温度反演经典文章(9)

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Z.-L.Lietal./RemoteSensingofEnvironment131(2013)14–37

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GSWalgorithmpreparedforthereprocessingandforwardprocessingofthecollection-6orversion-6MODISLSTproductinthenearfuture.3.1.2.2.Non-linearsplit-windowalgorithm.Becauseoftheerrorsintro-ducedbylinearizingoftheRTEandalsobysomeapproximationsusedinthedevelopmentofSWalgorithms,e.g.,approximatingthetransmittanceasalinearfunctionoftheWV,thelinearSWalgorithmdescribedbyEq.(7)resultsinlargeerrorsinLSTretrievalunderwetandhotatmosphericconditions.ToimprovetheaccuracyofLSTre-trieval,non-linearSWalgorithmshavebeendeveloped:LST¼c 2

0þc1T1þc2Ti Tjþc3Ti Tj;

ð12Þ

whereck(k=0–3)arecoef cientspre-determinedbyregressingEq.(12)onsimulatedsatellitedatawithasetofatmospheresandsurfaceparameters,similartotheakinEq.(7).

Manysimilarformsofnon-linearSWalgorithmshavebeendevel-opedintheliteratureinrecentdecades(Atitar&Sobrino,2009;Coll&Caselles,1997;François&Ottlé,1996;Sobrino&Raissouni,2000;Sobrinoetal.,1994).SimilartothelinearSWalgorithms,someofthesenon-linearSWalgorithmsincorporatetheLSEsintothecoef -cientsck,someuseboththeLSEandtheWV,andsomealsoincorpo-ratetheVZA.

(1)WithconsiderationofLSEs

ToaccountfortheeffectoftheLSEsonLSTretrieval,Sobrinoetal.(1994),CollandCaselles(1997)proposedanon-linearSWalgorithmwithaformsimilartoEq.(12)withc0formulatedasalinearfunctionofεandΔε:

c0¼D0þD1ð1 εÞþD2Δε;

ð13Þ

wherethecoef cientsDk(k=0–2)areconstantsthatareinde-pendentoftheatmosphere.SunandPinker(2003)alsopro-posedanon-linearSWalgorithminwhichtheLSEsareimplicitlyconsideredbymakingeachparameterckinEq.(12)dependentonthelandsurfacetype.(2)WithconsiderationofLSEsandWV

Tofurtherimprovetheaccuracyofandreducethein uenceofwetatmosphericconditionsonLSTretrieval,SobrinoandRaissouni(2000)andSobrinoetal.(2004a)developedanon-linearSWalgorithmtoretrievetheLSTfromthegloballand1-kmAdvancedVeryHighResolutionRadiometer(AVHRR)datawithanestimat-ederrorof1.3KcomparedwithasetofthreehundredLSTsmea-suredinsituintworegionsofAustralia(Prata,1994b).TheyparameterizedDk(k=1,2)inc0(Eq.(13))aslinearfunctionsofWV,i.e.,

Dk¼E0;kþE1;kWV

ðk¼1;2Þ;

ð14Þ

inwhichthecoef cientsEaresensor-dependentconstants.(3)WithconsiderationofLSEs,WV,andVZA

ToimprovetheaccuracyofLSTretrievalfromTIRdatameasuredatlargerVZA,theVZAhastobeconsideredwhendevelopingtheLSTretrievalalgorithm.SobrinoandRomaguera(2004)andAtitarandSobrino(2009)proposedaphysics-basednon-linearSWalgorithmforSEVIRIdataintwoTIRchannels.Theysetc1=1andparameterizedthecoef cientsck(k=2,3)inEq.(12)andEinEq.(14)aslinearfunctionsofthesquareofthesecantoftheVZA.IthasbeenshownthatthistypeofSWiscapableofobtainingLSTvalueswitharootmeansquarederror(RMSE)of1.3KusingSEVIRIdataatVZAslowerthan50°.3.1.2.3.Linearornon-linearmulti-channelalgorithms.WhentherearethreeormoreTIRchannelsavailable,theLSTcanberetrievedfromalinearornon-linearcombinationoftheTOAbrightnesstemperatures

inthosechannelsusingmethodssimilartotheSWalgorithmsdescribedabove(Sun&Pinker,2003,2005,2007).Forinstance,SunandPinker(2003)developedathree-channellinearalgorithmtoretrievenight-timeLSTsfromtheGeostationaryOperationalEnvironmentalSatellite(GOES)data,assumingthattheLSEsinthesethreechannelscanbees-timatedfromthelandsurfacetypes.Theyproposedtousethecharac-teristicsoftheMIRchanneli1at3.9μmtoimprovetheatmosphericcorrectionatnight,andthecoef cientsinthethree-channellinearequationexplicitlyincludethechannelLSEs,butneglecttheWVandtheVZA:

LST¼dd1 εi1 ε!0þd1þ2

Tdj

iþd3þ4Tj iþd1 ε

j

i1

5þd6

Ti1;ð15Þ

i1

wherethecoef cientsdk(k=0–6)areconstants,parisonwithsomepublishedSWalgorithms(Becker&Li,1990b;Wan&Dozier,1996)demonstratedthatthepro-posedthree-channelalgorithmobtainedthebestLSTvalues,withanRMSElessthan1K(Sun&Pinker,2003).Furthermore,SunandPinker(2007)alsoproposedafour-channelnon-linearalgorithmtore-trievetheLSTfromSEVIRIdata,withthecoef cientsdependingonlandsurfacetypestoaccountforLSEeffects.ForLSTretrievalatnight-time,Eq.(16)isused

LST¼e 2

0þe1Tiþe2Ti Tjþþe3ðTi1 Ti2Þþe4Ti Tj

þe5ðsecVZA 1Þ;

ð16Þ

wherethesubscripti2representstheTIRchannelat8.7μmandtheco-ef cientsek(k=0–5)aredependentonthelandsurfacetype.Toac-countforthesolarradiationre ectedbytheEarth'ssurfaceintheMIRchanneli1duringthedaytime,asolarcorrectiontermd6Ti1cosθswasaddedtoEq.(16)(Sun&Pinker,2007)orasolarcorrectionmustbeperformedtotheTi1usingthemethodproposedbyAdamsetal.(1989)andMushkinetal.(2005).Whenevaluatedagainstgroundob-servations,theresultsshowedthattheLSTsretrievedusingthefour-channelalgorithmweremoreaccuratethanthoseobtainedusingtheGSWalgorithm.

However,itshouldbenotedthatMIRdatameasuredattheTOAduringthedaytimeconsistsofacombinationofre ectedsolarradi-anceandemittedradiancefromboththesurfaceandtheatmosphere,andtheerrorcausedbythesolarcorrectiontermcanaffecttheaccu-racyofLSTretrievalespeciallyinaridandsemi-aridregionswithhighre ectanceintheMIR.Inaddition,introducingonemorechannelcomeswiththeexpenseofincreasedmeasurementerrors.Theerrorsrelatedtoinstrumentalnoiseandotheruncertainties,suchasinsur-faceemissivityofthe8.7μmchannelinaridregions,alsoin uencethe nalLSTretrievalaccuracy.Therangeofemissivityvaluesandre-spectiveuncertaintyfornaturalorman-madesurfacesissigni cantlyhigherforMIRand8.7μmchannelsthanforthemostcommonlyusedSWchannels(Trigoetal.,2008b),furtherlimitingthewidespreaduseofthosechannelsforoperationalpurposes.

3.1.3.Multi-anglemethod

SimilartotherationaleofSWmethod,themulti-anglemethodisbasedondifferentialatmosphericabsorptionduetothedifferentpath-lengthswhenthesameobjectisobservedinagivenchannelfromdifferent …… 此处隐藏：3782字，全部文档内容请下载后查看。喜欢就下载吧 ……