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1 Developmental Testbed Center Report AOP 2016 Activities 1 April 2016 – 31 March 2017 1 Introduction The Developmental Testbed Center (DTC) is a distributed facility with components at the National Center for Atmospheric Research (NCAR) and the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) Global Systems Division (GSD). The purpose of the DTC is to provide a link between the research and operational communities so Numerical Weather Prediction (NWP) research can be efficiently transferred to operations. In addition, the DTC provides the research community access to the latest operational NWP code packages for research applications. The DTC meets its goals by: maintaining and supporting community code packages that represent the latest NWP technology, performing extensive testing and evaluation (T&E) of new NWP technology, developing and maintaining a state-of-the-art verification package, and connecting the NWP research and operational communities through workshops and its visitor program. Over the past year, DTC activities were organized into five focus areas: Verification, Data Assimilation (DA), Hurricanes, Regional Ensembles and Global Model Test Bed (GMTB). Funding for the DTC is provided by NOAA’s National Weather Service (NWS) and Office of Oceanic and Atmospheric Research (OAR), the Air Force (AF), NCAR, and the National Science Foundation (NSF). This report provides a description of the activities undertaken by the DTC between 1 April 2016 and 31 March 2017. These activities include those described in the DTC 2016 Annual Operating Plan (AOP), as well as a few carry-over activities from the DTC AOP 2015. The performance period for the GMTB is 1 July through 30 June. This report also provides a status update on the GMTB activities through 31 March 2017. 1.1 DTC Management The external management structure of the DTC includes an Executive Committee (EC), a Management Board (MB), and a Science Advisory Board (SAB). Current memberships are listed below. The MB and EC are responsible for approving the DTC Annual Operating Plan (AOP), which defines the work to be undertaken by the DTC in a given year, whereas the SAB is charged with providing the DTC Director with advice on future directions of the DTC and reviewing proposals submitted to the DTC Visitor Program. The DTC hosted its annual SAB meeting at NCAR’s Foothills Campus in Boulder, CO, on 14-15 September 2016. The purpose of this meeting was to discuss strategic future directions for the DTC. Participation in this annual meeting was stronger than usual, with 16 SAB members participating in-person and the 17 th member participating remotely. Day 1 of the meeting consisted of briefings from the DTC’s operational partners, an overview presentation, highlights by task area and a breakout group discussion on building community. Day 2 started off with a presentation on DTC’s community interactions, followed by breakout group discussions by task area. The meeting wrapped up with a briefing and discussion of SAB recommendations. General and task specific recommendations stemming from this meeting are posted on the DTC website (http://www.dtcenter.org/SAB/SAB-recommendations- Sept2016.pdf). In March 2016, the National Centers for Environmental Prediction (NCEP) director, Bill Lapenta, charged the UCAR Community Advisory Committee for NCEP (UCACN) with conducting a review of four

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    DevelopmentalTestbedCenterReportAOP2016Activities

    1April2016–31March2017

    1 Introduction

    TheDevelopmentalTestbedCenter(DTC)isadistributedfacilitywithcomponentsattheNationalCenterforAtmosphericResearch(NCAR)andtheNationalOceanicandAtmosphericAdministration(NOAA)EarthSystemResearchLaboratory(ESRL)GlobalSystemsDivision(GSD).ThepurposeoftheDTCistoprovidealinkbetweentheresearchandoperationalcommunitiessoNumericalWeatherPrediction(NWP)researchcanbeefficientlytransferredtooperations.Inaddition,theDTCprovidestheresearchcommunityaccesstothelatestoperationalNWPcodepackagesforresearchapplications.TheDTCmeetsitsgoalsby:maintainingandsupportingcommunitycodepackagesthatrepresentthelatestNWPtechnology,performingextensivetestingandevaluation(T&E)ofnewNWPtechnology,developingandmaintainingastate-of-the-artverificationpackage,andconnectingtheNWPresearchandoperationalcommunitiesthroughworkshopsanditsvisitorprogram.Overthepastyear,DTCactivitieswereorganizedintofivefocusareas:Verification,DataAssimilation(DA),Hurricanes,RegionalEnsemblesandGlobalModelTestBed(GMTB).

    FundingfortheDTCisprovidedbyNOAA’sNationalWeatherService(NWS)andOfficeofOceanicandAtmosphericResearch(OAR),theAirForce(AF),NCAR,andtheNationalScienceFoundation(NSF).ThisreportprovidesadescriptionoftheactivitiesundertakenbytheDTCbetween1April2016and31March2017.TheseactivitiesincludethosedescribedintheDTC2016AnnualOperatingPlan(AOP),aswellasafewcarry-overactivitiesfromtheDTCAOP2015.TheperformanceperiodfortheGMTBis1Julythrough30June.ThisreportalsoprovidesastatusupdateontheGMTBactivitiesthrough31March2017.

    1.1 DTCManagement

    TheexternalmanagementstructureoftheDTCincludesanExecutiveCommittee(EC),aManagementBoard(MB),andaScienceAdvisoryBoard(SAB).Currentmembershipsarelistedbelow.TheMBandECareresponsibleforapprovingtheDTCAnnualOperatingPlan(AOP),whichdefinestheworktobeundertakenbytheDTCinagivenyear,whereastheSABischargedwithprovidingtheDTCDirectorwithadviceonfuturedirectionsoftheDTCandreviewingproposalssubmittedtotheDTCVisitorProgram.

    TheDTChosteditsannualSABmeetingatNCAR’sFoothillsCampusinBoulder,CO,on14-15September2016.ThepurposeofthismeetingwastodiscussstrategicfuturedirectionsfortheDTC.Participationinthisannualmeetingwasstrongerthanusual,with16SABmembersparticipatingin-personandthe17thmemberparticipatingremotely.Day1ofthemeetingconsistedofbriefingsfromtheDTC’soperationalpartners,anoverviewpresentation,highlightsbytaskareaandabreakoutgroupdiscussiononbuildingcommunity.Day2startedoffwithapresentationonDTC’scommunityinteractions,followedbybreakoutgroupdiscussionsbytaskarea.ThemeetingwrappedupwithabriefinganddiscussionofSABrecommendations.GeneralandtaskspecificrecommendationsstemmingfromthismeetingarepostedontheDTCwebsite(http://www.dtcenter.org/SAB/SAB-recommendations-Sept2016.pdf).

    InMarch2016,theNationalCentersforEnvironmentalPrediction(NCEP)director,BillLapenta,chargedtheUCARCommunityAdvisoryCommitteeforNCEP(UCACN)withconductingareviewoffour

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    representativetestbedsmanagedorco-managedbyNCEPinassociationwithoneoftheNCEPCenters.TheDTCwasoneoftheselectedtestbeds.ThereviewcommitteefortheDTCconsistedof:ShuyiChen(chair–UniversityofMiami),PeterNeilley(TheWeatherCompany),LanceBosart(StateUniversityofNewYork[SUNY]-Albany)andAndyBrown(UKMetOffice).Aspartofitsreview,theDTCmanagementhostedaDTCOverviewwebinaron30Septembertoprovidebackgroundinformationtotheexternalreviewpanel,followedbyanonsitevisitbythereviewcommitteeon6-7October2016.TheonsitevisitconsistedofpresentationsbyDTCmanagementandtaskleadsandone-on-onediscussionsbetweenthereviewcommitteeandacross-sectionofDTCstaff.

    DTCExternalManagementCommittees:

    ExecutiveCommittee ManagementBoard JimHurrell NCAR JoshHacker NCAR MikeFarrar NOAA/NWSBillLapenta NOAA/NWS JoeKlemp NCAR FredToepfer NOAA/NWSRalphStoffler AirForce MichaelGremillionAirForce StanBenjamin NOAA/OAR/ESRLKevinKelleher NOAA/OAR JeffCetola AirForce Jian-WenBao NOAA/OAR/ESRL

    ScienceAdvisoryBoardAdamClark NationalSevereStormsLaboratory(NSSL)RobertFovell SUNY–AlbanyKristenCorbosiero SUNY–AlbanySharanyaMajumdar UniversityofMiamiKathyGilbert NationalCentersforEnvironmentalPrediction(NCEP)/WeatherPredictionCenterGeoffDiMego NCEP/EnvironmentalModelingCenter(EMC)JenniEvans PennsylvaniaStateUniversityDavidGochis NCARS.R.Gopalakrishnan NOAA/AtlanticOceanographicandMeteorologicalLaboratory(AOML)DavidVollmer UnitedStatesAirForce(USAF)AcademyTomAuligne JointCenterforSatelliteDataAssimilation(JCSDA)TimWhitcomb NavalResearchLaboratory(NRL)BradColman ClimateCorporationZhuoWang UniversityofIllinoisKellyMahoney CooperativeInstituteforResearchinEnvironmentalSciencesRussSchumacher ColoradoStateUniversityKayoIde UniversityofMaryland

    Overthepastyear,theDTChostedtwoMBmeetings:atwo-hourconferencecallon31October2016anditsannualin-personMBmeetingon18-19January2017atNCAR’sFoothillsCampusinBoulder,CO.ThefocusoftheOctoberconferencecallwastoreportonrecommendationsfromtheSABanddiscussinitialguidanceonprioritiesforAOP2017.ThepurposeoftheJanuarymeetingwastodiscussandrefinetheDTC’sproposalforAOP2017anddiscussnominationsforSABmemberstoreplacecurrentmemberswhosetermexpiresinJune2017.

    DTCmanagementparticipatedintwoDTCECconferencecalls(17May2016,29September2016)andtheannualin-personECmeetingatNWSHeadquartersinSilverSpring,MD,on3March2017.RecentDTCaccomplishments,recommendationsfromtheSAB,proposedactivitiesforAOP2017,andthefuturedirectionoftheDTCwerediscussedatthein-personmeeting.TheECalsoapprovedtheDTCDirector’sproposaltorotateoffsixSABmemberswhosetermsexpireinJune2017(RobertFovell,KristenCorbosiero,SharanyaMajumdar,GeoffDiMego,JenniEvans,andKellyMahoney)andaddsixnewSABmembers(three-yeartermbegins1July2017).ThesixnewSABmembersare:VincentLarson

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    (UniversityofWisconsin-Milwaukee),XuguangWang(UniversityofOklahoma),TomGalarneau(UniversityofArizona),PhilPegion(ESRL/PhysicalSciencesDivision),RustyBenson(GeophysicalFluidDynamicsLaboratory[GFDL])andVijayTallapragada(NCEP/EMC).QuarterlyreportsontheprogresstodatewerealsopreparedforeachactivityanddistributedtotheECandMBmembers.

    1.2 CommunityInteractions

    MaintainingstrongtiestoboththeresearchandoperationalNWPcommunitiesiscriticaltotheDTC’sabilitytosuccessfullymeetitsmission.Overthepastyear,strongtieswiththeoperationalcommunityweremaintainedthroughtheDTC’sinteractionswithourpartnersattheoperationalcenters(i.e.,EMCandAirForce)bothatthemanagementlevelandthroughourteamleadinteractionswiththeappropriateteamleadsand/orfocalpointsattheoperationalcenters.TheDTCalsoworkedtowardstrengtheningitstiestothebroaderresearchcommunitythroughworkshops,tutorialsandtheDTCVisitorProgram.InformationonDTC-sponsoredtutorialsisprovidedinSection2.3.TheDTCalsoengagesthecommunitythroughthedistributionofitsnewsletter“Transitions”thatservesasaforumfortheresearchandoperationalcommunitiestoshareinformation.Overthepastyear,theDTCdistributedthreeissuesofTransitions.AllissuesofTransitionscanbeaccessedat:http://www.dtcenter.org/newsletter/.

    1.2.1 CommunityOutreachEvents

    InJune2016,theDTCco-hostedwithNCAR’sMesoscaleandMicroscaleMeteorology(MMM)Laboratorythe17thWeatherResearchandForecasting(WRF)Users’WorkshopatNCAR’sCenterGreenCampusinBoulder,CO.ThefirstdayconsistedoflecturesonWRFsoftwareandbestcomputingpractices,followedbya3-dayworkshopconsistingof67talksandnearly80posters.Thelastdayconsistedoffourmini-tutorialsontheMesoscaleModelEvaluationTestbed(MMET),VisualizationandAnalysisPlatformforOcean,AtmosphereandSolarResearchers(VAPOR),ensemblepredictionandNCARCommandLanguage(NCL).TheMMETinstructionalsessionwasorganizedandconductedbyDTCstaff.About190peoplefrom19countriesattendedtheworkshop(http://www2.mmm.ucar.edu/wrf/users/workshops/WS2016/WorkshopPapers.php).

    AlsoinJune2016,theDTCco-hostedwithNCEP/EMCthe7thEnsembleUsers’WorkshopattheNOAACenterforWeatherandClimatePrediction(NCWCP)inCollegePark,MD.Thisworkshopattractedmorethan150participantsrepresentingabroadcross-sectionofexpertiserangingfromensembledeveloperstotheendusersofensembleproducts.Theover-archinggoaloftheworkshopwasdetermininghowtosupporttheNWSasitmovestowardaseamlessoperationalensembleforecastsystematstorm-toglobal-scales,fromshort-termtoseasonaltimescales,usingatmosphere-onlytoocean-waveandcoupledensemblepredictionsystems.Theworkshopconsistedoforalandposterpresentations,aswellasopendiscussionovera3-dayperiod.Workshoppresentationsandalistofattendeesarepostedathttp://www.dtcenter.org/events/workshops16/ensembles/.AreportontheworkshopisalsoavailableontheDTCwebsite(http://www.dtcenter.org/eval/ensembles/).

    1.2.2 DTCVisitorProgram

    TheDTCVisitorProgramsupportsvisitorstoworkwiththeDTCtotestnewforecastingandverificationtechniques,modelsandmodelcomponentsforNWP.Thegoalistoprovidetheoperationalweatherpredictioncenters(e.g.,NCEPandAirForce)withoptionsfornear-termadvancesinoperationalweatherforecastingandtoprovideresearcherswithNWPcodesthatrepresentthelatestadvancesintechnology.Italsooffersanopportunityforvisitorstointroducenewtechniquesthatwouldbeof

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    particularinteresttotheresearchcommunityintothepublicly-releasedsoftwaresystemssupportedbytheDTC.

    Overthepastyear,theDTCprovidedsupportforonevisitorprojectselectedin2014(seeTable1.2.2-1),fourprojectsselectedin2015(seeTable1.2.2-2)andfourprojectsselectedforfundingin2016(seeTable1.2.2.-3).Duringthistimeperiod,Dr.Roebbercompletedhisprojectandsubmittedhisprojectreport,soallprojectsawardedin2014arenowcomplete.Mr.Otkinandcolleaguesalsocompletedtheirprojectandsubmittedtheirprojectreport.Theremaining2015projectsarenearingcompletion,withonlytheprojectreportsremaining.Forthe2016projects,Mr.IaconoandMr.HendersonhavecompletedtheirprojectandsubmittedtheirprojectreportandonlythereportremainsforDr.Niyogi’sgraduatestudentprojectbySubashiniSubramanian.Theotherprojectsawardedin2016arewellunderwayandtheprojectsawardedin2017areeitherunderwayoranticipatedtogetunderwayinthecomingmonths.Allvisitorprojectreportsreceivedoverthepastyearareavailableonthe“VisitorProgram”portionoftheDTCwebsite(http://www.dtcenter.org/visitors/).Inadditiontoprojectreportsandrelevantcodedeliverables,theDTCstartedschedulingvisitorseminarsduringtheirfinalDTCvisitthatareopentolocalareascientistsaswellasremoteparticipants.FeedbackfromboththevisitorsandlocalareascientistsaboutthisincreasedexposureoftheDTCvisitorprojectshasbeenoverwhelminglypositive.Oneadditionalprojectisintheprocessofbeingawarded.

    Table1.2.2-1.2014VisitorProjectsPI Institution ProjectTitle

    PaulRoebberUniversityofWisconsin-Milwaukee

    Demonstrationproject:Developmentofalargememberensembleforecastsystemforheavyrainfallusingevolutionaryprogramming

    Table1.2.2-2.2015VisitorProjectsPI Institution ProjectTitle

    JasonOtkinUniversityofWisconsin-Madison

    ObjectbasedverificationfortheHRRRmodelusingsimulatedandobservedGOESinfraredbrightnesstemperatures

    GretchenMullendore(MariuszStarzec)

    UniversityofNorthDakota

    Mesoscalemodelintercomparisonatconvection-allowingresolutionusingMODE

    DevNiyogi(XingLiu) PurdueUniversity

    ImprovingWRFweatherforecastthroughenhancedrepresentationofcropland-atmosphereinteractions

    JoelBedardUniversityofQuebec-Montreal

    Implementationandvalidationofageo-statisticalobservationoperatorfortheassimilationofnear-surfacewindsinGSI

    Table1.2.2-3.2016VisitorProjectsPI Institution ProjectTitle

    MichaelIacono/JohnHenderson

    AtmosphericandEnvironmental

    Research

    TestingrevisionstoRRTMGcloudradiativetransferandperformanceinHWRF

    RobertFovell SUNY-Albany ImpactofplanetaryboundarylayerassumptionsonHWRFDevNiyogi(Subashini

    Subramanian)PurdueUniversity DevelopingcapabilityinidealizedHWRFforassessingtheimpactoflandsurfaceontropicalcycloneevolution

    ShaowuBao CoastalCarolinaUniversityEvaluationofthemicrophysicsschemeinHWRF2016versionwithremote-sensingdata

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    Table1.2.2-4.2017VisitorProjectsPI Institution ProjectTitle

    PatrickSkinner UniversityofOklahoma

    QuantifyingthevalueofradardataassimilationintheCommunityLeveragedUnifiedEnsembleusingobject-basedverificationmethods

    KarinaApodaca ColoradoStateUniversityR2OtransitionoftheGOES-RGLMlightningassimilationcapabilityinGSIforuseintheNCEPGDAS

    BillGallus IowaStateUniversityUseoftheCLUEtoexamineimportanceofmixedphysicsinensembles

    PaulRoebberUniversityofWisconsin-Milwaukee

    AnAdaptiveBayesianModelCombination(BMC)PostProcessorfortheHRRR-TLEForecastSyste

    JiangZhu UniversityofAlaska-FairbanksAdvancedDataAssimilationTechniquesAppliedtoaRegionalHighResolutionRapidRefreshModelinAlaska(HRRR-Alaska)

    Ting-ChiWu ColoradoStateUniversity

    EvaluationoftheNewlyDevelopedObservationOperatorsforAssimilatingSatelliteCloudandPrecipitationObservationsinGSIwithintheHWRFsystem

    2 SoftwareSystems

    Toserveasabridgebetweenoperationsandresearch,theDTCprovidesaframeworkforthetwocommunitiestocollaborateinordertoacceleratethetransitionofnewscientifictechniquesintooperationalweatherforecasting.Thisframeworkisbasedonsoftwaresystemsthatareasharedresourcewithdistributeddevelopment.Thecurrentoperationalsystemsareasubsetofthecapabilitiescontainedinthesesoftwaresystems.Ongoingdevelopmentofthesesystemsismaintainedunderversioncontrolwithmutuallyagreeduponsoftwaremanagementplans.TheDTCcurrentlyworkswiththefollowingsoftwaresystems:

    • WeatherResearchandForecasting(WRF)–NWPmodel+pre-andpost-processors• HurricaneWRF(HWRF)-setoftoolsfortropicalstormforecasting,includingacoupled

    atmosphereandoceansystem• UnifiedPost-Processor(UPP)• GridpointStatisticalInterpolation(GSI)dataassimilation(DA)system• EnsembleKalmanFilter(EnKF)DASystem• Modularend-to-endensemblesystem• ModelEvaluationTools(MET)–Verificationpackage

    TheDTCdoesnotgenerallycontributetothedevelopmentofnewscientifictechniquesforthesesoftwarepackages.ThetwoexceptionsareMETdevelopmentandsomelimitedphysicspackagedevelopmentforWRFtoaddressshort-comingsbroughttolightbyDTCT&E.TheDTCcontributestothesoftwaremanagementofallofthesesystemsandusersupportforthepublicly-releasedsystems(WRF,HWRF,UPP,GFDLvortextracker,GSI,EnKFandMET).Allsoftwaremanagementandusersupportactivitiesarecollaborativeeffortswiththedevelopers,wheretheexactroleoftheDTCdependsonthesoftwarepackage.ThemaindevelopersofthesepackagesareaffiliatedwithEMC,ESRL,NCAR,GlobalModelingandAssimilationOffice(GMAO)oftheNationalAeronauticsandSpaceAdministration(NASA),NationalEnvironmentalSatellite,DataandInformationService(NESDIS),JCSDA,GFDL,UniversityofRhodeIsland(URI)andtheHurricaneResearchDivision(HRD)ofNOAA’sAOML.

    TheDTCisworkingwithEMCtounifytheverificationsystemsbetweenthetwoorganizationsthroughMETandMETViewer,MET’saccompanyingdatabaseanddisplaysystem.DTCstaffvisitedEMCforaweekduringearlyMay.Thisvisitconsistedof18meetingswithapproximately50EMCstafftodiscuss

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    theircurrentverificationpracticesandimmediateneeds.InformationgatheredduringthesemeetingsissummarizedinarequirementsdocumentthatwasreleasedtoallparticipantaswellastheEMCDirectoron15September2016.TheDTCisusingthisinformationtodevelopaunifiedverificationsystem,calledMET+,throughNextGenerationGlobalPredictionSystem(NGGPS)fundingoutsideoftheDTC.Briefly,MET+isasetofpythonwrapperstosimplifysetting-upandrunningMETtoallowresearcherstoleveragetheirownuniquealgorithms,andsystematicallyplotthefieldsandresults.

    FortheGMTB,theDTChasbeenworkingwithEMCandthephysics-developmentcommunity(ESRL,NCAR,NRL,anduniversities)toestablishaCommonCommunityPhysicsPackage(CCPP)thatwillserveasaframeworkforefficientlydevelopingandtransitioningcurrentandnext-generationphysicsparameterizationsintooperationstomeettheneedsofNGGPS.AnotherimportantcomponentofthisworkisestablishinganInteroperablePhysicsDriver(IPD)thatprovidesaframeworkforphysicalparameterizationsuiteswithintheCCPPtointerfacewithdifferentdynamiccores.Overthepastyear,therequirementsfortheIPDandCCPPhaveundergoneextensivereviewandrefinement,andinformedasoftwaredesign.TheinitialdesignwaspresentedtoEMCandtheNationalUnifiedOperationalPredictionCapability(NUOPC)PhysicsInteroperabilitygroup,aswellasseveralsubsequentrevisionsthatincorporatedfeedbackfromthesegroups.Thisdesigndocument,aswellasthephysicsaliasinglayer(alsoknownasIPDv4)developmentperformedbyGFDLandmadeavailableforFV3inMarch2017,servedasthefoundationfortheinitialCCPPandIPD.GMTB’scontributiontotheIPDeffortwillenableconstructingphysicssuitesatruntimebyparsingauser-friendlyconfigurationfile,allowingforrunningtheparameterizationswithintheCCPPinaveryflexiblemanner.

    TheGMTBintendstofacilitateanenvironmentfortheCCPP,definedasasetofpracticesinwhichdesign,development,anddeploymenthappensimultaneouslyandrapidlyinthesameecosystem.Tosupportthisbasicprincipleofmodernsoftwaredesign,theGMTBalsocompleteddocumentsthatdescribetheconceptandmanagementoftheCCPPdevelopmentandsoftware,aswellasaproposedgovernancestructuretomanagetheevolutionoftheCCPP.TheconceptanddesignoftheCCPPdescribesanecosystemfordevelopmentandtransitionofphysics,whereanEMCdevelopercaneasilydeveloponhisownorengageexternaldevelopers.Codeiselevatedtosupportedoroperationalstatusfollowingasuiteofscientifictests.Detailsofthesetestsaretobedeterminedbyagovernancestructureyettobefinalized.AproposalforthisgovernancestructureisincludedintheGMTB’sCCPPRoadmap.TheGMTBtestharnesswillplayakeyroleinmakingthesetestsaccessibletoalldevelopers.Acodemanagementplanwascreatedtosupporttheecosystemandmeetthegovernanceneeds.

    Duringthefinaltwomonthsofthereportingperiod(Feb-March2017),theCCPPwascreatedwithplaceholderphysics–askeletontoguidetheconnectiontorealphysics.Fortestingpurposes,theGMTBSingleColumnModel(SCM)wasmodifiedtocallasuitecomposedoftheCCPPplaceholderphysicsthroughtheIPD.Thisimplementationcanbeconsideredthesimplest“dycorecap”fortheIPD–theSCMreplacesactualdynamicswithadvectiveforcing,butitenablesthetranslationofSCMstateanddiagnosticvariablestothosewithinthephysicssuite.ThefirstCCPPreleaseisplannedforearly2018.NCARandGSDphysicsdevelopershavebeenengaged,andwillbeconnectingnewphysicsunderseparatefunding

    Buildingondocumentationeffortsfromyear1,comprehensivetechnicalwebdocumentsarenowservedfromtheDTCwebsite,describingboththebackgroundandcurrentfunctionoftheIPDv2usedduringtheNGGPSdynamicalcoretestandtheinitialmemberoftheCCPP,the2016operationalGlobalForecastSystem(GFS)physicssuite.ThecontentofbothdocumentswasgeneratedroughlyequallybytheNCARandGSDmembers,drawingonexpertisefromallcontributorsasappropriate.AreviewbyphysicsexpertsatNOAAEMCwassolicitedandobtained,withfeedbackintegratedintothefinaldocuments.ThedocumentationfortheIPDandCCPPcanbeaccessedatthefollowingURLs,

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    respectively:http://www.dtcenter.org/GMTB/gmtb_ipd_doc/andhttp://www.dtcenter.org/GMTB/gfs_phys_doc/.

    Theprocessforupdatingthedocumentationgoingforwardisinfluxatthistime.AttherequestofEMC,sourcefilescontainingtheDoxygen-formattedcommentsusedtogeneratethedocumentationwebpagesweremergedintothetrunkofEMC’scoderepository.Inaddition,allexternalfiguresandfilesnecessarytogeneratethedocumentationhavebeenplacedinsidea‘docs’directorynexttothephysicssourcefiles.Asaresult,documentationmaybeversioncontrolledanditispossibleforbothDTCstaffandthoseatNOAAEMCtogeneratethedocumentationoutput.AlthoughaplanforfullyintegrateddocumentationforallcomponentsofNGGPSisnotcomplete,theDTChasprovidedinputtodecision-makerswithinNOAAregardingtheuseofDoxygenastheappropriatetoolandfordefiningtheprocessfordeveloperstoupdatedocumentationasdevelopmentprogresses.

    2.1 SoftwareManagement

    Whilespecificsoftwaremanagementplansdifferbetweenthevarioussoftwarepackages,theyallcontainthefollowingelements:

    • Coderepositoriesmaintainedunderversioncontrolsoftware.• Protocolsforproposingmodificationstothesoftware,whetherthemodificationsaresimply

    updatestocurrentfeatures,bugfixesortheadditionofnewfeatures.• Testingstandardsproposedsoftwaremodificationsmustpasspriortobeingcommittedtothe

    coderepository.• Additionaltestingstandardsusedtomorethoroughlychecktheintegrityoftheevolvingcode

    base.

    Givenallthesesoftwarepackagescontinuetoevolveovertime,alltestingstandardsmustbeupdatedperiodicallyinordertomeetthemaintenancerequirementsofthecodebase.Overthepastyear,theDTCcontinuedtocollaboratewiththevariousdevelopergroupsontheseongoingsoftwaremanagementactivities.TheDTCalsocontinuedtoprovideapathwayfortheresearchcommunitytocontributetothedevelopmentofthesesoftwaresystems.Noteworthyeventsfromthisworkoverthepastyearare:

    • WRF–Overthepastyear,worktowardsaddinganoptiontoruntheAdvancedResearchWRF(ARW)dynamiccorewithanewsmoothedterrain-followinghybrid-verticalcoordinatewascompleted.ThiscodewillbeincludedinthenextreleaseofWRFandwillbebackwardscompatibleifthenewoptionisnotselected.All2016operationalHWRFforecastsystemcapabilitieswerecommittedtotheWRFtrunk,andweremadeavailableforthenextcommunityreleaseofWRF.ThesecapabilitiesincludetheGFShybridEddy-DiffusivityMass-Flux(EDMF)PlanetaryBoundaryLayer(PBL)scheme(availableforbothARWandNonhydrostaticMesoscaleModelontheEgrid-NMME),updatestothesurfacefluxexchangeswiththecoupledocean(NMMEonly),updatedscale-awareSimplifiedArakawa-Schubert(SAS)cumulusparameterization(ARWandNMME),alandfalloptionfortheidealizedtropicalcyclone(TC)capability(NMMEonly),aswellasmiscellaneousbugfixesandtuningparameters.

    • UPP–TheDTCcontinuedtoworkcloselywithEMCtomanagetheUPPcodebasethroughregularbi-monthlymeetings.TostreamlinetheeffortstokeepthecommunityUPPinsyncwithEMC’soperationalUPP,thecommunityUPPsourcecodewasmigratedtoabranchoftheEMCrepositoryforeasiercodesharingandsyncing.ThroughcollaborationswithoperationaldevelopersandsupportedDTCvisitors,themostrecentcommunityreleaseofUPPincludedfull

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    GRIB2outputcapability,alongwithnewmicrophysics-specificreflectivityoutputandsyntheticsatellitefields.

    • HWRF–TheDTCcontinuedtosupportHWRFdevelopersinusingandaddinginnovationstothecoderepository.TheDTCcompleteddevelopmenttoenablethemultistormconfigurationtorunusingthesamesetupastheoperationalconfiguration,withtheexceptionofoceancoupling,andaddedthiscapabilitytotheHWRFrepository.FixeswerecommittedtotherepositorytoenablebackwardscompatibilityforthepreviousoperationalHWRFconfiguration.Additionally,theDTCdevelopedanewcapabilitytostartaHWRFrunfromtheWRFcomponentwhenusingwrapperstoaidHWRFcommunitydeveloperswhowanttomodifyandruntheatmosphericforecastcomponentwithoutgainingexpertiseonthefullend-to-endsystem.Theabilitytosimulatelandfallwithintheidealizedtropicalcyclonecapability,aninnovationdevelopedbyaDTCvisitor,wastransitionedtotheHWRFcoderepository.TheHWRFrepositorywasadaptedtoaccommodatethetransitionoftheWRFandWRFPre-processingSystem(WPS)repositoriesfromSubversion(SVN)toGitandthecommunityGSIrepositorytransitiontoVLab.UpdatedproceduresandinstructionswerepublishedtotheHWRFdevelopers’webpageandassistancewasprovidedviatheHWRFhelpdesk.TheDTCprovidedcoordinationofdevelopmentactivitiesbychairingtheHWRFdevelopers’committeebi-weeklymeetings.Additionally,DTCprovidedenhancedsupportfordeveloperscontributingtotheHWRFsystem,includingHurricaneForecastImprovementProject(HFIP)-fundedprincipalinvestigators.Tofacilitateinter-developercollaboration,theDTCcontinuedtohostanhwrf-contribrepositoryforpeer-to-peersharingofcode.TheNCARandGSDstaffconductedthisworkjointly.TheHWRFv3.7aandv3.8aUsers’GuideswerepublishedasGSDtechnicalnotes:

    Biswas,M.K.,L.Carson,C.Holt,L.Bernardet,2016:CommunityHWRFUsersGuideV3.7a.NOAATechnicalMemorandumOARGSD-46,doi:10.7289/V5SJ1HMD,144pp.

    Biswas,M.K.,L.Carson,K.Newman,L.Bernardet,C.Holt,2017:CommunityHWRFUsers’GuideV3.8a,NOAATechnicalMemorandumOARGSD-47,doi:10.7289/V5/TM-OAR-GSD-47,149pp.

    • GSIandEnKF–Overthepastyear,theDTCmadeafewcriticalupgradestocurrentcodemanagementandsupporteffortsfortheDAsystems.TheDTCtransitionedthehelpdesktoRequestTracker(RT)forbettertrackingofusers’requestsandquestions.TheDTCbuiltanewcommunityrepository(svn)onNOAA’sVlabserverandsuccessfullytransitionedallcommunityrepositorydeveloperstothisnewrepository.TheDTCalsoinitiatedeffortstoworkwithEMCtoimprovetheefficiencyofcodemanagementfrombothsidesasfollows:startedeffortstounifythecodebuildtool(usingcmake)forGSI,EnKF,andNCEPI/Olibraries;convertedtheuser’sguidestoLaTeXtosharewithalldevelopersthroughthecoderepository;andtransitionedcommunityutilities(e.g.,formatconversion,diagnosticplottingscripts)totheEMCrepository.TheseeffortswillcontributesignificantlytotheunificationoftheDTC-EMCcoderepositoriesoverthecomingyear.On-goingeffortsincluded:supportGSI/EnKFusersthroughthenewcoderepositoryandhelpdesk,performcodereviewsforeachproposedcodeupdateandsynchronizetheDTCcommunitycoderepositorywiththetrunkofEMC’soperationalrepository,coordinatetheGSI/EnKFdevelopmentamongdistributeddevelopersbychairingtheDAReviewCommitteeandhostingthreereviewcommitteemeetings.AnotableoutcomeofthereviewcommitteemeetingswastheadditionofJCSDAasthe10thmemberofthecommittee.

    ForAOP2016,theDTCscaledbackitsworkwiththeNOAAEnvironmentalModelingSystem(NEMS)/NonhydrostaticMultiscaleModelontheBgrid(NMMB)duetothelackofanyT&Eactivitiesutilizingthis

  • 9

    softwarepackage.WhiletheDTCisnolongeractivelyengagedincodemanagementorusersupportforthiscodebase,itdidcontinuetotesttheportabilityoftheNEMSsoftwarepackageandassociatedlibrariesthroughregressiontestingforregionalapplicationsontheNCARsupercomputer,Yellowstone.Overthepast6months,significantinfrastructureandcodearchitecturechangesoverthepastsixmonthsledtofailedportabilitytestsandretrofittingtoanewplatformisconsideredbeyondthescopeoftheDTCactivitiesatthistime.RelevantfeedbackwasprovidedtoEMCNEMSdevelopers.

    2.2 VerificationToolDevelopment

    Overthepastyear,theDTCverificationteamcompletedtwoMETreleases.METv5.2wasreleasedtothecommunityon15August2016andMETv6.0on3April2017.Approximately20majorenhancementsand50smallerbugfixesweresupportedtothecommunityinthereleases,includingtheupgradetoreading/writingNetworkCommonDataForm(NETCDF)4,a25%speed-upoftheGridpointStatisticalInterpolation(GSI)diagnostictool,andconfigurationfilechangestomakeMETeasiertoset-up.

    Tosupportglobalverification,thegrid-to-gridverificationtoolswereupdatedtoincludeaconfigurationoptiontoapplygridboxareaorcosine-latitudeweightingtothecomputationofcontinuousstatistics,suchasAnomalyCorrelation,RootMeanSquareErrorandBias.AlltoolsareprovidedwithGRIB1/2tablesupportfornon-NCEPtablessuchasUKMetOfficeandEuropeanCenterforMediumRangeForecasting(ECMWF).TheASCII2NCtool,whichcreatesNetCDFfilesfrompointobservationsinASCIIformat,wasenhancedtoincludeconfigurationoptionstospecifytheexpectedfrequencyofobservationsandomitoutputwhennotenoughvaliddataarepresent.ThisfeaturewasrequestedbytheNEMSGlobalAerosolComponent(NGAC)group.A“DESC“column(shortfordescription)wasaddedtoMETtoallowuserstoaddadescriptorformoreeffectivestratificationofstatisticsinbothMETandMETViewer.TosupportNOAA’stropicalcyclone(TC)verification,theTC-pairstool,whichmatchesTCforecastsandobservations,wasupdatedtohandleinterpolatedmodelswhosemodelidendsin'3',readprobabilisticforecastsfromthe“E-deck”fileformat,andincludemoreflexiblewaysofpassingthetooldifferentfilenamesforthebestandoperationaltracks.

    SeveralmeasuresandmethodswereaddedtoMETtosupportverificationoftotalcloudfractionontheglobalscale.NewinterpolationmethodswereaddedtoallowinterpolationofmodeloutputtobehandledinthemannersimilartotheWorldWideMergedCloudAnalysis(WWMCA)cloudfractionmapping.ThetoolforregriddingWWMCAwasenhancedtodrawadditionalfields,suchasSatelliteID(SatID)andpixelage,fromthebinarycloudanalysisfiles.Also,theGen-VX-masktool,whichcreatesabitmappedmaskedarea,wasupdatedtocomputethesolarazimuthandanglevaluesbasedonlocationandtimeofdaytoallowforthederivationofday/nightmask.

    TheMETViewerdatabaseanddisplaysystemisanotherverificationtoolunderdevelopmentduringtheAOP.Itwasmodifiedtosupportthenewfileformats,statisticsand“line”typesintroducedviatheMETv5.2andMETv6.0releases.TheDTCmodifiedtheloadinglogictohandlespecialcasesintroducedbydifferentversionsoftheNOAAmesoscaleandensembleverificationstatisticdatabasefileformat(VSDB).TheinterfacewasalsoenhancedtocomputethemeanandaratioofseveralcurvestosupporttheRegionalEnsemblesteam.Basicdatabasepurgingscriptswerealsogenerated.METViewerv1.9-1.12werereleased,includingtheadditionofaTaylorDiagramtemplate,enhancementstotheeventequalizationlogicandtheMethodforObject-basedDiagnosticEvaluation(MODE)attributecomputationforEMC’sMesoscaleandGlobalbranches,respectively.METViewerdatabasedesignwasinterrogated,severalchangesweremadetospeedupdataloadingandquerying.Thesechangesincludedpartitioningthedatabase,notattemptingtoloademptyfiles,andprovidingthecapabilitytoremoveasingleormultiplerecords,ifneeded.Newdatabasetechnologies(e.g.Couchbase)werealso

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    investigatedandfoundpromising.TheDTCalsoinvestigatedoptionstomodifytheMETViewerinterfacetoallowuserloginsandsaveuserpreferences.

    TeleconswithNOAAMETandMETVieweruserswereheldeverymonth,startinginOctober2016.Inviteesinclude25engagedNOAAstafffromEMC,WeatherPredictionCenter(WPC)andGSD.ThediscussionsweredrivenbyquestionsarisingfromincreaseduseofMETandMETViewer.Inresponsetothesemeetings,theDTCstaffansweredmanyquestions,fixedseveralbugsintroducedwithloadingVSDBdataintoMETViewer,improvedthespeedofloadingMETViewerandaddednewfeaturestobothMETandMETViewer.METViewercodewasmovedintoGitHubtoallowbothDTCnodesandexternalcollaboratorsaccess.Additionally,planninganddevelopmentoftheinitialpythonwrappersaroundthecomponents,calledMET+,wasdistributedacrossbothDTCnodes.TheGSDnodecontributionestablishedagreaterunderstandingoftheMET+components(METandMETViewer)andallowedmoremeaningfulcollaborationbetweenthenodes.

    2.3 Publicly-ReleasedSystems

    TheDTCcurrentlycollaborateswithdevelopersonsevensoftwaresystemsthatundergoapublicreleaseprocess:WRF,UPP,HWRF,GFDLvortextracker,GSI,EnKFandMET.Assistancecontinuedtobeofferedthroughemailhelpdesksforallpackages.Informationregardingthetimingandversionofthemostrecentrelease,alongwiththecurrentnumberofregisteredusersandaveragehelpdeskticketspermonthforeachpackagearelistedinTable2.3-1.Table2.3-2containsalistofthewebaddressesforeachsoftwarepackage’susers’page.

    Table2.3-1:Codereleases,numberofregisteredusersandnumberofhelpdeskticketspermonthforthepublicly-releasedsoftwarepackagessupportedbytheDTCoverthepastyear.

    SoftwarePackagePublicRelease

    Version Timing RegisteredUsers Helpdeskticketspermonth

    WRFV3.8 April2016

    ~32,700 ~400V3.8.1 August2016

    UPP V3.1 September2016 ~740 ~10HWRF V3.8a November2016 1399

    ~30GFDLVortexTracker V3.5b September2013 617

    GSI V3.5 August20161,687

    ~20EnKF V1.1 August2016 ~2-5MET V5.2 August2016 3180 ~20-25

    Table2.3-2:Userspagewebsitesforpublicly-releasedsoftwarepackages.SoftwarePackage UsersWebsites

    WRF http://www.mmm.ucar.edu/wrf/users/

    UPP http://www.dtcenter.org/upp/users/

    HWRF http://www.dtcenter.org/HurrWRF/users/

    GSI http://www.dtcenter.org/com-GSI/users/

    EnKF http://www.dtcenter.org/EnKF/users/

    MET http://www.dtcenter.org/met/users/

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    InadditiontogeneralMETusersupport,theDTCverificationteamactivelyrespondedtorequestsfromNOAAusersregardingtheuseofMETandMETViewer.Accomplishmentsoverthepastyearinclude:1)increasednumberofMETandMetViewerusersfromNOAA(from74to100);2)workedwithNCEPEnvironmentalModelingCenter(EMC),WeatherPredictionCenter(WPC),andClimatePredictionCenter(CPC)toidentifyrequirementsnecessarytounifyverificationbetweenDTCandEMC;3)whitepaperelucidatingtherequirementssubmittedtopointsofcontactatEMCandEMCdirector;4)startedexploringdatabasedesignstohandlelargedatasets;and5)participatedintheNGGPSVerificationandValidationTeamdiscussions.

    TheDTCrevampedtheonlinetutorialsforbothGSIandEnKF.Theonlinetutorialswereredesignedtoprovidemoreuser-friendlyinstructionsalongwiththelatestGSIandEnKFcapabilities.Testcaseswerecarefullyselectedwithnewtestingperiodsanddomains,coveringupdatedandadditionalconfigurationswithalternativedataassimilationtechniques[3DVar,3Dhybrid,4DhybridEnsembleVariational(EnVar)],datatypes(conventionalandsatelliteradiancedata),andforecastmodels(ARW,HWRF,NMMB,WRF-chem,GFS).

    2.4 DTC-supportedsoftwarecontainers

    Manytimesthebiggesthurdlewhenrunninganewsoftwaresystemisgettingitsetupandcompiledontheintendedcomputerplatform.Buildingcomplexsystemsthatrequireanumberofexternallibrariescanbealargeissueforuserstoovercome.Inordertorelievesomeofthisdifficulty,anewtechnologyreferredtoasa“container”hasbeendevelopedthatallowsforcompletesoftwaresystemstobebundledandshippedtousers.Thecontainersincludeeverythingthatisneededtorunthesoftwarecomponent,includingtheoperatingsystem(toolsandlibraries)andcode-thusallowingfortheusertoquicklyproduceoutputwithoutbeingdelayedbytechnicalissues.

    ContainershavebeenestablishedoutsideoftheDTCforportionsofanend-to-endNWPsystem,includingWPS,WRF,andNCL.DuringAOP2016,DTCstaffestablishedcontainersfortheUPPandMETsoftwaresystems.Inaddition,datasetsthatmakeuptwoMesoscaleModelEvaluationTestbed(MMET)caseswerebundledinacontainer.ContainersareavailableviaGitHubtorunMET(https://github.com/NCAR/container-dtc-met)andtoruntheend-to-endsystem(includingMETandMMETdataset(https://github.com/NCAR/container-dtc-nwp).Byestablishingtheseadditionalcontainers,theDTCisassistingtheusercommunity(especiallystudents)withefficientlyrunningNWPcomponentsinanefforttofosterconnectionswithfuturecollaborators.

    3 TestingandEvaluationT&EactivitiesundertakenbythedevelopersofnewNWPtechniquesfromtheresearchcommunityaregenerallyfocusedoncasestudies.However,inordertoadequatelyassessthesenewtechnologies,extensiveT&Emustbeperformedtoensuretheyareindeedreadyforoperationalconsideration.DTCT&Egenerallyfocusesonextendedretrospectivetimeperiods.Thecasesselectedincorporateabroadrangeofweatherregimesrangingfromnull,toweakandstrongevents.Theexactperiodschosenvarybasedonthephenomenonoffocusforthetest.ThetechniquetobetestedmustbepartofthecoderepositoriessupportedbytheDTCtoensurethatthecodehasreachedacertainlevelofmaturity.TheDTC’sevaluationoftheseretrospectiveforecastsincludesstandardverificationtechniques,aswellasnewverificationtechniqueswhenappropriate.Allverificationstatisticsundergoastatisticalsignificance(SS)assessmentwhenappropriate.Byconductingcarefullycontrolled,rigoroustesting,includingthegenerationofobjectiveverificationstatistics,theDTCisabletoprovidetheoperationalcommunitywithguidanceforselectingnewNWPtechnologieswithpotentialvalueforoperationalimplementation.DTCtestingalsoprovidestheresearchcommunitywithbaselinesagainstwhichtheimpactsofnew

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    techniquescanbeevaluated.Thestatisticalresultsmayalsoaidresearchersinselectingmodelconfigurationstousefortheirprojects.

    3.1 RegionalEnsembles

    MesoscaleNWPsystemsareutilizedinbothresearchandoperationalforecastingapplicationsandcanbeconfiguredtosuitabroadspectrumofweatherregimes.DuetothenumberofapproachesdevelopedandofferedbyNWPsystems,itisnecessarytorigorouslytestselectconfigurationsandevaluatetheirperformanceforspecificapplications.

    OnepaperassociatedwithapastRegionalEnsemblesactivitywaspublishedinMonthlyWeatherReview:

    Jankov, I., J. Berner, J. Beck, H. Jiang, J.B. Olson, G. Grell, T. G. Smirnova, S. G. Benjamin, J. M. Brown, 2017: A performance comparison between multiphysics and stochastic approaches within a North American RAP ensemble. Mon. Wea. Rev., 145, 1161-79.

    3.1.1 MesoscaleModelEvaluationTestbed(MMET)

    TheMesoscaleModelEvaluationTestbed(MMET;http://www.dtcenter.org/eval/meso_mod/mmet)providestheopportunityfortheresearchcommunitytoconducttheirownT&Eofanewtechnique.DatasetsforanumberofcasesdeemedtobeofhighinterestbyEMCaredistributedviaRAMADDA,aRepositoryforArchiving,ManagingandAccessingDiverseDAta(http://ramadda.org/).MMETdatasetsincludeavarietyofinitializationandobservationdatasets,aswellasbaselinesforselectoperationalconfigurations.Casesofinterestand/orpersistentoperationalmodelissueswereidentifiedthroughouttheyearbyleveragingadirectlinktoEMC’sModelEvaluationGroup(MEG)throughDTCstaffparticipationinMEGweeklytelecons.Alistofoperationalcasesofinterestand/orpersistentmodelweaknesseswascompiledbasedontheseweeklydiscussionsandpublicizedontheMMETwebpage(http://www.dtcenter.org/eval/meso_mod/mmet/additional_cases.php).

    Inthepast,asnewversionsoftheWRFandNEMScodewerereleased,MMETcaseswerereruntoprovidecurrent,baselineresultsfortheusercommunity.Whilethefullend-to-endsystemisnolongerupdatedonanannualbasis,previousversionswillremainavailablethroughtheRAMADDAdataserver.Rather,thisyear,operationalmodeloutputforseveralNWPsystems(bothdeterministicandprobabilistic)wereevaluatedandtheobjectiveverificationscoresprovidedtotheresearchcommunitythroughMMET.TheoperationalforecastsystemsincludedtheNorthAmericanMesoscale(NAM),RapidRefresh(RAP),High-ResolutionRapidRefresh(HRRR),andHurricaneWRF(HWRF).ThesebaselinesareprovidedforallnewandexistingMMETcasesforeachavailableoperationalmodel.Twonewcaseswereestablishedthisyear:1)acaseoverAlaska(20150826:TyphoonAtsaniremnantsaffectingAlaska)and2)ahurricanecase(20160928-29:HurricaneMatthew).AnothernewadditionthispastyearistheevaluationoftheStormScaleEnsembleofOpportunity(SSEO)datacollectedfromthe2016HazardousWeatherTestbed(HWT)SpringExperiment.ThisevaluationincludeddeterministicperformanceresultsforeachindividualSSEOmemberalongwithprobabilisticresultsfromtheensembleasawholeforselectvariables;theplotsforselectvariables,thresholds,andmetrics,aswellastheMETViewerXMLsusedtogeneratetheplots,areavailableviaRAMADDA.

    Inaddition,communityoutreacheventscontinuetobeprovidedbytheDTCtopromoteenhancedconnectionswithfuturecommunitycollaboratorsandpromotetheuseofMMETdatasets.A1.5hourinstructionalsessionwasofferedduringthe17thWRFUsers’WorkshopinJune2016toraiseawarenessaboutandhighlightthetoolsavailabletothecommunity-at-largethroughMMET.AposterwaspresentedonMMETattheAmericanMeteorologicalSociety(AMS)AnnualMeetinginJanuary2017;

  • 13

    Harrold,M.,J.K.Wolff,andT.Hertneky,2017:MesoscaleModelEvaluationTestbed(MMET):HelpingConnecttheResearchandOperationalCommunities.28thConferenceonWeatherandForecasting/24thConferenceonNumericalWeatherPrediction,Seattle,WA,January24-27,2017.

    andaproposaltoholdashortcourseonusingDTC-supportedcontainers(includingMMETcases)atthe2018AnnualAMSmeetingisbeingwrittenforsubmissionattheendofApril.Finally,amanuscriptwaspreparedandacceptedforpublicationintheNovembereditionoftheBulletinoftheAmericanMeteorologicalSociety(BAMS).

    Wolff,J.K.,M.Harrold,T.Hertneky,E.Aligo,J.Carley,B.Ferrier,G.DiMego,L.Nance,Y.-H.Kuo,2016:MesoscaleModelEvaluationTestbed(MMET):AresourcefortransitioningNWPinnovationsfromresearchtooperations(R2O).Bull.Am.Met.Soc.DOI:http://dx.doi.org/10.1175/BAMS-D-15-00001.1

    3.1.2 HRRREnhancements

    TheHigh-ResolutionRapidRefresh(HRRR)modelbecameoperationalatNCEPon30September2014,andhasfoundwideacceptancebyforecastersinsideandoutsideoftheNationalWeatherServiceasguidanceforavarietyofweatherphenomenaacrossallseasons.TheHRRRusestheARWdynamicalcore,aphysicspackagethathasprovedeffectiveatcapitalizingonthecloud-permittingresolutionofthemodel,anduniqueinitializationproceduresusingradarandsatellitedata,aswellasconventionalin-situobservations,togetherwithaRapidRefresh(RAP)forecast.Inviewoftheimportanceofaccurateshort-termforecastsforvulnerablecoastalareas,particularlyalongtheGulfandAtlanticcoasts,theDTCinvestigatedthevalueofexpandingtheHRRRdomaintowardtheeastandsouth.Atthetimethisworkwasoriginallyproposed,theoperationalNCEPHRRRforecastsonlyextendedto15h,butESRLisnowrunningtheHRRRexperimentallyto36h.ThelateralboundariesoftheHRRRdomainareoftenwithinthecirculationofnortheastcoastalsnowstormsandland-fallingtropicalcycloneswhenthesesystemsarewithina24-36-hstrikingdistanceoftheUSmainland.ExpandingtheboundariesofthecurrentHRRRdomainthusbecameincreasinglyimportantfortheselongerforecastlengths.

    ThreetropicalcyclonecasestudieswereconductedwithHRRRversion2(HRRRv2),whichistheversionimplementedoperationallyatNCEPinAugust2016.Themodelinitializationtimesforthethreestormswerechosensuchthatthecenterofeachstormwasnearorslightlyoutsidethestandarddomainbutwellinsidetheextendeddomain.Thestormsandinitializationtimesofinterestwere:Bonnie(12UTC27May2016),Colin(00UTC6Jun2016)andHermine(12UTC31Aug2016).ExtendeddomainsimulationswerealsoconductedforHurricaneHermine,withandwithoutlightningdataassimilation,toaforecastlengthof36h.Herminewaschosenbasedonthelargenumberoflightningstrikesoccurringinanareaofrelativelylowsimulatedreflectivityvaluesatmodelinitializationtime.

    Projectdeliverablesweretwo-fold:(1)upgradedproceduresforinitializationofconvection-permittingmodelsoveroceanareaspronetodeepconvection,mesoscaleconvectivesystemsandtropicalcyclones,and(2)arecommendationfordomainconfigurationandphysicssuiteforanexpandedHRRR.Theresultsofourexperiments,particularlythoseforHurricaneHermine,suggestedforecastvalueassociatedwithexpandingtheHRRRdomaintothesouthandeast.ResultsofsensitivityteststolightningdataassimilationpromptedinclusionofalightningreflectivityproxyalgorithmwithintheexperimentalHRRRv3,foreventualimplementationatNCEPin2018.Amorecomprehensivesummaryofthisworkisavailableonlineat:http://www.dtcenter.org/eval/ensembles/dtc_expanded_domain_report.docx

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    3.1.3 Testingandevaluationofsmoothedterrain-followingcoordinateinWRF

    Oncethenewsmoothed,terrain-followingcoordinatewascommittedtotheRAP/HRRRrepositoryinlate2016,theGSDnodeofDTCbeganimmediatetestingtoanalyzetheimpactsofthisnewverticalcoordinate.ThisnewfeaturewasemployedintheexperimentalRAPandHRRRmodelsrunatGSD,andanumberofcoldstartRAPrunswereconductedascontrolledtestsofthenewverticalcoordinate.Itquicklybecameclearthataproblemexisted,asnumerousmodelcrashesfollowedandspurious/excessivejet-levelwindcharacteristicswerefounduponanalysisofmodelresults.ThesefindingsweresharedwiththeWRFdevelopers.Abugrelatedtothemapscalefactorwasfoundandcorrectedinearly2017.

    FollowinganewversionofthecodebeingcommittedtotheGSDrepository,testingbeganagaininMarch2017toassessthehybridverticalcoordinate.Initialqualitativetestsusingcold-startRAPforecastsproducedstableresults.Differenceswerefoundtobenegligibleatinitializationtime,butbysixhoursintotheforecasts,250-hPawindspeedvalueswithinthecoreoftheupper-leveljetforthehybridcoordinatewerefoundtoexceedvaluesinforecastsusingtheoriginalverticalcoordinate.Outsideofthemajorupper-leveljet,anumberofareaswerefoundwherewindswereslowerforthehybridcoordinate.Mostofthedifferenceswerefoundtooccurover,ordownwindofmajormountainranges,specificallyinthewesternareasofNorthAmerica.

    Furthertestingwasundertakenwithaweek-long,fully-cycledRAPexperiment,conductedfortheperiodbetween7-13March2017andanotherfive-dayexperimentfor3-7September2016.Resultsfromthesetworetrospectiverunsindicatedthehybridcoordinateresultsweresensitivetothestrengthoftheupper-leveljet.FortheSeptember2016experiment,ContiguousUnitedStates(CONUS)-wide,upper-levelrelativehumidityandwindspeedRMSEandbiasimprovedbyastatisticallysignificantamountwhenthehybridcoordinatewasused.FortheMarch2017timeperiod(Fig.3.1.3-1),similarstatistically-significantreductionsinRMSEandbiaswerefoundfortheCONUSasawhole;however,windspeedbiasfortheWesternCONUSshowedastatistically-significantdegradation.Theupper-leveljetwasstrongerintheMarch2017retro,andthereforeitishypothesizedthatthesmoothed,terrain-followingcoordinateisresultinginwindsthatareslightlytoostrongovermountainousterrainduringsynopticallyactiveperiods.Itshouldbenotedthatverificationbelowabout500hPashowednostatisticallysignificantdifferencesbetweenthetworetrospectivesimulations,highlightingtheimpactofthehybridverticalcoordinateonjet-levelwinds,particularlyinmountainousregions.

    Afinalweek-longsimulationwasconductedwiththeHRRRfrom3-10September2016toassesstheimpactofthesmoothed,terrain-followingcoordinateatconvective-resolvingresolution.Resultsfromthisretrospectivesimulationshowedavastlyreducedimpactofthehybridcoordinate.Nostatisticallysignificantdifferenceswerefoundbetweenthetwoverticalcoordinatesouttothefull12hoursofeachforecast,andonlyminor,non-statisticallysignificantdifferenceswerefoundat12hours,limitedtoregionsabove200hPa.Onepossibleexplanationforthesefindingsisthatthehybridcoordinateissensitivetoresolution,withtheconvective-allowingmodelbeingabletobetterresolvemountainousterrain,therebyminimizinganydifferencesfoundbetweentheretrospectiveruns.Givenanypotentialdecreasedsensitivityathigherresolutions,itisalsopossiblethattheretroperiodofSeptember2016didnotcontainupper-levelwindspeedvaluesnecessarytoillustrateadifferenceinverticalcoordinatesat3-kmresolution.

    Overall,thehybridverticalcoordinateappearstoproducethelargestimpactatupperlevels,particularlyforwindspeed.Inaddition,thesedifferencesareamplifiedovermountainousterrain,wherethelargestdisplacementsofthehybridverticalcoordinatefromthetraditionalverticalcoordinatearefound.

  • 15

    Resultsalsoshowedthatasresolutionincreases,theexpecteddifferencesbetweenthetwoverticalcoordinatesdecrease,likelyrelatedtoimprovedterraininhigher-resolutionmodels.

    Giventhesefindingsandapparentsensitivitytoseasonandresolution,theNCARnodeoftheDTCwillinvestigatethehybridverticalcoordinatethroughanumberofMMETcasestudiesoveravarietyofdifferentsynopticconditions.TheseresultsareforthcomingandafinalreportforthistestingactivitywillbeavailableontheDTCwebsitebytheendofJune2017.Amanuscripthighlightingfindingsforthisactivitywillbesubmittedbeforetheendof2017.

    Figure3.1.3-1.Hybridcoordinate(red)andterrain-followingcoordinate(blue)resultsfromtheRAPretrospectiveforecastsfor7-13March2017.CONUSRMSEisshownfortemperature(upperleft),relativehumidity(uppercenter),andwindspeed(upperright),andbiasforwindspeed(lowerleft).WindspeedbiasforthewesternCONUSisshowninthelowercenterplot,andatimeseriesofaveragedwindspeedbiasforthewesternCONUSfrom300-150hPaisshowninthelowerright.

    3.1.4 AddressinguncertaintythroughstochasticparameterperturbationswithintheHRRRensemble

    Inmostexistingregionalensemblesystems,model-relateduncertaintyisaddressedbyusingmultipledynamiccores,multiplephysicssuites,oracombinationofthesetwoapproaches.Whiletheseapproacheshavedemonstratedpotential,itistime-consumingandcostlytomaintainsuchsystems,especiallyinoperations.Inordertomovetowardamoresustainableandunifiedsystem,stochasticparameterperturbationswithintheHRRRphysicssuitewereinvestigatedwithafocusonplanetaryboundarylayer(PBL)andLandSurfaceModel(LSM)processes.

    ForAOP2016,theRegionalEnsembleteamestablishedatestharnessusingtheRocotoWorkflowManagementSystemtoconductfunctionallysimilarend-to-endtestingoftheHRRRmodelinbothadeterministicandensemblemode.ThistestharnessincludesMETverificationtaskstoevaluatethedeterministicandprobabilisticforecastoutput.TheinclusionofMETintheworkflowprovidesthe

  • 16

    opportunitytonotonlyverifythefinalproducts,buttoalsoiterativelyadjusttheensembledesignwhileexamininghowprobabilisticstatisticschangewhendifferentapproachesareutilized.

    Duetothehighlevelofcomplexityofrunningafrequentlyupdating(hourly),highspatialresolution(3km),largedomain(ContiguousUnitedStates-CONUS)ensemblesystem,extensivehighperformancecomputing(HPC)resourceswereneededtomeetthisobjective.AproposalwaswrittenandsupercomputingresourceswereprovidedthroughtheNCARStrategicCapability(NSC)projectsupport.ThisHPCallocationallowedforamoreextensivesetoftestsleadingtomorerobustresultsthanwouldhaveotherwisebeenpossible.

    Asafirststeptowarddesigningthetest,numeroussensitivitytestsofstochasticparameterperturbations(SPP)appliedtovariousparameterswithinthePBLschemeandincombinationwithmorecommonlyusedstochasticapproachesStochasticKineticEnergyBackscatter(SKEB)andStochasticPerturbationofPhysicsTendencies(SPPT),werecarriedout.AvarietyoftestswerealsoperformedinvolvingtheLSMscheme.Preliminaryresultshighlightinginitialtestingofselectspatialandtemporalde-correlationlengthscalesofsoilmoistureperturbationswerepresentedaspostersatthe2016FallAGUmeeting

    Wolff,J.K.,I.Jankov,J.Beck,L.Carson,J.Frimel,M.Harrold,H.Jiang:M.Xu,2016:AddressingmodeluncertaintythroughstochasticparameterperturbationswithintheHighResolutionRapidRefresh(HRRR)ensemble.Presentedat2016FallMeeting,AGU,SanFrancisco,CA,December12-16,2016.andthe2017AnnualAMSmeeting.

    Andthe2017AnnualAMSmeeting

    Beck,J.,I.Jankov,H.Jiang,J.K.Wolff,M.Harrold,J.Frimel,andL.Carson,2017:AnevaluationofstochasticphysicswithintheHighResolutionRapidRefreshEnsemble(HRRRE)andtheimpactsofHighPerformanceComputing(HPC).3rdSymposiumonHighPerformanceComputingforWeather,Water,andClimate,Seattle,WA,January24-27,2017.

    Basedontheoutcomeofthesensitivitytests,aretrospectiveexperimentwasdesigned.Inadditiontothestochasticensembleconfiguration,theplanincludedacontrolensembledesignedtoincludeavarietyofPBLandLSMschemestorepresentthecurrentstateofregionalensembleconfigurations.TheSSEOobtainedfromNSSLandSPCcolleaguesforalimitedvariabledatasetservedasasecondbaselineforthistest.AdeterministicHRRRrunwithoutperturbationswasalsoperformedtoprovideabaselinetomakesuretheSPPperturbationsdidnotintroduceanunrealisticbias.Severalextendedretrospectiverunshavebeencompletedandtheteamisintheprocessofanalyzingtheresults.AreportonthefindingswillbeavailableontheDTCwebsitebytheendofJune2017.TheRegionalEnsembleteamwillalsobepreparingamanuscriptforsubmissiontoMonthlyWeatherReview,asafollowuptorecentlypublishedresultsfortestingofSPPintheRAPframework.

    3.1.5 WRFtestingandevaluationactivity

    InresponsetoWRFconfigurationrecommendationsfromNCAR’sMMMdivision,theAFrequestedtheDTCconductaWRFconfigurationtestwithWRFv3.8.1toprovidecriticalinformationforapossibleoperationalimplementation.InadditiontotransitioningtoanewversionofWRF,theseconfigurationupdatesincludedmigrationtotheThompsonaerosol-awaremicrophysicsschemeandtheupdatedRapidRadiativeTransferModelforGlobalClimateModels(RRTMG)radiationscheme.Toaddressthisrequest,DTCstaffconductedanend-to-endtestandevaluationactivitytoassessthesensitivityofreplacingtheAirForce’scurrentWRFv3.5.1operationalconfiguration,whichwaspreviouslytestedbytheDTC,withaproposedconfigurationforv3.8.1.Forthistest,theDTCgeneratedretrospectiveWRFv3.8.1forecastsforthesamecasesusedforitspriorWRFv3.5.1testingactivity(1July-30September

  • 17

    2011and1January-31March2012)andcomparedthesenewretrospectiveforecaststothearchivedv3.5.1forecasts.DetailsoftheWRFv3.5.1andv3.8.1configurationsaresummarizedinTable3.1.5-1.Aprojectwebpageisbeingfinalizedandwillincludepertinentinformationregardingthetestsetupandthefullsuiteofresults,alongwithacomprehensivefinalreport(http://www.dtcenter.org/eval/meso_mod/afwa_test/wrf_v3.8.1/index.php).

    Table3.1.5-1:Physicssuiteconfigurationsettingsforversion3.5.1and3.8.1,alongwithothernamelistdifferencesbetweenversions.

    PhysicsSuite v3.5.1 v3.8.1 Othernamelistchanges(v3.5.1→v3.8.1)

    Microphysics WSM5 Thompsonaerosol-aware timestep:90s→60s eta_levels rh2qv_method:1→2 icloud:1→3 aer_opt:1→3 swint_opt:turnedon ysu_topdown_pblmix:turnedon use_aero_icbc:true diff_opt:1→2 dampcoef:0.05→0.2 epssm:0.1→0.5 scalar_adv_opt:0→1

    Radiation(LW/SW) RRTM/Dudhia RRTMG/RRTMG

    SurfaceLayer Monin-ObukhovsimilaritytheoryRevisedMM5Monin-Obukhov

    LandSurface Noah NoahPBL YSU YSUConvection Kain-Fritsch Kain-Fritsch

    Thetestingmethodologyallowedforpair-wisedifferencestobecomputedbetweenv3.5.1andv3.8.1,includinganassessmentofbothstatisticallysignificant(SS)andpracticallysignificant(PS)pair-wisedifferences.Consistentwiththesignificantchangesassociatedwiththev3.8.1configuration,alargenumberofSSandPSpair-wisedifferenceswereobservedforboththesurfaceandupperairmetrics.Briefly,intermsofBCRMSE,anumberofPSdifferenceswereseenfor2-mtemperatureanddewpointtemperature,generallyfavoringAFv3.8.1;veryfewofthedifferencesfor10-mwindspeedwerePS(notshown).Intermsofbias(seeFig.3.1.5-1),acoldtemperaturebiasat2mwasgenerallyobservedforbothconfigurations;however,AFv3.8.1wasgenerallythepreferredconfiguration,withafewexceptions.For2-mdewpointtemperature,PSdifferencesforbiasgenerallyfavoredAFv3.8.1.WhileveryfewPSdifferenceswerenotedfor10-mwindspeed,theSSdifferencesforbiasfavoredAFv3.5.1.Intermsofupperairverificationresults,upper-airtemperaturebiasshowedAFv3.8.1asthepreferredconfigurationovertheWestduringthesummer;resultsweremoremixedovertheWestduringthewinterandintheEastforbothseasons.Upper-airdewpointtemperaturebiasshowedAFv3.5.1wasfavoredintheWest,whileintheEast,AFv3.8.1wasfavoredduringthesummerwithmoremixedresultsinthewinter.Upper-airwindbiasSSdifferencesgenerallyfavoredAFv3.5.1inthesummerwithsomePSdifferences,whilewinterwasmixedwithonlyoneinstanceofPSdifferences.

    WhenexaminingtheGOIndex(Fig.3.1.5-2),askillscoredevelopedbytheAF,AFv3.5.1wasshownasthebetterperformerforboththe00and12UTCinitializationsduringthesummerandwinterseasons.Basedontheoverallresultsfortheindividualmetrics,aninvestigationintothecauseoftheAFv3.8.1degradationintermsoftheGOIndexwasconductedandshowedthatremovalofRMSEfor400hPaheightfromthecalculationresultedinareversalofperformance,whereAFv3.8.1waspreferredforallbutthe00UTCwinteraggregation.

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    Figure3.1.5-1.Timeseriesplotof(a)2-mAGLtemperature(°C)(b)2-mAGLdewpointtemperature(c)10-mAGLwindspeedmedianmeanerror(bias)forthe00UTCinitializationsaggregatedacrossthesummercasesfortheEast(solid)andWest(dashed)verificationdomains.AFv3.5.1isinblueandAFv3.8.1inred.Theverticalbarsattachedtothemedianrepresentthe99%CIs.

    Figure3.1.5-2.BoxplotsofGOIndexvaluesaggregatedacrossthesummerandwinterseason,stratifiedbyinitializationtime,where00UTCisinredand12UTCisinbluefor(a)thestandardGOIndexcalculationand(b)theGOIndexcalculationwithout400hPaheight.Themedianvalueisthethickblacklinelocatedatthevertexofthenotches,thenotchesaroundthemedianareanapproximationofthe95%confidenceaboutthemedian,thewhiskers,denotedbytheblack,dashedlines,denotethelargestvaluesthatarenotoutliers,andthecirclesrepresenttheoutliers.

    b)

    c)

    a)

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    3.2 Hurricanes

    3.2.1 ImpactofThompsonmicrophysicsinHWRF

    2013T&EactivitiesrevealedthatThompsonmicrophysicsinthe2013versionofHWRFproducedimprovementsintrackfortheAtlantic(AL)basin,butdegradedthetrackforecastsfortheEasternNorthPacific(EP)basin.GiventhesignificantupgradestotheoperationalHWRFsystemafterthe2013version,performancewhenusingtheThompsonmicrophysicsschemewithinthe2015HWRFwasre-evaluated.ThisT&EactivitywasdesignedinclosecollaborationwiththeEMCHWRFteamtoinform2016pre-implementationtesting,wheretheThompsonandadvectedFerrier-AligomicrophysicsschemeswerebothcandidatesforreplacementoftheoperationalFerrier-Aligomicrophysicsscheme.ThefocusoftheDTC’sevaluationwastodeterminetheimpactofreplacingtheoperationalFerrier-AligomicrophysicsschemewiththeThompsonmicrophysicsscheme.TheoperationalFerrier-Aligoschemeadvectstotalcondensateonly,whereastheThompsonschemeadvectsindividualspecies.TheexperimentsincludedfivestormsfromtheALbasinandelevenstormsintheEPbasinthatoccurredduringthe2014and2015seasons.ParticularemphasiswasplacedonEPbasinstormsinresponsetothe2013T&Eresults.Priortoconductingtheretrospectivetest,boththeThompsonschemeandthepartialcloudiness(PC)schemewithintheRapidRadiativeTransferModelforGlobalClimateModels(RRTMG)parameterizationweremodifiedinanefforttounderstandandaddressthecauseoftheincreasedtrackerrorintheEPbasin.ThesemodificationsincludedfallspeedchangeswithintheThompsonmicrophysicsschemeandalterationstotheRRTMGpartialcloudinessschemetoimplementabugfixandchangethelowerlimitofthesnowandiceparticlesize.ThemajorityoftheworkonthisT&EactivitywascompletedpriortothisreportingperiodandwasdescribedfullyintheAOP2015report.ResultsrevealedthattheexperimentalconfigurationproducedimprovedtrackandintensityforecastsintheALbasin.However,intheEPbasin,theexperimentalconfigurationimprovedthespatialdistributionofclouds,buttheseimprovementsdidnottranslateintoimprovementsintrackandintensityforecasts.

    ThefullreportforthisThompsonmicrophysicsevaluationisnowavailableontheDTCwebpage:http://www.dtcenter.org/eval/hwrf_thomp2016/.

    TheDTCpresentedresultsfromthisworkduringthe32ndAMSHurricaneandTropicalMeteorologyConference(April2016)andthe17thAnnualWRFUsers’Workshop(June2016):

    Holt,C.,M.Biswas,Z.Zhang,S.Trahan,L.Bernardet,G.Thompson,K.Newman:Anevaluationofalternativespecies-advectingmicrophysicsschemesinHurricaneWRF,32ndConferenceonHurricanesandTropicalMeteorology,18-22April2016,SanJuan,PR.

    Thompson,G.,L.Bernardet,K.Newman,M.Biswas,andC.Holt:Towardsimprovingexplicitlyresolvedandsub-grid-scalecloudsinHurricaneWRF.32ndConferenceonHurricanesandTropicalMeteorology,18-22April2016,SanJuan,PR.

    Holt,C.M.K.Biswas,Z.Zhang,S.Trahan,L.R.Bernardet,G.Thompson,K.M.Newman:Anevaluationofalternativespecies-advectingmicrophysicsschemesinHurricaneWRF.WRFUsers’Workshop,27-30June2016,Boulder,CO.

    3.2.2 HWRFphysicsadvancementForAOP2016,theDTCpartneredwithDTCVisitorProgramPrincipleInvestigatorsandsubjectareaexpertstohelpcoordinateandtesttheperformanceofalternatephysicsschemesandinnovationsrelativetothecurrentparameterizationswithintheHWRFphysicssuite.Physicsadvancementsconsideredfortestingcoveredradiation,planetaryboundarylayer(PBL),microphysicsandcumulus

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    parameterizations,summarizedinTable3.2.2-1.InadditiontocoordinationandsupportforHWRFphysicsdevelopers,theDTCevaluatedthecodereadinessofcandidatephysicsadvancementsandconsultedwiththeEMChurricaneteamontopprioritiesforHWRF2017pre-implementationtesting.

    Table3.2.2-1.Candidatephysicsadvancementsfortestingandevaluation.Innovationsselectedfortestingareindicatedinbold.

    PhysicsDeveloper Institution Scheme DescriptionM.Iacono,J.Henderson AER–DTCVisitor

    ProgramPIRRTMGradiation Cloudoverlapmethodology

    G.Thompson NCAR/RALandDTC RRTMGradiation Modifiedpartialcloudinessscheme

    G.Thompson NCAR/RALandDTC Thompsonmicrophysics

    EnhancedschemebasedonAOP2015T&Eresults

    S.Bao CCU–DTCVisitorProgramPI

    advectedFerrier-Aligomicrophysics

    InvestigationofadvectedmicrophysicswithinHWRF

    R.Fovell U.Albany–DTCVisitorProgramPI

    YonseiUniversityPBL HWRFsensitivitytoalternativePBL/surfacelayerschemes

    G.Grell,E.Grell NOAA/ESRL–NGGPSPI

    Grell-Freitascumulus Replacementschemeforscale-awareSimplifiedArakawa-Schubertscheme

    RetrospectivecaseswererunforfourstormsintheALbasin(Edouard,Gonzalo,Matthew,Fiona)andtwostormsintheEPbasin(Patricia,Dolores)thatoccurredduringthe2014-2016hurricaneseasons.Alimitednumberofstormswererunduetocomputationalconstraints.Inanefforttoincreasestormdiversitywithlimitedresources,126hourforecastswererunevery18hours,with12hourforecastsforallinitializationsforcyclingpurposes.Thisrestrictionlimitsthesamplesizeforforecastleadtimesbeyond12hours,decreasingthelikelihoodofobtainingstatisticallysignificantdifferences.Fourparallelexperimentswereruntotestthesensitivityofthethreeexperimentalphysicsconfigurations.Thecontrol(CL)wasrunusingthe2016operationalHWRFdefaultsettings.TwoRRTMGcloud-radiationexperimentswereconductedtotestthesensitivityofanalternatecloudoverlap(CO)methodologyandtheimpactofamodifiedpartialcloudinessscheme.Additionally,acumulusparameterizationreplacementtest(GF)wasruntoinvestigatetheimpactoftheGrell-Freitas(GF)schemecomparedtotheoperationalscale-awaresimplifiedArakawa-Schubert(SAS).

    AnewcloudoverlaptechniquefortheRRTMGradiationparameterization,exponential-random(ER),wastestedasareplacementforthedefaultmaximum-randomassumption.TheERtechniquealterstheoverlapofcontinuouscloudlayerstoallowforanexponentialtransitionfrommaximumtorandom.Otherapplicationshaveshownthismethodtobemorerealisticrelativetoradarmeasurementswithinverticallydeepclouds,addingmotivationtotestwithinHWRF.ThetrackandintensityresultsintheALbasinsuggestedmodestreductionsintrackerror,particularlybeyond2days(Figure3.2.2-1).However,thesedifferencesarenotstatisticallysignificant(SS).Absoluteintensityerrorsindicatesmallernon-SSmeanerrorsoutto30hours,withmixedimpactthroughouttheintermediateandlongerleadtimes(Figure3.2.2-1).Boththeexperimentalandcontrolconfigurationsexhibitedanegativeintensitybias(notshown),withreducednon-SSmeanbiasesforCObeyond3days.DuetolimitedcasesintheEPbasin,resultsarependingtheadditionofstormstothesample.

    ApartialcloudinessschemewasimplementedwithintheRRTMGradiationschemeforthe2015operationalHWRFsystemtoaddressexcessiveshort-waveradiationreachingthesurfaceduetotransparencyofSAScloudstoRRTMGandalackofstratusrepresentation.Adjustmentsweremadetotherelativehumiditythresholdmethodologytofurtheraddresssolarradiationbiases.PriortestsofthesemodificationsusingWRF-ARWoverCONUSresultedinreducedsolarradiationbiases.TheseupdatesweretestedtoassesswhetherschemeimprovementswouldtranslatetotheHWRFsystem.SimilartotheCOconfiguration,trackerrorsintheALbasinhadatendencyforslightlyreducedmeanerrorsforthePCconfigurationrelativetoCLatthelongestleadtimes.Again,thesedifferenceswere

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    notSS(Figure3.2.2-1).AbsoluteintensityerrorsweresmallerforthePCconfigurationbeyond48hours,withSSdifferencesfavoringPCatthe84-,90-,and108-hourleadtimes.ThePCconfigurationexhibitedanegativeintensitybiasof-5to-10kts(notshown),similartotheCLconfiguration.Meanintensitydifferenceswithrespecttoleadtimeweremixedandnon-SS.AswiththeCOconfiguration,resultsfromtheEPbasinarependingincreasedsamplesize.

    Figure3.2.2-1.Meantrackerrors(left)andabsoluteintensityerrors(right)intheALbasinwithrespecttoleadtime.TheCL(operational)isinblack,PCingreen,andCOinblue.Pair-wisedifferences(experimentminuscontrol)areshowninlightshadeswith95%confidenceintervals.

    TheGFschemeemploysanensembleapproachtorepresentconvection,usingacollectionofparametersandalgorithmstorepresentconvectivetriggers,verticalmassflux,andclosures.Additionally,theschemeisscale-aware,makingitsuitableforHWRF’snestedgridconfiguration.Trackerrorsindicatestatisticallysignificant(SS)differencesbetweentheGFandCLforsomeoftheearlyleadtimes(18-himprovementand48-h,54-hdegradation),whereasmeandifferencesshownon-SSsmallertrackerrorsforGFbeyond84-hours(Figure3.2.2-2).ThemeanintensitybiasforGFappearstobesmallerthanthatfortheCL,butthedifferencesarenotSS(Figure3.2.2-2).TheoperationalHWRFisknowntounder-predictintensityforstrongALstorms,whichisheavilyrepresentedwiththissample.TheGFconfigurationtendstoreducethisdominatetendency;however,errorbarssuggesttheGFconfigurationmaytendtowardover-prediction.IntheEPbasin,intensitytracessuggestatendencyfortheGFconfigurationtobetterrepresentrapidintensification(RI)forspecificinitializationtimes.AdditionalRIcasesintheEPbasinareunderinvestigation.

    AdditionalevaluationisunderwaytoverifyHWRF-simulatedbrightnesstemperatures(BT)againstGeostationaryOperationalEnvironmentalSatellite(GOES-13,channel4)BTs.Currently,HurricaneMatthewhasbeenverifiedontheparentdomain(d01)andinnermostnest(d03).Inadditiontothefouraforementionedconfigurations,asupplementaltest(PC+CO)wasruntoincorporatethecombinedimpactofthePCandCOinnovations.Figure3.2.2-3demonstratesthedifferentattributesofeachconfigurationanddomain,shownbyprobabilitydensityfunctions(PDFs)ofthebrightnesstemperature.Fortheparentdomain,theobservedBTfrequencyincreasessteadilyupto280K,followedbyasharpincreasepeakingat290K.TheGFandCOconfigurationspeakatcoolertemperatures,whereasthePCandPC+COexperimentsdemonstrateanimprovementastheyshiftthePDFtowardswarmerBTs.Fortheinnernest,theobservationaldistributionisapproximatelyuniform.Conversely,themodel-simulatedBTPDFsareclearlybi-modal.Notably,onbothdomainsthemodel-simulatedBTsallunderestimatetheobservedfrequencyofBTfrom235-275K.

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    Figure3.2.2-2.Meantrackerrors(left)andmeanintensityerrors(right)intheALbasinwithrespecttoleadtime.CL(operational)isinblack,GFinred,pair-wisedifferences(GF-CL)areshowningreywith95%confidenceintervals.

    Fig.3.2.2-3.Probabilitydensityfunctions(PDFs)oftheobserved(yellowline)andmodel-simulatedbrightnesstemperaturesfortheGF(green),PC+CO(purple),CO(blue),PC(red),andCL(black)simulationsatforecasthour24ond01(left)andd03(right).

    Fractionsskillscore(FSS)wasalsocomputedtoshowtheskillofeachconfiguration(notshown).ResultsindicatetheGFconfigurationperformsthebestforallBTthresholdsexceptthewarmest(greaterthan290K)ontheparentdomain,whereasthePCconfigurationdemonstratedthebestskillontheinner-nestforBTthresholdsgreaterthan250K.Notably,noneoftheconfigurationsworsenedHWRF’sabilitytoreproducetheobservedBTPDForsubstantiallydegradedtheFSSrelativetotheCL.

    Theresultsofthepre-implementationtestingweretoadoptthePCinnovationsforthe2017operationalHWRFconfiguration.TheGFconfigurationcontinuedtodemonstratepromisewithlargerpre-implementationtestsperformedbyEMC,howeverreproducibilityissueswhenrunningwithadifferentnumberofprocessorscauseddelays,resultinginadeferreddecisionontheGFconfigurationforthe2018HWRFimplementation.Finally,inclusionoftheCOinnovationintoHWRFwastableduntil

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    developersimplementanamelistoptionforthenewoverlapmethod.Furtheranalysisofallthreeconfigurationsareunderwayforinclusionintheprojectfinalreport,whichwillbepostedontheDTCwebsite(http://www.dtcenter.org/eval/hwrf_GF_PC_CO/).Additionalcasesarebeingaddedtoincreasethesample,particularlyintheEPbasin.Furthermore,casestudiesfocusingonparticularstormsareongoingtobetterunderstandthebehaviorofeachphysicsinnovation.

    3.3 DataAssimilation

    OnepaperassociatedwithpastDAactivitieswaspublishedinBAMS:

    H.Shao,J.Derber,X.-Y.Huang,M.Hu,K.Newman,D.Stark,M.Lueken,C.Zhou,L.Nance,Y.-H.Kuo,andB.Brown,2016:BridgingResearchtoOperationsTransitions:StatusandPlansofCommunityGSI.Bull.Amer.Meteor.Soc.,97,1427–1440,doi:10.1175/BAMS-D-13-00245.1.

    3.3.1 RegionalEnsembleBasedDAT&E

    UnderAOP2015funding,theDTCbuiltanexperimental4DhybridEnVardataassimilationsysteminthecontextofRAP,evaluatedthecodereadinessforregionalapplications,andprovidedfeedbacktodevelopersonitsinitialassessmentofforecastimpactsof4DhybridEnVardataassimilation.Throughouttheprocessofsettingupandtestingthiscapability,theDTCreportedbugfixesandmissingcapabilitiestotheGSIdevelopers.Replacingthe3DhybridEnVardataassimilationstepintheRAPworkflow,4DhybridEnVardataassimilationgeneratedminimalimpactsontheanalysesandforecasts.Inadditiontoreportingontheoutcomeofitstest,theDTCidentifiedareasthatneedmoreworktoimprovethecurrent4DEnVarcapabilities.Thefinalreport,whichisavailableontheDTCwebpageathttp://www.dtcenter.org/eval/data_assim/4denvar/rap_15km/,providesadetaileddescriptionoftheexperimentsanddiscussionoftheresults.

    TheDTCalsopresentedtheresultsattwoworkshops:

    H.Shao,M.Hu,C.Zhou,K.Newman,X.Zhang,andC.Holt,2016:Testingandevaluationoffour-dimensionalensemblevariationaldataassimilationforregionalweatherforecasts.The7thNOAATestbedandProvidingGroundsWorkshop,CollegePark,Maryland.

    C.Zhou,M.Hu,K.Newman,H.Shao,andX.Zhang,2016:InitialassessmentoftheGSI-based4Dhybridensemble-variationaldataassimilationanditsapplicationforregionalforecasts.The17thAnnualWRFUsers'Workshop,Boulder,Colorado.

    K.Newman,M.Hu,C.Zhou,andH.Shao,2016:InvestigatingthecapabilityofGSIfour-dimensionalensemblevariationaldataassimilationforWRF-ARWapplications.The17thAnnualWRFUsers'Workshop,Boulder,Colorado.

    3.3.2 HighResolution(3km)EnVarTestingandEvaluation

    TheDAT&EactivityforAOP2016focusedon4DhybridEnVarcapabilitiesforhigh-resolutionregionaldataassimilationincontextoftheHRRRsystem.HRRRcurrentlyusesaGSI-based3DhybridEnVarDAsystem,whichusestheglobalensemble(~30km)fortheensemblebackgrounderrorcalculationandone-hourARW(3-km)forecastsinitializedwithRAP(13km)analysesfromthepreviouscycle(socalled“pre-forecast”)astheDAbackground.ThisT&Eactivitywasdividedintotwofocusareas:1)demonstrationof4DhybridEnVarsystemforHRRR,and2)feasibilityandimpactassessmentforfastcyclingof4DhybridEnVar.

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    3.3.2.1 Demonstrationof4DhybridEnVarsystemforHRRR

    TheDTCsetuptwoworkflows:1)aworkflowbasedonoperationalHRRRsystemand2)aworkflowthatreplacedthe3DhybridEnVarDAsystemwithanexperimental4DhybridEnVarsystem.Similartothe3DhybridEnVar,the4DhybridEnVarwasconfiguredtouseensembleinputfromtheglobalensembletocomputetheflow-dependenterrorcovariance.Notethateach4Danalysisrequiresmultiple-timelevels(3timelevelsforthistest)ofensembleandbackgroundinputfiles,incontrasttotheoneensembleandonebackgroundfilerequiredforeach3Danalysis).TheDTCusedtheseworkflowstoconducthourlyupdateexperiments.Duetocomputingconstraints,theDTCselectedareducedHRRRdomainforthetest.Thistestfocusedonthetimeperiod3-10September2016,whichincludedafast-evolvingconvectivescaleevent.Figure3.3.2.1-1showsthetestdomainwiththeanalyzedreflectivityfromthe4DhybridEnVarexperimentat1200UTCon8September2016(leftpanel)andtheobservedradarreflectivityat1155UTCon8September2016(rightpanel).

    Figure3.3.2.1-1.Thetestdomainand4DhybridEnVaranalyzedreflectivityat1200UTCon8September2016(leftpanel)andtheobservedradarreflectivityat1155UTCon8September2016(rightpanel).

    Figure3.3.2.1-2showsthedomain-averagedRMSEforthewindbackgroundandanalysesfrom3Dand4Druns.Theresultsindicatethe4DhybridEnVartechniqueimprovesthefitofbothbackgroundandanalysestoobservations.Similarresultswerealsofoundforhumidityandtemperatureatmostofverticallevels.Fortheforecasts,theimpactsofthe4Dtechniquebecamelargerforlongerforecastrangeandresultedinremarkabledifferencesfromthe3Dresults.Figure3.3.2.1-3showsthedifferencebetweenthesimulatedreflectivityforecastsfromthe4Dand3Drunsatdifferentleadtimes.Thepatterninthedifferencefieldspointstotheimpactsofthe4Dtechniqueontherainbandlocationsandmagnitudeatconvectivescales.Atforecasthour6,themagnitudeofthedifferenceislargersuchthatthereflectivitydifferencesareofthesameorderofmagnitudeastheobservedreflectivity.TheDTCiscurrentlyperformingmorein-depthdiagnosticsandanalysisofverificationresultsfromthistestingactivity.AdetailedreportisexpectedtoavailablebetheendofMayandwillbepostedontheDTCwebpage.

    Inaddition,theDTCexaminedtheimpactsofreplacingtheGFSensemblewithahigh-resolutionARWensembleinthehybridruns.Acasestudyshowsthata3DhybridrunusingtheARWensemble(notshownhere)canresultinlargedifferencesin6-hforecastscomparedwith3DhybridrunsusingtheGFSensemble.Thisoutcomeindicatestheensemblerepresentationatconvectivescalescanleadtoimpactssimilartoreplacing3Dwith4Ddataassimilation.

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    Figure3.3.2.1-2.Thetimeseries(leftpanel)andverticalprofilesofdomainaveraged(rightpanel)RMSEsforthewindbackgroundandanalysesgeneratedfromthe3D(redlinesforbackgroundandgreenlineforanalyses)and4D(blacklinesforbackgroundandbluelinesforanalyses)hybridEnVarexperiments.

    Figure3.3.2.1-3.Differencebetween1-hforecasts(leftpanel)and6-hforecasts(rightpanel)ofmodelsimulatedreflectivityproducedbythe4Dand3DhybridEnVarexperiments.

    3.3.2.2Feasibilityandimpactassessmentforfastcyclingof4DhybridEnVar

    Basedontheoutcomefromthefirstfocusarea,theDTCmodifiedtheworkflowtoincreasetheanalysisupdatefrequencyandcycledthehybriddataassimilationtoevery15minutesthroughoutthepre-forecasthour.TheDTCalsoaddedthecapabilitytoGSItoperformsub-hourly(inminutes)analysisupdates.Thenewworkflowsforthe3Dand4Dsub-hourlycyclingdataassimilationsystemforHRRRareshowninFigure3.3.2.2-1.Duetothesubstantialincreaseincomputationalresourcesassociatewithgoingtosub-hourly,theDTConlyperformedtestsforasubsetoftestingperiod(8-10September2016)usedforthefirstfocusarea.Theresultsshowedthatboththe3Dand4Dsub-hourlycyclinganalysisproducedabetterfittoobservationsthanthatofthe3Dhourlycycling,followedbyneutraltoslightlynegativeimpactsatthefollowinghours(figuresnotshown).Thesub-hourly3Dand4DEnVarconfigurationsmayneedtobetunedintermsofobservationtimewindowsforassimilation,orobservationerrormayneedtobeadjustedforhigh-frequencycycling.Itisalsoimportanttokeepinmindthatthesesub-hourlyexperimentsusedaGFSensemble,whichmayleadtorepresentationissuesforbackgrounderrorsatconvectivescales.TheDTCisperformingfurtherdiagnosticstocomparethe3Dand4Dresults.AdetailedreportisexpectedtoavailablebytheendofMayandwillbepostedtotheDTCwebpage.

    3Dbackground4Dbackground3Danalysis4Danalysis

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    Figure3.3.2.2-1.Sub-hourly3D(leftpanel)and4D(rightpanel)hybridEnVarworkflowdiagramsshowingtheevolutionofthe15-minuteassimilationcyclespriortothe24-hourforecastissuedonthehour.NotethatmultipleGFSensemblesand30-minHRRRforecastsateachcycleareneededfor4DhybridEnVarassimilation.

    3.4 GlobalModelTestBed(GMTB)

    3.4.1 PhysicsTestbed

    TofacilitatethedevelopmentofanadvancedphysicssuiteforNWS’sNGGPS,theDTCisdevelopingauniform‘testharness’toenablein-depthinvestigationofvariousphysicalparameterizations.ThistestharnessiscurrentlybeingusedbytheGMTBforitsT&Eactivities,andhasbeenmadeavailabletocommunityscientistsworkingwiththeGMTB.Asanexample,developersoftheGrell-FreitascumulusparameterizationranpreliminarytestsusingtheGMTBtestharnesstopreparecodeforamorecomprehensivetest,whichwillbeconductedbytheGMTBstaff.Thetestharnessmimicsthelogicalprogressionfortestingnewlydevelopedparameterizationsthattypicallytakesplacewithinthescientificcommunity.Componentsaregraduallyaddedasonemovesthroughthehierarchyuntilthefullforecastmodelcomplexityisreached.ItisdesignedtocomplementboththeexistingtestingprotocolatEMCandindependenttestingtypicallyperformedbyparameterizationdevelopers.Figure3.4.1-1illustratesthehierarchicaltiersofthetestharness,representshowtheDTCenvisionsthedivisionofeffort(GMTB’slikelyroledenotedbyblue)andshowshowtheharnessfitswithinEMC’sexistingtestingframework.

    3.4.1.1 SingleColumnModel

    AspartoftheGMTBphysicstestharness,aSingleColumnModel(SCM)thatmakesuseoftheIPDhasbeendevelopedandlightlytested.TheSCMisdrivenbyspecifyinganinitialprofilerepresentingthethermodynamicstateandaccompanyinghorizontalwinds.Changestotheprofilecausedbylarge-scaleadvectionareappliedthrough“forcing”terms,whicheffectivelyreplacethedynamicsofathree-dimensionalmodel.Aphysicssuitecalculatessub-gridscaleprocessesandchangestheprofileinconcertwiththeappliedforcing.

    DesignoftheSCMfocusedoncommunity-friendlinessbyminimizingexternaldependenciesandusingcommunity-sanctionedcodingpractices.UsingtheSCMonlyrequiresthecmakeutilityforbuildingandtheFortrannetCDFlibrary(I/O)tobeinstalledandaccessible.Python-basedscriptsforplottingandanalysis,easilysetupwithaneditableconfigurationfile,areincludedinthedistribution.Asofnow,theGFSphysicssourcecodeisbundledwiththeSCMsourcecodeasaseparaterepository.Fortestingpurposes,thiscodeisupdatedoccasionallytoworkwiththetop-of-trunkGFSphysicscode,althoughit

  • 27

    willlikelyonlysupportspecific,taggedversionsofthiscodeinthefuture.ThecodehasbeentestedonalatemodelMacintosh,aswellasonNOAA’sResearchandDevelopment(R&D)machine(Theia)andNCAR’sYellowstone.Inaddition,aGMTBSCMUser’sGuideandtechnicaldocumentationwasdevelopedwithDoxygenandisavailableontheDTC’swebsite:http://www.dtcenter.org/GMTB/gmtb_scm_doc/.

    Figure3.4.1-1.DiagramillustratingthetestinghierarchyplantosupportphysicsdevelopmentforNGGPS.LRindicateslowresolution,MRmediumresolution,andHRhighresolution.Colorshadingindicateswherethedifferentgroupsareanticipatedtofocustheirefforts(red–physicsdevelopers,blue–GMTBtaskwithintheDTC,andgreen–EMC).PPstandsforphysicsparameterization.

    Sofar,theSCMissetuptorunindividualcaseslikethosesuppliedbytheGlobalEnergyandWatercycleEXchanges(GEWEX)GlobalAtmosphericSystemStudies(GASS)program.Thesecasesoftenderiveinitialconditionsandadvectiveforcingfromfieldcampaigns,andareintendedtostudyspecificphysicalphenomenaandhowtheyarerepresentedbyphysicssuites.The“catalog”ofcasestousewiththeSCMisawork-in-progress,withoneshallowconvectivecasebasedonthetransitionfromstratocumulus-to-cumulusasobservedduringtheAtlanticStratocumulustocumulusTransitionEXperiment(ASTEX)fieldcampaignandonedeepconvectivecaseasobservedduringtheTropicalWarmPool–InternationalCloudExperiment(TWP-ICE)fieldcampaign.Bothcasesareinitializedandforcedbasedonobservationsmadeduringtheirrespectivefieldcampaigns.Althoughbothcasesusehorizontaladvectivetendencieswithprescribedverticalmotion,itispossibletoconfiguretheSCMtousetotaladvectivetendenciesandrelaxationforcingasdescribedinRandallandCripe(1999).Goingforward,theGMTBwilladdmorecasestothecatalog,includingcasesthatwillrequirechangestotheunderlyingGFSphysicscode(e.g.,abilitytoturnoffspecifiedphysicsschemeswithinthesuite).ThecasesaddedbytheGMTBcanalso

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    serveasanexampleforcommunitymemberstoaddcasesofinterest.Inaddition,theSCMissetuptoeasilyrunusingforcingensemblesthatcanbeusedtounderstandaphysicssuite’sresponsetouncertaintyintheforcing.

    3.4.1.2 WorkflowforLow/MediumResolutionGlobalForecastTests

    Buildingonpreviousprogress,theGMTBsuccessfullyestablishedanend-to-endworkflowsystemforrunningNEMS/GlobalSpectralModel(GSM)andUPP(stronglyleveragingEMCcapabilities),aswellasrunningDTC-contributedcomponents.Theend-to-end-workflowsystemreachedamaturestatethatallowedforrunningatestoftheGrell-Freitas(GF)convectiveparameterization(seedescriptioninsection3.4.2).TheDTC-contributedworkflowcomponentsforcreatingPython-basedforecastplots(e.g.temperature,moisture,convectivevs.non-convectiveprecipitation)andverificationresults(e.g.,near-surface,upper-air,andprecipitationverification)continuedtobeupgradedtoincludeadditionalfeaturesandflexibility.AscripttoplottropicalcyclonetracksforeachmodelinitializationwascreatedandaddedtotheautomatedworkflowanumberofconfigurationfilesforMETViewer(auserinterfaceforplottingMEToutput)weremodifiedandupgradedtogenerateimprovedverificationplots.Thisworkincludedaddingthe‘scorecard’capabilitytotheverificationarsenal;the‘scorecard’isawaytosummarizepatternsintheperformancedifferencesbetweentwoconfigurations,includinglevelofsignificance,forspecifiedmetrics,variables,levels,regions,andtimes.The‘scorecard’wasdevelopedbytheNCARVerificationteamwithNGGPSfundingandwasmadeavailabletoGMTBforbeta-testingaheadofitsreleasetoEMCandothers.

    Workisalsounderwaytoexpandthetestbedcapabilitiestoequipphysicsdeveloperswithawiderangeoftoolstoassessstrengthsanddeficienciesofphysics.ThecapabilitytoproducebiasinformationfromGSIdiagnosticfiles,whichprovideO-B(observation–background)informationwillsoonbeavailable.Inaddition,theGMTBiscollaboratingwithNGGPSPIJasonOtkintoincludesyntheticsatelliteoutputfromUPPtohelpwithevaluatingthemodel’sabilitytoaccuratelysimulatecloudsandmoisture.TheGMTBhasbeeniteratingwithJ.OtkinandhisteamtouserawmodeloutputfromtheGFtesttorunthroughUPPinordertotestupdatestotheradiativetransfermodelemployedbyUPP.Tropicalcyclogenesisverificationisintheprocessofbeingimplemented.Inaddition,thecapabilitytoperform6-hglobalprecipitationverificationisunderdevelopment. TheGMTBrevitalizeditscollaborativedialoguewithEMC’sglobalteamwithrespecttomigratingfromtheircurrentscriptingarchitecturetoaunifiedglobalworkflow,whichincludesattendingbi-weeklymeetingshostedbyEMC.TheGMTBisactivelytestingandrunningthenewRocoto-basedworkflow(v3.0.0)inpreparationforthenexttestingeffort,whichwillincludecycledDA.

    Inaddition,theteamhascontinuedtomanagethescripts,andconfigurationfilesusedintheGMTBworkflowthroughaGitrepositoryonVLab.AsubstantialefforthasalsobeenputforthtodocumenttheGSM/UPPworkflow,aswellasthediagnosticandverificationworkflow.AstheGMTBtransitionstoEMC’sunifiedglobalworkflow,thedocumentationwillcontinuetobeupdatedaccordingly.SimilartootherGMTBdocumentation,theworkflowdocumentationusesDoxygen.

    3.4.2 Grell-Freitasconvectiveparameterizationtest

    TheGMTBconductedatestoftheGrell-Freitas(GrellandFreitas2014)convectiveparameterizationtoprovideinputontheestablishmentanddevelopmentofanadvancedphysicssuiteforNOAA’sGFS.Thisparameterizationwasselectedfortesting,throughconsultationwithEMCandtheNGGPSProgramOfficeandPhysicsTeam,becauseofitspotentialforimprovingforecasts.Itisastate-of-the-artschemethatincludesascale-awarefeature,whichmakestheschemesuitableforuseacrossawiderangeof

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    modelresolutions.Itincorporatesanensembleapproachinitsrepresentationofconvection,whichallowsperturbationbystochasticfieldsfordeterministicforecasting,aswellasensembledataassimilation.Flux-formverticaltracertransport,wetscavenging,andaerosolawarenessarealsooptionsinthisscheme.Thescheme’smaturity,itshistoryofoperationaluseatNCEPintheRAP,andthefactthatitsdevelopmentisfundedbyNGGPSalsoledtochoosingtheGFschemefortesting.

    ThistestwasconductedusingGMTB’shierarchicaltestbed,whichcurrentlyconsistsofaSCMandaworkflowforrunningtheGFS.Inbothcases,acontrolusingtheGFSoperationalSimplifiedArakawaSchubert(SAS)convectiveschemewascreated(GFS-SAS)andcomparedagainsttheexperimentalconfiguration(GFS-GF)whosephysicssuitewasthesameasGFS-SASexcepttheGFdeepandshallowconvectionschemeswereusedinplaceofSAS(Table3.4.2-1).Theentiretestresults,aswellasthefinalreport,arepostedontheDTCwebsite.Selectresultsarepresentedbelowtohighlightthekeyfindings.

    Table3.4.2-1.TablesummarizingthebasicelementsofGrell-Freitasconvectiveparameterizationtest.

    FortheSCM,asinglecasebasedonadeepconvection-focusedfieldcampaignwasusedtoprovideinsightintohowGFS-SASperformscomparedtoGFS-GF.ThetestingparadigmfollowstheonedescribedinRandalletal.(2003)andZhangetal.(2016),namelyinitialconditionsandcolumnforcingarederivedfromobservationsobtainedduringIntenseObservationPeriods.TheatmosphericphysicssuitethatmakesuptheSCMisallowedtorespondtotheforcingbygeneratingparameterizedcloudsandprecipitation,radiativeheating,verticalmixing,etc.Givenidenticalforcing,theGFS-GFsuiteproducedsmallerconvectivetendenciesandamuchlowerconvectiveprecipitationratiothantheGFS-SASsuite(Fig.3.4.2-1).GFS-GFreducedthedrybiasintheboundarylayerandgenerallyproducedahighercloudfractionduringthedeepconvectiveperiodcomparedtoGFS-SAS.

    Theglobalforecastswererunatarelativelylowresolution(~34km),infree-forecastmode(nodataassimilationorcycling)andwithouttuningofthephysicssuite.TheoperationalGFSanalyseswereusedtoinitializetheretrospectivecoldstartforecastscoveringthetimeperiodJune–August2016(JJA).TheglobalmodelforecastsdisplayedbehaviorsimilartotheSCM,inthesensethatGFS-GFhadlowerconvectiveprecipitation(Fig.3.4.2-2).DifferencesbetweenprecipitationcharacteristicsofGFS-SASandGFS-GFwerenoticeableovertheCONUSdomain.Whilethe6-hprecipitationfrequencybiasesshowedaprominentdiurnalsignalforbothconfigurationsatthe0.01”threshold(Fig.3.4.2-3),aswellas0.1”and0.25”thresholds(notshown),GFS-GFproducedalargerdiurnalsignalinthefrequencybias,withsimilarmagnitudestoGFS-SASat18-UTC,butlowerbiasat00UTC.

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    Figure3.4.2-1:Meanprofilesoftemperaturetendencies(Kday-1)fortheactivephaseoftheTWP-ICEcase.Colorsdenoteforcing(red),PBLscheme(green),convectiveschemes(deep+shallow,blue),andmicrophysicsscheme(purple).Linetypesdenotethephysicssuite:GFS-SAS(solid)andGFS-GF(dashed).Tendenciesduetolongwaveandshortwaveradiationareinorangeandbrown,respectively.

    Figure3.4.2-2:Average6-haccumulatedconvectiveprecipitation(mm)overthethree-monthtestperiod(JJA2016)atthe120-hforecastleadtimeforGFS-GF-GFS-SAS.

    Theglobalforecastswererunatarelativelylowresolution(~34km),infree-forecastmode(nodataassimilationorcycling)andwithouttuningofthephysicssuite.TheoperationalGFSanalyseswereusedtoinitializetheretrospectivecoldstartforecastscoveringthetimeperiodJune–August2016(JJA).TheglobalmodelforecastsdisplayedbehaviorsimilartotheSCM,inthesensethatGFS-GFhadlowerconvectiveprecipitation(Fig.3.4.2-2).DifferencesbetweenprecipitationcharacteristicsofGFS-SASandGFS-GFwerenoticeableovertheCONUSdomain.Whilethe6-hprecipitationfrequencybiasesshowedaprominentdiurnalsignalforbothconfigurationsatthe0.01”threshold(Fig.3.4.2-3),aswellas0.1”and

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    0.25”thresholds(notshown),GFS-GFproducedalargerdiurnalsignalinthefrequencybias,withsimilarmagnitudestoGFS-SASat18-UTC,butlowerbiasat00UTC.

    Figure3.4.2-3:Frequencybiasof6-haccumulatedprecipitation(in)forGFS-SAS(red)andGFS-GF(green)aggregatedovertheCONUSdomainforthe0.01”thresholdasafunctionofforecastleadtime(h)forJJA2016.Theverticalbarssurroundingtheaggregatevaluerepresentthe95%CIs.

    Withthecopiousamountofverificationresultsproducedforthistest,a“scorecard”wasastraightforwardwaytoidentifypatternsintheperformancedifferencesbetweenthetwoconfigurations,includinglevelofsignificance,forspecifiedmetrics,variables,levels,regions,andtimes.Thescorecardforglobalsub-regionshelpedidentifythatupper-airwindspeedhadthefeweststatisticallysignificant(SS)differencescomparedtoothervariables,asshowninFig.3.4.2-4forNorthernHemisphere(NH).TheNHclearlysignaledGFS-SASasperformingbetterfortheearlierpartoftheforecastperiod.However,GFS-GFwasthebetterperformerfortemperaturebiaslaterintheforecastperiod.Follow-updiagnosticsindicatedtheimprovedperformanceofGFS-GFforthismetricwasrelatedtotheGFS-SASwarmingupprogressivelyovertheNHthroughouttheforecastperiod.

    Tropicalcyclonetrackerrorsaveragedoverallthebasinsweresimilarforbothmodelconfigurations(Fig.3.4.2-5a).WhileaccuracyinTCintensityforecasts(Fig.3.4.2-5b)isnotexpectedofamodelrunatthiscoarseresolution,itisinterestingtonotethatstormsproducedbyGFS-SASaremoreintense(notshown)andhavelessabsoluteintensityerrorthanthoseproducedbyGFS-GF.

    TheGMTB’stestingandevaluationoftheGFcumulusparameterizationillustratedthecomplexity--yetscientificusefulness--ofconnectinganewschemetotheGSM.ThesuccessofthistestwasheavilydependentoninteractionsamongandinvestmentbytheGMTB,thephysicsdeveloper,andEMC’sGlobalTeam.TheclosecollaborationanditerationwiththedeveloperhelpedensuretheGMTBproperlyconnectedtheGFparameterizationwithintheGSMcode.Inaddition,thecollaborationwiththeEMCGlobalTeamwasessentialtotheGFtest.TestingwiththeSCMresultedinseveralkeyfindings,withonefindingaligningwithresultsfromthe3-Dglobalforecasts.WhilenotallresultsfromtheSCMcouldbetranslatedtothefullglobalforecasts,thistesthighlightedtheutilityandprocessofthehierarchicaltesting.Movingforward,itwillbenecessarytofurtherengagewithEMCandcontinuetogetfeedbackregardingdesiredverificationmethodsanddisplays,whichwouldthenbeprioritizedforfutureimplementationinthetestbed.

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    Figure3.4.2-4:ScorecarddocumentingtherelativeperformanceofGFS-SASandGFS-GFovertheNHformeanbiasandRMSEfortemperature,relativehumidity,andwindspeedbyforecastleadtimeandverticallevelforJJA2016.Green(red)shadingindicatesGFS-GF(GFS-SAS)wasbetterthanGFS-SAS(GFS-GF)atthe95%significancelevel.Smallgreen(red)arrowsindicateGFS-GF(GFS-SAS)wasbetterthanGFS-SAS(GFS-GF)atthe99%significancelevel.Largegreen(red)arrowsindicateGFS-GF(GFS-SAS)wasbetterthanGFS-SAS(GFS-GF)atthe99.9%significancelevel.GreyshadingindicatesnostatisticallysignificantdifferencesbetweenGFS-SASandGFS-GF.

    Figure3.4-6:(a)Meantrackerrors(nm),and(b)meanabsoluteintensityerrors(kt)with95%confidenceintervalswithrespecttoleadtime(h)forGFS-SAS(red),GFS-GF(green)andtheirpairwisedifferences(black)inallbasinsforJJA2016.

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    3.4.3 CICEtest

    Overthepastyear,theGMTBcompletedatestofTheLosAlamosseaicemodel(CICE),whichstemmedfromtheNGGPSSeaIceModelingWorkshoporganizedbyGMTBinFebruary2016.Asdescribedintheworkshop’sfinalreport(link),participantsrecommendedthetentativeadoptionofCICE,pendingfollow-uptesting,andaddressingconcernsraisedregardingmodelgovernanceanddifferencesinstaggeringbetweenthegridsusedinNCEP’sUnifiedGlobalCoupledSystem(UGCS)oceanmodelsandCICE.

    Thetestplan,devisedjointlybyGMTB,EMC,theworkshopcommitteeandinterestedworkshopparticipants,includedexperimentsoveraone-yearperiod,withCICEbeingruninastandaloneframework,forcedbyatmosphericandoceanicfieldsfromtheNCEPoperationalClimateForecastSystemversion2(CFSv2).GMTBconductedthe30-dayforecastruns,andevaluationwasperformedjointlybyGMTB,EMC,andESRL.

    Theexperimenthadthreephases,asdescribedinTable3.4.3-1,withvaryingmodelresolutionandapproachestoinitializingtheatmosphereandoceanfields,aswellasconstrainingtheSeaSurfaceTemperature(SST).

    Table3.4.3-1.CICEmodelresolutionatthepole(km),datasetforatmosphericinitializationandforcing,datasetforoceaninitialization,andmethod/datasetforoceanforcing.

    CICE Atmos Init and Forcing Ocean Init Ocean Forcing

    Phas

    e 1 30 km CFSv2 1.00 CFSv2 1.00 CFSv2 10 6-hourly forcing

    2 15 km CFSv2 0.20 CFSv2 0.50 CFSv2 0.50 6-hourly forcing

    3 15 km CFSv2 0.20 CFSv2 0.50 Freely evolving

    Generallyspeaking,thePhase-1andPhase-2forecastsattheendofthemonth-longintegrationsareingoodagreementwiththeCFSv2initialconditionsatthebeginningofthenextmonth,indicatingaverygoodforecastfortheendofthemonth.Themajorexceptionsareinthesummerseasonsofbothhemispheres,whereexcessivemeltingoccurs(Fig.3.4.3-1).Follow-updiagnosticsindicatedthatbasalmelting,causedbywarmSSTs,wasthecauseoftheexcessivemelting.

    Figure3.4.3-1.Iceextent(1012m2)duringmonth-longintegrationsforPhase1(dashed)and2(solid)intheNorthern(top)andSouthernhemisphere(bottom).ThecirclesindicatetheinitialconditionsfromCFSv2atthebeginningofeachmonth.

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    WhentheSSTfromCFSv2forcingwasreplacedbyfreely-evolvingSSTfromtheCICEinternalmixed-layeroceanmodel,basalmeltingwasreducedandpredictionoficeextentattheendofsummerwassubstantiallyimproved(Fig.3.4.3-2).Comprehensiveresultsfromthistestcanbefoundinthereport(link)andonthetestwebsite(link).

    Figure3.4.3-2.SameasFig.3.4.3-1,exceptforPhase2(solid)andPhase3(dashed).

    3.5 CloudVerification

    AttherequestoftheAF,theDTCinvestigatedapproachesforevaluatingcloudpredictionsfromNWPmodelsandstatisticalpredictionsofcloudproperties.ThisevaluationincludednumerousNWPmodelforecastsutilizedbytheAF.RawmodeloutputfromtheARWlimitedareamodel,overtheNorthernHemisphere,andtheAF