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Theinfluenceofseaiceextentvariabilityonthe

Greenlandsurfacemassandenergybalance

M.Tedesco1,A.Quillet2,P.Alexander1,

A. Rennermalm3,J.Stroeve4,X.Feweis5,B. E.Orantes1,T.Davis6andM.Parkan6

1. TheCityCollegeofNewYorkCUNYNYC,USA2. ISITV,Toulon,France

3. RutgersUniversityNJ,USA4. NSIDCBoulder,COUSA

5. UniversityofLiege,Liege,Belgium6. EcolePolytechniqueFdraledeLausanne,CH

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SurfaceprocessesandSMBoverGreenland

2012anomalyofnumberofmel]ngdays

(seeSessionC43Ftomorrowa_ernoon)

Importanceofalbedo,accumula]onandlargescalecircula]ononrecentobserved

records

Newrecordsweresetin2012concerningmel]ng,albedo,runoff,SMBandtotalmass

balance(seeSessionC43Ftomorrow

a_ernoon,Tedescoetal.,2008,2011,2012)

Seaiceextenthasalsobeendecreasing,drama]callyoverthepastrecentyears

IstherealinkbetweenseaiceandSMB/SEBoverGreenland?

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Previouswork winddirec+onpa/ernsandasta+s+callaganalysisoficeretreatadvance

andsurface-meltevent+mingssuggestthatseaiceextentchangeisa

poten.aldriveroficesheetmeltHere,latesummerwinddirec+onsfacilitate

onshoreadvec.onofoceanheat,andenhancedmel+ngontheicesheet

commonlyoccursa>erreduc+onsinoffshoreseaice(Rennermalmetal.,

2009).

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Methods

Thistalk

UseofregionalclimatemodelMARforSEB/SMBquan]]esoverGreenlandandsensi]vityexperiment

SICvs.meltwaterproduc]on(ratherthanextent)

Supportvectorregressionanalysis(SVR) Analysisofgroundsta]ons

data

Rennermalmetal.2009 SICvs.meltextentbasedon

PMWdata

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5

TheMARmodel

Forcing(e.g.,ECMWF)

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Replica]ngpreviouswork

(correla]onbetweenSICandmel]ng)

MeltExtent

Meltwaterproduc]on

2

4

6

8

10

12

14

16

Region#

24681012

Month

1

2

3

4

5

6

8

7

9

11

12

13

14

16

15

10

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Correla]onanalysisbetweenSeaIceand

SEB/SMBmodeledterms

August Region6 Region7 Region8OWvs.Melt 0.67 0.75 0.42OWvs.Ts 0.64 0.54Tsvs.Melt 0.74 0.81 0.86

Albedovs.Melt -0.88 -0.83 -0.73SHFvs.Melt -0.47LHFvs.Melt -0.52

Rainfallvs.Melt 0.50LWDvs.Melt 0.63

1

2

34

5

6

8

7

9

11

12

13

14

16

15

10

AugustOnly99%stat.sign.valuesreported

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Sensi]vityexperimentusingtheregionalclimate

model

Replace the1979 1994 SICand SST anomalies (every 6

hours) with actual SIC and

SST condions in the forcing

oftheMARmodel

JJASICanomaly

JJASKTanomaly[C]

Example:2012

MAR

Actual

SeaIce/

SST(e.g.

2012)

Atmospheric

Forcing

(e.g.2012)

Control

Exp.(e.g.

2012)

19791994

SeaIce/SST

climatology

MAR

Sensi]v.

Exp.

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2012

2008

2008

Changewithrespecttousing

the19791994climatology

2012

+1.96.4%2008+0.65.9%

SensibleHeatFlux(SHF)

[W/m2 [W/m2

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0.985.17%change(en]redomain)

[Gt

2012minusclimatologyCumula]veMeltwater

produc]on

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Cumula]veSMB(e.g.,2012)

[Gt

Control(2012 CTRL-SENS

[Gt

Changewithrespecttousing

the19791994climatology

2012+0.022.32%

Resultsaresimilarforother

yearsfortheperiod2002-2012

[Gt

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Istheanswerblowinginthewind?

JJAmeanwindsfromMAR

JFM JJA

Aasiaat

Kangerlussuaq

JFM JJA

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UsinggrounddataandMachineLearning

Algorithms Goal:es]ma]ngrecordedsurfacetemperaturethroughan

ensembleofpredictors(134features)

Iden]fythepredictors(e.g.,variables)thataredrivingtheop]malpredic]on(featureranking)

Analysisofde-trendedandde-seasonalizeddoesnotshowalargedifferenceinseawindfrac]onbeinglinkedtoalarge

temperaturedifference.

M.Parkan-Coastalatmospherictemperaturepredic+oninGreenlandusingsupportvectorregression,MasterThesis-Ecole

PolytechniqueFdraledeLausanne:Supervisor:T.Davis,Advisor:M.Tedesco

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Usingasta]s]calapproach,SVR,itwasshownthatacorrela]onlinkcanbefoundbetweenoffshorevariablesandcoastalatmospheric

temperatures.Thenatureofthiscorrela]onlinkseemstobehighlydependentonloca]onand]meofyear.

ThefeaturerankingsobtainedwithSVRindicatethatwindfeaturesplayaprominentroleformost

sta]ons,withseasurfacetemperaturesandseaiceconcentra]onalsohavinganimportantinfluence.

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Apreviouslyiden]fiedcorrela]onisconfirmedbetweenSeaIceExtentandMel]ngalongthewestcoastofGreenlandthroughmodeloutputsin

August,withhighercorrela]onwhenconsideringliquidwaterproduc]on

ratherthanmeltextent

ARCMsensi]vityexperimentshowslileeffectofseaice/SSTcondi]onsonSEBandSMBovertheicesheet

Sta]ondataanalysisandmachinelearningalgorithmsconfirmtherela]onshipbetweenwinddirec]ononnear-surfacetemperaturefor

sta]onalongthecoastduringAugust

InconclusiveresultsaregeneratedfromSVRconcerningwhetherhighertemperaturesarerelatedtostrongerwindsblowingfromtheseaice

Theeffectofkataba]cwindsonreducingthepoten]alofwarmairadvectedfromtheoceantoclimbuptheiceandimpactSMBislikelyone

oftheexplana]onforthemodeledsmalleffect

Conclusions