到加热的地面和diabatic的数字实验被进行，并且结果建议地面并且diabatic加热的合作效果贡献了波浪的繁殖和改进。

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简介：Background:Overthelastdecadesinteresthasgrownonhowclimatechangeimpactsforestresources.However,oneofthemainconstraintsisthatmeteorologicalstationsarefiddledwithmissingclimaticdata.Thisstudycomparedfiveapproachesforestimatingmonthlyprecipitationrecords:inversedistanceweighting(IDW),amodificationofIDWthatincludeselevationdifferencesbetweentargetandneighboringstations(IDWm),correlationcoefficientweighting(CCW),multiplelinearregression(MLR)andartificialneuralnetworks(ANN).Methods:Acompleteseriesofmonthlyprecipitationrecords(199.5-2012)fromtwentymeteorologicalstationslocatedincentralChilewereused.Twotargetstationswereselectedandtheirneighboringstations,locatedwithinaradiusof25km(3stations)and50km(9stations),wereidentified.Cross-validationwasusedforevaluatingtheaccuracyoftheestimationapproaches.Theperformanceandpredictivecapabilityoftheapproacheswereevaluatedusingtheratiooftherootmeansquareerrortothestandarddeviationofmeasureddata(RSR),thepercentbias(PBIAS),andtheNash-Sutcliffeefficiency(NSE).Fortestingthemainandinteractiveeffectsoftheradiusofinfluenceandestimationapproaches,atwo-levelfactorialdesignconsideringthetargetstationastheblockingfactorwasused.Results:ANNandMLRshowedthebeststatisticsforallthestationsandradiusofinfluence.However,theseapproacheswerenotsignificantlydifferentwithIDWm.InclusionofelevationdifferencesintoIDWsignificantlyimprovedIDWmestimates.Intermsofprecision,similarestimateswereobtainedwhenapplyingANN,MLRorIDWm,andtheradiusofinfluencehadasignificantinfluenceontheirestimates,weconcludethatestimatesbasedonnineneighboringstationslocatedwithinaradiusof50kmareneededforcompletingmissingmonthlyprecipitationdatainregionswithcomplextopography.Conclusions:ItisconcludedthatapproachesbasedonANN,MLRandIDWmhadthebestperformanceintwosectorslocatedinso

简介：Twoassumptionsaretypicallymadewhenradarechosignalsfromprecipitationareanalyzedtodeterminethemicro-physicalparametersofraindrops:(1)theraindropsareassumedtobespherical;(2)multiplescatteringeffectsareignored.Radarcrosssections(RCS)areusuallycalculatedusingRayleigh'sscatteringequationwiththesimpleadditionmethodintheradarmeteorologicalequation.Weinvestigatetheextenttowhichconsiderationoftheeffectsofmultiplescatteringandofthenon-sphericalshapeswithinactualraindropswarmswouldresultinRCSvaluessignificantlydifferentfromthoseobtainedbyconventionalanalyticalmethods.First,weestablishsphericalandnon-sphericalraindropmodels,withGamma,JD,JT,andMPsizedistributions,respectively.WethenuseXFDTDsoftwaretocalculatetheradarcrosssectionsoftheaboveraindropmodelsattheS,C,XandKuradarbands.OurXFDTDresultsarethencomparedtoRCSvaluescalculatedbytheRayleighapproximationwithsimpleadditionmethods.Wefindthat:(1)RCSvaluescalculatedusingmultiplescatteringXFDTDsoftwarediffersignificantlyfromthosecalculatedbythesimpleadditionmethodatthesamebandforthesamemodel.Inparticular,forthesphericalraindropmodels,therelativedifferencesinRCSvaluesbetweenthemethodsrangefromamaximumof89.649%toaminimumof43.701%;forthenon-sphericalraindropmodels,therelativedifferencesrangefromamaximumof85.868%toaminimumof11.875%.(2)OurmultiplescatteringXFDTDresults,comparedtothoseobtainedfromtheRayleighformula,againdifferatallfoursizedistributions,byrelativeerrorsof169.522%,37.176%,216.455%,and63.428%,respectively.Whennonsphericaleffectsareconsidered,differencesinRCSvaluesbetweenourXFDTDcalculationsandRayleighcalculationsaresmaller;attheabovefoursizedistributionstherelativeerrorsare0.213%,0.171%,7.683%,and44.514%,respectively.RCSvaluescomputedbyconsideringmultiplescatteringandnon-sphericalparticleshapesarelargerthanRayleighRCS

简介：Theroleofwintersea-iceintheLabradorSeaasaprecursorforprecipitationanomaliesoversoutheasternNorthAmericaandWesternEuropeinthefollowingspringisinvestigated.Ingeneralterms,astheseaiceincreases,theprecipitationalsoincreases.Inmoredetail,however,analysesindicatethatboththewintersea-iceandtheseasurfacetemperature（SST）anomaliesrelatedtoincreasesinwintersea-iceintheLabradorSeacanpersistintothefollowingspring.Thesefeaturesplayaforcingroleinthespringatmosphere,whichmaybethephysicalmechanismbehindtheobservationalrelationshipbetweenthewintersea-iceandspringprecipitationanomalies.TheoceanicforcingsinspringincludeArcticsea-iceanomaliesandSSTanomaliesinthetropicalPacificandhigh-latitudeNorthAtlantic.Multi-modelCoupledModelIntercomparisonProjectPhase5andAtmosphericModelIntercomparisonProjectsimulationresultsshowthattheatmosphericcirculationresponsetothecombinationofsea-iceandSSTissimilartothatobserved,whichsuggeststhattheoceanicforcingsareindeedthephysicalreasonfortheenhancedspringprecipitation.SensitivityexperimentsconductedusinganatmosphericgeneralcirculationmodelindicatethattheincreasesinprecipitationoversoutheasternNorthAmericaaremainlyattributabletotheeffectoftheSSTanomalies,whiletheincreasesoverWesternEuropearemainlyduetothesea-iceanomalies.AlthoughmodelsimulationsrevealthattheSSTanomaliesplaytheprimaryroleintheprecipitationanomaliesoversoutheasternNorthAmerica,theobservationalstatisticalanalysesindicatethattheareaofsea-iceintheLabradorSeaseemstobetheprecursorthatbestpredictsthespringprecipitationanomaly.

简介：ThisstudyinvestigatesclassificationanddiurnalvariationsoftheprecipitationechoesoverthecentralTibetanPlateaubasedontheobservationscollectedfromaC-bandvertically-pointingfrequency-modulatedcontinuous-wave(C-FMCW)radarduringtheThirdTibetanPlateauAtmosphericScientificExperiment(TIPEX-Ⅲ)2014-IntensiveObservationPeriod(2014-IOP).Theresultsshowthat51.32%oftheverticalprofileshavevalidechoeswithreflectivity>-10dBZ,and35.06%ofthevalidechoprofilesproduceprecipitationattheground(precipitationprofiles);stratiformprecipitationwithanevidentbright-bandsignature,weakconvectiveprecipitation,andstrongconvectiveprecipitationaccountfor52.03%,42.98%,and4.99%oftheprecipitationprofiles,respectively.About59.84%oftheprecipitationoccursintheafternoontomidnight,while40.16%oftheprecipitationwithweakerintensityisobservedinthenocturnalhoursandinthemorning.Diurnalvariationofoccurrencefrequencyofprecipitationshowsamajorpeakduring2100-2200LST(localsolartime)with59.02%beingthestratiformprecipitation;thesecondarypeakappearsduring1300-1400LSTwith59.71%beingtheweakconvectiveprecipitation;thestrongconvectiveprecipitationoccursmostly(81.83%)intheafternoonandeveningwithtwopeaksover1200-1300and1700-1800LST,respectively.Startingfromapproximately1100LST,precipitationechoesdevelopwithenhancedverticalairmotion,elevatedechotop,andincreasingradarreflectivity.Intenseupwardairmotionoccursmostfrequentlyin1700-1800LSTwithasecondarypeakin1100-1400LST,whilethetopsofprecipitationechoesandintenseupwardairmotionreachtheirhighestlevelsduring1600-1800LST.Theatmosphericconditionsintheearlymorningaredisadvantageousforconvectiveinitiationanddevelopment.Aroundnoon,theconvectiveavailablepotentialenergy(CAPE)increasesmarkedly,convectiveinhibition(CIN)isgenerallysmall,andasuper-dry-adiabaticlayerispresentnear