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简介：在2005的四个landfalling台风盒子与全球/地区性的吸收和预言系统(葡萄)模型为数字模拟研究被选择。包括台风轨道的预言，模型的表演的初步的评价结果乍见陆地预定，地点和紧张，等等，被介绍，错误的来源被分析。由模型的台风中心的24小时的距离预报错误被显示是大约131km，当48小时的错误是252km时。模型是相对在预报更熟练乍见陆地时间和地点比那些紧张在乍见陆地。平均，24小时的预报比48小时的稍微好。数据影响的分析显示异乎寻常的观察数据的吸收为模型模拟的改进是必要的。模型能被增加模型分辨率模仿mesoscale和好规模系统并且由改进地面精炼处理的方法也改进。

简介：Radiosondeprofilesoftemperatureanddewpointtemperaturefromonestationareusedtoforecast12-hprecipita-tionoverNairobi,Kenya.Theforecastschemeisbasedonstatisticalregressionmodelling.Fourpredictorsarederivedfromdatatouseinaprognosticequationtoget12-hprecipitationforecast.Observedandpredictedrainfallvaluesareplottedonagraphagainsttime.Forecastverificationshowsthattheforecastsarepositivelycorrelatedwithobservations.

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简介：公共天气服务是向向用户提供概率的天气预报的trending，代替传统的确定的预报。概率的预报技术不断地正在被改进优化可得到的预报信息。预报(BPF)的贝叶斯的处理器，为概率的预报的一个新统计方法，能根据在那个预报系统产生的观察和预报之间的历史的统计关系把一张确定的预报转变成一张概率的预报。这种技术在确定说明一个确定的预报系统的典型预报性能预报无常。meta-Gaussian可能性的模型对有单调可能性的比率的许多随机的依赖结构合适。收养这种可能性的模特儿的meta-GaussianBPF能因此越过许多地被使用，包括气象学和水文学。有二个连续随机的变量和正常线性的BPF的Bayes定理简短被介绍。为用一个单个预言者的连续predictand的meta-GaussianBPF然后被介绍并且讨论。meta-GaussianBPF的表演在一个初步的实验被测试。在在长沙和武汉车站的0000UTC的每日的表面温度的控制预报被用作确定的预报数据。这些控制预报从整体预言被拿，一96-h铅时间由中国气象学的管理的国家气象学的中心产生了，中等范围的天气的欧洲中心预报，并且US公民为在2008年1月期间的环境预言集中。实验的结果证明meta-GaussianBPF能从三整体预言中的任何一个把表面温度的一张确定的控制预报转变成表面温度的一张有用概率的预报。这些概率的预报确定控制预报的无常；因此，概率的预报的表演基于内在的确定的控制预报的来源不同。

简介：Theimpactsoftheenhancedmodel’smoistphysicsandhorizontalresolutionupontheQPFs(quantitativeprecipitationforecasts)areinvestigatedbyapplyingtheHIRLAM(highresolutionlimitedareamodel)tothesummerheavy-raincasesinChina.Theperformanceofthecontrolrun,forwhicha0.5°×0.5°gridspacingandatraditional“grid-boxsupersaturationremoval+Kuotypeconvectiveparamerization”areusedasthemoistphysics,iscomparedwiththatofthesensitivityrunswithanenhancedmodel’smoistphysics(Sundqvistscheme)andanincreasedhorizontalresolution(0.25°×0.25°),respectively.Theresultsshow:(1)Theenhancedmoistphysicsscheme(Sundqvistscheme),byintroducingthecloudwatercontentasanadditionalprognosticvariableandtakingintoaccountbrieflyofthemicrophysicsinvolvedinthecloud-rainconversion,doesbringimprovementsinthemodel’sQPFs.AlthoughthedeterioratedQPFsalsooccuroccasionally,theimprovementsarefoundinthemajorityofthecases,indicatingthegreatpotentialfortheimprovementofQPFsbyenhancingthemodel’smoistphysics.(2)Byincreasingthemodel’shorizontalresolutionfrom0.5°×0.5°,whichisalreadyquitehighcomparedwiththatoftheconventionalatmosphericsoundings,to0.25°×0.25°withoutthesimultaneousenhancementinmodelphysicsandobjectiveanalysis,theimprovementsinQPFsareverylimited.Withhigherresolution,althoughslightameliorationinlocatingtherainfallcentersandinresolvingsomefinerstructuresofprecipitationpatternaremade,thenumberofthemis-predictedfinestructuresinrainfallfieldincreaseswiththeenhancedmodelresolutionaswell.

简介：InthispaperweinvestigatetheimpactoftheAtmosphericInfra-RedSounder(AIRS)temperatureretrievalsondataassimilationandtheresultingforecastsusingthefour-dimensionalLocalEnsembleTransformKalmanFilter(LETKF)dataassimilationschemeandareducedresolutionversionoftheNCEPGlobalForecastSystem(GFS).OurresultsindicatethattheAIRStemperatureretrievalshaveasignificantandconsistentpositiveimpactintheSouthernHemisphericextratropicsonbothanalysesandforecasts,whichisfoundnotonlyinthetemperaturefieldbutalsoinothervariables.IntropicsandtheNorthernHemisphericextratropicstheseimpactsaresmaller,butarestillgenerallypositiveorneutral.

简介：Thispaperintegratesgeneticalgorithmandneuralnetworktechniquestobuildnewtemporalpredictinganalysistoolsforgeographicinformationsystem(GIS).ThesenewGIStoolscanbereadilyappliedinapracticalandappropriatemannerinspatialandtemporalresearchtopatchthegapsinGISdataminingandknowledgediscoveryfunctions.ThespecificachievementhereistheintegrationofrelatedartificialintelligenttechnologiesintoGISsoftwaretoestablishaconceptualspatialandtemporalanalysisframework.And,byusingthisframeworktodevelopanartificialintelligentspatialandtemporalinformationanalyst(ASIA)systemwhichthenisfullyutilizedintheexistingGISpackage.Thisstudyofairpollutantsforecastingprovidesageographicalpracticalcasetoprovetherationalizationandjustnessoftheconceptualtemporalanalysisframework.

简介：Daily850-hPameridionalwindfieldsinEastAsiafromMarchtoSeptember2002wereusedtoestablishamodeloftheprincipaloscillationpattern(POP).Thismodelwasthenusedtoconductindependentextended-rangeforecastsoftheprincipaltemporalandspatialvariationsinthelow-frequencymeridionalwindfieldonatimescaleof20-30days.ThesevariationsaffecttheoccurrenceofheavyprecipitationeventsinthelowerreachesoftheYangtzeRivervalley(LYRV).Theresultsof135forecastexperimentsduringthesummerhalfyearshowthatthepredictedandobservedanomaliesarestronglycorrelatedataleadtimeof20days(meancorrelationgreaterthan0.50).Thisstrongcorrelationindicatesthatthemodeliscapableofaccuratelyforecastingthelow-frequencyvariationsinmeridionalwindthatcorrespondedtothe3heavyprecipitationeventsintheLYRVduringthesummerof2002.Furtherforecastexperimentsbasedondatafrommultipleyearswithsignificant20-30-dayoscillationsshowthatthesepredictionmodesareeffectivetoolsforforecastingthespace-timeevolutionofthelow-frequencycirculation.ThesefindingsofferpotentialforimprovingtheaccuracyofforecastsofheavyprecipitationovertheLYRVatleadtimesof3-4weeks.