national urban database and access portal tool

NATIONAL URBAN DATABASE AND ACCESS PORTAL TOOLBy Jason Ching MiChael Brown steVen Burian Fei Chen ron CionCo adel hanna

torrin hultgren tiMothy MCPherson daVid sailor haider taha and daVid williaMs

C urrent mesoscale weather prediction and microscale dispersion models are limited in their ability to perform accurate assessments in urban areas A project called the National Urban Database

with Access Portal Tool (NUDAPT) is beginning to provide urban data and improve the parameterization of urban boundary-layer processes (Ching 2007) The impetus for NUDAPT came from results of an American Meteorological Society Board of Urban Environment survey and recommendations from the Office of the Federal Coordinator for Meteorologyrsquos (2005) Urban Environment Workshop Recognizing the need to address issues ranging from the prediction of exposure to a deadly toxic release to the assessment of health risk from poor air quality in urban areas NUDAPT was initiated by the US Environmental Protection Agency (US EPA) and supported by several federal and state agencies and private and academic institutions NUDAPT will fill a critical gap for providing refined and specialized information to fulfill the operational needs of new urban models (Dupont et al 2004 Chen et al 2006 2007a) and for running their applications (Chen 2007bc Taha 2008andashc) NUDAPT builds on the emergence of

Detail from one of the examples of a model sensitivity study showing PBL height for MM5 simulations See Fig 6 for more information

NUDAPT is a new Web-based urban data resource designed to facilitate implementation of the latest advanced urban meteorological air quality and climate modeling systems

bull newscienceandmodeladvancementsforurbanmeteorologymodeling

bull newdatasetsthatinclude newlyacquiredhigh-resolutionbuildingdatafor

mostlargecitiesintheUnitedStates evolvingdescriptionandresolutionofurbanland

usesandcoverdata griddeddaughterproducts includingurban

canopyparameters(UCPs)derivedfromthe high-resolutionbuildingandvegetationdata and

ancillarydataincludinggriddeddayandnight populationandanthropogenicheating

bull newtechnologytofacilitateNUDAPTrsquosdissemi-nationtoandusagebythemodelingcommunitywithWeb-baseddataaccesstoolsinacentralizeddatabase

NUDAPTisadatabaseanddecisionsupportsys-temthatishostedinaGeographicInformationSystem(GIS)environmentonanArcGISserverattheUni-versityofNorthCarolinaatChapelHillInconceptNUDAPToffersacentralcyberlocationforusers(researchersanalystsmodelersandpolicymakers)toaccesshigh-resolutionurban-scaledatacollectedbyconventionalandremotesensingmeasurementsthatareneededtocharacterizeandmodeltheurbanatmosphereCurrentlyNUDAPThostssuchdatafor33citiesintheUnitedStateswithdifferentdegreesofcoverageandcompletenessDataarepresentedintheiroriginalformatsuchasbuildingheightsdayandnightpopulationvegetationdataandlandsurfacetemperatureandradiationorinaldquoderivedrdquoformatsuchastheUCPswhichareusedinurbanmeteorologyandairqualitymodelingapplicationsAsanopensourcepublicdomainportalNUDAPTisdesignedwithtoolsforuserstosharedataexchangeinformationdiscussresultsandposttheirfindingspapersandconferencepresentations

URBAN MODELING NUDAPTwillprovidedataformodeldevelopmentandapplicationsinurbanareasMeteorologicalmodelsprovideinformationneeded forplanningandconductingairqualityassessmentsandfortransportinganddispersingairpollutantsandhazardoustoxicagentsMesoscalemodelsgeneratemeteorological fieldsused fornear-surfacetransportpredictionsbasedonsurfaceroughness(Zo)andstability(MoninndashObukovlength)parametersfortheprimarylanduseofeachmodelgridHoweverformanyurbanapplicationsgreaterspatialdetailandfidelityofthef lowfieldswillberequiredRecentadvancesinurbanmeteorologicalmodelsnowaccountfortheinfluenceofbuildingstreesandothermorphologicalfeaturesontheurbanboundarylayerf lowsGriddedUCPsusedinthemodelsrepresentthegeometricalcharacteristicsofthemorphologicalfeaturesthatincorporatetheinfluenceandcomplexitiesofspatialdistributionsofbuildingdensitiesandofbuildingsofdifferentshapessizesandmaterialcompositionaswellasotherdominanturbanfeatures(Fig1)Aerialsurveysarenowgenerat-inggeospatialdatathatcapturewithhighdefinition(1ndash5m)thethree-dimensionalgeometryofindividualandconglomeratesofbuildingsandvegetationinurbanareasfromwhichmodelUCPscanbederived(Burianetal200420062007abFig2)

Urbanizationschemeshavebeenintroducedintothefifth-generationPennsylvaniaStateUniversity(PSU)ndashNationalCenterforAtmosphericResearch(NCAR)MesoscaleModel (MM5) theWeatherResearchandForecasting(WRF)modelandothermodelsandarebeingtestedandevaluatedforgridsizesoftheorderof1kmorso(Dupontetal2004Chenetal20042007andashcOtteetal2004Chinetal2005)Thegoverningequations(introductionandimplementationofcanopy-layerparameterizations)foreachsystemweremodifiedanduniquesetsofUCPswereintroducedtorepresenttheirurbaniza-

AFFILIATIONS ChingmdashAtmospheric Modeling Division National Exposure Research Laboratory Office of Research and Development US Environmental Protection Agency Research Triangle Park North Carolina Brown and MCPhersonmdashLos Alamos National Laboratory Los Alamos New Mexico BurianmdashUniversity of Utah Salt Lake City Utah ChenmdashNational Center for Atmospheric Research Boulder Colorado CionComdashConsultant Roseville California hannamdashInstitute for the Environment University of North Carolina Chapel Hill North Carolina hultgrenmdashComputer Sciences Corporation Research Triangle Park North Carolina sailormdashPortland State University Portland Oregon tahamdashAltostratus Inc Martinez California

williaMsmdashUS Environmental Protection Agency Kansas City KansasCORRESPONDING AUTHOR Jason Ching Atmospheric Modeling Division National Exposure Research Laboratory US EPA MS (E243-04) Research Triangle Park NC 27711E-mail chingjasonepagov

The abstract for this article can be found in this issue following the table of contentsDOI1011752009BAMS26751

In final form 2 February 2009copy2009 American Meteorological Society

1158 august 2009|

tion(Table1Fig2)CurrenturbanizedversionsofMM5andWRFemployslightlydifferentlanduseschemesForMM5anurbanizedlandsurfacemodel[SoilModelforSubmesoscalesurbanizedversion(SM2U)Fig3]alsowasintroducedtoremovelimi-tationsofboththedominantlanduseschemeandthelimited(oneortwourbanclasses)classificationschemesofthestandardMM5versionInWRFtheNoahlandsurfacemodel(ChenandDudhia2001Eketal2003)oneofthreeoptions for land surfacephysicswascoupledtoasingleurbancanopymodel(UCMKusakaetal2001)and is applied tourbanareas

Computational f luiddynamics (Coirier et al2005Huberetal2004)and fast-responseurbandispersionmodels(Brown2004)arenowalsocapableofmodelingflowsaroundbuildingsandallrequiredetailed informationofthe urbanmorphologyespecia l ly the bui ldinggeometryOtherapplica-

tions(CioncoandEllefsen1998)requireinformationat a scale of 50ndash100mwhichfallsintermediatelybetween themesourban(1km)andthe1-to10-m-si zed bu i ld ing sca les Transportsimulationsatthis scale basedonob-jectiveanalysesschemesrequire high-resolutionbare-Earthdigitaleleva-tiondataandspecializedurbanmorphologicaldataincludinggeometryandmaterial characteristicsof individualbuildingsanddensityporosityandroughness of groups ofbuildings

F E AT U R E S A N D COMPONENTS OF NUDAPT Communi t y

design concept and features NUDAPTutilizesWeb-basedportaltechnologytoenableacommunity-basedmodelingresourceforhandlingthedatabasesandforfacilitatingcollaborationThedatabaseisarepositoryofmultipleheterogeneousdatasetsthatalladheretoaconsistentformatandmetadataspecificationanditallowsforscienceknowledgeintegrationandanefficientmeansofsharingandperformingdetailed

Fig 1 Schematic of urban canopy parameterization concept and methodology Here sky-view factor is the ratio of the radiation received in the street canyon to the hemispheric radiation above the canopy

Fig 2 Selected UCPs derived for 1-km2 cells for Harris County TX as used in the urbanized MM5 system PAD is plan area density and FAD is frontal area density of the buildings in each cell Note that each cell has a unique combination of UCPs

1159august 2009aMERICaN MEtEOROLOgICaL sOCIEtY |

analysisThedatabasesystemoperatesattwolevelsFirstdatasetsofhigh-resolutionfull-featuredigitalterrainelevationcontainingthethree-dimensionalrepresentationofurbanmorphologicalfeatures(egbuildingsandtrees)andextractedbuildingfoot-

printsandgeometriesresideatthelowestlayerTheportalmanagesaccessibilitytothislayertopreserveandmaintainasnecessaryproprietaryandothersensitivestatusrequirementsandtomanagethenet-workbandwidthburdenProcesseddataincluding

computedUCPs are inother layersat this levelThesecondlevelcontainstoolsandcapabilities forgeneralcommunityusageHereuserscanquerythedatabaseforrelevantdataprocessandretrievedatainaformthatismostcom-patiblewiththeirspecificmodeling requirementsand submit addit iona linformation to thedata-baseUsersofNUDAPTare encouraged to enteracycleof inquiryusageandimprovedinsightstoenabletheimprovements-to-modelingdividends

Theportal allows re-searchers the ability tosearchthroughindicesof

Fig 3 Schematic showing the urbanized version of MM5 based on (drag approach) DA-SM2U (Dupont et al 2004) Drag force approach is used in contrast to the standard roughness approach (left) Street canyon radiative fluxes are included and a land surface model (SM2U) provides for within-grid variations of fluxes

Table 1 UPCs used in MM5 and WRF

MM5 WRF

bull Mean and standard deviation of building and vegetation height bull Urban fraction

bull Plan areandashweighted mean building and vegetation height bull Building height ZR

bull Building height histograms bull Roughness for momentum above the urban canopy layer Z0 C

bull Plan area fraction and frontal area index at ground level bull Roughness for heat above the urban canopy layer Z0 HC

bull Plan area density bull Zero-displacement height above the urban canopy layer ZDC

bull Rooftop area density bull Percentage of urban canopy (PUC)

bull Frontal area density bull Sky-view factor (SVF)

bull Complete aspect ratio bull Building coverage ratio (roof area ratio) R

bull Building area ratio bull Normalized building height HGT

bull Building height-to-width ratio bull Drag coefficient by buildings CDS

bull Sky-view factor at ground level and as a function of height bull Buildings volumetric parameter AS

bull Aerodynamic roughness length and displacement height bull Anthropogenic heat AH

bull Mean orientation of streets bull Heat capacity of the roof wall and road

bull Surface fraction of vegetation roads rooftops water and impervious area

bull Heat conductivity of the roof wall and road

bull Albedo of the roof wall and road

bull Albedo bull Emissivity of the roof wall and road

bull Emissivity bull Roughness length for momentum of the roof wall and road

bull Building materials bull Roughness length for heat of the roof wall and road

1160 august 2009|

relevantdatasetsIthandlesWeb-baseddataextrac-tionandconversioninbothrasterandvectorformatsTheEnvironmentalSystemsResearchInstitutersquos(ESRIrsquos)relativelynewArcGISserverprovidesasingleenginewithmanydesirablefunctionsthatareneededtohandlerasterandvectordataArcObjectsJavaisthepreferablelanguagethusiftheserver-sideprocessingdemandbecomesseveretheapplicationeasilycanbeportedtoahigh-performanceLinuxenvironment

Databases NUDAPThasbeenpopulatedwithawidearrayofdatabasescriticaltoaccurateurbanmodelingThree-dimensionalbuildingsdatabaseduponairbornelightdetectionandranging(lidar)signals thatproducea full-featuredigitaleleva-tionmodel(DEM)adigitalterrainmodel(DTM)amicrometeorologicaldatabasegriddedUCPspopulationanthropogenicheatingandlanduselandcoverarethecoredatabasesincorporatedwithinNUDAPTtodate

high-resolution Building data Dataonbuildingssuchastheirsizeshapeorientationandrelativelocationtootherbuildingandurbanmorphologicalfeatures(treeshighwayoverpassesetc)arenowavailableforthelargesturbanareasintheUnitedStatesTheemergenceoftheseheretoforeunavail-abledatasetshasstimulatedtheuseofurbancanopyparameterizationsinmesoscalemeteorologicalmod-elingbecauseofthepossibilityofderivingthenec-essaryUCPsBuildingdatabasesingeneralcanbeextractedfrompairedstereographicaerialimagesbyphotogrammetricanalysistechniquesorfromDTMsacquiredbyairbornelidardatacollectionLidardataareacquiredbyflyinganairbornelaserscanneroveranurbanareaandcollectingreturnsignalsfrompairsofrapidlyemittedlaserpulsesThelaserreturnsareprocessedtoproduceterrainelevationdataproductsincludingfull-featureDEMsandbare-EarthDTMsThemorphologicalpropertiesofbuildingsandtrees(egheightandfootprintextent)canbedeterminedbysubtractingtheDTMfromtheDEMtoproduceadatabaseofheightsabovegroundlevelThemaxi-mumresolutionisdeterminedfromacombinationofaircraftspeedandlaserpulseratesandtypicallyisoftheorderof1ndash5mLidarisespeciallyenticingbecauseitprovidesahigh-resolutionrepresentationofurbanmorphologicalfeaturesespeciallybuildingsandtreesforentiremetropolitanareaswithamini-malsetofairplaneflyoversHoweverlidariscostlyandpresentsadatamanagementchallengegiventhemassivesizeofdatasets

ForexampletheHoustonTexasprototypecon-structedinNUDAPTnowcontains1-and5-mDEMandDTMdatabasesforalargesectionoftheHoustonmetropolitanareabasedona2001lidarflyover(seethenextsection)Ingeneralavarietyofautomatedandsemiautomatedapproachestoextractbuildingand treeobjects fromthe lidar-basedDEMandDTMhavebeendevelopedandprovidebuildingandtreedatacoverageinvectorformatforlargepartsofmostofthemajorcitiesintheUnitedStatesFortheHoustonprototypea650000-buildinggeographicinformationsystemdatasethasbeenincorporated

NUDAPTcontains archived copiesof lidarDEMandDTMdatacurrentlybeingacquiredbytheNationalGeospatialIntelligenceAgency(NGAformerlytheNationalImageryandMappingAgency)WhencompletedNGAwillhaveobtaineddatafromasmanyas133urbanareasThatprojectispartoftheHomelandSecurity InfrastructureProgram(HSIP) theNunn-Lugar-DomeniciAct(DefenseAgainstWeaponsofMassDestructionActof1996)establishedaprojectinwhichtheUSDepartmentofDefensewastaskedtohelprespondtochemicalbiologicalandnuclearincidencesinthe133urbancentersThesedata[togetherwiththeNationalMapProjectoftheUSGeologicalSurvey(USGS)]provideacriticalinfrastructureinformationbaseforHSIPWithcopiesofsuchdataformostmajorcitiesintheUnitedStatesNUDAPTwillprovidethebasisforderivingurbanmodelingparametersonanationalscale

MorPhology and urBan CanoPy ParaMeters Asin-dicatedearlier inadditiontoroughnessandbulkscalingparametersavarietyofgeometricalandden-sitydescriptorsofurbanmorphologicalfeaturesarenowbeingintroducedintoadvancedurbanmodels(Table1)FortheHoustonprototypeasanexampletheUCPdatabaseprovides250-mand1-kmresolu-tioncoverageofUCPsTheseparametershavebeencalculatedforeachgrid inthemodelingdomainbasedonthe650000-buildingdatabaseintegratedwiththelidarDEMandDTM(Burianetal2004)Figure2showsexamplesofmorphologicalandgeo-metricalparametersusedintheMM5griddedfor1-kmcellsforHoustonClearlyeachgridcellhasauniquesetofUCPsdescribingitsbuildingvegetationandlandusefeaturesconsequentlyeachcellhasauniqueinfluenceontheresultingmodelsimulationTheWRFmodelutilizesadifferentsetofUCPs(Table1)foritssingle-layerurbancanopyversion(Kusakaetal2001Chenetal20062007andashc)AtthistimeUCPshavebeenderivedfor44citiesundera


DepartmentofHomelandSecurity(DHS)-sponsoredurbandatabaseproject(Burianetal2007c)

anthroPogeniC heating and PoPulation data EnergyusageisconcentratedbutnotevenlydistributedinurbanareasInsomeareastheheatthatisgeneratedcanbeasignificantfractionoftheoverallenergybudgetintheurbanareaandthiscontributionvariesbothspatiallyandtemporallyacrossthecityGriddedfieldsofthisenergycomponentwouldreplacetheoversimplifiedfieldsbasedongrossassumptionsthattypicallyareusedinoperationalmodelsNUDAPTnowincludesAHasoneof itspriorityvariablesGriddedvaluesofAHat500-mresolution(Fig4)nowinNUDAPThavebeenpreparedusingmethodologydevelopedbySailorandLu(2004)andSailorandHart(2006)forrepresentativesummerandwinterdaysResultsofasensitivitystudyutilizinggriddedAHinNUDAPTareshown

TheNUDAPTprototypealsocontainsdaytimeandnighttimepopulationsgriddedat250maccordingtoMcPhersonandBrown(2003)andshowninFig5a(Houston)andFig5b(nationalmapofdatabase)Thenighttimedataarebasedonthe2000USCensusandaremodifiedtoaccountforpopulationnearroadsthedaytimedatarepresentworkeranddaytimeresidentialpopulationsbasedontheTexasBusinessDirectoryandtheCensusTransportationPlanningPackage2000datasetsAtthistimeitdoesnotincludethetrafficshoppingschoolspecialeventsandtouristpopulationsNonetheless thecurrentpopulationdataalongwithurbanconcentrationfieldswouldbea

powerfulsetofinformationforconductingassessmentstudiesofexposuresrangingfromagentreleasestoairpollutantldquohotspotsrdquo

Portal features TheNUDAPTportalsystemprovidesurbandatabaseandsupporttoolstobeappliedtoadvancedurbanmodelingsystemsItusesaWeb-basedtoolQuickPlacethatprovidesanenvironmentdesignedtofosterfutureresearchanddevelopmentcollaborationstoadvancethestateofscienceofurbanmodelingThecurrentprototypeportaldeliversserv-er-sidedataprocessing(thusminimizingoreliminat-ingtheneedfordesktopgeographicalinformationsystems)andprovidesaresponsivemapviewerfordataexplorationofthesourceandgriddeddatasetsToolsareavailabletoclipreprojectresamplerefor-matandcompresssubsetsofthedataThecliptoolallowsseveralchoicesforselectingasubdomainei-therbyusingaboundingboxenvelopeprojectedintospatialreferenceofrasterandoutputorbyspecifyingcoordinatesThereprojectiontoolallowsdatasetstobereferencedintovarioususer-specifiedcoordinatesystemsCurrentlyNUDAPTsupportsmanycoor-dinatereferencesystems[allNorthAmericanDatumof1983(NAD83) includingspherical latitudendashlongitudeuniversal transversemercator(UTM)andAlbersequalarea]foritsoutputsadditionallyothercustomprojectionssupportedbyarcGIScanbeinvokedNUDAPTuserswillhaveseveralmethodstoperformresamplingtoretaintotheextentpossibletheuniquepropertiesofthedatafromthebasepro-jectionCurrentlyoptionsincludenearest-neighbor

bilinearinterpolationandcubicconvolutionmethodsFormaxi-mal conservationof thedatapropertiesNUDAPTusersalsocaninvoketheso-calledspatialallocatortool(EythandBrunk2007)Severaloutput formatsareavailableforcompressinganddownloadinguser-customizeddatasets including networkCommonDataForm(NetCDF)AmericanStandardCode forInformationExchange(ASCII)f loatingpointImagineImageandGeographicTaggedImageFile(GeoTIFF)

NUDAPT PROTOTYPE HoustonwasselectedtoserveastheNUDAPTprototypeThisprototypeincludesasetoflidar-

Fig 4 Example of maximum AH fluxes (Qf) gridded at 500 m on an hourly basis in NUDAPT based on the method by Sailor and Lu (2004) Example shown is for Houston TX for a ldquotypicalrdquo day at 2000 UTC in Aug

1162 august 2009|

derivedbuildingdata setsofgriddeddaughterproducts(UCPs)anthropogenicheatf luxesanddayndashnightpopulationdataFortheprototypedem-onstrationapplicationsutilizedurbanizedversionsofMM5WRFand theUSEPArsquosCommunityMultiscaleAirQuality(CMAQ)modelingsystemfortheTexasAirQualityStudy2000intensivefieldstudy(wwwutexaseduresearchceertexaqs)HoustonisthefourthmostpopulouscityintheUnitedStateslargeamountsofoxidantprecursorsareintroducedtherefromtrafficandlargeamountsofairtoxicpollutantsareemittedfromitsshipchannelareathuscontributingtopoorairqualityModelingwasperformedusingnestingmethodsinwhichbound-aryconditionsareprovidedsequentiallytodomainsofeachsubsequently finergridmeshGiventheproximitytoGalvestonBayhourlyobservedseasurfacetemperatureswereintroducedtoincrease

theaccuracyofsimulatingthebayndashlandbreezeflowreversalintheHoustonareaExamplesshowing sensitivityof em-ployingNUDAPT-suppliedparametersagainstbasecasesimulationsthatutilizeastan-dard setofparameters areillustrated

Urbanized MM5 and CMAQ simulations Figure6comparesmodelsimulationsofpredicteddispersion parameters forHoustonon30August2000Thestandardsetemploysasingleurban landuseclassof theUSGSclassif icationschemeforHoustonIncon-trast theurbanizedcanopyversion ofMM5 employsadditional urban landuseclassesandUCPsthatreflectbui ldings and vegetat iondata(seeTable1)Asaresultintraurbanspatialgradientsin themetropolitanareaofHoustonarenegligibleinthestandardimplementationincontrast toresults fromtheurbanizedversionBothsetsofmeteorologywereusedtosimulateairqualityusingtheUSEPArsquosCMAQmodelingsystem (Byun and Schere

2006)theresultsexhibitedsignificantdifferencesinmagnitudeandspatialpatternsforozone(Fig7)Thesesimulationsshowtheeffectofozonetitrationbyelevatedlevelsofnitrogenoxide(NOx)primarilyfrommobile sourcecontributions (Simulationsperformedat4-kmgridsizeexhibitedconsiderablyreducedlevelsofNOxandaconcomitantreductionintitrationeffectsonozone)

Sensitivity studies using urbanized WRF Theurban-izedWRFmodel(version22)wasusedtoconductsensitivityexperimentsusingNUDAPT for thisstudy thisversionofWRFwasconfiguredwithfourtwo-wayinteractivenestedgridshavinggridspacingof2793and1kmTherewere31verticallevelswith16levelswithinthelowest2kmintheatmospheretobetterresolvetheatmosphericbound-arylayerItwasinitializedat0000UTC30August

Fig 5 Daytime and nighttime population for (a) central Houston TX grid-ded at 250-m resolution and (b) the conterminous United States (CONUS) coverage of both day and night population data in NUDAPT Nighttime maps are derived from 2000 US Census and daytime values are based on worker population (processing methodology based on McPherson and Brown 2003)


Fig 6 Examples from model sensitivity study showing sensible heat fluxes and PBL height for MM5 simulations at 1-km grid size using urbanized version (DA-SM2U) of Dupont et al (2004) and standard version for 2000 UTC 30 Aug 2000 Standard version uses single (urban) land use category for all of Houston TX

Fig 7 Example results of ozone simulations based on CMAQ model driven by urbanized (UCP) versus standard version (no UCP) of MM5 at 1-km grid size for Houston TX at 2100 UTC 30 Aug 2000

1164 august 2009|

2000withtheNationalCentersforEnvironmentalPredictionrsquosEnvironmentalDataAssimilationSystemand integrated for 36h andused thefollowingphysicsoptionsDudhiarsquos shortwaveradiationschemeRapidRadiativeTransferModellongwaveradiationschemeMellorndashYamadandashJanjićPBLschemeandtheNoahlandsurfacemodelwithone-layerUCMModelstudiestestingthesensitiv-itytomodelinputsofmorphologicalpropertiesofbuildingsandotherroughnessfeatureslandcoverandanthropogenicheatingratedatafromNUDAPTandlookuptablevalues forWRFhavebeenper-formedWRF-simulatedshelter(2m)temperaturedifferencesbetweenusingtheNUDAPTanthropo-genicheatingrateandusingthetable-basedanthro-pogenicheatingrateareshowninFig8b(corre-spondingdifferencesindailyanthropogenicheatingrateareshowninFig8a)Notethatemployingtablelookupvaluesforthoseparametersalreadyrepresentasignificantmodelingimprovementoverthenon-urbanizedWRFversionsResultsshowdifferencesreaching15degCdifferenceswerealsonotedforwindspeedandmixingheightsWehavesurmisedthattheuseofactualbuildingdataandanthropogenicheatingdoaffecttheaccuracyandprecisionofthesimulationsofsurfacemeteorologicalvariablesandmixingheightsconsistentwiththeexperiencewiththeurbanizedMM5

Urban heat island modif ication studies Anotherex-ampleapplicationofUCPmeteorologicalmodelsandrelatedmorphologicaldataisinstudyingUHIsandtheirmitigation(TahaandChing2007)Heatislandsarephenomenaassociatedwithurbaniza-tionTheirintensityisinfluencedprimarilybythecomplexitiesintheradiationpropertiesofbuildingsandurbancanyonsandmorphologicalfeaturesthedegreeofsurfaceimperviousnessandsoilmoistureavailabilityenhancedthermalheatstoragecapacityandtheintroductionofanthropogenicsourcesofheat(Sailor2006Taha19961997)Taha(2008ab)conductedmodelingexperimentstoinvestigatethepotentialformitigatingUHIsandtostudytheirairqualityconsequencesUsinghisurbanizedversionofMM5inanapplicationtoSacramentoCalifornia(Taha2008c)heshowedthattemperaturereductionsfromvegetationandalbedochangeinexcessof1degCeachfromitsbasecasewasachievable(Fig9)WhensuchresultswereappliedtoanairqualitymodelmdashourexampleComprehensiveAirQualityModelwithextensions(CAMxseeENVIRON2008)inthiscasemdashitproducedadecreaseinozoneoftheorderof10ppbv(Fig10)Theseresultsillustratethepoten-

Fig 8 (a) Difference of daily mean AH rate (W mminus2) for Houston WRFUCM lookup tablemdashNUDAPT data (b) 2-m air temperature differences (K) at 1200 UTC 30 Aug 2000 between the WRF simulation that used WRFUCM table-based AH rate and the simulation that used NUDAPT anthropogenic heating rate

tialforapplicationsusingNUDAPTforperformingurbanplanningstudysimulationsthataltertheurbanlandscapewiththegoalofreducingadverseimpactsonairqualityvisibilityandcomfortinurbanareas(Taha2008a)

SUMMARY NUDAPTwasdevelopedtoprovidetothemodelingcommunityaresourcetofacilitateaddressingmanyof theevolvingenvironmentalproblemsofurbanareasItfeaturesadatabasewithhigh-resolutionurbanmorphologicalfeaturesandspe-cializeddaughterproductsrepresentingthegeometrydensitymaterialandroughnesspropertiesofthemor-phologicalfeaturesTheHoustonprototypeexamplepresentedhereinisextensibletomosturbancentersintheUnitedStatesbecausedatasetscontainingtheirmorphologicalfeaturesandinsomecasesderivedbuildinginformationisavailableThecommunityis


nowinvitedtouseNUDAPTforadvancedapplica-tionsincludingimprovedurbanclimatepredictionsadvancedatmosphericdispersionmodelingassess-mentofexposuretoairbornehazardsforpopulations

intransit throughoutthedayandhumanexposureassessmentofairquality(wwwnudaptorg)

ACKNOWLEDGMENTS Many of the objectives ofNUDAPT were ach ievedthroughcollaborationsandcontributionsfromateamofinterestedinvestigatorsfrompublicprivateandacademicorganizationsmanyalsocon-tributingas coauthorsWerecognizeandthankthefol-lowingwhohavecontributedandparticipated invariousways including attendingandparticipatinginourtwoworkshopsandprofessionalmeetingsChrisKileyRichardEllefsenMarkEstesJosephFeddemaJoeFernandoRick

FryTeddyHoltMaudoodKhan JocelynMailhotKungsunParkandLelaPrashad

TheresearchpresentedherewasperformedunderthememorandumofunderstandingbetweentheEPAandthe

Fig 10 Sensitivity of air quality (ozone) to UHI reduction scenario described in Fig 9 (Taha 2008ac) (a) Simulated base-case ozone (O3) ppm for central California 31 Jul 2000 (1300 PDT) at 4-km resolution (b) The 1-km-resolution detail of simu-lated base-case ozone (O3) at 1300 PDT 31 Jul 2000 within the uMM5 grid for the Sacramento area The approximate location of the area with high-rise buildings is shown with black ellipse (c) Changes in ozone concentrations (ppm) as a result of UHI control via increased urban albedo in the Sacramento area

Fig 9 Results of nested model experiments for Sacramento CA illustrating the capability of simulating urban heat islands (UHI) and mitigation (cooling) uMM5 is an urbanized version of MM5 (Taha 2008c) based on Dupont et al (2004) (a) Mesoscale (MM5 12 and 4 km) and mesourban (uMM5 1 km) meteorologi-cal simulation domains (Taha 2008a) The small white rectangle indicates the Sacramento-area uMM5 modeling domain that is shown enlarged in (b) and (c) (b) Simulated surface temperature change (ordm) as a result of increased urban albedo in Sacramento Decrease in surface temperature reaches up to 7ordmC in and near the downtown area (square inset) Example is for 1300 PDT 31 Jul (c) Building plan-area density function (PAD) (1 mndash1) at 1 m AGL for the Sacramento area note the near-perfect correspondence between decrease in surface temperature in (b) and change in

roof albedo [as indicated via PAD in (c)] (d) Change in 2-m air temperature 28 Julndash2 Aug at an arbitrary point [red dot in (b)] as a result of increased urban albedo (blue line) and urban forest (red line)

1166 august 2009|

USDepartmentofCommercersquosNationalOceanicandAtmosphericAdministration(NOAA)andunderAgree-mentNumberDW13921548ThisworkconstitutesacontributiontotheNOAAAirQualityProgramAlthoughthismanuscripthasbeenreviewedbytheEPAandNOAAandapprovedforpublicationitdoesnotnecessarilyreflecttheirpoliciesorviews

REFERENCESBrownMJ2004UrbandispersionmdashChallenges

forfastresponsemodelingPreprintsFifth Conf on Urban Environment VancouverBCCanadaAmerMeteorSocJ51[AvailableonlineathttpamsconfexcomamsAFAPURBBIOtechprogrampaper_80330htm]

BurianSJSWStetsonWSHanJKSChingandDWByun2004High-resolutiondatasetofurbancanopyparametersforHoustonTexasPreprintsFifth Conf on the Urban Environment VancouverBCCanadaAmerMeteorSoc93[Availableon-lineathttpamsconfexcomamsAFAPURBBIOtechprogrampaper_80263htm]

mdashM JBrownTNMcPherson JHartmanWHan I Jeyachandran and JRush 2006EmergingurbandatabasesformeteorologicalanddispersionmodelingPreprintsSixth Symp on the Urban Environment AtlantaGAAmerMeteorSoc52 [AvailableonlineathttpamsconfexcomamsAnnual2006techprogrampaper_103023htm]

mdashmdashNAugustus2007aDevelopmentandassessmentof the secondgenerationNationalBuildingStatisticsdatabasePreprintsSeventh Symp on the Urban Environment SanDiegoCAAmerMeteorSoc54[Availableonlineathttpamsconfexcomams7Coastal7Urbantechprogrampaper_127218htm]

mdashmdashDJSailorRMCioncoREllefsenMEstesandTHultgren2007bDatabasefeaturesoftheNationalUrbanDatabaseandAccessPortalTools(NUDAPT)PreprintsSeventh Symp on the Urban Environment SanDiegoCAAmerMeteorSoc62[Availableonlineathttpamsconfexcomams7Coastal7Urbantechprogrampaper_127266htm]

mdashNAugustusI JeyachandranandMBrown2007cNationalBuilding StatisticsDatabaseVersion2LosAlamosNationalLaboratoryRepLA-UR-08-192182pp

ByunD andKL Schere 2006Reviewof thegoverningequationscomputationalalgorithmsandothercomponentsoftheModels-3Community

MultiscaleAirQuality(CMAQ)ModelingSystemAppl Mech Rev 59 51ndash77

ChenFandJDudhia2001Couplingandadvancedland surfacendashhydrologymodelwith thePennStatendashNCARMM5modelingsystemPartIModelimplementationandsensitivityMon Wea Rev 129 569ndash585

mdashHKusakaMTewariJ-WBaoandHHarakuchi2004UtilizingthecoupledWRFLSMurbanmod-elingsystemwithdetailedurbanclassificationtosimulatetheurbanheatislandphenomenaovertheGreaterHoustonareaPreprintsFifth Symp on the Urban Environment VancouverBCCanadaAmerMeteorSoc9-11[Availableonlineathttpamsconfexcomamspdfpapers79765pdf]

mdashMTewariHKusakaandTTWarner2006Currentstatusofurbanmodelinginthecommu-nityWeatherResearchandForecast(WRF)modelPreprintsSixth Symp on the Urban Environment AtlantaGAAmerMeteorSocJ14[AvailableonlineathttpamsconfexcomamsAnnual2006techprogrampaper_98678htm]

mdashmdashSMiaoYLiuBBornsteinJChingandHKusaka2007aChallengesindevelopingadvancedurbanparameterizationschemesforthecommunityWRFmodelPreprintsSeventh Symp on the Urban Environment SanDiegoCAAmerMeteorSocJ32[Availableonlineathttpamsconfexcomams7Coastal7Urbantechprogrampaper_126816htm]

mdashmdashandJChing2007bEffectsofhigh-resolutionbuildingandurbandatasetsontheWRFurbancoupledmodel simulations for theHouston-GalvestonareasPreprintsSeventh Symp on the Urban Environment SanDiegoCAAmerMeteorSoc65[Availableonlineathttpamsconfexcomams7Coastal7Urbantechprogrampaper_126835htm]

mdashSMiaoMTewariandJChing2007cEffectsofusinghigh-resolutionurbanland-useandbuildingmorphologicaldatasetsontheWRFUrbanCoupledmodelsimulationsfortheHouston-GalvestonareasExtended Abstracts Sixth Annual CMAS Conf ChapelHillNCCommunityModelingandAnalysis734pp[Availableonlineatwwwcmascenterorgconference2007abstractschen_session7_2007pdf]

ChinHNSMJLeachGASugiyamaJMLeoneJrHWalkerJSNasstromandMJBrown2005EvaluationofanurbancanopyparameterizationinamesoscalemodelusingVTMXandURBAN2000Mon Wea Rev 133 2043ndash2068

ChingJ2007Nationalurbandatabaseandaccesspor-taltools(NUDAPT)aprojectoverviewPreprints


Seventh Symp on Urban Environment SanDiegoCAAmerMeteorSoc61 [Availableonlineathttpamsconfexcomams7Coastal7Urbantechprogrampaper_126637htm]

CioncoRMandREllefsen1998Highresolutionur-banmorphologydataforurbanwindflowmodelingAtmos Environ 32 7ndash17

CoirierW JDMFrickerMFurmanczykandSKim2005Acomputational f luiddynamicsapproachforurbanareatransportanddispersionmodelingEnviron Fluid Mech 5 443ndash479

DupontSTLOtteandJKSChing2004Simula-tionofmeteorologicalfieldswithinandaboveurbanandruralcanopieswithamesoscalemodel(MM5)Bound-Layer Meteor 113 111ndash158

EkMBKMitchellYLinERogersPGrunmannVKorenGGaynoandJTarpley2003Imple-mentationofNoahland-surfacemodeladvancesin theNCEpoperationalmesoscaleEtamodelGeophysical Research Abstracts Vol108Abstract12845[AvailableonlineatwwwcosisnetabstractsEAE0312845EAE03-J-12845pdf]

ENVIRON2008UserrsquosGuideComprehensiveAirQualityModelwithExtensionsVersion450ENVIRONInternationalCorporation[AvailableonlineatwwwcamxcomfilesCAMxUsersGuide_v45pdf]

EythAandBBrunk2007Newfeaturesinversion3oftheMIMSSpatialAllocatorExtended Abstracts Sixth Annual CMAS Models-3 Userrsquos ConfChapelHillNCCommunityModelingandAnalysis23Availableonlineatwwwcmascenterorgconfer-ence2005archivecfm]

HuberAPGeorgopoulosRGilliamGStenchikovS-WWangBKelly andHFeingersh2004ModelingairpollutionfromthecollapseoftheWorldTradeCenterandassessingthepotentialimpactsonhumanexposuresEMFeb35ndash40

KusakaHHKondoYKikegawaandFKimura2001Asimplesingle-layerurbancanopymodelforatmosphericmodelsComparisonwithmulti-layerandslabmodelsBound-Layer Meteor 101 329ndash358

McPhersonTandMBrown2003USdayandnightpopulationdatabase(Revision20)mdashDescriptionofmethodologyLosAlamosNationalLaboratoryRepLA-CP-03-072230pp

OfficeoftheFederalCoordinatorforMeteorology2005ProceedingsoftheForumonUrbanMeteorologyMeetingweatherneedsintheurbancommunityUSDeptofCommerceRep108pp[Availableonlineatwwwofcmgovhomepagetextpubshtm]

OtteTLALacserSDupontandJKSChing2004Implementationofanurbancanopyparameteriza-tioninamesoscalemeteorologicalmodelJ Appl Meteor 43 1648ndash1665

SailorDJ2006MitigationofurbanheatislandsmdashRecentprogressandfutureprospectsPreprintsSixth Symp on the Urban Environment AtlantaGAAmerMeteorSocJ31[AvailableonlineathttpamsconfexcomamsAnnual2006techprogrampaper_105264htm]

mdashandLLu2004Atop-downmethodologyfordevelopingdiurnalandseasonalanthropogenicheatingprofilesforurbanareasAtmos Environ 38 2737ndash2748

mdashandMHart2006Ananthropogenicheatingdata-baseformajorUScitiesPreprintsSixth Symp on the Urban Environment AtlantaGAAmerMeteorSoc56[AvailableonlineathttpamsconfexcomamsAnnual2006techprogrampaper_105377htm]

TahaH1996ModelingtheimpactsofincreasedurbanvegetationontheozoneairqualityinthesouthcoastairbasinAtmos Environ 30 3423ndash3430

mdash1997ModelingtheImpactsofLarge-ScaleAlbedoChangesonOzoneAirQualityintheSouthCoastAirBasinAtmos Environ 31 1667ndash1676

mdash2008aUrbansurfacemodificationasapotentialozoneair-qualityimprovementstrategyinCaliforniaAmesoscalemodellingstudyBound-Layer Meteor 127 219ndash239doi101007s10546-007-9259-5

mdash2008bEpisodicperformanceandsensitivityoftheurbanizedMM5(uMM5)toperturbationsinsurfacepropertiesinHoustonTXBound-Layer Meteor 127 193ndash218doi101007s10546-007-9258-6

mdash2008cMeso-urbanmeteorologicalandphoto-chemicalmodelingofheatislandmitigationAtmos Environ 42 8795ndash8809

mdashandJKSChing2007UCPMM5modelinginconjunctionwithNUDAPTModelrequirementsupdatesandapplicationsPreprintsSeventh Symp on the Urban Environment SanDiegoCAAmerMeteorSoc64[Availableonlineathttpamsconfexcomams7Coastal7Urbantechprogrampaper_127201htm]

1168 august 2009|

bull newscienceandmodeladvancementsforurbanmeteorologymodeling

bull newdatasetsthatinclude newlyacquiredhigh-resolutionbuildingdatafor

mostlargecitiesintheUnitedStates evolvingdescriptionandresolutionofurbanland

usesandcoverdata griddeddaughterproducts includingurban

canopyparameters(UCPs)derivedfromthe high-resolutionbuildingandvegetationdata and

ancillarydataincludinggriddeddayandnight populationandanthropogenicheating

bull newtechnologytofacilitateNUDAPTrsquosdissemi-nationtoandusagebythemodelingcommunitywithWeb-baseddataaccesstoolsinacentralizeddatabase

NUDAPTisadatabaseanddecisionsupportsys-temthatishostedinaGeographicInformationSystem(GIS)environmentonanArcGISserverattheUni-versityofNorthCarolinaatChapelHillInconceptNUDAPToffersacentralcyberlocationforusers(researchersanalystsmodelersandpolicymakers)toaccesshigh-resolutionurban-scaledatacollectedbyconventionalandremotesensingmeasurementsthatareneededtocharacterizeandmodeltheurbanatmosphereCurrentlyNUDAPThostssuchdatafor33citiesintheUnitedStateswithdifferentdegreesofcoverageandcompletenessDataarepresentedintheiroriginalformatsuchasbuildingheightsdayandnightpopulationvegetationdataandlandsurfacetemperatureandradiationorinaldquoderivedrdquoformatsuchastheUCPswhichareusedinurbanmeteorologyandairqualitymodelingapplicationsAsanopensourcepublicdomainportalNUDAPTisdesignedwithtoolsforuserstosharedataexchangeinformationdiscussresultsandposttheirfindingspapersandconferencepresentations

URBAN MODELING NUDAPTwillprovidedataformodeldevelopmentandapplicationsinurbanareasMeteorologicalmodelsprovideinformationneeded forplanningandconductingairqualityassessmentsandfortransportinganddispersingairpollutantsandhazardoustoxicagentsMesoscalemodelsgeneratemeteorological fieldsused fornear-surfacetransportpredictionsbasedonsurfaceroughness(Zo)andstability(MoninndashObukovlength)parametersfortheprimarylanduseofeachmodelgridHoweverformanyurbanapplicationsgreaterspatialdetailandfidelityofthef lowfieldswillberequiredRecentadvancesinurbanmeteorologicalmodelsnowaccountfortheinfluenceofbuildingstreesandothermorphologicalfeaturesontheurbanboundarylayerf lowsGriddedUCPsusedinthemodelsrepresentthegeometricalcharacteristicsofthemorphologicalfeaturesthatincorporatetheinfluenceandcomplexitiesofspatialdistributionsofbuildingdensitiesandofbuildingsofdifferentshapessizesandmaterialcompositionaswellasotherdominanturbanfeatures(Fig1)Aerialsurveysarenowgenerat-inggeospatialdatathatcapturewithhighdefinition(1ndash5m)thethree-dimensionalgeometryofindividualandconglomeratesofbuildingsandvegetationinurbanareasfromwhichmodelUCPscanbederived(Burianetal200420062007abFig2)

Urbanizationschemeshavebeenintroducedintothefifth-generationPennsylvaniaStateUniversity(PSU)ndashNationalCenterforAtmosphericResearch(NCAR)MesoscaleModel (MM5) theWeatherResearchandForecasting(WRF)modelandothermodelsandarebeingtestedandevaluatedforgridsizesoftheorderof1kmorso(Dupontetal2004Chenetal20042007andashcOtteetal2004Chinetal2005)Thegoverningequations(introductionandimplementationofcanopy-layerparameterizations)foreachsystemweremodifiedanduniquesetsofUCPswereintroducedtorepresenttheirurbaniza-

AFFILIATIONS ChingmdashAtmospheric Modeling Division National Exposure Research Laboratory Office of Research and Development US Environmental Protection Agency Research Triangle Park North Carolina Brown and MCPhersonmdashLos Alamos National Laboratory Los Alamos New Mexico BurianmdashUniversity of Utah Salt Lake City Utah ChenmdashNational Center for Atmospheric Research Boulder Colorado CionComdashConsultant Roseville California hannamdashInstitute for the Environment University of North Carolina Chapel Hill North Carolina hultgrenmdashComputer Sciences Corporation Research Triangle Park North Carolina sailormdashPortland State University Portland Oregon tahamdashAltostratus Inc Martinez California

williaMsmdashUS Environmental Protection Agency Kansas City KansasCORRESPONDING AUTHOR Jason Ching Atmospheric Modeling Division National Exposure Research Laboratory US EPA MS (E243-04) Research Triangle Park NC 27711E-mail chingjasonepagov

The abstract for this article can be found in this issue following the table of contentsDOI1011752009BAMS26751

In final form 2 February 2009copy2009 American Meteorological Society

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