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WhyLSTisimportantforclimateapplica5ons

NickRayner,DarrenGhent,LizzieGoodandClaireBulgin

Contents

•  Introduction – why LST is important •  General requirements:

– Length of record – Coverage – Homogeneity/stability – Communication of uncertainties

ImportanceofLSTforclimateapplica5ons• Landsurfacetemperature(orLST)providesavaluablesetofobserva5onsforcharacterisinglandsurfacestatesandland-atmosphereexchange.• Increasinglyrecognisedasanessen5alparameterfordiagnosingEarthSystembehaviourandevalua5ngEarthSystemModels:- providesagloballyconsistentrecordfromsatelliteofclear-sky,radia5vetemperaturesoftheEarth’ssurface- providesacrucialconstraintonsurfaceenergybalances,par5cularlyinmoisture-limitedstates.- providesametricofsurfacestatewhencombinedwithvegeta5onparametersandsoilmoisture,andisrelatedtothedrivingofvegeta5onphenology.

Modellingofevapotranspira5on

ImportanceofLSTforclimateapplica5ons• Landsurfacetemperature(orLST)providesavaluablesetofobserva5onsforcharacterisinglandsurfacestatesandland-atmosphereexchange.• Increasinglyrecognisedasanessen5alparameterfordiagnosingEarthSystembehaviourandevalua5ngEarthSystemModels:- animportantsourceofinforma5onforderivingsurfaceairtemperatureinregionswithsparsemeasurementsta5ons,suchaspartsofAfricaandtheArc5c

Inter-annualvariabilityforsurfaceairtemperatureandsurfaceskin

temperatureSkintemperatureisfromMODISday5meobserva5onat0.05°la5tude/longitude,andairtemperatureismonthlymeanfromGHCN(fromJin&Dickinson,2010)

ESTIMATINGAIRTEMPERATUREFROMSKINTEMPERATURE

EOBS ECA&D

LizzieGood,MetOfficeHadleyCentre

SatelliteLSATHighest available resolution in-filled air temperature analysis from weather station measurements

Publicly available weather station records

Higher resolution information on air temperature estimated using surface (skin) temperature from satellites Tmin

Tmax

Lengthofrecord

RequirementsBaselineDocumentRef.:GlobTemp-WP1.1-DEL-05-i1r0

Needaslongarecordaspossible–atleast30yearsfor“Climate”,e.g.:• Modelevalua5on• A`ribu5onofchangesoverAfrica(lackofinsituhere)• Reconstruc5ngpastairtemperature

Lengthofrecordneeded

Modelevalua5on/changea`ribu5onEastAfricaSouthernAfrica

Here,surfaceairtemperatureuncertaintyofsameorderasmodelspread–useLSTinstead?

AndyCiavarella,MetOfficeHadleyCentre

Need for multi-decadal record: calculating changes relative to a baseline

•  To assess changes, a baseline must be established •  Best station data starts 1920s, but satellite data are only from 1980s – some of this record needs to be used to create the baseline

FraserLo`,MetOfficeHadleyCentre

Homogeneity/stability


•  Requirementforstability:• 0.1K/decadeatbreakthrough(GlobTemperatureUserRequ)

•  Needconsistent:• sensorcalibra5on



•  Needconsistent:• sensorcalibra5onandalgorithms• auxiliarydata(earlyATSRauxiliarydatahadinconsistenciesleadingtolargeuncertain5es)

©ESA–GlobTemperatureConsor7um

DUEGlobTemperature

16

IMPROVEMENTSTOATSRLST•  EarlyATSRauxiliarydata(land

coverinformaIon,emissivityinformaIon,atmosphericprofiles)hadinconsistenciesleadingtolargeuncertainIes

•  GlobTemperaturehasresolvedtheseissueswithuseofhighspaIalandtemporalresoluIonauxiliarydata

Existing operational

GlobTemp Existing operational

GlobTemp



•  Needconsistent:• sensorcalibra5onandalgorithms• auxiliarydata• cloudclearing(changingclearskybiases,etc;GlobTemperaturedoingthisforATSRonly)

ImpactonLSTretrievalsofdifferentautoma5ccloudclearingalgorithms

ClaireBulgin,Univ.Reading



•  Needconsistent:• sensorcalibra5onandalgorithms• auxiliarydata• cloudclearing(changingclearskybiases,etc.;GlobTemperaturedoingthisforATSRonly)

• Changinguncertain5esduetoinconsistenciesleadstounstablesystem

Coverageandresolu5on


Notetheneedforglobalproducts,butalsoforcountryandcity-scaleproducts:• Needed,forexample,forpolicy-relatedworkandurbanclimatechangestudies,includingassessmentsofe.g.heatstress

Spa5aldomainneeded

Heatstressinurbanenvironments

BenedicteDousset


Spa5alresolu5onneeded


Temporalresolu5onneededEUSTACEuserrequirementsanalysisalsoindicatesaneedforinforma5onondailyTmaxandTmin.Thisisimportant,e.g.fortheanalysisofextremes,andclimate-relatedeventa`ribu5on.

DiurnalcycleobservedbySEVIRIandinsitusta5on60735(3540N,1006E–Tunisia)withapproximatesatelliteoverpass5mes

(Blue=MODIS/Aqua,Yellow=MODIS/Terra,Red=ATSR).Squaresindicate15-minuteSEVIRIobserva5ons.


Near-globalcoverage(overland)fromMODISinoneday

DiurnalcycleobservedbySEVIRIandinsitusta5on60735(3540N,1006E–Tunisia)withapproximatesatelliteoverpass5mes

(Blue=MODIS/Aqua,Yellow=MODIS/Terra,Red=ATSR).Squaresindicate15-minuteSEVIRIobserva5ons.


Temperatureobserva5onsfromtheARMOklahomasiteon16August2014.Cloudhasstronginfluenceontemperature

evolu5on,par5cularlyonLST.

Good(2015),inprepara5on

Duringtheday,LSTismuchwarmerthanairtemperatureinclearskies(16:00-20:00GMT),butthetwoaremuchcloserundercloud(from22:00GMT)

Coverageandresolu5on•  GeneralLSTrequirements:1kmorfinerto0.05°,atleastday/night(GlobTemperatureuserrequs.)

•  EUSTACEuserrequirements:dailyTmaxandTmin;consistencywithothersurfaces

Consistencywithothersurfacesneeded

Coverageandresolu5on•  GeneralLSTrequirements:1kmorfinerto0.05°,atleastday/night(GlobTemperatureuserrequs.)

•  EUSTACEuserrequirements:dailyTmaxandTmin;consistencywithothersurfaces

•  Globtemperaturelookingates5ma5ngclearskybiasfrommicrowave,butwon’tcovermerging

•  Combina5onofsensors(AVHRR,ATSR,MODIS,VIIRS,geosta5onaries,microwave)neededtoachievewhatusersneed

Communica5onofuncertain5es

EUSTACEMODISL2UNCERTAINTIESEUSTACE/GlobTemperatureMODISL2Product• Traceableglobally-robustcoefficients• UncertaintyanalysisfromfirstprinciplesUncertainIes• UncertainIescategorisedbyeffectswhoseerrorshavedisInctcorrelaIonproperIes:

Ø  Random,e.g.sensornoise,emissivityspecifica5onØ  Locallysystema5c,e.g.atmosphericstatespecifica5on,otheremissivity

issuesØ  (large-scale)Systema5c,e.g.calibra5oncorrec5ons

• Thisthree-componentmodelcanbeappliedtoallprocessinglevelsandLSTproducts• PropagaIonofuncertainIes:

Ø  L1 L2 L3 L4(MergedProduct)

EUSTACEMODISL2UNCERTAINTIESOVERWESTERNRUSSIA

Randomeffects Locally-correlatedeffects

Othercommunica5onneeds

•  Guidanceforuserstoenablethemtousethedataintheircontext,e.g.canyousubs5tuteLSTanomalyforsurfaceairtemperatureanomaly?

•  Guidanceonuncertain5es•  Rela5onshiptomodelskintemperatures

Summary•  LSTisanimportantvariableformanyaspectsofclimateresearchandservicesonglobalandlocalscales

•  Inordertomeetclimateusers’needsforlong,homogeneous,sub-daily,<0.05°resolu5oninforma5onwithsplituncertaintycomponents,acombina5onofallavailablesensortypesisneeded

Extraslides

EUSTACEAIMSEUSTACEwillgivepubliclyavailabledailyesImatesofsurfaceairtemperaturesince1850acrosstheglobeforthefirstImebycombiningsurfaceandsatellitedatausingnovelstaIsIcaltechniques.Todothis,weneedto:• Iden5fynon-clima5cdiscon5nui5esindailyweathersta5ondata,souserscantrustthechangesourrecordsshow• Produceconsistentuncertaintyes5matesforsatelliteskintemperatureretrievalsoverallsurfaces(land,ocean,iceandlakes),soweknowhowfartotrustthees7mateseverywhere• Understandhowsurfacetemperaturemeasuredinsituandbysatelliterelates,toes7mateairfromskintemperature• Es5matevaluesinareaswherewehavenoinsituorsatellitedata,souserscanhavedailyinforma7onhere

ESTIMATINGAIRTEMPERATUREFROMSKINTEMPERATURE

Satellitevariables,includingskin

temperatureandvegeta5on

Sta5cdatasets(la5tude,eleva5on)

Observedsta5onairtemperatur

e

Regressionmodel(perdayforspecificregion)

Airtemperaturees5matedforeverycloud-

freesatellitepixel

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