For JCLI CCSMSpecialIssue

The Community Climate System Model: CCSM3

William D. Collins���, Cecilia M. Bitz

�, Maurice L. Blackmon

�,

Gordon B. Bonan�, Christopher S. Bretherton

�, James A. Carton

�,

Ping Chang�, Scott C. Doney

�, James J. Hack

�,

Thomas B. Henderson�, Jeffrey T. Kiehl

�, William G. Large

�,

Daniel S. McKenna�, Benjamin D. Santer

�, and Richard D. Smith

�

�NationalCenterfor AtmosphericResearch,Boulder, Colorado80307

�Universityof Washington,Seattle,Washington98195

�Universityof Maryland,CollegePark,Maryland20742�

TexasA&M University, CollegeStation,Texas77843�

WoodsHole OceanographicInstitution,WoodsHole,Massachusetts02543�

LawrenceLivermoreNationalLaboratory, Livermore,California94551�

LosAlamosNationalLaboratory, LosAlamos,New Mexico 87545

NCAR, P.O.Box 3000,Boulder, CO.80307,email: wcollins@ucar.edu

1

Abstract

A new versionof theCommunityClimateSystemModel(CCSM)hasbeen

developedandreleasedto the climatecommunity. CCSM3is a coupledcli-

matemodelwith componentsrepresentingtheatmosphere,ocean,seaice,and

landsurfaceconnectedby a flux coupler. CCSM3is designedto producere-

alistic simulationsover a wide rangeof spatialresolutions,enablinginexpen-

sive simulationslasting several millennia or detailedstudiesof continental-

scaledynamics,variability, andclimatechange.This paperwill show results

from the configurationusedfor climate-changesimulationswith a T85 grid

for theatmosphereandlandandagrid with approximately1-degreeresolution

for the oceanand sea-ice. The new systemincorporatesseveral significant

improvementsin the physicalparameterizations.The enhancementsin the

modelphysicsaredesignedto reduceor eliminateseveral systematicbiases

in the meanclimateproducedby previous editionsof CCSM. Theseinclude

new treatmentsof cloudprocesses,aerosolradiative forcing, land-atmosphere

fluxes,oceanmixed-layerprocesses,andsea-icedynamics.Therearesignif-

icant improvementsin the sea-icethickness,polar radiationbudgets,tropical

sea-surfacetemperatures,andcloudradiativeeffects.CCSM3canproducesta-

ble climatesimulationsof millennial durationwithout ad hoc adjustmentsto

the fluxesexchangedamongthe componentmodels. Nonetheless,thereare

still systematicbiasesin the ocean-atmospherefluxesin coastalregionswest

of continents,thespectrumof ENSOvariability, thespatialdistributionof pre-

cipitation in the tropical oceans,andcontinentalprecipitationandsurfaceair

temperatures.Work is underwayto extendCCSMto amoreaccurateandcom-

prehensivemodelof theEarth’sclimatesystem.

2

1. Introduction

TheCommunityClimateSystemModel (CCSM) is a coupledmodelfor simulatingpast,

present,andfuture climates. In its presentform, CCSM consistsof four componentsfor

the atmosphere,ocean,seaice andland surfacelinked througha couplerthat exchanges

fluxesandstateinformationamongthesecomponents.It is developedandusedby aninter-

nationalcommunityof studentsandscientistsfrom universities,nationallaboratories,and

other institutions. Applicationsinclude studiesof interannualand interdecadalvariabil-

ity, simulationsof paleoclimateregimes,andprojectionsof future anthropogenicclimate

change. The most recentversion,CCSM3, was releasedto the climate communityon

23 June2004.Thecode,documentation,input datasets,andmodelsimulationsarefreely

availablefrom theCCSM (2004)website.This paperdescribessomeof themostimpor-

tantadvancesin modelphysicsanddynamics,improvementsin thesimulatedclimate,and

remainingscientificchallengesfor futuredevelopmentof CCSM.

CCSM3 is the third generationin an ongoing seriesof coupledmodelsdeveloped

throughinternationalcollaboration.The first generation,the ClimateSystemModel ver-

sion1 (CSM-1),wasreleasedin 1996(Boville andGent1998).Thismodelwasnoteworthy

sinceit did not requireadjustmentsto the fluxesexchangedamongthe physicalcompo-

nentsin orderto simulatestable,relatively drift-free climates.Thesecondgeneration,the

CommunityClimateSystemModel version2 (CCSM2),wasreleasedin 2002(Kiehl and

Gent2004). Theclimatesimulatedwith CCSM2exhibits several improvementsover the

climategeneratedfrom CSM1. CCSM2producesbettersimulationsof extratropicalsea

surfacetemperatures,bettertropical variability, andmorerealistic land surfacetempera-

tures.However, several importantdeficienciesprompteda new cycle of developmentthat

hasresultedin CCSM3. The main modelbiasesin CCSM2includea doubleITCZ and

extendedcold tongue;overestimationof winter landsurfacetemperatures;underestimation

3

of tropical tropopausetemperatures;erroneouscloud responseto SSTchanges;errorsin

theeastPacific surfaceenergy budget;andunderestimationof tropical variability. As we

will show, thenew modelhasreducedor eliminatedsomeof thesebiases.SinceCSM1and

CCSM2arecomparedin detailby Kiehl andGent(2004),thediscussionherewill address

the differencesin the model formulationsandclimatesimulationsbetweenCCSM2and

CCSM3.

This overview and many other papersin this issuewill focus on a configurationof

CCSM3with atmosphereandlandmodelsonEulerianspectralgridswith T85wavenumber

truncationandoceanandsea-icemodelsongridswith anominalequatorialresolutionof 1

degree(AppendixA). This configurationhasbeenappliedto simulationsfor international

climate-changeassessments.Lower-resolutionversionsof CCSMhavebeencreatedfor ap-

plicationsincludingrapidscientificdevelopment,simulationsof biogeochemicalprocesses

requiring multi-centurysimulationsfor equilibration,and studiesof deep-timepaleocli-

materegimes.Thesensitivity of thesimulatedclimateto modelresolutionis examinedin

detailby Hacketal. (2005),Yeageretal. (2005),Otto-Bliesneretal. (2005),andDeWeaver

andBitz (2005).

Basicfeaturesof the meanclimateandits stability arediscussedin this paper. Com-

prehensiveanalysesof thevariability andtransientbehavior of thesystemarepresentedin

Deseret al. (2005),Alexanderet al. (2005),Meehl et al. (2005),andGentet al. (2005).

Major improvementsin the componentmodelsareoutlinedin section2. More complete

descriptionsof theenhancementsin individualcomponentsaregivenelsewherein thisspe-

cial issue(e.g.,Collinsetal.2005b;Danabasogluetal.2005).Improvementsin theclimate

simulationandreductionsin systematicerrorsrelativeto CCSM2arediscussedin section3.

Thestability of themeanclimateandanalysisof seculartrendsin climateparametersare

presentedin section4. Someof themostsignificantchallengesfor improving thesimula-

4

tions in future versionsof CCSMarediscussedin section5. Plansfor further evaluation

anddevelopmentaresummarizedin section6.

2. Overview of CCSM3

TheCCSM3systemincludesnew versionsof all thecomponentmodels.Theatmosphereis

CAM version3.0(Collinsetal. 2004,2005b),thelandsurfaceis CLM version3.0(Oleson

et al. 2004;Dickinsonet al. 2005),theseaice is CSIM version5.0 (Brieglebet al. 2004),

andthe oceanis baseduponPOPversion1.4.3(Smith andGent2002). New featuresin

eachof thesecomponentsaredescribedbelow. Eachcomponentis designedto conserve

energy, mass,totalwater, andfreshwaterin concertwith theothercomponents.

a. Designfor multipleresolutionsandformulationsof atmosphericdynamics

CCSM3 hasbeendesignedto producesimulationswith reasonablefidelity over a wide

rangeof resolutionsand with a variety of atmosphericdynamicalframeworks. This is

accomplishedby introducingdependenceon resolutionanddynamicsin thetime stepand

twelveotheradjustableparametersin CAM3 (Collinsetal. 2004).Thoseparametersaffect

the physicsgoverningcloudsandprecipitationandthe biharmonicdiffusion coefficients

for temperature,vorticity, anddivergence. The parametervalueshave beenadjustedto

yield climatesimulationswith nearlybalancedtop-of-modelenergy budgetsandrealistic

zonal-meantop-of-atmospherecloudradiative forcing.

Thestandardversionof CAM3 is basedupontheEulerianspectraldynamicalcorewith

triangularspectraltruncationat 31, 42, and85 wavenumbers.Thezonalresolutionat the

equatorrangesfrom 3.75 to 1.41 for theT31 andT85 configurations.It is alsopossible

to integrateCCSM3with a finite-volumedynamicalcore(Lin andRood1996;Lin 2004)

5

at2 by 2.5-degreeresolution,althoughatpresentthisvariantof CCSM3is anexperimental

versionrequiring further refinement. The vertical dimensionis treatedusing 26 levels

with a hybrid terrain-following coordinate.Theverticalgrid transitionsfrom apuresigma

region in thelowestlayerthroughahybridsigma-pressureregion to apurepressureregion

above approximately83 mb. The landmodelis integratedon thesamehorizontalgrid as

the atmosphere,althougheachgrid box is further divided into a hierarchyof land units,

soil columns,andplant types.Therearetensub-surfacesoil layersin CLM3. Landunits

representthe largestspatialpatternsof subgridheterogeneityandincludeglaciers,lakes,

wetlands,urbanareas,andvegetatedregions.

The oceanmodelusesa dipole grid with a nominalhorizontalresolutionof 3 or 1 .

The semi-analyticgrids have the first pole locatedat the true SouthPoleandthe second

pole locatedover Greenland(Smith et al. 1995). The vertical dimensionis treatedusing

a depth( � ) coordinatewith 25 levels extendingto 4.75 km in the 3-degreeversionand

40 levelsextendingto 5.37km in the1-degreeversion. The 1-degreegrid has320zonal

pointsand384 meridionalpoints. The spacingof the grid points is 1.125degreesin the

zonaldirectionandroughly0.5degreesin themeridionaldirectionwith higherresolution

neartheequator. Thesea-icemodelis integratedon thesamehorizontalgrid astheocean

model.

The threestandardconfigurationsof CCSMcombinetheT31 CAM/CLM with the3

POP/CSIM,theT42CAM/CLM with the1 POP/CSIM,andtheT85CAM/CLM with the

1 POP/CSIM.For brevity, we will referto theseconfigurationsaslow (T31� 3), interme-

diate(T42� 1), andhigh (T85� 1) resolution,respectively. This focusof this paperis on

thehigh-resolutionconfiguration.To facilitateits application,themodelhasbeenported

to vectorsupercomputers,scalarsupercomputers,andLinux clusters.OnanIBM SP4sys-

tem, the low, intermediate,andhigh-resolutionconfigurationsrequire62, 292, and1146

6

CPUhoursto simulateoneyear. Furtherinformationon thecomputationalperformanceis

givenin Yeageret al. (2005).

b. Developmentof theatmospherecomponent

Thenew atmosphericmodelincludessignificantchangesto thedynamics,cloudandpre-

cipitation processes,radiationprocesses,and treatmentsof aerosols.The finite volume

dynamicalcore is now includedas a standardoption for integratingCAM (Boville and

Rasch2005). The tendency equationscanbe integratedwith eitherprocess-splitor time-

split formulationsof the numericaldifferenceapproximations(Williamson 2002). In the

process-splitformulation, the dynamicsandphysicstendenciesareboth calculatedfrom

the samepastmodelstate,while in the time-split formulation,the dynamicsandphysics

tendenciesarecalculatedsequentially. Theprocess-splitandtime-split representationare

usedfor theEulerianandfinite-volumedynamics,respectively. Thephysicsof cloudand

precipitationprocesseshasbeenmodified extensively (Boville et al. 2005). The modi-

ficationsincludeseparateprognostictreatmentsof liquid and ice condensate;advection,

detrainment,andsedimentationof cloudcondensate;andseparatetreatmentsof frozenand

liquid precipitation.Theradiationcodehasbeenupdatedwith a generalizedtreatmentof

cloudgeometricaloverlap(Collinsetal.2001)andnew parameterizationsfor thelongwave

andshortwave interactionswith watervapor(Collins et al. 2002a,2005a).Theprognostic

sulfur cycle developedby Barth et al. (2000)andRaschet al. (2000) for predictingsul-

fateaerosolsis now a standardoption for themodel. A prescribeddistribution of sulfate,

soil dust,carbonaceousspecies,andseasalt derived from a three-dimensionalassimila-

tion (Collins 2001;Raschet al. 2001)is usedto calculatethedirecteffectsof tropospheric

aerosolson the radiative fluxesandheatingrates(Collins et al. 2002b). The correspond-

ing effectsof stratosphericvolcanicaerosolsareparameterizedfollowing Ammannet al.

7

(2003).Indirecteffectsof aerosolsoncloudalbedoandcloudlifetime arenot incorporated

in CAM3.

c. Developmentof theoceancomponent

TheCCSM3oceanmodelhasimprovedphysicsandnumerics,andtheimplementationand

impactof themoreimportantof theseimprovementsarediscussedby Danabasogluet al.

(2005). The betternumericsincludea moreefficient solver for the barotropiccontinuity

equationthat improvesthescalabilityof themodelto largenumbersof processors.Also,

a shallow bias in the boundarylayer depthis substantiallyreducedusinga higherorder

(quadratic)interpolationschemein theK-profile Parameterization(KPP)of verticalmix-

ing. Improvementsin thephysicalbasisof KPPandtheintroductionof greaterconsistency

in thediscretizationhavebothproducedamodestdeepeningof theboundarylayer. Instead

of theuniform transmissionusedin CCSM2,theabsorptionof solarradiationin theupper

oceanvariesmonthly andspatiallybasedon in situ chlorophyll andsatelliteoceancolor

observations(Ohlmann2004).Themoreecologicallyproductivemid-latitude,coastal,and

equatorialoceansabsorbmore insolationnearthe surface,while subtropicaloceansare

moretransmissive. In anotherdeparturefrom previous generationsof CCSM,a parame-

terizationof doublediffusive mixing in the oceanis now includedby default in CCSM3

althoughits effectsarequitesmall (Danabasogluet al. 2005).Theair-seaturbulentfluxes

of momentum,heatandmoisturearenow computedusingthewind vectorrelative to the

oceansurfacecurrent.However, theeffectsof wind gustsarenot includedin theturbulent

fluxes.Theparameterizationsof wind gustsarestill quiteuncertain,andexperimentswith

someof theexisting treatmentssuggesttheeffectsarerelatively minor.

8

d. Developmentof thelandcomponent

Thenew landmodelis basedupona nestedsubgridhierarchyof scalesrepresentingland

units, soil or snow columns,andplant functionaltypes(Bonanet al. 2001;Olesonet al.

2004).CCSM3includestheeffectsof competitionfor wateramongplantfunctionaltypes

in its standardconfiguration.Oneof theprimaryobjectivesof thelanddevelopershasbeen

to reducethepositive continentaltemperaturebiasesduringborealwinter. Modifications

to therelationshipbetweensnow heightandfractionalsnow coverage,whichhaveasignif-

icant impacton land-surfacealbedos(Olesonet al. 2003),have beenconsideredbut have

not beenadoptedin CCSM3. Theformulationof thebiogeophysicshasbeenmodifiedto

increasethe sensibleandlatentheatfluxesover sparselyvegetatedsurfaces. In previous

versionsof CCSM,theturbulenttransfercoefficientbetweensoil andtheoverlyingcanopy

air hasbeensetto aconstantvaluefor densecanopies.Thenew formulationmakesthisco-

efficient dependenton canopy densitycharacterizedby leaf andstemareaindices(Oleson

etal. 2004).Thetransfercoefficient is usedto obtainaerodynamicresistancesfor heatand

moisturethatareinputsto thecalculationsfor latentandsensibleheatfluxes. Over large

areasof Eurasia,thesechangesresultin a reductionin the2-meterair temperatureby 1.5

to 2 K.

e. Developmentof thesea-icecomponent

Thenew CSIM includesmodificationsto theformulationof icedynamics,sea-icealbedos,

andexchangesof saltbetweensea-iceandthesurroundingocean.Thehorizontaladvection

of seaice is now treatedwith incrementalremapping,amoreaccurateandefficientscheme

thanthatusedin previousversions(LibscombandHunke2004).Themomentumequation

hasbeenmodifiedusingscalingargumentsto bettersimulatemarginal ice underfreedrift

9

(Connolley etal. 2004).Saltandfreshwaterexchangebetweentheseaiceandsurrounding

oceanare calculatedusing a nonzero,constantreferencesalinity of seaice in CCSM3

(Schmidtet al. 2004).Theadoptionof a singlevalueof salinity in theseaice insuresthat

saltis conservedin thefull ocean-icesystem.

The albedoparameterizationin CCSM3matchesobservationsof the seasonaldepen-

denceof thealbedoon snow depth,ice thickness,andtemperaturewithin theuncertainty

of themeasurementsin theArctic andAntarctic(Perovich et al. 2002;Brandtet al. 2005).

Thedependenceontemperatureprovidesasimplemechanismto accountfor snow wetness

andponding.However, whentheice is coveredby colddry snow, thealbedoparameteriza-

tion in CCSM3is biasedlow by about0.07comparedto observations.TheCCSM3applies

a valuemoreappropriatefor wet snow ratherthandry snow undertheseconditions.Since

the incomingshortwave is too low by about50 Wm � in May and90 Wm � in June,the

albedoadjustmentis necessaryto insurethecorrecttiming for theonsetof sea-icemelting.

f. Couplingmethodology

The physicalcomponentmodelsof CCSM3communicatethroughthe coupler, an exec-

utive programthat governsthe executionandtime evolution of the entiresystem(Craig

et al. 2005;Drake et al. 2005). CCSM3is comprisedof five independentprograms,one

for eachof thephysicalmodelsandonefor thecoupler. Thephysicalmodelsexecuteand

communicatevia thecouplerin a completelyasynchronousmanner. Thecouplerlinks the

componentsby providing flux boundaryconditionsand,wherenecessary, physicalstate

informationto eachmodel.Thecouplermonitorsandenforcesflux conservationfor all the

fluxesthat it exchangesamongthecomponents.Thecouplercanexchangeflux andstate

informationamongcomponentswith differentgrid andtime steps.Both of thesecapabil-

ities areusedin thestandardconfigurationsof CCSM3. Statedatais exchangedbetween

10

differentgrids usinga bilinear interpolationscheme,while fluxesareexchangedusinga

second-orderconservative remappingscheme.Thebasicstateinformationexchangedby

the couplerincludestemperature,salinity, velocity, pressure,humidity, andair densityat

themodelinterfaces.Thebasicfluxesincludefluxesof momentum,water, heat,andsalt

acrossthemodelinterfaces.

In thestandardT85� 1 configuration,theatmosphere,land,andseaiceexchangefluxes

andstateinformationwith the couplerevery hour, while the oceanexchangesthesedata

onceperday. Theinternaltime stepsfor theland,atmosphere,ocean,andseaice compo-

nentsaretenminutes,twentyminutes,onehour, andonehour, respectively. Specialpro-

visionsaremadein theoceanto approximatethediurnalcycleof insolation(Danabasoglu

et al. 2005). During integration, the couplerrepeatsa sequenceof couplingoperations.

This cycle includestransmissionof datato theocean,land,andsea-ice;receptionof data

from thesea-iceandland; transmissionto theatmosphere;andfinally receptionfrom the

oceanandatmosphere.

3. The mean coupled climate

Therehavebeenseveralsignificantimprovementsin theclimateproducedby CCSM3rela-

tive to theclimatesimulatedby CCSM2.Theseimprovementsareevidentin acomparison

of thecontrol integrationsof thetwo modelsfor present-dayconditions.In thesecompar-

isons,the meanclimateproducedby CCSM2is representedby the averageof years900

to 1000from its controlsimulationin its standardT42� 1 configuration.This time period

includesthe interval thatKiehl andGent(2004)usedto describetheclimateof CCSM2.

Themeanclimateproducedby CCSM3is representedby theaverageof years400to 500

from a controlsimulationusingthemodelat its higheststandardresolution(T85� 1) (Ap-

pendixA). Thistimeperiodis thesameinterval evaluatedby Hurrell etal. (2005).Because

11

of seculardrift, thecomparisonbetweenthetwo integrationscandiffer dependinguponthe

choiceof timeperiodsusedin theanalysis(section4 andKiehl andGent2004).However,

thetrendsaresufficiently smallthatthedifferencesin thefieldsexaminedin this overview

of CCSM3arenot appreciablyaffected. This comparisonis alsoaffectedby changesin

boththephysicsandtheresolutionof theatmosphereandlandcomponentsfrom CCSM2

to CCSM3. Theeffectsof just changingresolutionin thesecomponentsarediscussedby

Hacket al. (2005).

a. Thermodynamicanddynamicpropertiesof theatmosphere

The atmospherictemperaturesfrom CCSM3have improved in two main aspectsrelative

to the simulationwith CCSM2(Figure1). First, CCSM2exhibits a significantcold bias

in thetemperaturesnearthetropical tropopause.In theregion 30 S to 30 N andbetween

70 to 150mb, theannual-meantemperaturefrom CCSM2is 3.9K colderthantheaverage

temperaturefrom theECMWFreanalysis(Kallberg et al. 2004).Dueprimarily to changes

in thecloudparameterizationsto produceoptically thickercirruscloudsin accordancewith

observations(Boville et al. 2005),theCCSM3is warmerin this region by 2.3K compared

to CCSM2. Thusthetropopausetemperaturesin CCSM3are1.6K too low relative to the

reanalysis.This representsa60%reductionin thecold temperaturebias.Second,thetem-

peraturesin bothpolaratmospheres(150to 300mb) from CCSM2aresignificantlycolder

thanmeteorologicalanalyses.For thenorthernpolar region between60 N and90 N and

the correspondingsouthernregion between60 S and 90 S, CCSM2 underestimatesthe

annual-meantemperaturesby 6.9K and11.3K,respectively. Thetemperaturesin CCSM3

increasein thesetwo regionsby 2.3K and3.9K, respectively. This representsa 33% de-

creasein thetemperaturebiasin bothhemispheres.TheCCSM3is still too cold by 4.6K

and7.4K in thenorthernandsouthernpolarregions.

12

Severalaspectsof thezonalwind havealsoimprovedin CCSM3.In CCSM2,theveloc-

ities in thewesterlyjet centeredat200mbin thesouthernhemispherearetoolargeby upto

11m/s(Figure2). In CCSM3,themaximumbiasin wind speedin this jet is reducedto ap-

proximately8.5m/s.CCSM2alsooverestimatestheannual-meaneasterlyvelocitiesin the

equatorialatmosphere.Thelargestbiasesshown in Figure2 occurat roughly50 mb near

thelower edgeof themesosphericjets. In CCSM3,thedifferencerelative to meteorologi-

cal analysesis reducedby nearly4 m/s. However, thetendency of themodelto simulate

strongerwindsin thenortherntroposphericjet is somewhatexacerbatedin CCSM3.

b. Energybalanceat thesurfaceandtopof model

Themostsignificantchangein theradiationbudgetof CCSM3(Table1) is thedisposition

of solarradiationin theatmosphere.Theatmospherein CCSM3absorbs7.1Wm � more

shortwave radiationin clear-sky conditionsand7.9 Wm �

moreunderall-sky conditions

thanCCSM2.Theincreasedabsorptionis causedprimarily by theintroductionof absorb-

ing aerosolspecies(section2b) andtheupdatesto theextinctionof near-infraredradiation

by watervapor. Thenew aerosolsincreasetheabsorptionby 2.8Wm � for bothclear-sky

andall-sky conditions.Thenew treatmentof near-infraredextinctionby H� O increasesthe

global-meanclearandall-sky atmosphericabsorptionby 4.0and3.1 Wm �, respectively.

Theenhancedabsorptionreducessurfaceinsolationby anequalamount.As a result,the

netsurfaceshortwave flux in CCSM3is 9 Wm � smallerthanthat in CCSM2(Figure3).

The new annualmeaninsolationof 160 Wm � is consistentwith several empiricalesti-

mates(Kiehl andTrenberth1997),althoughit is lower thanthemostrecentISCCPvalue

of 166Wm �

(Zhangetal. 2004).Despitetheimprovementsin thephysicsof CCSM3,the

changesin insolationin several regionsdegradethecorrespondencewith the ISCCPesti-

mates.Someof thelargestdiscrepanciesbetweenmodelandISCCPcalculationsoccurin

13

thetropics.Hereit is interestingto notethatISCCPoverestimatestheall-sky downwelling

flux by 21 Wm � comparedto surfaceradiometerssincethe ISCCPcalculationsdo not

fully accountfor theeffectsof tropicalaerosolsfrom biomassburning(Zhangetal. 2004).

The fidelity of the shortwave cloud forcing in CCSM3hasimproved relative to esti-

matesfrom the EarthRadiationBudgetExperiment(ERBE) (Harrisonet al. 1990;Kiehl

andTrenberth1997),especiallyin thestormtracks(Figure4). CCSM2underestimatesthe

magnitudeof global annual-meanshortwave cloud forcing by 5.8 Wm � , while CCSM3

reproducestheERBEestimatesto within 0.1 Wm � . The largestzonal-meandifferences

occurin thestormtracklatitudesat60 N and60 Sandin thetropicallatitudesof theITCZ

between10 N and10 S.Theincreasedforcing is in betteragreementwith thesatellitedata

for thestormtracksandin slightly worseagreementfor thetropics.

Theglobal-meanall-sky andclear-sky surfacelongwavefluxeshavedecreasedby6.9Wm �

and7.5Wm � relative to CCSM2.Thereductionsin clear-sky flux in polarregionsarere-

latedto thenew longwave parameterizationfor watervapor(Collins et al. 2002a).These

changesbring the model into muchbetteragreementwith in situ observations(Briegleb

andBromwich1998).

c. Seasurfacetemperatureandsalinity

Severalof thesystematicerrorsin SSTsin CCSM2havebeenreducedin CCSM3.Earlier

versionsof CCSMhave consistentlygenerateda region of equatorialsurfacewaterin the

easternPacific that is colder thanobserved andextendstoo far west into the warm pool.

The cold SSTbiasin the centralequatorialPacific exceeds2K in CCSM2,andit is less

than1K in CCSM3. For CCSM3,theSSTsin this region have increasedby between1K

14

and2K in the centralandwesternPacific (Figure5). A substantialfraction of the SST

increaseis causedby revisionsto thetreatmentof thediurnalcycle of insolationabsorbed

in theoceanmixedlayer(Danabasogluet al. 2005).In CCSM3,theequatorialSSTsin the

warmpoolareunderestimatedby between0.2 to 0.5K.

Like CCSM2,the CCSM3alsooverestimatesthe SSTsby asmuchas7C in narrow

coastalregionswestof BajaandsouthernCalifornia,PeruandChile,andsouthwestAfrica

(section5d). As discussedin Large andDanabasoglu(2005),surfaceheatfluxescannot

accountfor suchlarge biases.Instead,oceanprocessessuchascoastalupwellingappear

to be playing an importantrole in establishingthesebiases. This is consistentwith the

insensitivity of thebiasesto thereductionin solarinsolationin theseregionsfrom CCSM2

to CCSM3. The SST dependson both the strengthand temperatureof the upwelling.

Therefore,improvementsin the alongshorewind componentshouldaffect the upwelling

strengthbut maynotnecessarilyhavemuchinfluenceon theSSTs.

Theglobalseasurfacesalinity is about0.4psutoo freshin bothCCSM2andCCSM3,

but therearemoresignificantregionaldifferences.In thetropicalIndianandPacificoceans,

CCSM3rainfall generallyexceedsCCSM2andobservationalestimates(Figure6). There-

fore, areassuchasthewesterntropicalPacific warm pool whereCCSM2is too salty are

improvedin CCSM3,while areassuchasthewesternIndianOceanandcentralSouthPa-

cific arenow muchtoo fresh(Large andDanabasoglu2005). The reductionin salinity is

relatedto thestrongerdoubleITCZ in CCSM3.Theeffectsof CCSM3precipitationerrors

onsurfacesalinity, oceanstratificationandtropicalPacificcirculationarefurtherdiscussed

in LargeandDanabasoglu(2005).

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d. Oceanicheattransport

Figure7 shows thenorthwardoceanheattransportsby theAtlantic andglobaloceans.At

24 N acrosstheNorth Atlantic theCCSM3transportof 1.10PW is within theuncertainty

of the observationalestimateof ������������� PW, but the CCSM2transportof 0.80 PW is

not. Thismodeldifferenceis relatedto achangein theoverturningcirculationin theNorth

Atlantic wherethemaximumbelow 500maveragesabout22 Sv in CCSM3(Bryanet al.

2005)andonly about15Sv in CCSM2.Themodeledandobservedtransportsacross24 N

in thePacific areall within 0.08PW of 0.82PW, sotherelative global transportis similar

to theAtlantic.

e. Sea-icethicknessandconcentration

Thefidelity of Arctic sea-icethicknessanddistribution have improvedin CCSM3relative

to earlierversionsof themodel.Theannualmeanicethicknessis between2 and2.5m over

thecentralArctic basin,with thicknessesreaching3–4m next to theCanadianArchipelago

andin theEastSiberianSea(Figure8). CCSM3agreeswell with submarinemeasurements

of seaice thicknessfrom Bourke andGarrett(1987)andRothrocket al. (1999),although

themodelis toothin by aboutonemeterwithin about400km of theCanadianArchipelago

and too thick by abouttwo metersin the EastSiberianSea. The seaice in CCSM2 is

considerablythinner, with ice in thecentralArctic averagingabout1.5m. Theincreasein

the thicknessin CCSM3is dueto improvementsin the downward longwave radiationin

winter.

Improvementsin thepatternof seaice thicknessin CCSM3canbeattributedto effects

of theincreasedresolutionof theatmosphereonthepolarwind field (Figure9) (DeWeaver

andBitz 2005). In winter theseaice concentrationin theAtlantic sectorof theArctic in

16

CCSM3is aboutthesameasin CCSM2,with too little ice in theBarentsSeaandtoomuch

ice in theLabradorSea.Thewintertimeice coverageis now too extensive in theOkhotsk

Seain CCSM3.In thenorthernhemisphere,themeansummertimeseaicecoverageagrees

well with satelliteobservations(Hollandet al. 2005).

The characteristicsof the seaice in the southernhemisphereare describedin detail

by Holland et al. (2005). The seaice concentrationin CCSM3is lessextensive thanin

CCSM2yearround. CCSM3is still too extensive by about20%comparedwith satellite

observationsof theSouthernOcean(Cavalieri etal. 1997).Icethicknessis muchimproved

in CCSM3comparedto recentobservationalestimatesof Antarcticseaice (Timmermann

et al. 2004).

The CCSM3model’s seaice describedhereis from thehigh resolutionconfiguration

of themodel.No changesaremadeto theseaice modelcomponentfor theconfigurations

at lower atmosphericresolution,althoughthe seaice that is simulatedchangesconsider-

ably. Thekey differenceis that theperennialice is about1 meterthicker in themoderate

resolutionconfigurationthanit is at higherresolution. In addition,thereis a shift in the

thicknesspatternmentionedabove,andtheice tendsto bemoreextensive. Thesechanges

aredocumentedby Hollandet al. (2005)andDeWeaverandBitz (2005).

f. Climatesensitivity

Climatesensitivity is ameasureof thechangein aclimatesimulationin responseto external

forcing. Accordingto its traditionaldefinition,climatesensitivity is theincreasein global-

averageannual-meansurfacetemperaturewhenthe atmosphericconcentrationof carbon

dioxideis doubled.Althoughclimatesensitivity is not a usefulmetricfor regionalclimate

change,it hasprovedto beaveryusefulindex for categorizingtheresponseof multi-model

ensemblesto agivenclimate-changescenario(IPCC2001).

17

Theequilibriumsensitivity of CCSM3in its high-resolutionconfigurationis 2.7K for

doublingCO� from 355to 710ppmv(Kiehl etal.2005).Thisis higherthantheequilibrium

sensitivity of 2.2K for CCSM2 and the sensitivity of 2.0K for CSM1 (Kiehl and Gent

2004).Thetwo factorscontributingto theincreasedsensitivity arethechangesin thecloud

processesin CAM (section2b) andtheresolution-dependenttuningof thecloudprocesses

(section2a). The largestdifferencesin cloud responseare associatedwith low clouds.

The global-meanlow-cloudcover increasesin responseto higherradiative forcing much

lessrapidly in CCSM3thanin CCSM2,andthe zonal-meanlow-cloudcover in CCSM3

actuallydecreasesbetween30 Sand60 Swhenconcentrationsof CO� aredoubled(Kiehl

etal. 2005).In addition,theclimatesensitivity of CCSM3increaseswith increasingspatial

resolutionfrom theT31� 3 to T85� 1 configurations.Thechangein sensitivity is directly

relatedto thevariationin low-cloudradiativefeedbackswith resolution(Kiehl etal. 2005).

The aspectsof the cloud parameterizationsthat causethe low cloudsto be particularly

sensitive to greaterradiative forcing andspatialresolutionarestill underinvestigation.

4. Stability and long-term behavior of the coupled integra-

tion

CCSM3hasbeendesignedto provide stablesimulationsrelatively free of seculartrends

underfixedboundaryconditions.Thestability in themodelsystemis animportantdesign

objectivefor two reasons.First, theabsenceof largetrendsis anecessarybut notsufficient

testof theconservationof energy, mass,andtotalwatercontentof eachof thecomponents.

Second,drift-freesimulationsarerequiredfor someof themoredemandingapplicationsof

themodel,includingsimulationsof thecarboncyclethatrequiremillenniato attainequilib-

rium. Thestability canbeaddressedby examiningtheenergy budgetandotherproperties

18

of anintegrationfor present-dayconditionsduringyears100to 600(AppendixA).

In orderfor theclimatesystemto be in equilibrium, theexchangeof radiative energy

acrossthe top of the atmosphericmodel (TOM) mustbe zero. During the initial stages

of a climatemodel integration,it is usuallyvery difficult to achieve a precisetime-mean

energy balance,andinsteadthesystemgainsor losesasmallamountof energy duringeach

annualcycle. Theexchangeof radiantenergy is thedifferencebetweenthenetshortwave

radiationabsorbedby the systemandthe net longwave radiationemittedby the system.

For CCSM3, the annual-meanand RMS TOM energy balanceis ��������� �!�����#" Wm �

underpresent-dayconditions(Figure10). Sincethesignconventionon theTOM balance

is positivedownward,onaveragetheCCSM3losesenergy. Thislossrateis nearlyidentical

to thelossrateof �$����� Wm � for CCSM2(Kiehl andGent2004).Sincetheannual-mean

netsolarradiationabsorbedattheTOM underall-sky conditionsis 234.2Wm � , theenergy

imbalancein thesystemis equivalentto 0.08%of thenetsolarinput. TheTOM all-sky and

clear-sky fluxesarerelatively stable,with trendsbetween��������� and �$������� Wm � /century.

Similarly, equilibriumof theclimatesystemrequiresthat theglobal-meansurfaceen-

ergy balancealsobeidenticallyzero.The(positive-downward)exchangeof energy among

theatmosphereandsurfacecomponentsis thedifferencebetweenthenetdownwardall-sky

shortwaveradiation,thenetupwardall-sky longwaveradiation,thelatentheatflux includ-

ing theeffectsof precipitation,andthe sensibleheatflux. In the model,the heatstorage

in soil andthe energy usedto melt snow arerelatively minor comparedto the individual

termsin the surfaceenergy exchange. For CCSM3, the annual-meanandRMS surface

energy balanceis ��������%&�'������� Wm �

(Figure10). Detaileddiagnosticsprovidedby each

componentandby thecouplerindicatethat this imbalanceis not causedby a violation of

theconservationof energy. Thelandandoceanmodelcomponentseachsupplyabouthalf

theflux comprisingthetotalsurfaceimbalance.Thelandcomponentof thesurfacebalance

19

is associatedwith theheatrequiredto melt snow. The fact that thesurfaceandTOM are

losingenergy indicatesthatthemodelis not in equilibriumevenafter600yearsof integra-

tion. Evidencefrom long simulationsof paleoclimateregimessuggeststhatthetime-scale

for CCSM3to approachenergeticequilibriumis greaterthan2000years.

The net energy absorbedby the atmosphereis just the differencebetweenthe TOM

andsurfaceenergy balances.For CCSM3, the meanandRMS energy absorbedby the

atmosphereis �������(�)���*�+� Wm � (Figure10). Theatmosphericmodelincludesacorrection

appliedat eachtime stepthatsetsthechangein atmosphericenergy equalto theglobally-

integratedfluxesexchangedwith the surfaceandtop of the model (Collins et al. 2004).

The atmosphericenergy is approximatedasthe sumof the total potentialenergy andthe

lateralkinetic energy. The correctionis introducedasa vertically-uniformadjustmentto

the atmospherictemperatures.In the absenceof that correction,the time-meanglobal-

averageenergy lost by theatmosphereis �������#� Wm � . This residuallossis dueprimarily

to temperaturediffusionandsecondarilyto numericalapproximations.

Sincethe simulatedclimatesystemis slowly losing energy, the global meansurface

temperatureshoulddecreaseslowly with time. By the endof the first century, the area

of Arctic seaice hassettledinto anoscillationaboutits long-termmeanvalue. After this

initial 100-yearperiod,thesurfacetemperaturedecreasesby ����������� K percentury. Most

of this trendis manifestedin thesouthernhemispherebetween30 Sand90 S,whichcools

at a rateof ��������% K percentury. The temperaturesin the tropicsbetween30 S and30 N

andthenorthernhemispherebetween30 N and90 N increaseby lessthan �,�-�+�� #. K per

century. The trendin the global volume-meanoceantemperatureis �$������/ K per century.

As in CSM1(Boville andGent1998),theinitial oceanadjustmentto theenergy imbalances

at theoceansurfaceoccurswell below themixedlayer(Figure11).

The decreasein the temperatureof the southernhemispherecanbe explainedeither

20

by the expansionof the southernsea-iceextent or by the persistentcooling of the deep

oceanwaterupwelling adjacentto Antarctica. The trendsin seaice in the northernand

southernhemispheresare �$���������-�+�10 and ���*�+"2�3�+�10 km�

percentury, respectively (Fig-

ure12). Thesechangescorrespondto changesin iceconcentration(expressedin fractional

area)of �������#��� % and �������+/ % percentury. Thetemperaturetrendcanbedecomposedinto

a sumof termsassociatedwith the trendsin the areasand temperaturesof the southern

ocean,southernsea-ice,andiceoverAntarctica.Thedecompositionshowsthat83%of the

southern-hemispheretrendis determinedby thecombinationof theupwardtrendin sea-ice

areaandthe �4�+"���5 K averagetemperaturedifferentialbetweenthesea-iceandsurrounding

ocean.

Thetrendin theglobalvolume-meansalinity is �$5����6�3�+�� #7 psu/century(Figure11).

Comparedto the global meansalinity of 34.72psu, the trendin salinity is equivalentto

a relative changeof ���4�8�+�9 #. % percentury. This reductionin salinity is causedby the

adjustmentof thesoil moisturein thedeepestlayersof thelandmodelduringthefirst 300

yearsof integration(Kiehl andGent2004).Excessdeepsoil moistureis graduallyreleased

to theoceansby river runoff. Thesetrendsaresmallerin magnitude,but oppositein sign,

to thechangesin salinity in CCSM2(Kiehl andGent2004).

5. Challenges for further development

While many featuresof the climate are simulatedwith greaterfidelity by CCSM3 than

CCSM2, thereare still significantbiasesthat shouldbe addressedin future generations

of CCSM. Thesesystematicerrorscanbe illustratedby comparingthe CCSM3 control

integrationagainstobservationsandmeteorologicalanalysesfor thepresent-dayclimate.

21

a. Representationof major modesof variability

Thebasiccharacteristicsof theENSOepisodessimulatedby CCSM2andCCSM3arequite

similar. Two of the most importantpropertiesarethe total varianceandpower spectrum

of SSTanomaliesin thecentralPacific. The resultsfor theNino 3.4 region (5 S to 5 N,

120 W to 170 W) arerepresentativeof otherregionsin thetropicalPacific.

Themeteorologicalreanalysisby Kistler et al. (2001)for 1951–2000providestheob-

served propertiesfor this region. The reanalysisrepresentsa relatively shortdatarecord

comparedto the length of the CCSM2 andCCSM3 control runs. In addition, the vari-

ancesimulatedfor the Nino 3.4 region in CCSM2andCCSM3canchangeconsiderably

on timescalesof 50 years. For thesereasons,the control runs for CCSM2andCCSM3

aredivided into 50-yearsegments.Thevarianceandpower spectrafor eachsegmentare

determinedseparatelyandthenaggregatedfor comparisonagainstthemeteorologicalre-

analysis.Themodeldatausedfor this purposeincludes650yearsof theCCSM2control

integrationand500yearsof theCCSM3integration.TheNino 3.4 temperatureanomalies

aresmoothedusinga running5-monthboxcaraveragebeforeanalysis.

Thetotal variancefor thesmoothedmonthlyanomaliesin theNino 3.4temperaturefor

the analysisis 0.78 K, andthe meanvariancesfor the 50-yearsegmentsof CCSM2and

CCSM3are0.81K and0.73K. Theseresultsshow thattheCCSM2tendsto overestimate

andthe CCSM3tendsto underestimatethe variability in the observed record. Approxi-

mately70%of the50-yearsegmentsfrom CCSM2and40%of thesegmentsfrom CCSM3

have greatervariability thanobserved. The power spectraof the monthlySSTanomalies

for thelow andintermediateresolutionsof CCSM3arediscussedin detail in Yeageret al.

(2005). The power spectrafor the high resolution(T85� 1) configurationof CCSM3are

comparedagainstthespectrafor CCSM2andtheNCEPreanalysisin Figure13. Theob-

servedENSOshavea relatively broadspectrumspanningthreeto fiveyears.TheCCSM3,

22

like CCSM2,tendsto produceENSOswith a periodicityof approximatelytwo years. In

fact, the spectraof CCSM3areeven morestronglypeaked at periodsof two yearsthan

thoseof CCSM2,andthevarianceat periodsof fiveyearsis smallerandhencelessrealis-

tic in CCSM3thanin CCSM2.

b. DoubleITCZ in thePacific

Like previousgenerationsof this model,CCSM3producesa doubleITCZ in the tropical

Pacific. ThesouthernPacific convergencezone(SPCZ)in theobservationsextendssouth-

eastfrom the tropicalwarmpool into thecentralsouthernPacific (Figure6). In CCSM3,

theSPCZis replacedby a southernbranchof theITCZ that is nearlyzonalin orientation.

Theerror is particularlyevidentduringJJA whentherealSPCZis muchweaker andless

extensive thanthemodeledconvectionsouthof theequator. Themodeloverestimatesthe

local precipitationratein bothbranchesof theITCZ by up to 10 mm/day. Themaximum

precipitationin thenorthernhalf of thewarmpool is too intense,andit is displacedwest-

wardby approximately30 degreesrelative to theobservedmaximum.Theexcessrainfall

indicatesthat the modelproducesan overly vigoroushydrologicalcycle for the tropical

Pacific ocean. It alsoadverselyaffects the meridionalstructureof the equatorialPacific

undercurrent(LargeandDanabasoglu2005).

c. Biasesin continentalprecipitationandtemperature

Althoughthetemperatureerrorsin CCSM3aresmallerthanthosein CCSM2,therearestill

largebiasesin the2mair temperaturesfor sub-Arcticcontinentalregionsduringborealwin-

ter. The temperaturesrelative to observations(Willmott andMatsuura2000)during DJF

areoverestimatedby asmuchas10K in partsof AlaskaandnorthernEurasia(Figure14).

23

ThemeanandRMSoverestimatesfor sub-Arcticcontinentalregionsnorthof 50 N during

DJFare :$����;��</���� K. Themagnitudeof the local errorsaregenerallysmallerthanthose

in CCSM2(Kiehl andGent2004).In addition,therearesignificantdeficitsin precipitation

in thesoutheastUnitedSates,Amazonia,andsoutheastAsia throughouttheannualcycle

(Figure6). The biasesin annual-meanprecipitationfor thesethreeregionsare listed in

Table2. Theunderestimationof rainfall rangesbetween24%and28%for theseareas.

Thesebiasescausedynamicmodelsof vegetationto produceunrealisticdistributions

of plantfunctionaltypesin theaffectedregions(BonanandLevis 2005).CCSM3includes

a dynamicvegetationmodule(Levis et al. 2004),but it is not activeby default. Modelsof

the terrestrialcarboncycle arevery sensitive to both temperatureandprecipitation. It is

difficult to predicttheneteffect on CO� concentrationsfrom biasesin thesefieldsbecause

of themultitudeof ecologicalandbiogeochemicalprocessesaffected.Carbonuptake dur-

ing photosynthesis,carbonlossduring respiration,andvegetationgeographydependon

temperatureandprecipitation.In addition,thesensitivity of theseprocessesdiffersamong

typesof vegetation.Therefore,whentherearebiasesin bothtemperatureandprecipitation,

it maybedifficult to predictthesignof thechangein atmosphericCO� . For thesereasons,

it will beimportantto reducethesebiasesin futureversionsof CCSMthatincludebiogeo-

chemistry. Oneoptionto reducethepositive temperaturebiasesduringborealwinter is to

usea relationshipbetweensnow albedoandequivalentwaterdepththatis moreconsistent

with satelliteobservations(Olesonet al. 2003).

d. SSTbiasesandrelatedatmosphericissuesin westerncoastalregions

CCSM3producessea-surfacetemperaturesfor thewesterncoastalregionsthatarewarmer

thanobserved(Figure5). Experimentswith prototypesof thecoupledmodelsuggestthat

24

thebiasesin SSTscanbecausedbyunderestimatesof surfacestressparallelto thecoastand

by overestimatesof surfaceinsolation(LargeandDanabasoglu2005).Theweakersurface

stressresultsin weaker coolingof theoceanmixedlayer, andtheexcessinsolationresults

in too muchsolarheatingof theupperocean.Theseexperimentsalsoshow thatthebiases

in theseareasaffecttheSSTandprecipitationoverlargeportionsof theAtlantic andPacific

basins.Two examplesof thepositive SSTbiasesoccurin theoceansadjacentto southern

Africa andSouthAmerica. TheCCSM3is comparedin Table3 againstobservationsand

analysesfor thesetwowesterncoastalregionsaveragedovertheannualcycle. In thecoastal

region adjacentto SouthAmerica,CCSM3overestimatestheSSTby 1.8C.While earlier

generationsof CCSM overestimatedthe surface insolationoff SouthAmerica by more

than 50 Wm � in the annualmean,CCSM3 tendsto slightly underestimatethe surface

shortwave flux. Themuchsmallererror in insolationresultsfrom severalmodificationsto

the cloud parameterizationsintroducedin CCSM3(Boville et al. 2005)partly to address

this issue. The observationalcomparisonsuggeststhat the along-shoresurfacestressin

CCSM3 may still be too weak,and this may partially explain the 1.8C error in SST. It

shouldbenotedthatthesurfacestressproducedby CCSM3is strongerthanthatin CCSM2

by up to 0.1Nm�

partly becauseof theincreasedresolutionin theatmosphere(Hacket al.

2005). In the caseof Africa, CCSM3 underestimatesthe SST by 3.5C even thoughit

producesa realisticalong-shorestressandslightly underestimatesthe surfaceinsolation.

Theeffectsof otherphysicalprocesses,includingoceanupwelling,on theSSTbiasesare

examinedfurtherin LargeandDanabasoglu(2005).

25

e. Thesemi-annualSSTcyclein theeasternPacific

CCSM3producesa fairly strongsemi-annualcycle for SSTin theeasterntropicalPacific

thatdoesnot occurin therealclimatesystem(LargeandDanabasoglu2005). Theregion

wherethisdiscrepancy is particularlyevidentliesbetween5 N to 5 Sand110 W to 90 W.

An observationalclimatologyfor theseasonalcycle in SSTfor this region canbederived

from theHadley Centre’sseasurfacetemperaturedataset(Rayneretal. 2003).Theannual

andregional meantemperaturefrom CCSM3is 25.5C,andthis compareswell with the

HadISSTestimateof 25.2C.However, thesimulatedandobservedseasonalcyclesin the

regionalmeanSSTarequitedifferent.TheCCSM3-simulatedannualcyclehasasine-wave

amplituderoughly half that observed andis phased1.4 monthslate,while the sine-wave

amplitudeof the semi-annualcycle is roughly twice that observed. The causesfor these

systematicbiasesin themodelphysicshavenotyet beenidentified.

f. Underestimationof downwellingshortwaveradiationin theArctic

In theArctic, CCSM3underestimatesthedownwelling all-sky shortwave radiationat the

surfacethroughoutthe annualcycle. The insolationis underestimatedrelative to in situ

observationsfrom the SurfaceHeatBudgetof the Arctic (SHEBA) experiment(Persson

et al. 2002)and to estimatesfrom the InternationalSatelliteCloud ClimatologyProject

(Figure15) (Zhangetal. 2004).For this comparison,theISCCPdatafor 1984to 2000has

beenaveragedto producea climatology. Between70 N to 90 N, theannual-meandown-

welling shortwave fluxesfor all-sky conditionsare91 Wm �

from ISCCPand78 Wm �

from CCSM3.Thecorrespondingannual-meanclear-sky fluxesdifferby only �$����; Wm � ,

or ��� %. ThefluxesduringtheJJA seasonare214Wm � from ISCCPand169Wm � from

CCSM3.ThecorrespondingJJA-meanclear-sky fluxesdiffer by only 8.5Wm � , or 2.7%.

26

Sincethe clear-sky fluxesarein goodagreement,the underestimateof surfaceinsolation

by CCSM3 is causedby an overestimateof the surfaceshortwave cloud radiative forc-

ing. It shouldbe notedthat the excessive cloudinessin winter producesan overestimate

of downwelling longwave surfaceflux by 20 Wm � for DecemberthroughApril. The

overestimationof longwave flux partly compensatestheunderestimationof shortwave in-

solationin the total surfaceradiationbudget.Furtheranalysiswill berequiredto identify

thesourcesof theseerrorsin themodeledcloudamount,cloudcondensatepath,andcloud

microphysicalproperties.

6. Summary

A new versionof the CommunityClimateSystemModel, CCSM3,hasbeendeveloped

and releasedto the climate community. The improvementsin the functionality include

the flexibility to simulateclimate over a wide rangeof spatial resolutionswith greater

fidelity. This paperdocumentsthehigh resolution(T85� 1) versionusedfor international

assessmentsof climate change. The atmosphereand land sharea grid for the Eulerian

spectralatmosphericdynamicsrunningat T85 truncation.Theoceanandsea-icesharea

nominal1-degreegrid with adisplacedpolein thenorthernhemisphere.

The atmosphereincorporatesnew treatmentsof cloud and ice-phaseprocesses;new

dynamicalframeworks suitablefor modelingatmosphericchemistry; improved parame-

terizationsof the interactionsamongwatervapor, solar radiation,andterrestrialthermal

radiation;andanew treatmentof theeffectsof aerosolsonsolarradiation.Thelandmodel

includesimprovementsin land-surfacephysicsto reducetemperaturebiasesandnew ca-

pabilitiesto enablesimulationof dynamicvegetationandtheterrestrialcarboncycle. The

oceanmodel hasbeenenhancedwith new infrastructurefor studyingvertical mixing, a

morerealistictreatmentof shortwave absorptionby chlorophyll,andimprovementsto the

27

representationof theoceanmixedlayer. Theseaicemodelincludesimprovedschemesfor

thehorizontaladvectionof seaiceandfor theexchangeof saltwith thesurroundingocean.

The softwarehasbeendesignedso that CCSM3 is readily portableto a wide variety of

computerarchitectures.

The climate producedby the high-resolutionCCSM3 shows several significant im-

provementsover the climatesproducedby previous generationsof the model. Thesein-

cludereducedsub-Arcticsurfacetemperaturebiasesduringborealwinter, reducedtropical

SST biasesin the Pacific, andmore realisticmeridionaloceanheattransport. The new

atmospherefeaturesimprovedsimulationof cloudradiativeeffectsin thestormtracksand

duringENSOevents(section3.b) ; smallerbiasesin uppertropical tropospherictempera-

tures;andamorerealisticsurfaceradiationbudgetunderclear-sky conditions(Collinsetal.

2005b).Theseaice featuresa muchmorerealisticsimulationof thespatialdistributionof

iceconcentrationandof ice thickness.Theclimateis stableoverat least700yearssubject

to perpetualpresent-dayboundaryconditions.

Thereare still several aspectsthat shouldbe improved in future versionsof CCSM.

Theseincludethe periodicity andtotal varianceof ENSO;the doubleITCZ in the tropi-

cal oceans;andthe large precipitationbiasesin the westerntropical oceanbasins.Other

majormodesof variability thatarenot well-simulatedincludetheMadden-Julianoscilla-

tion (Collinsetal. 2005b).Theerrorsin continentalprecipitationandtemperaturesneedto

beaddressedto facilitatemodelingof dynamicvegetationandtheterrestrialcarboncycle.

While therepresentationof thesurfacefluxesin coastalregionswestof Africa andSouth

Americahasimproved,therearestill significantbiasesin thecoastalSSTs(LargeandDan-

abasoglu2005).Reductionin thesebiaseswill affect thesimulationover largeareasof the

Pacific andAtlantic basins.Finally, therearestill significanterrorsin theradiative energy

budgetof polarregions.Theseaffect boththeseasonalcycle andtheclimatefeedbacksof

28

seaice.

Researchis underway to diagnosethesebiasesat theprocesslevel andto testimprove-

mentsin physicsanddynamicsthat would improve the simulationfidelity. At the same

time, themodelis beingextendedto includea comprehensive treatmentof terrestrialand

oceanicbiogeochemistryand ecosystemdynamics. Detailedrepresentationsof reactive

chemistry, photochemistry, andaerosolmicrophysicshave beenaddedto theatmosphere.

Thesedevelopmentsarethe initial stepstowardbuilding a morecomprehensive modelof

theentireEarthsystemthatcanbeappliedto climatesof thepast,present,andfuture.

A. Control integrations of CCSM3

A comprehensivesuiteof controlexperimentshavebeenperformedwith CCSM3.Theout-

put from theseexperimentshasbeenreleasedto theclimatecommunityandmaybereadily

obtainedfrom the CCSM (2004)website. Most of the experimentshave beenintegrated

usingeachof the threestandardconfigurationsof CCSM (section2a). The experiments

includesimulationsunderconstantpresent-dayandpreindustrialconditionscorrespond-

ing to 1780and1870. In order to characterizethe sensitivity of the model to increased

atmosphericconcentrationsof CO� , the model hasbeenintegratedwith a 1% increase

in CO� per yearstartingfrom initial conditionsobtainedfrom the present-dayrun. Two

othersimulationshavebeenbranchedfrom thetransient1%CO� /yearsimulationwhenthe

decadal-meanCO� concentrationis equalto two timesandfour timesits present-dayvalue.

TheCO� concentrationis heldfixedin eachof theserunsto thevaluesat thebranchpoints

from the transientsimulation.For thepurposesof thesecontrolexperiments,thepresent-

dayglobal-meanannually-averagedmixing-ratioof CO� is equalto 355ppmv, its valuein

1990.

Thecontrolintegrationsareshown in Table4. Thetablelists thetypesof experiments,

29

theresolutionusedin eachintegration,thelengthof eachexperimentin years,andtheseries

identifier for eachsimulation.More detailsregardingthe typesof modeloutputavailable

andthemethodsfor accessto thesedataareavailablefrom theCCSM(2004)website.The

controlexperimentdiscussedin this paperis b30.009.

Acknowledgement The authorswish to acknowledgemembersof the CCSM Software

EngineeringGroupandNCAR’sDivisionsfor ClimateandGlobalDynamics,Atmospheric

Chemistry, andScientificComputingfor their substantialcontributionsto thedevelopment

of CCSM3. The suggestionsby two anonymousreviewershave helpedconsiderablyto

improvethis descriptionof CCSM3.

Thenew modelwouldnotexistwithoutthesignificantinputandeffort frommany mem-

bersof theCCSMworking groups.We would like to acknowledgethesubstantialcontri-

butionsto andsupportfor theCCSMprojectfrom theNationalScienceFoundation(NSF),

theDepartmentof Energy (DOE), theNationalOceanicandAtmosphericAdministration,

andtheNationalAeronauticsandSpaceAdministration.

This studyis basedon modelintegrationsperformedby NCAR andCRIEPIwith sup-

port andfacilitiesprovidedby NSF, DOE, MEXT, andESC/JAMSTEC. CRIEPI,MEXT,

ESC,andJAMSTEC aretheJapaneseCentralResearchInstituteof ElectricPower Indus-

try; theMinistry of Education,Culture,Sports,ScienceandTechnology;theEarthSimu-

lator Center;andtheJapanAgency for Marine-EarthScienceandTechnology.

We appreciatethe financialsupportfrom NSF for this specialissueof the Journal of

Climateon CCSM3.

30

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39

List of Figures

1 Differencesin theannual-mean,zonally-averagedatmospherictemperature

profilesbetweenCCSM3andtheECMWFreanalysis(Kallberg etal.2004)

(left); correspondingdifferencesfor CCSM2(right). . . . . . . . . . . . . 44

2 Differencesin the annual-mean,zonally-averagedzonal wind speedbe-

tweenCCSM3 and the ECMWF reanalysis(Kallberg et al. 2004) (left);

correspondingdifferencesfor CCSM2(right). . . . . . . . . . . . . . . . . 45

3 Differencesin annual-meannetsurfaceinsolationbetweenCCSM2andthe

ISCCPFD dataset(Zhangetal. 2004)(top);correspondingdifferencesfor

CCSM3(bottom). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

4 Annual-meanzonally-averagedshortwavecloudforcingfromCCSM2,CCSM3,

andERBE(Harrisonetal. 1990;Kiehl andTrenberth1997)(top);anddif-

ferencesamongtheshortwave forcing estimates(bottom). . . . . . . . . . 47

5 Differencesin annual-meansurfacetemperaturebetweenCCSM2andthe

HadISSTdataset(Rayneret al. 2003)(top); correspondingdifferencesfor

CCSM3(bottom). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

6 Differencesin annual-meantotal surfaceprecipitationbetweenCCSM2

andtheGPCPdataset(Adler et al. 2003)(top);correspondingdifferences

for CCSM3(bottom). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

7 Northwardtotal transportof heatin theoceanmodelfrom integralsacross

the Atlantic (dotted)andaroundthe globe(solid). The modelvaluesin-

cludetheresolvedandparameterizededdycomponentsandthe isopycnal

diffusion.Thesquaresandplusesare,respectively, theAtlantic andglobal

resultsof individual sectionanalysescompiledby Bryden and Imawaki

(2001).Uncertaintiesin theobservationalestimatesaretypically �$��� PW. . 50

40

8 Annual-meanseaice thicknessin the northernhemispherefrom CCSM3

(top left), CCSM2 (top right), and the differencebetweenCCSM3 and

CCSM2(bottom). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

9 DJF-meanseaiceareain thenorthernhemispherefrom CCSM3(top left),

CCSM2(top right), andthedifferencebetweenCCSM3andCCSM2(bot-

tom). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

10 Probabilitiesof annual-meanenergy imbalancesin CCSM3at the top of

model (TOM), the surface,and in the atmosphere.The probabilitiesare

obtainedfrom years100 through600 of the control integration. Vertical

arrows representseries-meanimbalances,andhorizontalarrows represent

the2-= rangeof annualimbalances.Valuesin upperright arethemeanand

1-= imbalancesfor theTOM, surface,andatmosphere(top to bottom). . . 53

11 Differencebetweensimulatedglobal-meanoceanpotentialtemperatureand

the observed climatologicalprofile (Levitus et al. 1998)asa function of

depthandyearof simulation(top). Dif ferencebetweensimulatedglobal-

meanoceansalinity andthe observedclimatologicalprofile asa function

of depthandyearof simulation(bottom). . . . . . . . . . . . . . . . . . . 54

12 Annual meanareaof sea-icefrom the CCSM3control integrationin the

northernhemisphere(bold lines)andsouthernhemisphere.Observational

estimatesfrom the HadISSTdataset (Rayneret al. 2003) are shown by

dashedlinesfor eachhemisphere. . . . . . . . . . . . . . . . . . . . . . . 55

13 Power spectraof the monthly Nino 3.4 anomaliesfor CCSM2,CCSM3,

andthe NCEPreanalysis(thick line) (Kistler et al. 2001). The rangeof

variancespannedby thespectraof individual50-yearssegmentsareshown

CCSM2(light hatching)andCCSM3(darkhatching). . . . . . . . . . . . 56

41

14 DJF-mean2-metersurfacetemperaturefrom CCSM3(top), the Willmott

andMatsuura(2000)dataset(middle);andthedifferencebetweenCCSM3

andtheWillmott estimates(bottom). . . . . . . . . . . . . . . . . . . . . . 57

15 JJA-meanall-sky netsurfaceshortwaveflux from CCSM3(topleft), theIS-

CCPFD dataset(Zhangetal.2004)(topright), andthedifferencebetween

CCSM3andISCCP(bottom). . . . . . . . . . . . . . . . . . . . . . . . . 58

42

List of Tables

1 Globalannual-meanradiativepropertiesof CCSM2andCCSM3(Wm � ) . 59

2 Modelprecipitationfor continentalregions . . . . . . . . . . . . . . . . . 60

3 Propertiesof westerncoastaloceanregions . . . . . . . . . . . . . . . . . 61

4 ControlintegrationsusingCCSM3 . . . . . . . . . . . . . . . . . . . . . 62

43

Figure1: Dif ferencesin theannual-mean,zonally-averagedatmospherictemperaturepro-

filesbetweenCCSM3andtheECMWFreanalysis(Kallberg etal.2004)(left); correspond-

ing differencesfor CCSM2(right).

44

Figure 2: Dif ferencesin the annual-mean,zonally-averagedzonal wind speedbetween

CCSM3andtheECMWFreanalysis(Kallberg etal.2004)(left); correspondingdifferences

for CCSM2(right).

45

Figure3: Dif ferencesin annual-meannetsurfaceinsolationbetweenCCSM2andthe IS-

CCPFD dataset(Zhangetal.2004)(top);correspondingdifferencesfor CCSM3(bottom).

46

Figure4: Annual-meanzonally-averagedshortwavecloudforcing from CCSM2,CCSM3,

andERBE(Harrisonet al. 1990;Kiehl andTrenberth1997)(top); anddifferencesamong

theshortwave forcingestimates(bottom).47

Figure 5: Dif ferencesin annual-meansurface temperaturebetweenCCSM2 and the

HadISSTdataset(Rayneret al. 2003)(top); correspondingdifferencesfor CCSM3(bot-

tom).

48

Figure6: Dif ferencesin annual-meantotal surfaceprecipitationbetweenCCSM2andthe

GPCPdataset(Adler et al. 2003)(top);correspondingdifferencesfor CCSM3(bottom).

49

Figure7: Northward total transportof heatin the oceanmodelfrom integralsacrossthe

Atlantic (dotted)and aroundthe globe (solid). The model valuesinclude the resolved

andparameterizededdycomponentsandthe isopycnaldiffusion. Thesquaresandpluses

are, respectively, the Atlantic andglobal resultsof individual sectionanalysescompiled

by BrydenandImawaki (2001). Uncertaintiesin theobservationalestimatesaretypically

�$��� PW.

50

Figure8: Annual-meanseaice thicknessin the northernhemispherefrom CCSM3(top

left), CCSM2(top right), andthedifferencebetweenCCSM3andCCSM2(bottom).

51

Figure 9: DJF-meanseaice areain the northernhemispherefrom CCSM3 (top left),

CCSM2(top right), andthedifferencebetweenCCSM3andCCSM2(bottom).

52

Figure10: Probabilitiesof annual-meanenergy imbalancesin CCSM3at thetop of model

(TOM), thesurface,andin theatmosphere.Theprobabilitiesareobtainedfrom years100

through600of thecontrol integration. Verticalarrows representseries-meanimbalances,

andhorizontalarrows representthe2-= rangeof annualimbalances.Valuesin upperright

arethemeanand1-= imbalancesfor theTOM, surface,andatmosphere(top to bottom).

53

Figure11: Dif ferencebetweensimulatedglobal-meanoceanpotentialtemperatureandthe

observedclimatologicalprofile(Levitusetal. 1998)asafunctionof depthandyearof sim-

ulation (top). Dif ferencebetweensimulatedglobal-meanoceansalinity andtheobserved

climatologicalprofileasa functionof depthandyearof simulation(bottom).

54

Figure12: Annualmeanareaof sea-icefrom theCCSM3control integrationin thenorth-

ern hemisphere(bold lines) andsouthernhemisphere.Observationalestimatesfrom the

HadISSTdataset(Rayneret al. 2003)areshown by dashedlinesfor eachhemisphere.

55

Figure13: Powerspectraof themonthlyNino 3.4anomaliesfor CCSM2,CCSM3,andthe

NCEPreanalysis(thick line) (Kistler et al. 2001). The rangeof variancespannedby the

spectraof individual 50-yearssegmentsareshown CCSM2(light hatching)andCCSM3

(darkhatching).

56

Figure14: DJF-mean2-metersurfacetemperaturefrom CCSM3(top), the Willmott and

Matsuura(2000)dataset(middle); andthedifferencebetweenCCSM3andtheWillmott

estimates(bottom).

57

Figure15: JJA-meanall-sky netsurfaceshortwaveflux from CCSM3(top left), theISCCP

FD dataset(Zhangetal. 2004)(topright), andthedifferencebetweenCCSM3andISCCP

(bottom).

58

Table1: Globalannual-meanradiativepropertiesof CCSM2andCCSM3(Wm � )

Flux / convergence CCSM2 CCSM3 Observation

Shortwaveatmosphericconvergence

all sky 66.7 74.6 70.9 >

clearsky 62.8 69.9 68.3 >

Shortwavecloudforcing � 48.3 � 54.0 � 54.1 ?

Shortwavesurfacenetall-sky flux 168.5 159.5 165.9>

Longwavesurfacenetflux

all sky 65.3 59.4 49.4 >

clearsky 93.6 86.1 78.7 >

> ISCCPFD (Zhanget al. 2004)

? ERBE(Harrisonet al. 1990;Kiehl andTrenberth1997)

59

Table2: Modelprecipitationfor continentalregions

Region RegionBox Precipitation Error> % Error>

(mm/day) (mm/day) (percent)

SEUnitedStates 30 N–40 N, 80 W–100 W 2.4 �������#/ ����%

Amazonia 10 S–10 N, 60 W–80 W 4.5 �4����� ����"

SEAsia 10 N–30 N, 80 E–110 E 3.1 �4����� ����%

> Error is computedrelative to theWillmott andMatsuura(2000)dataset.

60

Table3: Propertiesof westerncoastaloceanregions

Region Source SST Stress @BAC> @BAED FG>

(C) (Nm � ) (Wm � ) (Wm � )

Africa? Obs.F 21.7 0.052 221.0 290.1

CCSM3 25.2 0.051 215.6 286.9

SouthAmerica? Obs.F 19.7 0.045 212.5 288.0

CCSM3 21.5 0.039 208.9 285.7

> @BA and @BAED F denotethedownwelling surfaceshortwave flux for all-sky andclear-sky

conditions,respectively.

? The biasesarecomputedwithin 15 longitudeof the westerncoastsof Africa (be-

tween30 Sandequator)andSouthAmerica(between40 Sandequator).Thestressis the

magnitudeof thealong-shorecomponent.

F Observed SSTis from the HadISSTdataset (Rayneret al. 2003),surfacestressis

from theNCEPreanalysis(Kistler et al. 2001),andsurfaceinsolationis from the ISCCP

FD dataset(Zhanget al. 2004).

61

Table4: Control integrationsusingCCSM3

Resolution Present 1%CO� /yr 2 � CO� 4 � CO� 1780 1870 20th C

(years) (years) (years) (years) (years) (years) (years)

T85� 1 b30.009 b30.026 b30.026a b30.026b – b30.020 b30.030

(661) (161) (152) (153) (0) (235) (8 � 130)

T42� 1 b30.004 b30.025 b30.025a b30.025b b30.100 b30.043 –

(1001) (214) (301) (301) (499) (302) (0)

T31� 3 b30.031 b30.032 b30.032a b30.032b b30.105 b30.048 –

(748) (171) (157) (160) (433) (154) (0)

62