Simulation of the Global Hydr ologicalCycle in

the CCSM Community Atmosphere Model

(CAM3): Mean Features

JamesJ. Hack�, Julie M. Caron, StephenG. Yeager, Keith W. Oleson,

Marika M. Holland, John E. Truesdale,and Philip J. Rasch

NationalCenterfor AtmosphericResearch,Boulder, Colorado80307

�NCAR, P.O.Box 3000,Boulder, CO.80307,email: jhack@ncar.ucar.edu

1

Abstract

The seasonalandannualclimatologicalbehavior of selectedcomponents

of thehydrologicalcyclearepresentedfrom coupledanduncoupledconfigura-

tionsof theatmosphericcomponentof theCommunityClimateSystemModel

(CCSM),theCommunityAtmosphereModel Version3 (CAM3). Theformu-

lationsof processesthatplay a role in thehydrologicalcycle aresignificantly

morecomplex whencomparedwith earlierversionsof theatmosphericmodel.

Major featuresof the simulatedhydrologicalcycle will be comparedagainst

available observational data,and the strengthsand weaknesseswill be dis-

cussedin thecontext of thefully-coupledmodelsimulation.

1. Intr oduction

Theaccuratetreatmentof Earth’shydrologicalcycle,thecirculationof waterin theclimate

system,is centralto scientificexplorationsof climatedynamicsandclimatechange.The

globalwatercycle is an integral partof theglobalenergy cycle andhenceplaysa funda-

mentalrole in determininglarge-scalecirculationandprecipitationpatterns.Thecomplex

webof feedbackslinking hydrologicalprocesseswith theenergy cycleoperateoveracon-

tinuumof timeandspacescales.

Watercanbefoundin all threephasesin theclimatesystem,andisastronglyradiatively-

activeatmosphericconstituentin all forms.Theliquid andfrozenphasesaremostcommon

in theform of clouds.Cloudsplay a dominantrole in regulatingtheenergy budgetof the

planet,andtheirbehavior remainsamajorsourceof uncertaintyin ourability to projectthe

effectsof climatechange(e.g.,StephensandWebster1981;Cesset al. 1990;IPCC2001).

They coolEarthby reflectingsolarradiationbackto space,while at thesametimewarming

theplanetby absorbingthermalradiationemittedfrom thesurfaceandlowerregionsof the

2

atmosphere.Theprocessesresponsiblefor phasetransitionsof wateralsocontributeto the

diabaticforcingof Earth’sdynamicalcirculations,andarekey to theoverallenergy budget.

This is particularlytrue for the thermallydrivencirculationsin the tropicsandsubtropics

(Chahine1992).

Thehydrologicalcyclebeginswith theevaporationorsublimationof waterfromEarth’s

surfacewhereit is transportedby theambientmotionfield. Whentheair is lifted, it cools

andallows waterin thevaporphaseto condensein clouds,whereit canexist in both the

liquid or frozenphase.Microphysicalprocessesdeterminewhetherthecloudcondensate

is re-evaporated,changesphase,or growsparticleslargeenoughin sizeto precipitateback

to thesurface.Oncetheprecipitationreachesthesurfaceit canbere-evaporated,produce

runoff thatfindsits way into lakes,rivers,andoceans,or infiltrate thesurfaceandbestored

in thewatertable.All of theseprocessesoperateonawide rangeof timeandspacescales,

andareverydifficult to quantifyobservationally. Themostreliableobservationsof hydro-

logic processesarelimited to relatively long time andlargespacescales.As such,current

observationaldataprovide relatively weakcontraintson the formulationof hydrological

processesin global models.A major challengeto the designof global climatemodelsis

to realisticallyincorporatethemany physicalprocessesinvolvedin thehydrologicalcycle

that operateon scalesof motion distinctly separatefrom thoseof the larger-scaleresolv-

ablecirculation,but stronglyinfluencethebehavior of theatmosphereonall timeandspace

scales.

Version3 of theCommunityAtmosphereModel (CAM3) is the latestin a succession

of generalcirculationmodelsthathave beenmadewidely availableto thescientificcom-

munity, originatingwith theNCAR CommunityClimateModel (CCM). This modelis the

atmosphericcomponentof theCommunityClimateSystemModel 3.0 (CCSM3),a fully-

coupledmodelingframework thatcanbeusedfor abroadclassof scientificproblems.The

3

CCSM3representsthe latestgenerationof this modelingframework, andis discussedin

moredetailby Collins et al. (2005a).CAM3 incorporatesa significantnumberof changes

to thedynamicalformulation,thetreatmentof cloudandprecipitationprocesses,radiation

processes,andatmosphericaerosols,andis discussedmorefully in Collins et al. (2005b).

Therepresentationof cloudandprecipitationprocesseshasbeensignificantlyrevised,in-

cluding separatetreatmentsof liquid and ice condensate,large-scaleadvection,detrain-

ment,andsedimentationof cloudcondensate;andseparatetreatmentsof frozenandliquid

precipitation(Boville et al. 2005).Theparameterizationof radiative transferhasbeenup-

datedto include a generalizedtreatmentof cloud overlap(Collins et al. 2001) andnew

treatmentsof longwave andshortwave interactionswith watervapor(Collins et al. 2002a,

2004). Finally, a prescribedclimatologicaldistribution of sulfate,soil dust,carbonaceous

species,and seasalt basedupon a three-dimensionalassimilation(Collins 2001; Rasch

et al. 2001) is usedto calculatethe direct effectsof troposphericaerosolson the heating

rates(Collins etal. 2002b).This latterchangeis noteworthy in thecontext of whatfollows

giventhattheradiativeeffectsof atmosphericaerosolhasbeenshown to stronglyinfluence

thebehavior of hydrologicalprocesses(Ramanathanet al. 2001;Menonet al. 2002).

The CAM3 hasbeendesignedto provide simulationswith comparablelarge-scalefi-

delityoverarangeof horizontalresolutionsfor severaldifferentdynamicalapproximations.

Thesemodificationsrequireadjustmentsto parametersin the physicspackageassociated

with cloud andprecipitationprocesses.Consequently, the detailedhydrologicalprocess

behavior hassomedependenceon horizontal resolutionand the formulation of the dy-

namicalcore. Someof theseissues,alongwith thesensitivity of thesimulatedclimateto

modelresolutionarediscussedin moredetail in Hack et al. (2005),Yeageret al. (2005),

andDeWeaver andBitz (2005). Thestandardconfigurationof theCAM3 is basedon an

Eulerianspectraldynamicalcore,wheretheverticaldiscretizationmakesuseof 26 levels

4

(L26) treatedusingsecond-orderfinite differences(Williamson 1988). The vertical do-

main is essentiallythesameasin earliermodels,but employs 8 additionallevelsto better

refinethe uppertroposphereandlower stratosphere.The discussionthat follows will fo-

cuson the standardCAM3 configurationthat usesa 26-level 85-wave triangularspectral

truncation(T85L26). This truncationtranslatesto a 1.4�transformgrid ( � 150 km near

theequator)on which non-linearandparameterizedphysicstermsareevaluated.This re-

flectsa four-fold increasein thenumberof horizontaldegreesof freedomwhencompared

to earliermodels(Hack et al. 1994;Kiehl et al. 1998;Kiehl andGent2003). A 22-year

5-memberensembleusingobservedseasurfacetemperaturesandobservedseaice is used

to characterizethemeanfeaturesof thesimulatedhydrologicalcycle in theuncoupledcon-

figuration.Thesesimulationcharacteristicsarethencontrastedwith simulationproperties

obtainedfrom thefully-coupledCCSM3.

Therearea largenumberof observationaldatasetsrelatedto Earth’s hydrologicalcy-

cle. The datasetswe will use include the 40-yearreanalysisproductERA40 from the

EuropeanCenterfor MediumRangeWeatherForecasting(ECMWF).Thearchiveconsists

of monthly meandataon 23 pressurelevels in the vertical at 2.5 degreeresolution. The

dataareregriddedto T42spectralresolutionfor our analysis.TheNimbus-7CloudMatrix

total clouddataarederived from the TemperatureHumidity InfraredRadiometer(THIR)

andTotalOzoneMappingSpectrometer(TOMS)measurementsfor theperiodApril 1979-

March1985.Retrieval algorithmsaredescribedin detail in Stowe et al. (1988)andStowe

et al. (1989). The Global PrecipitationClimatologyProject(GPCP)Version-2Monthly

PreciptationAnalysisis a globalprecipitationdataseton a 2.5degreegrid extendingfrom

1979-2003(Adler et al. 2003). It is a merged datasetconsistingof satellitemicrowave

andinfrareddataandsurfacerain gaugedata.TheCPCMergedAnalysisof Precipitation

(CMAP) is aglobalmonthlyprecipitationdatasetona2.5degreegrid, coveringtheperiod

5

1979-1998(Xie andArkin 1997). The NationalAeronauticsandSpaceAdministration

WaterVaporProjectglobal watervapordataset(NVAP) is a watervaporand liquid wa-

ter patharchive at 1 degreeresolutionthat extendsfrom 1988-1999(Randelet al. 1996).

The blendedanalysisincludessatelliteretrievals of watervaporfrom the Television and

InfraredOperationalSatellite(TIROS) OperationalVerticalSounder(TOVS), theSpecial

SensorMicrowave/Imager(SSMI), aswell asradiosondemeasurements.The SSMI col-

umnwatervaporandcloudliquid waterarederivedfrom satellitemicrowave radiometers

asdescribedin WentzandSpencer(1998). The MODIS total columnwatervaporprod-

uct wasobtainedfrom near-IR andIR algorithms,whilecloudliquid waterpathis derived,

alongwith a numberof physicalandradiativecloudproperties,usingIR andvisible algo-

rithms(King etal. 2003).WeusetheISCCPD2 griddedcloudproductdatafor totalcloud.

This is a monthlymean,globaldatasetonanequalareagrid (Rossow andDuenas2004).

2. Mean-StateSimulation Properties: UncoupledConfigu-

ration

a. GlobalMeanProperties:

We begin our discussionof thesimulatedhydrologicalcycle by examiningtheglobalan-

nualbudgetof waterin theCAM3 usingaa22-year5-memberensembledescribedearlier.

The land surfacein thesesimulationsis fully interactive. The simulatedglobal annual

precipitationrate of 2.86 mm/day is approximately7% larger than the CMAP satellite

estimate. We also note that the magnitudeof the hydrologicalcycle, as definedby the

global annualprecipitationrate, is slightly more than8% weaker than in the previously

documentedatmosphericmodelin this series(Hacket al. 1998).Thereductionin thehy-

drologicalcycle is largely attributableto significantchangesin thesurfaceenergy budget

6

associatedwith the introductionof specifiedatmosphericaerosols,andwill be discussed

elsewherein this specialissue. Figure 1 shows the breakdown of the precipitationand

evaporationexchangesof waterin absolutetermsbetweentheatmosphereandland,ocean,

and seaice surfaces,along with runoff from the land and ice to the oceans(definedas

thedifferencebetweenprecipitationandevaporation).Therelative distribution of surface

exchangeis remarkablysimilar to renormalizedobservationalestimates(e.g.,Peixotoand

Oort 1992).Theobservationalestimatesof precipitation,evaporation,andrunoff, arenor-

malizedby theCAM3 simulatedannualglobalprecipitationrate,andshow thatall terms

in thesurfaceexchangesgenerallyagreeto within a few percentof therelativepartitioning

containedin theobservationalestimate.

Figure1 alsoshows the time averagedstorageof waterin theatmospherein all three

phasesassimulatedby theCAM3, alongwith estimatesof watervapor(i.e., precipitable

water)andcloud liquid waterretrievedfrom MODIS. We have usedMODIS estimatesin

this comparisonbecausetheseretrievalsprovide themostcomprehensive globalcoverage

of cloud liquid water, but not necessarilythemostdefinitive retrievalsof precipitableand

cloud liquid water. The total reservoir of water in its frozen, liquid, and vapor stateis

brokendown by its distributionover land,oceanandice. Fromthisperspective,theCAM3

doesa reasonablejob of simulatingthe distribution of waterwith regardto surfacetype.

Sincethesenumbersarestronglyweightedby the fractionalareasof ocean,landandsea

ice, it’ s no surprisethat thelargestfractionfor eachphaseresidesover theoceans.Figure

1 suggeststhattheCAM3 generallyoverestimatesprecipitablewater, overestimatescloud

liquid waterover theoceans,andunderestimatescloudliquid waterover landandseaice.

Anotherway to look at the distribution of water, andits exchangewith the surface,is to

quantifytheaveragepropertiesfor eachof thethreeunderlyingsurfaces,asshown in Tables

1 and2.

7

Table1 shows precipitationandevaporationdatafor the CAM3, evaporationdatafor

the ERA40 reanalysis,andprecipitationdatafrom the CMAP climatology. We have not

includedERA40 precipitationestimatesbecauseof known spin-upproblemsin the anal-

ysis of precipitation(SakariUppala,personalcommunication).The evaporationsideof

thewaterbudget,however, doesnot suffer asmuchfrom hydrologicalspin-upproblems,

andcompareswell with the da Silva et al. (1994)climatology(Anton Beljaars,personal

communication).CMAP providesonly onesideof thewaterbudget,but providesa useful

quasi-independentmeasureof themagnitudeof thehydrologicalcycle,andthedistribution

of precipitationacrosssurfacetypes.To someextent,thedisagreementsin theseestimates

helpillustratecontinuinguncertaintyin quantifyingthemagnitudeof Earth’s hydrological

cycle,evenon long time scales.Althoughthemagnitudeof theCAM3 hydrologicalcycle

is largerthantheCMAP estimateusingglobalannualprecipitationasthemeasure,it bears

amuchcloserrelationshipto thereanalysisif weuseglobalannualevaporationasthemea-

sure. In a relative senseprecipitationratesaregreaterover landandseaice in theCAM3

whencomparedto oceanicratesusingCMAP estimatesasthereferenceobservation.

Thecomponentsof waterstoragein theatmospherearegenerallydifficult quantitiesto

observe on globalscales.Much of this datacomesfrom satelliteretrievals,oftenblended

with in-situ and/oranalysisdata,and is most often limited to vertical integrals of pre-

cipitable water and cloud water. Table 2 shows the simulatedprecipitablewater, cloud

liquid water, andcloud ice waterby surfacetype for the CAM3, alongwith comparable

estimatesfrom NVAP, MODIS, andERA40. Onecanseethat thereareconsiderabledif-

ferencesbetweenthe variousobservationalestimates,which areof similar magnitudeto

differenceswith the CAM3. Generallyspeaking,theCAM3 appearsto agreereasonably

well with NVAP andERA40estimatesof precipitablewater, whichareslightly higherthan

theMODIS retrievals. Cloud liquid waterover theoceansis higherin CAM3 thanany of

8

theestimates,but falls betweentheERA40andMODIS valuesoverbothlandandseaice.

b. ZonalMeanProperties:

The zonally averagedseasonalandannualdistribution of precipitationfor the CAM3 is

shown in Figure2 in comparisonwith precipitationestimatesfrom CMAP. In mostrespects

the CAM3 exhibits similar biasesto thoseseenin the CCM3 simulation. The amplitude

of the tropical precipitationin the Inter-Tropical ConvergenceZone(ITCZ) is generally

well captured,althoughthereis a slightly moreexaggerateddouble-ITCZthanin CCM3,

mostnotablyduring DJF. The simulatedlocationof the DJF ITCZ maximum,morethan

10�northof theanalyzedCMAP maximumillustratesa majorproblemwith therepresen-

tation of tropical precipitation,which is the persistenceof ITCZ-like precipitationin the

NorthernHemisphereyearround.This is in contrastto theobservationalestimates,which

show a clearseasonalmigrationof ITCZ precipitationacrosstheequator. Subtropicalpre-

cipitationminimaaregenerallydisplacedtoo far polewardseasonallyandannually, asare

thesecondaryprecipitationmaximain theextratropicalstormtracks.Thepolewardshift of

theCAM3 SouthernHemispherestormtrackresultsin amodestpositiveprecipitationbias

whencomparedto thesatelliteretrievals.

Thezonallyaveragedseasonalandannualevaporationrateis shown in Figure3 for the

CAM3 andCCM3. CCM3is usedin thiscomparisonbecauseof problemswith identifying

a comparableglobalobservationaldataset,andto illustratethereductionin themagnitude

of the hydrologicalcycle betweenCCM3 andCAM3. Thesefiguresclearly show a sig-

nificant andsystematicreductionin the CAM3 evaporationrateswhencomparedto the

CCM3. This reductionin themagnitudeof thehydrologicalcycle is primarily associated

with the introductionof a climatologically-specifieddistribution of atmosphericaerosol

that producea significantreductionof absorbedsolar radiationat the surface. As was

9

thecasefor the CCM3 atmosphericmodel,themostvigoroustransferof waterto theat-

mosphereoccursin the subtropicswith evaporationratesreachingmaximumvaluesnear

15�N and15

�S. Consistentwith observationalanalyses,theSouthernHemisphereoceans

aretheprincipalsourceof waterpoweringtheatmospherichydrologiccycle in theCAM3.

The suppressionof evaporationin the vicinity of ITCZ convection is a realistic feature

of theCAM3 simulation,andis in goodagreementwith correspondingoceanicestimates

(e.g.,seeOberhuber1988;Kiehl andTrenberth1997;Doney etal. 1998;LargeandYeager

2004). We alsonotea substantialreductionin thesurfaceflux of waterto theatmosphere

poleward of 80�

N which introducesa large changein the waterbudgetover the Arctic

whencomparedto theCCM3.

The zonally averagedseasonalandannualnet surfaceexchangeof water,�����

, is

shown for CAM3 andCCM3 in Figure4, and is quantifiedin units of energy (where1

mm day��� 29.055Wm� ). TheCAM3 simulatesa strongseasonalmeridionaloscilla-

tion in thesourceregions,but a relatively weakseasonalmovementof theequatorialwater

sink. The weakmeridionalexcursionof the net watersink in the deeptropics is largely

attributableto theunrealisticallyweakseasonalmigrationof ITCZ precipitation.The re-

gions10�N – 40

�N and10

�S – 40

�S arewell definedsourceregionsof total water, where

the deeptropicsandhigh-latitudeextratropicsrepresentthe principal sinks. In most re-

spects,the CAM3 net waterbudgetbearsremarkablesimilarity to the CCM3, especially

consideringtherelatively largelocalchangesto theindividualcomponentsof thewaterex-

change.Thelargestchangesin�����

occuralongtheequator, andpolewardof 60�N. The

equatorialdifferencesarelargely a consequenceof reducedprecipitationrates,manifested

in the form of a strongerdoubleITCZ, particularlyapparentin the Indian Ocean. Over

the Arctic the evaporationdeficit is nearlytwice aslarge asin the CCM3, largely dueto

systematicreductionsin thesurfaceevaporationrate.

10

Thezonallyaveragedprecipitablewater, or verticalintegralof thespecifichumidity, is

shown in Figure5, alongwith theNVAP climatology. TheCAM3 is systematicallymoister

than the CCM3, and in betteragreementwith zonally-averagedobservational estimates

suchasNVAP. Thelargestbiasis presentyearroundnear30�N, exceeding4 kg m� (or 4

mm)overmostof theregionbetween10�and40

�N. As wewill show, theagreementin the

zonalmeandistributionof precipitablewateris theconsequenceof afortuitouscancellation

of errorsin thelongitudinaldistribution.

As mentionedearlier, cloudsprovide importantforcingson theclimatesystemthrough

their modulationof the radiative heatingfield. The climatologicaldistribution of cloud

and cloud condensateis thereforeworthy of somediscussion. The radiative effects of

the simulatedcloud field are discussedin Collins et al. (2005b),wherewe confinethis

discussionto the extent of cloudcover andthe simulatedliquid waterandice waterpath

lengths.

Theannuallyandzonallyaveragedmeridionaldistributionsof total cloudamountare

shown in Figure6 for CAM3, ISCCP, andNimbus7. TheCAM3 cloudfield is markedly

differentfrom theCCM3. Totalcloudcover in thetropicsandpolewardof theextratropical

stormtracksis significantlyreducedin theCAM3. This is dominatedby a sharpreduction

in highcloudovermostof theglobe,andreductionsin mid andlow-level cloudathigh lat-

itudes.Thereductionsin tropicalhighcloudarecompensatedby increasesin middle-level

cloud,wherelow level cloudhassystematicallyincreasedequatorwardof 60�N and60

�S.

The reductionin high cloud is moreconsistentwith ISCCPestimates,while the increase

in low level cloud amountis more consistentwith Warrenet al. (1988). Despitesome

improvementin thedistributionof simulatedcloudamount,importantbiasesin themerid-

ional distribution remainin CAM3. Oneof the moreobvious longstandingdeficiencies

is the locationof the minima in subtropicalcloud cover, near20�latitudein the observa-

11

tional record,but closerto 30�in the CAM3 simulation. This differencehasimportant

consequencesfor the radiative budgetof the subtropicswhere,for example,the tropical

shortwave cloud forcing is too broadandthereforetoo strongfor muchof thesubtropics.

Theradiativeissuesrelatedto theCAM3 simulationof cloudandcloudopticalpropertiesis

not thefocusof thismanuscript,but will bediscussedelsewhereusingtheISCCPsimulator

developedby Klein andJakob (1999)andWebbet al. (2001).

As notedin Table2, condensedwaterin theatmosphereis severalordersof magnitude

smallerthan storagein the vaporstate,and yet is of comparableclimate importancein

termsof modulatingtheglobal radiationbalance(e.g.,Wielicki et al. 1995;Kiehl 1994).

Zonallyandannually-averageddistributionsof liquid waterpathareshown in Figure7 for

theCAM3, andfor severalsatellite-derivedproducts.TheCAM3 exhibits sharplydefined

maximafor cloudliquid waterin thedeeptropicsandat 60�N and60

�S. Simulatedcloud

waterin thetropicsandsubtropicsagreesmostcloselywith theSSMI retrievalsof Wentz

andSpencer(1998),andrepresentsa � 30%overestimateof cloudwaterin theITCZ for

boththeMODIS andNVAP retrievals.Cloudwaterin theextratropicalstormtracksis ap-

proximatelytwice aslargeasin theITCZ, andapproximatelytwice aslargeasdiagnosed

by any of theavailableretrievals.Theoneexceptionis anew MODIS retrieval underdevel-

opmentby membersof theNASA CERESScienceTeam,whichshowshigh latitudecloud

liquid waterpathsof comparablemagnitudeto theCAM3 simulation(personalcommuni-

cation,P. Minnis). Unlike theCCM3,theseasonalbehavior of thesimulatedzonalaverage

of cloudliquid waterdoesnotshow astrongseasonaloscillationathigh latitudes.TheJJA

simulationshows thestrongestdeparturefrom theannualmeandistribution, with slightly

enhancedliquid waterpathsin theITCZ andNorthernHemispherehigh latitudes.Similar

enhancementsareseenin thevariousobservationalestimates,althoughtherelative biases

discussedearlierremain.

12

A quantityfor whichlittle in thewayof globallyobserveddataareavailableis icewater

path.Zonally, annually, andseasonallyaverageddistributionsof icewaterpathassimulated

by the CAM3 are shown in Figure 8. As is the casefor cloud liquid water, cloud ice

waterexhibits largedifferencesbetweenthetropicsandextratropics.SouthernHemisphere

extratropical ice water pathsare nearly three times as large as in the ITCZ, exceeding

40 gm m� . Unlike the liquid water distribution, ice water hasa very strongseasonal

cycleathighlatitudes,with maximumextratropicalvaluesoccuringin therespectivewinter

hemispheres.Thereis alsoamuchstrongerseasonalshift in cloudiceat low latitudeswith

greatertropical icewaterloadingduringBorealsummer.

c. Vertical Structure:

Temperatureandwatervaporarethetwo statevariablesthat jointly definethemoiststatic

stabilityof theatmosphere.Theability to properlysimulatetheverticaldistributionof wa-

ter vaporis stronglyconstrainedby biasesin thesimulatedtemperaturestructure.Figure

9 shows theCAM3 annualzonalaveragedifferencesof temperatureandspecifichumidity

from the ERA40 reanalysisclimatology. Overall, the CAM3 doesa relatively good job

of reproducingtheanalyzedthermalstructure.Simulatedtemperaturesarewithin 1�K to

2�K of theanalyzedfield for mostof thedomainboundedby 50

�N and50

�S.Overall, the

CAM3 temperaturesimulationrepresentsa modestimprovementover theCCM3. Tropi-

cal tropopauseerrorsarenearlyhalvedwhencomparedto CCM3,andhigh-latitudelower

tropospherictemperatureshave beensignificantlywarmed.A sizablepartof thewarming

changeis associatedwith theincreasedhorizontalresolution,mostnotablyin high-latitude

mid-to-uppertropospherictemperatures(seeHacket al. 2005). Improvementsto the for-

mulationof CAM3 cloudprocessesexplainstheremainingimprovementsto thetempera-

turesimulation,particularlyfor thelowertroposphereathigh-latitudes(Boville etal.2005).

13

Despitetheseimprovements,thedifficulty in properlysimulatingpolartropopausetemper-

aturesremains,a longstandingdocumentedproblemfor atmosphericgeneralcirculation

models(Boeret al. 1992).

Global observationaldataon the vertical distribution of water in the atmosphereare

notoriouslydifficult to find, whereanalysisproductsprovide thebestavailableestimates.

Atmosphericanalysescontinueto containuncertaintiesin the moisturefield (e.g.,Tren-

berthandGuillemot 1995),sincethe watervapordistribution continuesto dependupon

theparameterizedtreatmentof processesinvolvedin thehydrologicalcycle. Nevertheless,

comparisonof thereanalysisproductagainstlocally availableradiosondeobservationssug-

gestthat the vertical structureof the biasesshown in Figure9 arerobust. Thesezonally

averagedbiasesgenerallyshow a wetterthananalyzedatmospherethroughoutmostof the

domain. The major exceptionis the meridionally-broadlow-level dry biasbetween600

and900 mb in the tropics,exceeding1 gm kg� in the zonalannualmean. The overall

structureof thewatervaporbiasis similar to CCM3,but slightly exaggeratedin amplitude.

Preliminaryanalysesof this errorsuggestthat theverticalstructurein thetropics,suchas

thepositivewatervaporanomalyat500mb,is stronglydeterminedby theform of parame-

terizedmoistconvection.Evidencethattheselarge-scalebiasesarerealis shown in Figure

10,whichillustratesverticalprofilesof ��� andspecifichumidityoverYapIslandin thetrop-

ical westPacific duringthemonthof July. Thesefiguresshow how theERA40reanalysis

comparesto radiosondedata,andthat the lower troposphericdry biasandmid-to-upper

troposphericmoistbiasarerobustfeaturesof thesimulation.Thedry biasmaximizesnear

850mbreaching3 gm kg� . Watervaporbiasesof this magnitudeandstructurehave a

significantimpacton themoiststaticstability of thetropicalatmosphere,asis seenin the

��� profiles,andarelikely to play animportantrole in thelow latitudedynamicalresponse

to diabaticheating.

14

Thezonalaverageof thesimulatedverticaldistributionof condensateis shown in Fig-

ure 11. Thecolor shadedregionsshow liquid waterconcentration,andthecontouredre-

gionsshow ice waterconcentration.The locationof the freezinglevel is alsoshown for

reference.Most of the liquid watershown in Figure7 residesbelow 900 mb with con-

centrationsrangingfrom 0.05– 0.15 gm m�� in the zonalannualmean. The mid- and

high-latitudeextratropicsexhibit very strongvertical gradients,while the vertical distri-

bution in the deeptropicsis considerablymorediffuse. The cloud ice waterdistribution

generallyreachesit’ smaximumconcentrationseveralkm abovethefreezinglevel,between

500mb and600mb in theextratropicalstormtracksandnear300mb in thedeeptropics.

Maximumice waterconcentrationsreach0.007gm m�� and0.003gm m�� in therespec-

tivezonalannualextratropicalanddeeptropicalmeans.Thehighlatitudeseasonalswingin

ice waterpathis primarily determinedby changesin ice waterconcentrationin thelowest

kilometerof theatmospherein theNorthernHemisphere.TheSouthernHemispheresea-

sonalcycle is largelydeterminedby icewaterloadingchangesthroughoutthetroposphere.

Also, muchof thehigh latitudecloudcondensateconsistsof mixedphaseclouds,whereas

iceandliquid waterregimesaremoreclearlyseparatedin thetropics.

Finally, we illustratethe vertical structureof the meridionaltransportof watervapor

in Figure12. Meanmeridionalwater transportis shown in the left panels,andtransient

meridionalwater transportis shown in the right set of panels. As shown in Figure 4,

thedeeptropicsareasinkof moisture,thesubtropicsareasourceof moisture,andregions

polewardof 40�aresinksof moisture.As mightbeexpected,thetransportof waterfrom the

subtropicsinto thedeeptropicsis generallyconfinedto thelower1500� of theatmosphere

andlargely handledby themeanmeridionalcirculation.This transportexhibits thestrong

seasonalasymmetriesassociatedwith theHadley Circulation(Trenberthet al. 2000).The

majority of watervaportransportto higherlatitudesoccursover a slightly deeperportion

15

of the atmosphere,occurringlargely in the form of transienteddy transport. Although

muchweaker thantheequatorwardtransportby theHadley Circulation,a third of thetotal

poleward transportoccursin the indirect or FerrelCirculation. At higher latitudeseddy

transportstowardthepoledominatetransportby themeancirculation(PolarCell), which

actsto movewatervaporfrom thepolarregionsto lower latitudes.

d. HorizontalStructure:

In this section,we will examinethe horizontaldistribution of vertically integratedmea-

suresof water and surfacewater exchangein the CAM3. We begin with the annually

averagedprecipitationfield shown in Figure13. AlthoughtheCAM3 simulationcaptures

many of theobservedfeaturesin theglobalprecipitationdistribution, it continuesto share

many of thesamebiasesexhibitedby theCCM3. Mostof theavailableretrieval dataagree

that the mostserioussimulationerrorsoccur in the form of excessive precipitationover

the westernIndian Ocean,the centralsubtropicalPacific, and in the vicinity of Central

America. The CAM3 alsocontinuesto underestimatethe strengthof the Atlantic ITCZ.

Another longstandingsimulationdeficiency is a tendency for the simulatedtropical pre-

cipitationmaximato remainin theNorthernHemisphereyearround,andaslightly greater

tendency for reducedprecipitationalongtheequator, particularlyin theIndianOcean.This

is in sharpcontrastwith mostsatelliteestimates,which show aclearseasonalmigrationof

ITCZ precipitationacrosstheequator, includingtheIndianOcean.

The precipitationanomaliesin the westernIndian Oceanare relatedin part to defi-

cienciesin theZhang-McFarlaneclosureassumptions,a topicwhich hasbeenexploredby

several investigators(Xie andZhang2000;Zhang2003). Themostseriousmanifestation

of theseproblemsappearsin the form of excessive precipitationratesover the Arabian

Peninsuladuring the NorthernHemispheresummermonths. Other factorscontribute to

16

this biasthroughouttheyear, including the tendency to inaccuratelyshift precipitationto

the northernIndian Oceanduring the borealwinter, coupledwith an overactive anddis-

placedprecipitationregime to the westandnorthwestof Madagascarextendingfrom the

MozambiqueChannelinto theIndianOceaneastof Tanzania.Borealsummeralsoexhibits

anextremelyoveractive precipitationregime just northof theequatorand1000km to the

southwestof the Indian subcontinent.The excessive precipitationin the centralPacific

subtropicsis associatedwith two simulationchallenges.TheCAM3 continuesto havedif-

ficulty in properlypositioningtheSouthPacific ConvergenceZone(SPCZ),which is too

strongin amplitudeandtoo zonalin structure,not extendingfar enoughinto thesouthern

extratropics.TheSPCZalsohasa tendency to extendtoo far east,anothersymptomof the

tendency for themodelto producea doubleITCZ. ThenorthernPacific biasis associated

with a poorsimulationof thevery well definedprecipitationpatternthatextendsfrom the

SouthChinaSeathroughthePhilippineSeaandinto thetropicalequatorialPacific during

themonthsof July throughAugust.Thisprecipitationpatternis representedasa relatively

diffuseextensionof the southeastAsian Monsoonwell into the centralPacific subtrop-

ics, andis a longstandingprecipitationbiasin theCCM andCAM models.Othernotable

featuresof the precipitationdistribution is the inability to capturethe seasonalcycle of

precipitationoff thewestcoastof CentralAmerica,andweaker thananalyzedprecipitation

ratesalongtheextratropicalwesternboundarycurrents.Precipitationoverthelandsurfaces

generallytendsto beexcessive,especiallyover theCongo.Exceptionsincludelargeareas

over theAmazonBasin,andmuchof UnitedStateseastof thecontinentaldivide. Finally,

simulatedprecipitationratesin thehigh-latitudeextratropicalstormtrackregionscontinues

to beslightly higherthancurrentsatelliteretrievalssuggest.

The simulatedevaporationfield (not shown) illustratesthe importantrole playedby

the oceansurfaceasa sourceof watervaporto the atmosphericgeneralcirculation. As

17

suggestedby the zonal means,both the northernand southernoceanscontribute to the

evaporationof water vaporyear round,but with importantseasonallongitudinal migra-

tionsof evaporationcenters.Thesimulationexhibits a clearevaporationminimumin the

ITCZ yearround,with extensiveregionsof highevaporationin therespectivewinterhemi-

spheres.Borealwinter includesevaporationmaximaalongthewesternboundarycurrents

(theKuroshioandGulf Stream),theRedSea,theeasternBay of Bengalandeasternequa-

torial Pacific, all of which exceed10 mm day� ( � 290W m� ) in the3-monthseasonal

mean.Otherfeaturesincludemaximain thewesternsubtropicalPacific, thewesternequa-

torial Atlantic, andSouthernIndian Oceanwith evaporationrates � 6 mm day� ( � 175

W m� ). As was the casewith CCM3, broadregionsof evaporationarealsoseenover

muchof SouthAmericaandSouthernAfrica exceeding4 mmday� ( � 120W m� ) in the

seasonalaverage.During theBorealsummer, thewell definedevaporationcenterstransi-

tion to anextensiveregionof highevaporationacrossthesouthernoceans,with maximain

the SouthernIndianOceanandTropicalWestPacific. Evaporationmaximain the north-

ernPacific oceanmigrateeastwardto thevicinity of theHawaiianIslandswith maximum

evaporationratesof 6 mmday� . Theprincipalevaporationregimein theAtlantic migrates

into theSouthernHemisphere,andcontinentalevaporationmovesinto theNorthernHemi-

sphere,mostnotablyeasternNorth America, India, large portionsof eastandsoutheast

Asia,andsub-SaharanAfrica.

Together, the evaporationandprecipitationfields definethe propertiesof freshwater

exchangebetweentheatmosphereandEarth’s surface. Theannuallyaveragedhorizontal

distribution of�����

is shown in Figure14 for the CAM3. We notethat a comparable

globalobservationaldatasetdoesnotexist. Theprincipaltropicalprecipitationfeaturesare

clearlyvisible. Local waterdeficitsin the ITCZ generallyexceed4 mm day� in thean-

nualmean.TheeasternPacific subtropics,centralAtlantic subtropics,andsouthernIndian

18

Oceansubtropics,aretheprincipalsourcesof waterfor theatmosphere.TheCAM3 simu-

latesa largeseasonalcycle in�����

over muchof SouthAmerica,CentralandSouthern

Africa, India, andSoutheastAsia, mostly a reflectionof the seasonalmigrationof deep

convectionin responseto solar insolation. Similar seasonalvariability is seenover most

of Europeextendinginto CentralAsia,andover muchof North America.Most of Europe

anda largeportionof North Americacanbeclearlycharacterizedaswatersourceregions

duringJJA, andwatersink regionsduringDJF.

Thehorizontaldistribution of theannually-averagedprecipitablewater, andits differ-

encefrom the NVAP climatology, is shown in Figure15. To a large extent, the CAM3

doesaverygoodjob of capturingthestructureandcorrectmagnitudeof precipitablewater

in the atmosphere.Thereare,however, importantlarge-scalesystematicbiases,despite

exceptionallygoodagreementin thezonalmeanstructure.Thelongitudinallycompensat-

ing arrangementof thesebiasesis responsiblefor thegoodagreementin thezonalmean,

wheresomeof theseregional biasesare well correlatedwith biasesin the precipitation

distribution. Precipitablewateris generallyoverestimatedthroughoutmostof thePacific

basin,in the westernIndian Ocean,ArabianSea,andcentralAfrica. In sharpcontrast,

thesimulationexhibits a largespatially-coherentdry region stretchingfrom theAmericas,

acrosstheequatorialAtlantic, NorthernAfrica, andinto SouthernandSoutheastAsia. In

generalterms,thesimulationis systematicallydry over continentalregions,mostnotably

duringthewarmseason.Thesewatervaporbiasesarelocally significant,particularlyover

SaharanAfrica wherethey canexceed10mm,or oftenhalf of of theobservedprecipitable

water.

Figure16 shows theannualglobaldistribution of cloud liquid waterandcloud ice for

theCAM3 simulation.Theextratropicalstormtracks,featuresof thelow latitudetropical

circulation, suchas the subtropicalsubsidenceregimes,and continentaldeserts,are all

19

clearlyvisible in thecloudliquid waterfield. Theliquid waterpathfrequentlyexceeds200

gm m� in the stormtracks,in contrastwith many of the satellite-retrieved cloud liquid

waterclimatologies.Liquid waterloadingat low latitudesis generallyin betteragreement

with satellite-derivedvalues,althoughpathlengthsin thesubtropicalsubsidenceregimes

are considerablysmaller, particularly in the SouthernHemisphere.This is a surprising

featureof thesimulation,giventhegreaterthanobservedcloudradiative forcing of these

regionsin the simulation. Cloud ice sharesmany of the sameregional characteristicsas

cloud water. The tropical distribution is highly correlatedwith areasof deepconvective

activity, suchasovertheCongo,westernIndianOcean,TropicalWestPacific,andAmazon.

As suggestedby the zonal meansin Figure 8, significantly greaterice water loading is

foundathigh latitudesin thestormtrackregions,whereicewaterpathsarefrequentlywell

in excessof two timesthemaximumicewaterpathsseenin thetropics.

3. Low FrequencyForcedVariability: UncoupledConfigu-

ration

Theseasonalcycleandchangesto theequatorialSSTdistributionassociatedwith El Nino-

SouthernOscillation(ENSO)aretwo examplesof majormodesof low frequency variabil-

ity in the climatesystem.Theseareessentiallyforcedmodesof variability in uncoupled

integrationsof theCAM3, andprovideausefulbasisfor evaluatingthesimulatedlocaland

far-field responsesascomparedto observations.

The CMAP andGPCPanalysesof global precipitationprovide an observationalop-

portunity to quantitatively examinetheCAM3 simulatedprecipitationresponseto ENSO.

Figure17 is a Hovmoller plot of precipitationanomaliesasestimatedby CMAP averaged

over the deeptropics (averagedbetween10�N and 10

�S) and the CAM3 simulationof

20

precipitationfor the periodJanuary1979 throughDecember2000. The CMAP product

shows theevolution of strongpositiveandnegativeprecipitationanomaliesin responseto

the warm andcold phasesof the observed ENSOcycle. Generally, the CAM3 doesex-

tremelywell at capturingboth the structureandamplitudeof the anomalypatternin the

centralandeasternPacific. Theeastwardextensionof thewarmphaseanomaliesarewell

reproduced.Themostseriousdeficiency is in thesimulationof theanomalypatternin the

westernPacificandIndianOcean,which is muchmoreweaklyrepresentedthanobserved.

A secondway of examiningtheresponseof thehydrologicalcycle to ENSOis to ex-

plore the spatialpatternof the anomalyresponseassociatedwith the time averagedpre-

cipitationdifferencebetweena specificwarmandcold event. This approachalsohasthe

advantageof amplifying the responseto the ENSOcycle. Figure18 shows the monthly

averagedprecipitationdifferencebetweenJuly 1994 (warm phase)andJune1999 (cold

phase)asanalyzedby GPCPandassimulatedby CAM3. Both panelsshow a very large

positive precipitationanomalystretchingacrossthe centralequatorialPacific flanked by

negative anomaliesto the north, west, andsouth(in the SPCZ).The CAM3 simulation

doesa very goodjob of representingthestructureandamplitudeof thepositive anomaly.

Thestructureandmagnitudeof thenegative anomalyresponseis not aswell represented,

particularly in the westernequatorialPacific andeasternequatorialPacific. The western

Pacific anomalyis too strongimmediatelynorth of the equatorand too weak along the

equator. This responsepatternis consistentwith the time-dependentresponseshown in

theFigure17 Hovmoller diagram.Nevertheless,theCAM3 simulationdoesa remarkably

goodjob of capturingtheoverall patternandamplitudeof theresponse,includingthefar-

field responseseenin theAtlantic andtheWesternIndianOcean.An importantexception

is therainfall anomalyover theAmazonbasin,which is veryweaklyrepresented.

Finally, weexaminetheability of theCAM to simulatetheseasonalmigrationof water

21

vaporbetweentheNorthernandSouthernHemispheres,which representsa regularmajor

meridionalredistribution of massin theatmosphere,andhasanimpacton Earth’s angular

momentumbudget(e.g.,Lejenaset al. 1997).As seenin thezonalmeansof Figure5, the

CAM3 correctlysimulatesa strongseasonalmeridionalmigrationof precipitablewater.

Figure19showsthisseasonalredistributionof watervaporby subtractingtheJJA distribu-

tion of precipitablewaterfrom theDJFdistribution. Despitethebiasesdiscussedearlier,

theseasonalredistribution of watervaporis well representedin theCAM3. Thestructure

of the seasonalresponseis very similar to the observed climatology, even on relatively

small spatialscales.Thereare large-scalesystematicbiases,suchasthe slightly weaker

seasonalcycle in the NorthernHemisphere,and slightly strongerseasonalcycle in the

SouthernHemisphere,thatleadto localdifferencesin amplitude.But thepropertiesof this

modeof variability aregenerallywell representedin theCAM3 simulation.Theseresults

demonstratethe ability of the CAM3’s hydrologicalcycle to respondto lower-frequency

externallyimposedforcing.

4. Mean-StateSimulation Properties: Coupled Configura-

tion

In this sectionweprovideanoverview of thehydrologicalcycleasrepresentedin CCSM3

coupledsimulations,whichemploy theCAM3 astheatmosphericcomponent.Wewill ex-

aminetheprincipaldifferencesin thehydrologicalcycle assimulatedby theatmosphere,

along with major featuresof the hydrologicalcycle asseenfrom the perspective of the

land,ocean,andseaicecomponentmodels.Thisdiscussionwill employ astandardCCSM

controlsimulationin which theatmosphereandlandmodelsarerepresentedon a T85L26

transformgrid, andtheoceanandsea-icemodelsmake useof a nominal1�horizontaldis-

22

cretization.TheT85x1configurationof thecoupledmodelis whathasbeenusedto doc-

umentthe CCSM3simulationsfor internationalclimate-changeassessments(seeCollins

et al. 2005a).

a. Atmosphere:

In anoverallsense,theCCSM3atmosphericglobalwaterandenergy cyclebudgetremains

remarkablysimilar to the uncoupledCAM3 simulation. The top of atmosphereenergy

budgetremainswithin 0.2 Wm� , while the individual componentsof thesurfaceenergy

balanceremainwell within 1 Wm� in the global annualmean. The global cycling of

waterin theCCSM3atmosphereis nearlyidenticalto thecharacterizationshown in Figure

1 for theuncoupledmodel. Themagnitudeof theglobalhydrologicalcycle is reducedby

approximately1%, primarily dueto a reductionin the magnitudeof the waterexchange

over landandseaice,but with comparablelevelsof runoff. Globalannualstorageof water

vaporandcondensatein the atmospherealso remainswell within 1% of the uncoupled

controlsimulation.Seasonally, thesedifferencesin measuresof theglobalwatercyclevary

only slightly morethanin their annualmeans.

Althoughglobalannualmeasuresof thehydrologicalcycle arevirtually identical,the

detailedregional behavior of the simulatedhydrologicalcycle in coupledmodeincludes

somenotabledifferences.Theseanomaliescanbe seenin the zonalmeanquantitiesre-

lated to the exchangeandstorageof water in the atmosphere(seeFigs. 2, 3, 4, and5).

Thereis a remarkableshift in thesurfaceexchangeof waterfrom theNorthernto South-

ernHemispheretropicsin thecoupledmodel.NorthernHemispheretropicalprecipitation

ratesarereducedby 1 mm/dayin thezonalannualmean,andareenhancedby morethan

twicethisratenear10�S.Thismeridionalshift producesasignificantandunrealisticchange

to the freshwaterbudgetover the tropical oceans,mostnotablyduring the Borealwinter

23

(seeSection4b). Although precipitationanomaliesappearin both the Atlantic andPa-

cific basins,thezonalmeananomalyis dominatedby changesover thePacific. This takes

the form of an unrealisticenhancementof a southernandmorevigorousbranchof ITCZ

convectionextendingacrossthe Pacific basinfrom the warm pool to the Equadorcoast

(seeFig. 20). Thechangeto theprecipitationdistribution is symptomaticof theso-called

double-ITZCproblemthatplaguesmany coupledmodels(e.g.,seeDavey etal.2002).De-

spitetheoverestimatedprecipitationratesin thesoutherntropicalPacificandsoutheastern

tropicalAtlantic, severalotherfeaturesin theprecipitationdistributionaresignificantlyim-

provedin thecoupledconfiguration.TheseincludeprecipitationoverCentralAmericaand

theCaribbean,alongthewesternmid-latitudeboundarycurrents,over theArabianPenin-

sula, and over the NorthernIndian Ocean. Precipitationreductionsin the north central

subtropicalPacific alsorepresentmodestimprovementswhencomparedto theuncoupled

simulation.

Changesin theprecipitationdistribution areassociatedwith similar shifts in thestor-

ageof waterin theatmosphere.Precipitablewatermovesfrom theNorthernto Southern

Hemisphereshowing a double-peaked tropical distribution in the zonal mean,which is

dominatedby anomaliesthatmaximizein DJF. Largepositiveanomaliesexceeding10mm

appearin the southcentraltropical Pacific andsoutheasterntropical Atlantic. Negative

anomaliesof similarmagnitudearelocatedovermuchof thetropicalandsubtropicalNorth-

ern Hemispherewith maximacenteredover the ArabianPeninsulaandCentralAmerica.

Generallyspeaking,changesto the precipitablewaterfield representadditionaldegrada-

tionsof thesimulationwhencomparedto observationalestimates.Thecloudcondensate

distribution reflectsthechangesto thedistribution of precipitationandprecipitablewater.

Cloudwaterandcloudicefollow theconvectivesourceregions,whichhavemigratedto the

southernoceans.Thesechangesto thehorizontaldistribution of waterstronglyimpactthe

24

energy budgetatboththetopof theatmosphereandsurface.Largelocalanomaliesareseen

in both clear-sky andall-sky radiative fluxesat the surfaceandat the top of atmosphere,

exceeding40Wm� for all-sky fluxes.Sinceprecipitationandradiativeprocessesareinte-

grally involvedin driving thetropicalcirculation,significantchangesto thelow level wind

field arealsoseenin the centralPacific andeasternAtlantic. Thesechangesgive rise to

differencesin themeridionalsurfacelatentandsensibleheattransfers,furtheraffectingthe

freshwaterandheatbudgetsover theoceans.

An exampleof CCSM3tropicalvariabilityof precipitationis shownin therightHovmoller

panelin Figure17. This shows muchweaker tropical variability than in the uncoupled

model. The responseis relatedto the strengthof CCSM simulatedENSOevents(asop-

posedto specifiedENSO eventsin the uncoupledsimulation),coupledwith the altered

dynamicalstructureof the deeptropics and a tendency for most of the precipitationto

occuraway theequator.

b. Ocean:

Oceantransportof freshwaterpreventsthedevelopmentof significantlocal trendsin ocean

salinitywheremeannetfreshwaterflux is stronglypositiveor negative. Netfreshwaterflux

is mainly a functionof precipitationandevaporationwhich have a geographicdistribution

determinedby large-scaleatmosphericcirculationslike the Hadley cells. The freshwater

forcingof theoceanis thuspredominatelyafunctionof latitude.Theocean’sprinciplerole

in the hydrologicalcycle of the climatesystemis to transportthe net positive freshwater

flux resultingfrom precipitationin the tropicsandhigh latitudestowardsthe midlatitude

evaporationzones.The oceanalsomovesfreshwaterpoleward from ice melting regions

to ice forming regionswheremeannet freshwaterflux is negative. Lastly, theoceanmust

redistributethelarge,highly-localizedinflux of freshwaterarisingfrom river runoff.

25

Netfreshwaterflux into theoceanasafunctionof latitudeis shown in Figure21,which

comparesthefully-coupledCCSM3control(T85x1)to astand-aloneoceanmodelsolution

(x1ocn)aswell asto anestimateof climatologicalfreshwaterflux (LY2004)derivedfrom

observedatmosphericandoceandatasetsspanning1984-2000,asdescribedin Largeand

Yeager(2004).Thex1ocnandLY2004curvestrackeachotherclosely, sincethey usethe

sameblendedprecipitationdataset.Themajordifferencebetweenthetwo is thattheformer

couplesobserved atmosphericstatefields spanning1958-2000to a fully evolving ocean

modelwhereasthelattercouplesthesamefieldsto anobservedSSTdataset.River runoff

fluxes from both computationsare identical and are basedon the climatologicalgauge

estimateschemeoutlinedin Large andYeager(2004). Thesecurvesarecharacterizedby

significantuncertainty, but neverthelessprovide somemeasureof real freshwaterfluxes,

with andwithoutpolarprocessesincluded,whichcanbecontrastedwith thecoupledmodel

solutionwheredeviationsarelarge.

In additionto differencesin SST, thex1ocnandLY2004curvesdeviateathighlatitudes

becausetheoceanmodelincorporatesice formationandicemeltflux algorithmsfor which

thereareno correspondingobservationaldatasets.Thus,at extremepolar latitudeswhere

theLY2004curve is missing,thex1ocnshows largenegative freshwaterfluxeswhereice

formationresultsin brine rejection. The x1ocnindicatesmorepositive freshwater input

thanLY2004nearice edgelatitudes( 65�S, 70

�N) wheremelting takesplace. As in the

uncoupledocean,T85x1 freshwaterflux is negative at high polar latitudes,andshows a

jumpto positiveneartheiceedgeto valueswhichexceedtheobservedflux estimate.Com-

paredto bothobservationally-basedbenchmarks,thereis excessivecoupledfreshwaterflux

to theoceanbetween����� � ��� � � andlessflux between�� �! � � ��� � , in bothhemispheres.

The SouthernHemisphereexcess(A) resultsprimarily from excessive precipitation(see

Fig. 22) togetherwith a moreequatorward peakin ice melt flux, which relatesto overly

26

extensiveicecoveragein theAtlantic andIndianoceansectorsof theSouthernOcean(Hol-

landet al. 2005).

Themidlatitudefreshwaterflux deficitnear30�S(B) arisesfrom a lackof coupledpre-

cipitationcomparedto observations(seeFig. 22)aswell asameanincreasein evaporative

flux over theselatitudes. The NorthernHemispherehigh latitudesarealsocharacterized

by someexcessive precipitationandmoreequatorward ice melt, but muchof the excess

freshwaterflux in thevicinity of 60�N (C) is dueto muchhigherthanobservedriver runoff

fluxesin the Arctic (seeSection4c). As in the South,thereis lesscoupledprecipitation

andmoreevaporationbetween�� �! � � ��� � N, resultingin a freshwaterflux deficit (D).

The freshwaterflux to the coupledoceanis mostunrealisticin the tropics,wherethe

doubleITCZ createsa spuriouspeakin zonalmeanprecipitationat � "#! � S. A peakin

T85x1 freshwater flux at the Equator(E) is relatedto colder SSTswhich generateless

evaporationin thePacific alongwith excessive precipitationin thewesternequatorialPa-

cific andIndianOcean.Thepositive flux biassouthof theequatorin Figure21 is further

exacerbatedby excessive runoff from the Congo. River runoff anomaliesare relatedto

precipitationanomaliesovercontinents,asdiscussedin section4c.

Thebiasesin T85x1zonalmeansurfacefreshwaterflux giveriseto biasesin themean

meridionaltransportof freshwaterby the ocean. In Figure22, the northward freshwater

transportsof thecoupledanduncoupledoceanmodels,computedfrom Eulerianmeanad-

vection,arecompared.Eddytransportsaremissingfrom thesecurves.Both modelsshow

polewardfreshwatertransportat high latitudesassociatedwith ice growth/meltprocesses.

While x1ocnshowssignificantfreshwatertransportsouthacrosstheEquator(about1/3 of

which occursin theAtlantic basin),theglobalzonalmeanfreshwatertransportacrossthe

Equatorin T85x1is verynearzero.In coupledCCSM3,thenegativefreshwaterflux zones

atsouthernmidlatitudes( �$"#! � � ��! � S)receive freshwatervia oceantransportfrom south-

27

ern high latitudesaswell as from the southerntropics,wherefreshwater input is higher

thanobservationalestimates.Sincetropicalprecipitationin natureis muchmoreasymmet-

ric aboutthe equatorthanit is in CCSM3(seeFig. 22), the x1ocntransportsfreshwater

southwardacrosstheequatorin eachoceanbasinin orderto compensatethesouthernmid-

latitudeevaporationzones.ThecoupledCCSM3oceantransportsaboutasmuchfreshwa-

ter northwardacrosstheequatorin theAtlantic asx1ocntransportssouthwardacrossthe

equator, andthereis muchlesstransportof freshwatersouthwardacrosstheequatorin the

Pacific.

Therewould appearto beanoverly robusthydrologicalcycle in theCCSM3in which

excessive midlatitudeevaporationin theSouthernHemisphereis relatedto excessive pre-

cipitation in thesoutherndeeptropicsaswell asin theSouthernOcean.Theoceanmust

thereforetransportmorefreshwaterpoleward from the tropicsthanis estimatedfrom ob-

servations,muchof it northward.Excessivehighnorthernlatituderiver runoff (section4c)

resultsin too muchfreshwatertransportsouthward to theextratropics.Theoriginsof the

biasedfreshwatercycle aredifficult to pinpoint, but areprobablyrelatedto the lack of a

dampingmechanismwhich would inhibit air-seafreshwaterexchangein wayscompara-

ble to heatexchange,whentheoceanbecomestoo freshor salty. SubtropicalSeaSurface

Salinity(SSS)andSeaSurfaceTemperature(SST)in thesoutharefresherandwarmerthan

observedin CCSM3LargeandDanabasoglu(2005).Thissuggeststhatexcesstropicalpre-

cipitation transportedto the subtropicsby the oceanrendersthe midlatitudeupperocean

toofreshandstable,thusinhibiting deepmixing whichwould lowertheSST. Anomalously

highSSTresultsin theenhancedevaporationrateswhich,afteratmospherictransportback

to the tropics, recursasexcessive precipitation. Processstudiesindicatethat, at leastin

the Atlantic, correctingthe westcoastoceanSSTbiasgreatlyreducesexcessive tropical

precipitationLargeandDanabasoglu(2005).

28

c. Land:

The hydrologicalbudgetover land in CCSM3is a balancebetweenprecipitation,evapo-

transpiration,runoff, andthechangein storagein soilsor snow. As seenin Table3, there

is no appreciablechangein storageduring the time period analyzedhere. Both annual

meanprecipitationandrunoff comparefavorablywith observations,with precipitationbe-

ing about3% high andrunoff about4% low if glaciersareincludedin themodelestimate,

and aboutright with glaciersexcluded. We note that observationsof runoff do not in-

cludemostof Greenlandandall of Antarctica.Estimatesof globalevapotranspirationare

not available. However, Brutsaert(1984),basedon a numberof estimates,proposesthat

evapotranspirationis about60-65%of precipitation. Simulatedevapotranspirationin the

CCSM3is 63%of precipitation.

Evaporationfrom thegroundis thelargestcomponentof evapotranspiration(59%)fol-

lowedby canopy evaporation(28%)andtranspiration(13%). Otherestimatesof thepar-

titioning of global evapotranspirationsuggestthat transpirationshouldbe the dominant

componentfollowedby groundevaporationandcanopy evaporation.In particular, Choud-

huryetal. (1998),usingaprocess-basedbiophysicalmodelof evaporationvalidatedagainst

field observations,foundthatthepartitioningwas52%(transpiration),28%(groundevap-

oration),and20%(canopy evaporation).Furthermore,sincephotosynthesisis coupledto

transpirationthroughstomatalconductance,theunderestimateof transpirationhasimplica-

tionsfor carbonassimilationin themodel.Globalphotosynthesisis about57 PgC, which

appearsto beabout50%low (Table3). Thedominantform of runoff in CCSM3is surface

runoff (52%of total runoff), followedby drainagefrom thesoil column(41%),andrunoff

from glaciers,lakes, and wetlands(7%). This latter runoff term is calculatedfrom the

residualof thewaterbalancefor thesesurfaces.This termmayalsobenon-zerofor other

surfacesaswell becausethesnow packis limited to a maximumsnow waterequivalentof

29

1000kg m� .Zonal annualaveragevaluesof the hydrologic cycle are shown in Figure 23. The

CCSM3 simulationoverestimatesprecipitationnorth of 45�N, generallyunderestimates

it in thenortherntropics,andoverestimatesit in southernSouthAmerica. The latitudinal

distribution of evaporationgenerallyfollows thatof precipitationwith a maximumin the

tropics.Generally, therunoff biasescoincidewith thoseof precipitationsuggestingthatim-

provementsin thesimulatedprecipitationmayleadto improvementsin therunoff. At high

latitudes,theprimaryactive hydrologicalcomponentis runoff. At otherlatitudes,ground

evaporationgenerallydominates.An exceptionto this is in the deeptropics (10S-10N)

wherecanopy evaporationis equallyimportant.Transpirationis thesmallestcomponentof

evaporationat all latitudes.

Total runoff from the landmodel is routedto the oceanusinga river transportmodel

(Olesonet al. 2004).Thus,biasesin runoff have thepotentialto affect seasurfacesalinity

andregional oceancirculation. The annualdischarge into the global oceanis shown in

Figure24. Total discharge is 1.33Sv. Discharge excluding Antarcticais about1.25Sv,

which is about6% higherthantheestimateof Dai andTrenberth(2002). Theriver trans-

port schemedoesnot accountfor lossof waterdueto humanwithdrawal or impoundment

of water, seepageinto groundwater, or evaporationfrom the river channel. In particular,

consumptionof water for irrigation may accountfor someof the discrepancy. Doll and

Siebert(2002)estimatenetandgrossglobalirrigation requirementsas0.035Svand0.078

Sv, respectively. The loss of freshwater from Antarcticais estimatedto be 0.07 Sv by

Vaughanet al. (1999),which is thesameasthat from CCSM3.However, this comparison

is fortuitousbecausethemajorityof Antarcticrunoff from CCSM3comesfrom thecapping

of snow over glaciers.More detailedglaciermodelsneedto beincorporatedinto CCSM3

to properlydescribeglacialprocessesincludingiceberg calvingandbasalmelting.

30

Clearly, therearenotabledeficienciesin themodeleddischargeat certainlatitudesthat

arisefrom thelandrunoff fields. In particular, dischargefrom theAmazonandtheCongo

is 42%low and109%high, respectively. Thedeficienciesin partitioningof evapotranspi-

ration describedpreviously areevident in the hydrologicalbudgetof the AmazonBasin

(not shown). The partitioningof annualevapotranspirationin the model is 49% canopy

evaporation,30%groundevaporation,and21%transpiration.As discussedin Dickinson

etal. (2005),toomuchwateris interceptedby thecanopy andre-evaporatedin thewetsea-

son,thusresultingin limited wateravailability for plantrootsparticularlyin thedry season.

Photosynthesisexhibits a significantdeclinein thedry season,which affectstheability of

the dynamicglobal vegetationmodelto correctlysimulatethe compositionof vegetation

in this region (Levis andBonan2005). The year-roundwarm bias in this region that is

pronouncedin thedry seasonis furtherconfirmationthatthesimulationis deficient.

While improvementsin theprecipitationfield suppliedby theatmospheremodelwould

likely improvethelandhydrologicsimulationin theAmazonBasinandglobally, thereare

clearly aspectsof the land hydrology that requireattention. Currentresearchis focused

on improving the sunlit/shadedtreatmentof photosynthesis,stomatalconductance,and

transpiration,andtheparameterizationof canopy interception.

d. SeaIce:

As icegrows from seawater, it rejectssaltbackto theocean,resultingin a relatively fresh

ice cover with approximately4ppt salinity. If ice dynamicsis excludedandequilibrium

climateconditionsareconsidered,thelocal icegrowth is balancedby local icemeltandthe

netlong-termmeanseaicefreshwaterflux to theoceanis zero.Evenunderthermodynamic

only conditionshowever, theconsiderableseasonalcycle of the ice/oceanfreshwaterflux

canmodify theoceanbuoyancy forcingandinfluenceoceanmixing. Whenseaicedynam-

31

icsareconsidered,thetransportof relatively freshseaiceredistributeswaterin thesystem,

influencingtheglobalhydrologicalcycle. This hasthepotentialto modify the largescale

oceancirculationin both the southern(e.g.,GoosseandFichefet1999)andthe northern

(e.g.,Hollandet al. 2001)hemispheres.

In the SouthernHemispherethereis net seaice growth alongthe Antarctic continent

which is thentransportedequatorward. Figure25 shows the annualmeanmeridionalice

transportsimulatedby theCCSM3control integration.As theseaice hasonly 4pptsalin-

ity, this ice volumetransportis nearlyequivalentto a freshwatertransport.The transport

reachesa maximumof approximately0.25Sv at 65S.Estimatesderivedfrom satelliteice

motionobservationsandsparseice thicknessobservations(Weatherlyet al. 1998)suggest

a maximumvaluebetween0.05and0.1Sv. Comparedto theseestimates,theCCSM3has

excessive meridionalice transportin the SouthernHemisphere.The CCSM3 simulated

southernhemisphereice motion comparesquite well to observed estimates(not shown).

However, the ice thicknessis excessive, particularly in the Weddell Sea(Holland et al.

2005),resultingin thehigh meridionaltransport.This excessive ice transportandmelting

alongthe ice edge,modifiestheoceanseasurfacesalinity conditions,resultingin a fresh

biasalongtheAntarcticseaiceedgein thesouth-westernAtlantic.

In CCSM3,thelong-termaveragefreshwaterstoragein Antarcticseaiceequals15,630

km� . This correspondsto anannualaverageareaof 12 million km with anaveragethick-

nessof approximately1.4m anda salinity of 4ppt. As discussedin Hollandet al. (2005),

the simulatedareaof Antarctic seaice is large comparedto observations,which have an

annualaverageof approximately9-10million km .In theNorthernHemisphere,thereis netseaicegrowth in theArctic basin,resultingin

anetlossof waterfrom theArctic ocean.TheArctic ice is transportedby windsandocean

currentsand entersthe north Atlantic throughFram Strait. This provides an important

32

sourceof freshwater to the Greenland-Iceland-Norwegian seasand hasthe potential to

influenceoceanicdeepwater formation in this region (e.g., Holland et al. 2001). The

annualmeanflux of seaice throughFramStraitin theCCSM3T85-gx1controlintegration

is 0.08Sv. This agreeswell with theobservedestimateof 0.09Sv givenby Vinje (2001).

The flux hasa considerableannualcycle (Fig. 26) reachinga maximumvalueof almost

0.12Sv in late winter whenthe ice thicknessis at a maximumandthe windsareat their

strongest.As theicevolumeflux dependsonboththethicknessandvelocityof theseaice,

thegoodagreementwith observationssuggeststhatbothof thesepropertiesarereasonably

simulated.Thisdoesappearto bethecase,asdiscussedfurtherin Hollandetal. (2005)and

DeWeaver andBitz (2005). On the long-termaverage,the northernhemisphereCCSM3

seaicecovers10million km with ameanthicknessof approximately2 m. Accountingfor

theicesalinity, this representsa freshwaterstorageof 18,450km� .

5. Summary

We have presentedselectedfeaturesof the simulatedhydrologicalcycle for the CCSM3

CAM3 for bothcoupledanduncoupledapplicationsof themodel. TheCAM3 exhibits a

weaker hydrologicalcycle whencomparedwith predecessormodels,andcloserin mag-

nitudeto observationalestimates.Therelative distribution of surfacewaterexchangeand

atmosphericwaterstorageby surfacetype is in goodagreementwith observationalesti-

mates.Major precipitationandevaporationfeaturesaregenerallywell captured.

Although many featuresof water in the climate systemare well reproducedby the

CAM3, the modelcontinuesto exhibit several importantlongstandingsystematicbiases.

Thelongitudinaldistributionof precipitablewater, andits verticaldistribution,remaintwo

significantexamplesof thesedeficiencies.Biasesin theverticaldistribution of waterap-

pearsto bestronglylinkedto theparameterizedtreatmentof moistconvection.Thelarge-

33

scalelongitudinalanomaliesin precipitablewateraremuchmoredifficult to understand

andwill requireamorecomprehensiveanalysisof thewatervaporbudget.

Perhapsthe mostimportantweaknessin the simulationis the tendency for CAM3 to

form double-ITCZstructuresin thedeeptropics,andto inadequatelysimulatetheseasonal

meridionalmigrationof tropical precipitation.This simulationchallengeaffectsmostat-

mosphericgeneralcirculationmodelsatsomelevel,andis of particularimportancebecause

theerroris amplifiedwhentheatmosphereis coupledto afully interactiveocean.Givenits

importanceto thecoupledsimulation,identifying thereasonsfor thedouble-ITCZbiasis

likely to bethehighestpriority simulationchallengethatneedsto beaddressedin thenext

generationof theCCSMCAM.

Acknowledgement We would like to acknowledgethe substantialcontributions to the

CCSMprojectfrom theNationalScienceFoundation(NSF),Departmentof Energy (DOE),

theNationalOceanicandAtmosphericAdministration,andtheNationalAeronauticsand

SpaceAdministration.In particular, Hack,Truesdale,andCaronwishto acknowledgesup-

port from theDOE ClimateChangePredictionProgram,andNCAR WaterCycleAcross

ScalesInitiative.

This studyis basedon modelintegrationsperformedby NCAR andCRIEPIwith sup-

portandfacilitiesprovidedby NSF, DOE,MEXT, andESC/JAMSTEC.

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List of Tables

1 AnnualAveragePrecipitationandEvaporationRatesbySurfaceType(mm/day)

45

2 AnnualAverageStorageof Vapor, CloudWater, andCloudIce by Surface

Type(mm) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

3 Annualaveragesof global land precipitation(�

), evapotranspiration(�

),

andrunoff ( ' ) (mm day-1). Thecomponentsof�

aretranspiration(�)(

),

evaporationof canopy interceptedwater(��*

), andgroundevaporation(�)+

).

Thecomponentsof runoff aresurfacerunoff ( '-, ), drainagefrom thesoil

column ( '-. ), and runoff from glaciers,wetlands,and lakes and snow-

cappedsurfaces( '-/�021 ) (mm day-1). Photosynthesis(�43

) hasunits of

PgC. Observationsfor�

arefrom Willmott andMatsuura(2001), ' from

Feketeet al. (1999),and�43

from Schlesinger(1991). Glaciersin Green-

land andAntarcticaare includedin the model runoff. The observations

have no dataover theseregions. ExcludingGreenlandandAntarcticain

themodel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Table1: AnnualAveragePrecipitationandEvaporationRatesby SurfaceType(mm/day)

Ocean Land SeaIce Global

P E P E P E P E

CAM3 3.22 3.61 2.26 1.48 1.37 0.43 2.87 2.87

CMAP 3.11 —- 1.93 —- 1.10 —- 2.68 —-

ERA40 —- 3.58 —- 1.49 —- 0.41 —- 2.84

Table2: AnnualAverageStorageof Vapor, CloudWater, andCloud Ice by SurfaceType

(mm)

Ocean Land SeaIce

Vapor Liq. Ice Vapor Liq. Ice Vapor Liq. Ice

CAM3 27.92 .1270 .0191 18.29 .1055 .0199 6.40 .1530 .0334

MODIS 26.59 .0982 —– 15.64 .1311 —– 4.45 .2017 —–

NVAP 25.65 .1127 —– 20.15 —– —– 5.96 —– —–

ERA40 28.27 .1170 .0358 19.77 .0718 .0339 5.84 .0274 .0470

Table 3: Annual averagesof global land precipitation(�

), evapotranspiration(�

), and

runoff ( ' ) (mmday-1).Thecomponentsof�

aretranspiration(�)(

), evaporationof canopy

interceptedwater(�)*

), andgroundevaporation(��+

). Thecomponentsof runoff aresurface

runoff ( '-, ), drainagefrom thesoil column( '5. ), andrunoff from glaciers,wetlands,and

lakesandsnow-cappedsurfaces( '-/�021 ) (mmday-1).Photosynthesis(�23

) hasunitsof Pg

C.Observationsfor�

arefrom Willmott andMatsuura(2001), ' from Feketeetal. (1999),

and�43

from Schlesinger(1991). Glaciersin GreenlandandAntarcticaareincludedin

themodelrunoff. Theobservationshavenodataovertheseregions. ExcludingGreenland

andAntarcticain themodel.

� � �)( ��* ��+ '6 '-, '5. '-/�021 '- �23CCSM3 2.12 1.33 0.18 0.37 0.78 0.79 0.41 0.32 0.06 0.82 57.2

Observed 2.06 —- —- —- —- 0.82 —- —- —- 0.82 120

List of Figures

1 SimulatedGlobal WaterBudget. Storagetermsare in mm andexchange

ratesare in mm/day. Quantitiesin [ ] arederived from MODIS, while

quantitiesin ( ) area renormalizedversionof theglobalwatercycle de-

scribedin PeixotoandOort (1992). . . . . . . . . . . . . . . . . . . . . . 51

2 Zonally-averagedAnnual, DJF, andJJA precipitationrate in mm/dayfor

CAM3, CCSM3,andCMAP. . . . . . . . . . . . . . . . . . . . . . . . . . 52

3 Zonally-averagedAnnual, DJF, and JJA evaporationrate in mm/dayfor

CAM3, CCSM3,andCCM3. . . . . . . . . . . . . . . . . . . . . . . . . . 53

4 Zonally-averagedAnnual,DJF, andJJA netsurfacewaterflux 7 �8���69 in

:<; � for CAM3 andCCSM3.. . . . . . . . . . . . . . . . . . . . . . . . 54

5 Zonally-averagedAnnual, DJF, andJJA PrecipitableWater in =?> ; �@ for

CAM3, CCSM3,andNVAP. . . . . . . . . . . . . . . . . . . . . . . . . . 55

6 Zonally-averagedtotalcloudfractionfor CAM3 comparedwith ISCPPand

Nimbus7. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

7 Zonally-averaged,ocean-onlycloud liquid waterpath(LWP) in > ; � for

CAM3, CCSM3,MODIS, SSMI,andNVAP. . . . . . . . . . . . . . . . . 57

8 Zonally-averagedAnnual, DJF, and JJA cloud ice water path (IWP) in

> ; �@ for CAM3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

9 Zonally-averagedannualmeantemperatureandspecifichumidity differ-

encesbetweenCAM3 andERA40. . . . . . . . . . . . . . . . . . . . . . . 59

10 Profilesof equivalentpotentialtemperatureandspecifichumidityfor CAM3,

ERA40,andRAOBSatYapIsland( ACBD�FEHGJI�"#K�LCBM"NE � ). . . . . . . . . . . . . 60

11 CAM3 zonally-averagedannualmeancloudliquid waterconcentration(color

countours),ice waterconcentration(black contours),with 273K freezing

level contour(red)for reference. . . . . . . . . . . . . . . . . . . . . . . . 61

12 Zonally-averagedAnnual,DJF, andJJA mean(left column)andtransient

(right column)meridionalmoisturetransportin >O� ; =P>�Q for CAM3. . . . 62

13 Annualmeanprecipitationin mm/dayfor CAM3 comparedwith CMAP. . . 63

14 Annual,DJF, andJJA netsurfacewaterflux 7 �R�R�69 in:<; �@ for CAM3. 64

15 Annualmeanprecipitablewaterin =?> ; �@ for CAM3 comparedwith NVAP. 65

16 Annualmeancloudicewaterpath(IWP)andcloudliquid waterpath(LWP)

in > ; � for CAM3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

17 Equatorial( "#! E 3S� "#! E G ) precipitationanomaliesfor CAM3, CMAP, and

CCSM3.TheCAM3 andCMAP periodincludes1979-2000,andtheCCSM3

is anarbitraryrepresentative22-yearperiodfrom thecontrolsimulation . . 67

18 Warm (July 1994)minuscold (June1999)event precipitationanomalies

for CAM3 andGPCP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

19 Amplitude of seasonalprecipitablewaterchangesin mm for CAM3 and

NVAP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

20 Annualmeanprecipitationin mm/dayfor CCSM3comparedwith CAM3. . 70

21 Net freshwaterflux for theCCSM3(T85x1),uncoupledoceanmodel(x1

ocn),andobservations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

22 GlobalandAtlantic Basinnorthwardfreshwatertransport. . . . . . . . . . 72

23 Zonally averagedannualmeanland valuesfrom CCSM3comparedwith

observations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73

24 Totalaccumulateddischargefrom A�! E G from landinto theoceans.. . . . . 74

25 Theannualmeanmeridionalicetransportin theSouthernHemispherefrom

CCSM3. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

26 Thesimulatedannualcycleof FramStraitseaice transportin Sv. . . . . . . 76

Figure1: SimulatedGlobal WaterBudget. Storagetermsarein mm andexchangerates

arein mm/day. Quantitiesin [ ] arederivedfrom MODIS, while quantitiesin ( ) area

renormalizedversionof theglobalwatercycledescribedin PeixotoandOort (1992).

Figure2: Zonally-averagedAnnual,DJF, andJJA precipitationratein mm/dayfor CAM3,

CCSM3,andCMAP.

Figure3: Zonally-averagedAnnual,DJF, andJJA evaporationratein mm/dayfor CAM3,

CCSM3,andCCM3.

Figure4: Zonally-averagedAnnual,DJF, andJJA netsurfacewaterflux 7 �T�T�69 in:<; �

for CAM3 andCCSM3.

Figure5: Zonally-averagedAnnual,DJF, andJJA PrecipitableWaterin =?> ; �@ for CAM3,

CCSM3,andNVAP.

Figure6: Zonally-averagedtotalcloudfractionfor CAM3 comparedwith ISCPPandNim-

bus7.

Figure7: Zonally-averaged,ocean-onlycloudliquid waterpath(LWP)in > ; �@ for CAM3,

CCSM3,MODIS, SSMI,andNVAP.

Figure8: Zonally-averagedAnnual,DJF, andJJA cloudice waterpath(IWP) in > ; �@ for

CAM3.

Figure 9: Zonally-averagedannualmeantemperatureand specifichumidity differences

betweenCAM3 andERA40.

Figure10: Profilesof equivalentpotentialtemperatureandspecifichumidity for CAM3,

ERA40,andRAOBSat YapIsland( A�BD� E GJIC"UK�LCBM" E � ).

Figure11: CAM3 zonally-averagedannualmeancloud liquid waterconcentration(color

countours),ice water concentration(black contours),with 273K freezing level contour

(red)for reference.

Figure12: Zonally-averagedAnnual,DJF, andJJA mean(left column)andtransient(right

column)meridionalmoisturetransportin >O� ; =?>�Q for CAM3.

Figure13: Annualmeanprecipitationin mm/dayfor CAM3 comparedwith CMAP.

Figure14: Annual,DJF, andJJA netsurfacewaterflux 7 �R�V�29 in:<; �@ for CAM3.

Figure15: Annualmeanprecipitablewaterin =?> ; �@ for CAM3 comparedwith NVAP.

Figure16: Annualmeancloudice waterpath(IWP) andcloudliquid waterpath(LWP) in

> ; �@ for CAM3.

Figure 17: Equatorial( "#!WE 3R� "U!WE#G ) precipitationanomaliesfor CAM3, CMAP, and

CCSM3. The CAM3 andCMAP period includes1979-2000,and the CCSM3 is an ar-

bitrary representative22-yearperiodfrom thecontrolsimulation

Figure18: Warm (July 1994)minuscold (June1999)event precipitationanomaliesfor

CAM3 andGPCP.

Figure19: Amplitudeof seasonalprecipitablewaterchangesin mmfor CAM3 andNVAP.

Figure20: Annualmeanprecipitationin mm/dayfor CCSM3comparedwith CAM3.

Figure21: Net freshwaterflux for theCCSM3(T85x1),uncoupledoceanmodel(x1 ocn),

andobservations.

Figure22: GlobalandAtlantic Basinnorthwardfreshwatertransport.

Figure23: Zonallyaveragedannualmeanlandvaluesfrom CCSM3comparedwith obser-

vations.

Figure24: Totalaccumulateddischargefrom A�!WEHG from landinto theoceans.

Figure25: The annualmeanmeridionalice transportin the SouthernHemispherefrom

CCSM3.

Figure26: Thesimulatedannualcycleof FramStraitseaice transportin Sv.