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National Aeronautics and Space Administration
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MERRA-2DesignforApplications
PresentedbyMichaelG.BosilovichWithInputfrom
AllisonCollow,StevenPawson,AntonDarmenov RandyKoster andSarith Mahanama
National Aeronautics and Space Administration
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WhatisReanalysis?
• 3ComponentsofanObservationalAnalysis– Observations – Providereality,butincompleteinspaceandtime,andvariable,anddon’tforgetuncertainty
– Forecastmodel– Continuousinspaceandtime,butcandriftfromtheobservedweatherstate(moreuncertainty!)
– Assimilation – Thestatisticalmergerofobservationsandmodelforecast
• Retrospective-Analysis– Applythisprocesstohistoricalobservations,maintainingafrozenmodelandassimilationsystem
National Aeronautics and Space Administration
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ReanalysisWater(W)Budget
• Verticalintegral,Totaltendencyofwaterisequaltothesurfaceevaporativesource(E)minusthatwaterwhichisprecipitated(P),thewaterthatleavestheregion(DIV),andtheAnalysisIncrement(ANA)
• TheAnalysisIncrementrepresentstheaccumulatedeffectofallassimilatedwatervaporobservationsandsensitiveradiancechannelsonthereanalysis.
• Reanalysestypicallydonotprovidetheincrement,andappear‘imbalanced’.MERRA/MERRA-2doadheretoabalanceforstates.
ΔW=E- P+ANA - DIVVerticallyIntegrated,Simplified
National Aeronautics and Space Administration
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MERRA-2AspectsforApplications
• SurfaceWinds• RiverRouting
– LandPrecipitation– ObservationCorrections• ClimateIndices• DiagnosticDevelopment
National Aeronautics and Space Administration
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MERRA,ApplicationsandWind
• EarlyinthedevelopmentofMERRA,the‘A’wasintendedandpursuedinearnest
• Conversationswithprospectiveusers(e.g.PaulStackhouse)showedpossibilitiesbutperhapsalsolimitationsinstandarddiagnostics– 50mwindcomponents– 1hourlyfrequency,whereappropriate
• Routineupdatesandproductionforwardintimeweremaintained,whiledoneforgeneralreasons,isusefulinapplications
• Discussionsondiagnosticoutputdirectedatmakingthedatamoreuseful
National Aeronautics and Space Administration
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WindObservations• MERRA-2assimilatestremendousnumbersofobservations,thatarediscontinuousintimeandspace
National Aeronautics and Space Administration
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GlobalLandWindObservations
• Severalsourcesofwinddataoverland
• Aircraftwindsincreasingthroughtheperiod(SouthwestAir)
• LIDAR/RADARhasseasonalcycle
• Stationsurfacepressureisalsoassimilated
850mb – sfc CountAircraftLIDAR/RADARRAOBAMV
National Aeronautics and Space Administration
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MERRA-2SeasonalExtremeVariability
• Bosilovich(2013)showedMERRAhadpoorextremeinterannualvariability,especiallynoticeableintheMidwest
• MERRA-2:AllUSregionsareimproved• Demonstratesthatthelarge-scaleweatherrepresentationisusefulforevaluatingextremeevents
8
National Aeronautics and Space Administration
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EvaluatingRiverflowcapability
• Riverroutingmodelbeingtestedoffline
• Observationshavedatagaps
9
MissouriatHermann
MissouriatFortRandallDam
OhioatMetropolis
MissouriatGarrisonReservoir
Obs Sim
MERRA-2CorrelationtoTotalStreamflow ObservationsinBasins
RoutingMERRA-2totalrunoff(monthlytimeseries)
CourtesySarith Mahanama andRandyKoster,GMAO
National Aeronautics and Space Administration
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WarmandColdSpellDurationIndex
• Basedonconsecutivedayswarmerthanthe90thpercentileorcolderthanthelowest10th percentileofmeansurfaceairtemperaturefor2013-2014
National Aeronautics and Space Administration
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FireWeatherIndex(FWI)• BasicMeteorologyjointinput:T,RH,24hrPrecip andwind
• Intendedtobemoreofapredictive/warningtool
• Investigatingtherelationshipstothebiomassburning(AODandradiativeeffect)
11CourtesyAntonDarmenov,GMAO
National Aeronautics and Space Administration
gmao.gsfc.nasa.gov
ReanalysisDiagnosticDevelopment
• Tothispoint,50mwindshavebeenuseful,ifnotoptimal,butstillasolidconnectiontothewindenergyindustry– Otheruseswiththecurrentoutput,we’llseetoday
• TheGMAOisopentosuggestionsandcollaborationsondiagnostics,especiallythosebestcomputedatmodelruntime(asopposedtocomputedfromotherdiagnostics)
• Whatisthebestwaytogetthismessageout?• DiagnosticFeedbackform
https://goo.gl/forms/t9Aq7ETmbvv98EjD2
National Aeronautics and Space Administration
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CitingMERRA-2and DataFile• Gelaro,R.,W.McCarty,M.J.Suárez,R.Todling,A.Molod,L.Takacs,C.Randles,A.
Darmenov,M.G.Bosilovich,R.Reichle,K.Wargan,L.Coy,R.Cullather,C.Draper,S.Akella,V.Buchard,A.Conaty,A.daSilva,W.Gu,G.Kim,R.Koster,R.Lucchesi,D.Merkova,J.E.Nielsen,G.Partyka,S.Pawson,W.Putman,M.Rienecker,S.D.Schubert,M.Sienkiewicz,andB.Zhao,2017:TheModern-EraRetrospectiveAnalysisforResearchandApplications,Version2(MERRA-2).J.Climate,InPress,https://doi.org/10.1175/JCLI-D-16-0758.1
• ExampleDataFileDOIandCitation– GlobalModelingandAssimilationOffice(GMAO)(2015),MERRA-2
tavg1_2d_slv_Nx:2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Single-LevelDiagnosticsV5.12.4,Greenbelt,MD,USA,GoddardEarthSciencesDataandInformationServicesCenter(GESDISC),Accessed[DataAccessDate]DOI:10.5067/VJAFPLI1CSIV
National Aeronautics and Space Administration
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MERRA-2DataAvailability
• Projectpage:
http://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/http://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/docs/
• GES-DISCDataAccess
http://disc.sci.gsfc.nasa.gov/uui/search/”MERRA-2”• QuestionsList