NASA Technical Reports Server (NTRS) 20120013275: Intercomparison of MODIS Albedo Retrievals and In Situ Measurements Across the Global FLUXNET Network

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1 TITLE
2 IntercomparisonofMODISalbedoretrievalsandinsitumeasurementsacrosstheglobalFLUXNET
3 network.
4
5 Authorlist
6 AlessandroCescattia,BarbaraMarcollab,SureshK.SanthanaVannanc,JerryYunPanc,MiguelO.
7 Románd,XiaoyuanYange,PhilippeCiaisf,RobertB.Cookc,BeverlyE.Lawg,GiorgioMatteuccih,
8 MircoMigliavaccaa,EddyMoorsi,AndrewD.Richardsonj,GüntherSeuferta,CrystalB.Schaafe
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10
11
12 Affiliations
13 aEuropeanCommission-DGJointResearchCentre,InstituteforEnvironmentandSustainability,
14 ClimateChangeUnit,Ispra21027Italy
15 bEdmundMachFoundation,IASMAResearchandInnovationCentre,38010S.Micheleall'Adige
16 38010,Italy
17 cEnvironmentalSciencesDivision,OakRidgeNationalLaboratory,OakRidge,TN37831USA
18 d HydrosphericandBiosphericSciencesLaboratory,NASAGoddardSpaceFlightCenter,Greenbelt,
19 MD,UnitedStates
20 eCenterforRemoteSensing,DepartmentofGeographyandEnvironment,BostonUniversity,725
21 CommonwealthAvenue,BostonMA02215USA
22 fLaboratoiredesSciencesduClimatetdel’Environment(LSCE),JointUnitofCEA-CNRS-UVSQ,
23 Gif-sur-Yvette,France
24 gDepartmentofForestEcosystems&Society,OregonStateUniversity,Corvallis,OR,USA
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1 hCNR-ISAFOM,ViaCavour,4-6,87036Rende,CS,Italy
2 iESS-CC,AlterraWageningenUR,Wageningen,Netherlands
3 jHarvardUniversity,DepartmentofOrganismicandEvolutionaryBiology,HarvardUniversity
4 Herbaria,22DivinityAvenue,CambridgeMA02138USA
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6
7 Correspondingauthor
8 AlessandroCescatti [email protected]
9 EuropeanCommission-DGJointResearchCentre
10 InstituteforEnvironmentandSustainability
11 ClimateChangeandAirQualityUnit,TP290
12 ViaE.Fermi,2749,I-21027Ispra(VA),ITALY
13 Tel: [phone]
14 Fax: [phone]
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2
1 Abstract
2 SurfacealbedoisakeyparameterintheEarth’senergybalancesinceitaffectstheamountofsolar
3 radiationdirectlyabsorbedattheplanetsurface.Itsvariabilityintimeandspacecanbeglobally
4 retrievedthroughtheuseofremotesensingproducts.Toevaluateandimprovethequalityofsatellite
5 retrievals,carefulintercomparisonswithinsitumeasurementsofsurfacealbedoarecrucial.Forthis
6 purposewecomparedMODISalbedoretrievalswithsurfacemeasurementstakenat53FLUXNET
7 sitesthatmetstrictconditionsoflandcoverhomogeneity.Agoodagreementbetweenmeanyearly
8 valuesofsatelliteretrievalsandinsitumeasurementswasfound(R2=0.82).Themismatchis
9 correlatedtothespatialheterogeneityofsurfacealbedo,stressingtherelevanceoflandcover
10 homogeneitywhencomparingpointtopixeldata.WhentheseasonalpatternsofMODISalbedois
11 consideredfordifferentplantfunctionaltypes,thematchwithsurfaceobservationisextremelygoodat
12 allforestsites.Onthecontrary,innon-forestsitessatelliteretrievalsunderestimateinsitu
13 measurementsacrosstheseasonalcycle.Themismatchobservedat grasslandsandcroplandssitesis
14 likelyduetotheextremefragmentationoftheselandscapes,asconfirmedbygeostatisticalattributes
15 derivedfromhighresolutionscenes.
16 Keyword:MODIS,surfacealbedo,validation,FLUXNET,terrestrialecosystems,plantfunctional
17 types,remotesensing,
18 1. Introduction
19 LandsurfacebroadbandalbedodirectlyaffectsEarth’sclimatebydeterminingthefractionof
20 shortwaveradiationabsorbedatthegroundandthereforeinfluencingthesurfaceenergybudget
21 (Dickinson,1983).Surfacealbedoisacrucialparameterindeterminingthemagnitudeofenergyfluxes
22 inthesoil–plant–atmospherecontinuum(Bonan,2008;Chapinetal.,2008),affectingsurface
23 temperature,evaporationandtranspiration,cloudformationandprecipitation,thusultimately
24 impactinggrossprimaryproductivity(Dickinson,1983;Lawrence&Slingo,2004;Ollingeretal.,
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1 2008;Sellersetal.,1997).Severalauthorshaveinvestigatedtheinterplaybetweenalbedoanddrought
2 (Govaerts&Lattanzio,2008)orfires(Randersonetal.,2006),andtheclimatesensitivitytovariation
3 insurfacealbedocausedbymajorchangesinlandcoverastheexpansionofagriculturallandinthe
4 northernhemisphereduringthe18thcentury(Myhreetal.,2005;Vavrusetal.,2008).Surfacealbedois
5 alsoakeyfactorintheexpectedpositivefeedbackbetweensurfacetemperatureandglobalwarmingat
6 northernlatitudes(Chapinetal.,2005)andmayplayarelevantroleinoffsettingthecarbon
7 sequestrationpotentialofafforestationprograms(Andersonetal.,2010;Betts,2000;Bettsetal.,2007;
8 Birdetal.,2008;Rotenberg&Yakir,2010).
9 GiventherelevanceofsurfacealbedointheEarth’sclimatesystem,monitoringthisparameterinspace
10 andtimeisfundamentalforthedevelopmentofglobalclimatemodels(Alton,2009;FridaA-Metal.,
11 2006;Hollingeretal.,2009;Tianetal.,2004)andforclimatechangeandecosystemresearchin
12 general(Betts,2000;Charlsonetal.,2007;Charneyetal.,1977;Dirmeyer&Shukla,1994;Hall&Qu,
13 2006;Henderson-Sellers&Wilson,1983;Pintyetal.,2011a).Animportantsteptowardthe
14 availabilityofglobalsurfacespectralalbedohasbeenthelaunchofNASA’sTerraandAquasatellites
15 andtheMODerate-resolutionImagingSpectroradiometer(MODIS)(Luchtetal.,2000b;Salomonson
16 etal.,1989;Schaafetal.,2002).TheMODISsensorprovidesglobalmapsofsurfacealbedo
17 reconstructedfromretrievedmodelsofreflectanceanisotropyata500-mgriddedspatialresolution
18 every16daysforthefirstsevenMODISspectralbands(0.47–2.1(cid:2)m)andforthreebroadbandregions
19 (0.3–0.7,0.7–5.0,and0.3–5.0,(cid:2)m)(Luchtetal.,2000b;Moodyetal.,2008;Schaafetal.,2002).
20 Comparingsatellitealbedoretrievalswithsurfacemeasurementsandwithindependentsatellite
21 productsisfundamentalinevaluatingtheaccuracyofremotesensingproductsandimprovingretrieval
22 algorithms(Liangetal.,2002;Pintyetal.,2011b).Severalrecentstudieshaveevaluatedthe
23 consistencyofglobalalbedoproductsusinginsitudataatvariousspatialandtemporalscales(Chenet
24 al.,2008;Jinetal.,2003a;Jinetal.,2003b;Liangetal.,2002;Liuetal.,2009;Románetal.,2010;
25 Románetal.,2009; Wangetal.,2010)andunderspecificsnowcoverconditions(Stroeveetal.,2005).
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1 Mostofthesestudiesstressthatadirectcomparisonisverychallengingbecauseofscalemismatchand
2 heterogeneityofthelandsurfaceatthesatellitemeasurementscalethatreducesthespatial
3 representativenessofgroundpointmeasurements(Liangetal.,2002;Románetal.,2010;Románetal.,
4 2009).Asaconsequence,acarefulselectionofgroundpointsandthecharacterisationoftheirspatial
5 representativenessarecrucialforameaningfulpoint-to-pixelcomparison(Liangetal.,2002;Luchtet
6 al.,2000a;Románetal.,2009).
7 Intercomparisonsofsurfaceandsatellitealbedohavebeenperformedsofaratalimitednumberof
8 locations(Jinetal.,2003a;Liuetal.,2009;Románetal.,2010;Románetal.,2009;Salomonetal.,
9 2006;Wangetal.,2010)andaglobalanalysisacrossdifferentcontinentsandplantfunctionaltypes
10 (PFTs)isstilllacking.Theobjectiveofthisworkistoprovideacomprehensiveintercomparisonin
11 timeandspaceofinsitumeasurementsandsatelliteretrievalsofsnow-freebroadbandsurfacealbedo.
12 ForthispurposewecomparedMODISgriddedalbedoretrievalsatthe500-mscalewithground
13 measurementsperformedacrosstheFLUXNETnetwork(Baldocchietal.,2001),thelargestglobal
14 datasetofenergyandmassfluxmeasurementsat ecosystemscale.
15 ThegeographicalextentoftheterrestrialdatasetallowedthecomparisonofseveralPFTsina
16 comprehensiveandconsistentwayacrosstheseasonalcycle.Inaddition,thelargenumberof
17 experimentalsitesinthenetworkprovidedanunprecedentedopportunitytoperformacareful
18 evaluationofthesurfaceheterogeneityatthereferenceplots,basedonacombinationofqualitativeand
19 quantitativemetrics.ForthispurposeimagesfromGoogleEarth, MODISandEnhancedThematic
20 MapperPlus(ETM+)havebeenusedatvariousspatialscales(from1x1to7x7km).Differences
21 betweensatelliteretrievalsandin-situalbedohavebeenanalyzedasafunctionofsurface
22 heterogeneity,PFTandseasonality.Resultsoftheintercomparisonhavebeenfinallydiscussed
23 consideringthedifferentsourcesofuncertaintythataffecttheterrestrialandsatellitedatasets.
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1 2. Materials and methods
2 2.1. Surface data set
3 Inthisstudy,weusedinsituradiometricmeasurementsavailableintheFLUXNET“LaThuile”
4 database(www.fluxdata.org,October2010)releasedinDecember2007,whichincludeshalfhourly
5 observationsofecosystemfluxesandmeteorologicaldatafrommorethan250sites,foratotalof960
6 site-years.
7 Albedoiscomputedastheratioofdownwardandupwardglobalradiationasobservedwithdouble
8 pyranometers(e.g.CMA-11,CMA-6orCNR-1,Kipp&Zonen,Delft,TheNetherlands).Surfacealbedo
9 istypicallyestimatedinthespectralrange280-2800nm(accountingformorethan98.5%ofthe
10 surfacesolarradiationaccordingtoASTMG-173referencespectra)andisthereforecomparablewith
11 thebroadbandMODISalbedo(300-5000nm).Givingthatthefieldofview(FOV)ofpyranometersis
12 typically180deg,thefootprintofsurfacereflectancemeasurementsistheoreticalinfinite.However,
13 duetothecosineresponseofthesensor,50%ofthesignaloriginatesinaFOVof90degand80%ina
14 FOVof127deg.Thefootprintofsurfacealbedothereforedependsontheheightofthealbedometer
15 abovethecanopytop(rangingfrom5to10m)andtypicallyextendsupto10-20mfromthetowerat
16 80%ofthesignal.
17 Theuncertaintyofsurfacealbedomeasurementsdependsontheabsoluteaccuracyofphyranometers
18 (about5%)andonthenon-idealcosineresponse(about3%).Mostoftheerrorsassociatedwiththe
19 absoluteaccuracyoftheinstrumentaresimilarforupwardanddownwardfluxesandtherefore
20 compensate.Overalltheexpectedaccuracyisintheorderof4-7%inclearskyand1-4%inovercast
21 condition(Pirazzini,2004;Pirazzinietal.,2006).
22 ThegeographicaldistributionofthesitesisstronglyclusteredinEuropeandNorthAmerica(97and
23 106sitescorrespondingto38%and42%ofthetotal),whicharetheregionswiththelongesthistoryof
24 continuousecosystemfluxmeasurements(Baldocchietal.,2001).Severalsitesinthedatabaseare
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1 locatedintropicalAmazoniaandEastAsia,whilethecoverageinAfrica,CentralAsia,andAustralia
2 remainssparseandlimitedinthenumberofobservationyears.Despitetheunevengeographical
3 distribution,the“LaThuile”databaseguaranteesa goodcoverageofthemostimportantplant
4 functionaltypes,amongwhichevergreenneedleleafforest(ENF),grassland(GRA),deciduous
5 broadleafforest(DBF),andcropland(CRO)arethemostrepresentedwithrespectively28%,18%,
6 13%and12%ofthesites.
7 Outofthe138FLUXNETsitesreportingcontinuousmeasurementsofincomingandoutgoing
8 shortwaveradiation(300-2800nm;CMA-11,CMA-6orCNR-1,Kipp&Zonen,Delft,The
9 Netherlands)18havebeenexcludedafteraQA/QCanalysisofthealbedodataseries.TheQA/QC
10 procedurewasbasedonthefollowingcriteria:occurrenceofanoffsetintheincomingorreflected
11 radiation(night-timedatasystematicallyandsignificantlydifferentfromzero),occurrenceofphaselag
12 betweenincidentandreflectedradiationandsystematicoccurrenceofunrealisticvalues(e.g.reflected
13 radiationhigherthanincidentradiation).
14 Thelandcovercharacteristicsoftheremaining120siteshavebeencarefullyclassifiedusinghigh
15 resolutionsatelliteimages(availableviaGoogleEarth(cid:2)),toidentifythosematchingtherequirement
16 ofhomogeneityintheareasurroundingthemeasurementtower(Jinetal.,2003b;Románetal.,2010;
17 Románetal.,2009).AlthoughMODISalbedoisgriddedat500-mresolutionthelandclassificationhas
18 beenperformedat1km2,takingintoaccounttheuncertaintyinthegeospatialregistrationofsatellite
19 productsandthefactthatthealbedoretrievalalgorithmisbasedonmulti-angleobservationscovering
20 largerareasatedgeofscan.
21 Theclassificationprocesswasbasedonthefollowingfoursteps:
22 1. visualidentificationofthenumberandextensionofdifferentPFTsinthe1km2area
23 surroundingthetower;
24 2. verificationofthecorrespondencebetweenthedominantPFTinthe1km2areaandthePFTat
25 thetowersiteasreportedintheFLUXNETdatabase;
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1 3. qualitativerankingoflandscapeheterogeneityinthreeclasses(low,medium,high)basedonthe
2 plantcanopycharacteristics(treedensity,patchiness,etc.);
3 4. attributionofaconfidencelevelintheclassificationofthesites(low,medium,high)basedon
4 thequalityoftheimage.
5 Toguaranteethehighestlevelofhomogeneityandtominimizeissuesassociatedwithspatial
6 representativenessinthepoint-to-pixelcomparison,onlythosesitescharacterizedbythelowestlevel
7 ofheterogeneityandwithonlyonePFTinthe1km2areawereincludedintheanalysis.
8 2.2. MODIS products
9 TheMODISalbedoretrievalsattheFLUXNETsitesweregeneratedusingthreeMODISproducts,
10 namely,MCD43A1(BRDF-AlbedoModelParameters16-DayL3Global500m),M*D04(Aerosol
11 productdailyL2Global10km),andMCD43A2(BRDF-AlbedoQuality16-DayL3Global500m).All
12 theseproductsarefromtheCollectionV005MODISreprocessingcampaign.TheMODISsurface
13 reflectanceanisotropyandalbedoproductisbasedonallhighquality,cloud-free,atmospherically
14 correctedsurfacereflectancesthatareobtainedovera16-dayperiod.Whensufficientobservationsare
15 availabletoadequatelysamplethesurfaceanisotropy,anappropriaterenditionofthe
16 RossThickLiSparseReciprocalBidirectionalDistributionReflectanceModel(BRDF)modelisretrieved
17 (Luchtetal.,2000b;Schaafetal.,2002).Thisretrievalisattemptedevery8daysata500mgridded
18 resolution.Thisretrievalmodelisusedtogenerateintrinsicvaluesofclear-skydirectsurfacealbedo
19 (referredtoasdirectionalhemisphericalreflectanceorblack-skyalbedo)andwhollydiffusealbedo
20 underisotropicillumination(bihemisphericalalbedoorwhite-skyalbedo).Thesecanbecombined
21 underparticularilluminationandatmosphericaerosolopticaldepthconditions(Luchtetal.,2000b;
22 Románetal.,2010)toprovideclear-skyalbedoscomparabletothosemeasuredinsituatafluxtower.
23 Albedoquantitiesarereportedata500-mgriddedresolution,butallmulti-angleobservationsthat
24 encompassareasareutilizedintheretrieval.Therefore,althoughextendedobservationcoverageis
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1 somewhatcompensatedforintheretrievalprocess,itisbesttoconsiderregionslargerthan500 m
2 whencomparingobservationsmadefromsatellitetothosemadeontheground.
3 Thecalculationofclear-skysurfacealbedoatthetowersitesinvolvedthefollowingtwosteps.Thefirst
4 stepwasthegenerationoftheaerosolopticaldepthvaluesforeachsiteandeachcalendardateusing
5 theMODIS–Terra(MOD04)andMODIS-Aqua(MYD04)aerosolswathproducts.Togeneratethe
6 opticaldepth,theMODISAdaptiveProcessingSystem-MODAPS(Masuokaetal.,2000;Masuokaet
7 al.,2007)wasusedtoprepareM*04subsetsat50x50kmregioncenteredatthesite.Allpixelsthat
8 hadopticaldepthvaluesgreaterthan0.35oracloudfractiongreaterthan0.6werefilteredoutandnot
9 usedintheopticaldepthgeneration.Allpixelsthathadfillvaluesforsolarzenithanglewerealso
10 rejected.Afterthefilterswereapplied,acombinedM[OY]Dopticaldepthfilewasgeneratedforeach
11 site,takingvalidopticaldepthvaluesfromTerraandAquaandgeneratingonemeanvalueforthe
12 opticaldepthpersiteperday.Thismethodofcourseisnotasaccurateashavinginstantaneoussun
13 photometerdata(Holbenetal.,1998)atthesite,butthemeangivesanapproximationoftheaerosol
14 opticaldepthoverthelocalsolarnoon.
15 ThesecondstepwasthecalculationoftheclearskysurfacealbedoonthebasisoftheMODIS-derived
16 550nmaerosolopticaldepthscalculatedinthepreviousstep,thelocalsolarzenithangle,the
17 MCD43A1product,andQAflagsfromMCD43A2foreachsiteinvolvedintheanalysisandforeach
18 date.IfadatehasnovalidMCD43A1pixelsoriftheopticaldepthwasafillvalue,noalbedowas
19 calculatedforthatdate.Asfarasqualitycriteriaareconcernedonly“fullBRDFinversion”pixels
20 (QA=0processed,goodquality)wereincludedinthecalculation,whilethe"Snow_BRDF_Albedo"
21 bandoftheMCD43A2productwasusedtoidentifyandexcludesnowalbedoretrievals.Followingthis
22 procedureclear-skyMODISalbedoatlocalsolarnoonwereretrievedateachFLUXNETsiteforall
23 dayswithavailableaerosolMODISproduct(M*D04)information,snow-freeconditions,andsolar
24 elevationanglesgreaterthan20deg.Onthesamedates,thefluxtowermeasurementsofalbedohave
25 beenaveragedforthehourcenteredatsolarnoon.
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1 TointegratetheobservationsattheFLUXNETsitesintheglobalpicture,snow-freeglobalalbedo
2 averagesperPFTandlatitudinalbandwerecomputedfromtheMODISV0050.05degreeClimate
3 ModelingGrid(CMG)productandstratifiedwiththeMCD12C1landcoverproduct.Yearlyaverages
4 havebeencalculatedoneachpixelfulfillingthefollowingrequirements:QA=0(majorityprocessed,
5 goodquality),snowcoveragelessthan10%(basedonMODISestimates),andmajorPFTcoverage
6 greaterthan70%ofthepixel.Notethatthe0.05degreeMCD43C1productisanaverageofthe500m
7 pixelunderlyingeach0.05degreepixelandthequalityflagonlyrepresentsthequalityofthemajority
8 oftheunderlyingpixels.
9 2.3. Landscape heterogeneity
10 Oneofthekeyissuesintheintercomparisonofsatelliteretrievalandsurfaceobservationsisthe
11 objectiveandquantitativeevaluationoflandscapeheterogeneityandtherepresentativenessofinsitu
12 measurements(Liangetal.,2002;Románetal.,2009;Susakietal.,2007).
13 ForthispurposeweappliedthemethodologypresentedbyRománetal.(2009)andbasedonthe
14 estimationofgeostatisticalattributesfromhighresolutionscenes(EnhancedThematicMapperPlus).
15 Thespatialpatternsandscalesoflandscapeheterogeneityhavebeenestimatedfromvariogrammodels
16 fittedatFLUXNETsitesoverthespatialscalesofMODISobservations.
17 Insynthesis,themethodologyadoptedfortheestimationofgeostatisticalindexesisbasedonthe
18 comparisonofvariogrammodelparametersretrievedatdifferentspatialresolution(i.e.from1.0km2to
19 1.5km2squaredsubsets).Byexaminingthevariogramparametersattwoscales,thespatial
20 characteristicsofagivenmeasurementsiteiscomparedagainstthelargerlandscapesextendingto
21 severalMODISpixels.
22 Fourdifferentgeostatisticalattributesofspatialrepresentativenesshavebeenusedtodescribethe
23 overallvariability(R ),spatialextent(R ),strengthofthespatialcorrelation(R ),and
CV SE ST
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