NASA Technical Reports Server (NTRS) 20150011467: Observation of Mountain Lee Waves with MODIS NIR Column Water Vapor

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Geophysical Research Letters
RESEARCH LETTER Observation of mountain lee waves with MODIS
10.1002/2013GL058770 NIR column water vapor
KeyPoints: A.Lyapustin1,M.J.Alexander2,L.Ott1,A.Molod3,B.Holben1,J.Susskind1,andY.Wang1,4
(cid:129) Mountainwavesarediscoveredinthe
MODISNIRcolumnwatervapor 1NASAGoddardSpaceFlightCenter,Greenbelt,Maryland,USA,2NWRA-CoRAOffice,Boulder,Colorado,USA,3EarthSystem
(cid:129) Weobserve3-4to15kmleewaves
ScienceInterdisciplinaryCenter,UniversityofMaryland,CollegePark,Maryland,USA,4JointCenterforEarthScienceTechnology,
withanamplitudeof50-70%ofthe
totalCWV UniversityofMaryland,BaltimoreCounty,Baltimore,Maryland,USA
(cid:129) Theresultissupportedbyradiosonde
andGEOS-5 atmospheric
stability analysis Abstract Mountain lee waves have been previously observed in data from the Moderate Resolution
ImagingSpectroradiometer(MODIS)“watervapor”6.7μmchannelwhichhasatypicalpeaksensitivityat
550hPainthefreetroposphere.Thispaperreportsthefirstobservationofmountainwavesgeneratedbythe
Correspondenceto: AppalachianMountainsintheMODIStotalcolumnwatervapor(CWV)productderivedfromnear-infrared
A.Lyapustin, (NIR)(0.94μm)measurements,whichindicateperturbationsveryclosetothesurface.TheCWVwavesare
[email protected]
usuallyobservedduringspringandlatefallorsomesummerdayswithlowtomoderateCWV(below~2cm).
Theobservedleewavesdisplaywavelengthsfrom3–4to15kmwithanamplitudeofvariationoftencomparable
Citation: to~50–70%ofthetotalCWV.Sincethebulkofatmosphericwatervaporisconfinedtotheboundarylayer,this
Lyapustin,A.,M.J.Alexander,L.Ott,A.
indicatesthattheimpactofthesewavesextendsdeepintotheboundarylayer,andthesemaybethelowestlevel
Molod,B.Holben,J.Susskind,andY.
Wang(2014),Observationofmountain signaturesofmountainleewavespresentlydetectedbyremotesensingovertheland.
leewaveswithMODISNIRcolumn
watervapor,Geophys.Res.Lett.,41,
710–716,doi:10.1002/2013GL058770.
1. Introduction
Received19NOV2013 Watervaporisapotentgreenhousegasthebulkofwhichisconfinedtotheboundarylayer.Itisamajor
Accepted3JAN2014
Acceptedarticleonline8JAN2014 componentoftheEarthenergyandwatercyclesandamajorparameterinweatherforecastingandclimate
Publishedonline30JAN2014 modeling.Watervaporrespondstosurfacetemperaturechangesthroughradiativeeffectsandclimatefeed-
backs[Trenberthetal.,2005;Wagneretal.,2006;Solomonetal.,2010].Accurateknowledgeofatmospheric
watervaporiscrucialtocorrectthetimedelayandphasedistortionsfortherepeat-passInterferometricSynthetic
ApertureRadarapplications[e.g.,Lietal.,2006,2009]especiallyforsmall-amplitudegeophysicalsignalswithlong
wavelengths,includinginterseismicdeformationandsomeanthropogenicprocesses[e.g.,ZebkerandRosen,
1997].Satelliteandground-basedmeasurementsshowthatoverlanditmayexhibitlargespatialandtemporal
variability[e.g.,Kumaretal.,2010].Alargepartofthisvariabilitymayberelatedtotheairmasstransportor
evaporationfromopenwaterbodiesandevapotranspirationofvegetationandsoils.Inthispaper,wereportnew
observationspointingtoamechanismresponsibleforperiodicoscillationsinthecolumnwatervapor(CWV)
relatedtomountainleewaves.
Atmosphericgravitywavesaregeneratedbyloweratmosphericsources,e.g.,flowovermountains,sporadic
diabaticheatinginconvectivesystems,andimbalanceinjetstreamsandfronts[Kimetal.,2003].Mountain
leewavesarecausedbyanairflowovermountainridgeswithinastablystratifiedatmosphere[Smith,1976;
Durran,1986].Breakingwavesandsmall-scalewavescanbeasourceofturbulenceandstrongverticalair
currents,whichcanbeanaviationhazard[Uhlenbrocketal.,2007;Sharmanetal.,2012].Dependingon
temperatureandavailablemoisture,cloudsmayformintheleeofmountainrangesinrowsquasi-parallelto
theterrainandorthogonaltothedirectionoftheflow.Satelliteclassificationoforographiccloudsbeganwith
thefirstweathersatellite,theTelevisionInfraredOperationalSatellite,whichwaslaunchedin1960[e.g.,Conover,
1964].Sincethen,manystudiesreportedmountainwavecloudsignaturesonEarth[e.g.,Fritz,1965;Ernst,1976],
andevenMars[e.g.,KahnandGierasch,1982].
Atmosphericgravitywaveshavebeenwidelystudiedusinghigh-resolutionremotelysensedtemperature
observationsfromspace.Aquasatelliteobservationshavebeenusedtoimageandstudyorographicgravity
wavesinthestratosphere[e.g.,WuandZhang,2004;Eckermannetal.,2007;AlexanderandBarnet,2007;
Alexanderetal.,2009;AlexanderandTeitelbaum,2011].LimbScanningmeasurementsfromspacealsoprovide
observationsofstratosphericmountainwaves[e.g.,EckermannandPreusse,1999;Jiangetal.,2002;Alexander
etal.,2008].Mountain-generatedgravitywavesfromtheAndesobservedbytheAtmosphericInfraredSounder
havehorizontalscalesof~102kmandaltitudesof~20–40km[AlexanderandBarnet,2007;Jiangetal.,2013].
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Mountain-generatedwavesarealsoregularlyobservedfromradiancein6.7μm(watervapor)channelwith
mostradiancetypicallygeneratedataltitudesaboveapproximately550hPa[Uhlenbrocketal.,2007;Feltzetal.,
2009]wherethewavescanpresentaviationhazards.
Thehighspatialresolution(~1km)CWVisaremotesensingproductoftheModerateResolutionImaging
Spectroradiometer(MODIS)[GaoandKaufman,2003]andMediumResolutionImagingSpectrometer[Bennartz
andFischer,2001;Lindstrotetal.,2012].Inthiswork,weareusingcolumnwatervaporretrievedaspartofthe
Multi-AngleImplementationofAtmosphericCorrection(MAIAC)algorithmdevelopedforMODIS.MAIACisa
new-generationMODISalgorithmwhichusesatimeseriesanalysisandprocessingofgroupsofpixelsfor
simultaneousretrievalsofatmosphericaerosolandlandsurfacereflectanceproperties[Lyapustinetal.,2011,
2012].Itincludesclouddetection[Lyapustinetal.,2008]aswellasaCWVretrieval(basedonnear-infrared(NIR)
channelsat0.94μm)requiredforcorrectionofthewatervaporabsorption.DespitethefactthatCWVisan
operationalMODISproduct(MOD05)[GaoandKaufman,2003],MAIACalsoderivesCWVbecausetheretrieval
algorithmisfastandsimpleandsuchanapproachhelpsavoidunnecessarydatatransfersandcross-product
dependence.TheMAIACCWVretrievalapproachisdescribedinsection2,followedbyadiscussionofthe
mountainwavesobservedinCWVfieldinsection3.
2. MAIAC WaterVapor Retrieval
MAIACretrievescolumnwatervaporoverthelandsurfacesandtheinlandorcoastalwaterswithglint.The
algorithmusesthreeMODISNIRwatervaporchannelswiththefollowingbandcenterandwidth(nm):17
(905,30),18(936,10),and19(940,50).Theabsorptionishighestinband18anddecreasesinbands19and
17.Theretrievalsarebasedonthefollowingapproximateformulaforthetopofatmospherereflectance:
Ttotðμ ;μÞ
Rλðμ0;μ;φÞ≅RDλðμ0;μ;φÞþ1(cid:2)λqλðμ00Þc0;λρλðμ0;μ;φÞ; (1)
where(μ ,μ,φ)arecosinesofsolarandviewzenithanglesandrelativeazimuth, RD isapathreflectance,
0 λ
Ttλotðμ0;μÞ=〈T↓(μ0)T↑(μ0)〉λ is a total two-way atmospheric transmittance, c0,λ is spherical albedo of atmo-
sphere,andρλ(μ0,μ,φ)andqλ(μ0)aresurfacereflectanceandalbedo.The terms RDλ and Ttλot arespectrally
integratedwiththespectralresponsefunctionofagivenchannelandsolarirradiance.Duetostrongwater
vaporabsorptionandusuallylowaerosolscatteringintheNIR,thepathreflectanceandthemultiplescatter-
ingoflightbetweenthesurfaceandtheatmosphere(denominatorinthesecondterm)canbeomitted.Ifthe
surfacereflectancechangeslittleinanarrowabsorptionintervalof0.9–0.94μm,thenatwo-channelratio
algorithmcanbeusedtoderiveCWV:
Ttot R Ttot R
18 ¼ 18;and 19 ¼ 19: (2)
Ttot R Ttot R
19 19 17 17
Foragivenviewgeometry,thesolutionisfoundbysearchingthelook-uptable(LUT)oftransmittanceratio.
TheLUTwascomputedwithInterpolationandProfileCorrection(IPC)algorithm[Lyapustin,2003]designed
forfastandaccurateradiativetransfercomputationsinabsorptionbandswitharbitraryspectralresolution.
Themonochromaticwatervaporabsorptionwascomputedwithresolutionof0.01cm(cid:2)1basedonHITRAN-
2000[Rothmanetal.,2003]usingthestandardatmosphericprofiles.Toaccountfordifferenteffectiveabsorption
andsensitivityofdifferentbandratios,wefollow[GaoandKaufman,2003]andcomputethemeanwatervapor
asfollows:
W ¼f W þf W ; (3)
1 1 2 2
whereW arewatervaporvaluesderivedfromdifferentchannelratiosandf areweightingfunctionsrelated
i i
tothesensitivitiesofthetwobandpairs.TheyarecomputednumericallyfromtheratiosTtotðμ ;μ;WÞ=
18 0
Ttotðμ ;μ;WÞandTtotðμ ;μ;WÞ=Ttotðμ ;μ;WÞstoredintheLUT.
19 0 19 0 17 0
ThedevelopedalgorithmwasvalidatedagainstAerosolRoboticNetwork(AERONET)[Holbenetal.,1998]CWV
groundmeasurementsfor156stationsgloballywhichshowedthatincloud-freeconditionstheretrievalsare
generallyunbiasedandaccurateto5–10%.Thesenumbersagreewithaccuracyassessmentsofoperational
MOD05product.Similarly,wefoundloweraccuracy(20–30%)overareaswithrediron-richsoils(e.g.,Canberra,
Australia),whosereflectancechangesconsiderablyinthe0.9–1μmspectralregionduetoabsorptionofthe
ironcompounds.Ontheotherhand,MAIACCWVisfoundtobelowerthanMOD05by~5–20%,providingmore
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Figure1.MODIS(top)Terraand(bottom)AquaRGBandCWVimageforthemid-AtlanticU.S.regionon2June2011.The
differenceinTerra-Aquaoverpasstimeis1h40min.
accurateresult.ThisisconfirmedbyvariousMOD05CWVvalidationstudiesagainstradiosonde,GPS,and
MicrowaveWaterRadiometerdatashowingthewetbias(highervalues)ofMOD05productinthesamerange
of~5–20%[Liuetal.,2013;Luetal.,2011;Albertetal.,2005;Lietal.,2003;PrasadandSingh,2009;Kumaretal.,
2010].Atthesametime,validationstudiesreportaverygoodagreementofAERONETCWVwithGPSand
radiosondemeasurementswithr2~0.95–0.99[Liuetal.,2013;PrasadandSingh,2009;Kumaretal.,2010].Itis
worthmentioningthatAERONETCWValgorithmusesWV-bandmodelcoefficientsgeneratedbytheIPCcode
[Lyapustin,2003]foreachindividualSunphotometerfilterfunction.
Apartfrompossiblespectroscopy-relateddifferencesincomputingatmospherictransmittancethatremoves
wetbias,theMAIACapproachisalsosimplerthanMOD05algorithm.Thelatterassumesalinearchangeof
surfacereflectanceacross0.9–0.94μmintervalandusestwoadditionalMODISchannelsB2(0.865μm)andB5
(1.24μm)topredictsurfacereflectanceinbands17–19.GaoandKaufman[2003]assessedtheaccuracyofthe
linearmodelas2.4–3.9%formostsoils,rocks,vegetation,andsnowand8.4%fortheiron-richsoils.Wetried
theGaoandKaufman[2003]five-bandapproachandfoundahighernoise,oftenbyafactorof2–3,thanthe
selectedthree-bandmethod,basedoncomparisonwithAERONET.Theerrormaygrowfromusingmuch
widerspectralintervalwhenthelinearspectralmodelisnotagoodpredictorforthesurfacereflectancein
the0.85–1.24μmregion.
Athighaerosolloadingandelevatedprofiles,theaerosolscatteringincreasesthemeasuredsignalandtheband
ratiothusreducingretrievedCWV[seealsoBennartzandFischer,2001;Lindstrotetal.,2012].OurAERONET-based
analysisshowsthathighaerosoloutbreaksexplainover90%ofcaseswhenretrievedWVwassignificantlylower
thantheAERONETvalue.Thesedatashowtheneedforaerosolcorrectiononhazydayswhichiscurrentlynot
implementedineitherMAIACorMOD05.
3. Mountain WavesinMODIS CWV
AnexampleofmountainwavesinMAIACNIRCWVisshowninFigure1.TheTerra(top)andAqua(bottom)
imagescoveranareaof400×400km2for2June(dayofyear153)2011.TheMODISRGBimages(left)show
clearconditionswithlowcloudiness.TheaverageMAIACaerosolopticaldepthat0.47μmwaslessthan0.2.
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Figure2.MODISAquaRGBandCWVimagefor18March2011.ThecolorscaleisthesameasinFigure1butwiththemaximal
valueof2.5cm.
TherightimagesshowtheretrievedCWV;theblack(fill)valuescorrespondtoeitherdarkwaterordetectedclouds.
ThegeneratedwavetrainroughlyparalleltotheAppalachianmountainsiswellvisibleinthelower-middlepartof
theimagewithadissipationdistanceof~150km.Weakerwaveswithalargerperiodcanbeseeninthenortheast
sectionoftheTerraCWVimage.TheAquaimagewasobtained1hand40minaftertheTerraoverpass,sothe
wavetrainappearstobestationary.AnapparentreductionincontrastintheAquaCWVrelativetotheTerraCWVis
aconsequenceoftheviewgeometry,withanAquaviewzenithangleof~40°asopposedtothenadirviewof
Terra.Intheareaofmaximalcontrast,TerraCWVwaveshaveanaveragewavelengthof~6kmwithanamplitude
of~1.0cm,withCWVrangingfrom~0.5cminthetroughto~1.5cminthecrest.
Figure2showsanotherexamplefromAquaduring18March2011withwavelength~7km,inwhichcloud
formationonthecrestsofthewavescanbeseenintheRGBimageontheleft.Finally,Figure3showstwo
moreexamplesofCWVwaveswithverydifferentwavelengths,intherangeof3–4kmon3June(top)and
10–15kmon15October(bottom)of2011.
Generally,mountain-generatedleewavescanbefrequentlyobservedeastoftheAppalachianrangedur-
ingwinter,spring,andlatefallintheMODISNIRCWVimageryandonsomesummerdayswithlowto
moderatehumidity.Onsuchdays,theairofadrycolderupperlayerisalternatelyliftedandloweredby
Figure3.MODISAquaRGBandCWVimagesfor(top)3Juneand(bottom)15October2011.Thecolorscaleisthesameas
inFigure1butwiththemaximalvaluesof2cm(top)and2.5cm(bottom).
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gravitywaves,causingconvergenceand
divergenceofairinthewarmermoist
bottomlayer,whichisseenasbandsinthe
CWVfield.
Atmosphericprofilesoftemperatureand
windfieldswereusedtoassesstheability
oftheatmospheretosustaintrapped
gravitywaves.Theverticalprofileofthe
Scorerparameter(L)calculatedasN/U
[Smith,1976]fromradiosondesandfrom
theGEOS-5analysis[Rieneckeretal.,2008]
fieldsforthe2Junecase(Figure1)isshown
inFigure4.HereNisstaticstabilityandUis
Figure4.Radiosonde(blackandblue)andGEOS-5(red)derivedpro- windspeedapproximatelynormaltowave
filesoftheScorerparameter(L/2π)atIADon2June.Thedottedportion
phaselines.TheScorerparameter[Scorer,
oftheGEOS-5profileindicatestheunstableplanetaryboundarylayer
(PBL).Thedashedlineindicatesthehorizontalwavenumberofthe 1949]arisesfromthedispersionrelationfor
wavesobservedinMODISCWVon2June. atmosphericgravitywavesolutionstothe
Taylor-Goldsteinequationandisusedasan
indicatoroftrappedleewaves.WhenLdecreasesstronglywithheight,trappedleewavesofcertainfre-
quenciesarepossible.Theverticaldashedlineinthefigureisthehorizontalwavenumber(k=1/wavelength)
ofthewavemotionsseeninFigure1,andthelevelatwhichLdescendsbelowthedashedlinegivesthe
trappingheightofthegravitywaves.Belowthislevel(L>k),thewavesaretrappedorpropagatevertically,
andabovethislevel(L<k)thebuoyancy-restoringforcescannotsustainoscillationsatthosehighintrinsic
frequenciesandthewavemotionsdecay.Inaddition,theunstablestratificationintheatmosphericboundary
layernearthesurface(theregionwheretheredlineisdotted)alsocannotsustaingravitywaves.Thetrapped
waves,therefore,basedontheseatmosphericconditions,canexistinalayerbetweenapproximately1and
2kmabovethesurface,whereenoughwatervaporexiststorevealoscillationsintheCWVofMODIS.
Althoughthewavesdecaybelow1kmaccordingtotheanalysis,theystillpenetratesomedistanceintothe
moistersurfacelayer.Thenetresultisaseriesofcolumnsofalternatelymoisteranddrierair1–2kmdeep
nearthesurfacethataredetectedbytheMODISsensor.Similarresultswerefoundfortheothereventsin
Figures2and3,althoughtrappinginasomewhatdeeperlayerbelow3kmwasindicatedintheOctobercase
withthelongerhorizontalwavelength.
ThesewavesarenotobservedontypicalsummerdayswhenCWVvaluesof3–5cmareubiquitousforthe
EastCoastoftheU.S.TheabsenceofMODISCWVobservationsofmountainleewavesinthisseasonislikely
relatedtodeeperunstablePBLheightsandatmosphericconditionsthatwillnotsustaingravitywaves.
HigherCWVwouldalsoincreasethechanceofformingcloudsthatcanobscurethewaves.
4. Conclusions
Mountainleewavesareanimportantphenomenonintroposphericmeteorologywithpracticalimplications
(e.g.,aviationhazards).ThispaperreportsthefirstobservationofleewavesintheMODISNIRcolumnwater
vaporeastoftheAppalachianmountainsathigh1kmresolution.Generationandverticalpropagationof
thesewavesrequiresastablystratifiedatmospherewithstabilityandwindconditionsleadingtotrappingof
shorterhorizontalwaves.Bothradiosondeandatmosphericanalysisprofilesestablishedthatconditionsfor
leewavetrappingbelow2–3kmaltitudeexistedonthedayswhentheoscillationsintheMODISCWVwere
observed.Importantly,incontrasttopreviousstudiesbasedonsoundingdatawhichreportedgravitywaves
ataltitudesofthemidtroposphereandstratosphere,theCWVshowsperhapsthelowestnear-surfacewaves
thatcanbedetectedfromremotesensingdataoverland.KnowledgeofvariabilityinCWVatthesescaleswill
informregionalandglobalmodelsofmoistprocesses,whichrelyonassumptionsaboutthesubgridscale
probabilitydistributionfunctionsfortotalwater[e.g.,Molod,2012].Remotesensingmeasurementsof
greenhousegases,suchasCO andCH ,willalsobenefitfromimprovedcharacterizationofCWVvariability
2 4
becausesuchinformationallowsformoreaccuraterepresentationofthelinebroadeningbywatervaporand
potentialerrorreductioninsuchobservations.
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Geophysical Research Letters 10.1002/2013GL058770
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