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CAM(2+) Coupled to a Mixed Layer Ocean Model: Model Physics and Climate CCSM Workshop Santa Fe 2004 Christophe Cassou Mike Alexander Clara Deser

CAM(2+) Coupled to a Mixed Layer Ocean Model: Model Physics and Climate

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CAM(2+) Coupled to a Mixed Layer Ocean Model: Model Physics and Climate. Christophe Cassou Mike Alexander Clara Deser. CCSM Workshop Santa Fe 2004. In the code, COUP_MLM is equivalent to COUP_SOM, which allows for coupling with a Slab Ocean Model (SOM). Slab Ocean. Mixed Layer Model. - PowerPoint PPT Presentation

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Page 1: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

CAM(2+) Coupled to a

Mixed Layer Ocean Model:

Model Physics and Climate

CCSM Workshop Santa Fe 2004

Christophe CassouMike Alexander

Clara Deser

Page 2: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

What is the COUP_MLM option?

Coupling between CAM (2+) - ocean Mixed Layer Model (MLM) - the thermodynamic portion of the NCAR sea ice model (CSIM4)

In the code, COUP_MLM is equivalent to COUP_SOM,which allows for coupling with a Slab Ocean Model (SOM)

Slab Ocean

Tm Fixed H

Qnet

Tm = Qnet/cH

Qcor

+Qcor/cH

Mixed Layer Model

Tm/Sm

Qnet Qcor

Tb/Sb

Varying H

Accounts for vertical processes

1.1 Introduction : the model

Page 3: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

An individual column model with a uniform mixed layeratop a layered model that represents conditions in the pycnocline

MLM model: Alexander et al (2002, J. Clim) based on Gaspar’s (1988, JPO) formulation

Model characteristics:• Same grids as the atmosphere (128 lon x 64 lat)• 36 vertical levels (from 0m to 1500m depth) with a better resolution close to surface (10 levels for the first 50m)• Realistic bathymetry

MLM in more detail 1.2 Introduction : the model

Page 4: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

h (MLD)

Tb1

Tm1

Qnet Qcor

Qswh

SolarPenetration

Qwe

VerticalEntrainment

(We from turbulentKinetic energy equation)

CA

ConvectiveAdjustment

Diffusion

Mixed layer Temperature change in MLM 1.3 Introduction: the model

Page 5: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

Below ice there is fresh water flux due to: - ice volume change

- brine ejectionweighted by the ice fraction

The salinity equation 1.4 Introduction: the model

Page 6: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

Departure between 80yr mean and observed (HADISST) climatology

SST bias tied to ice (ovals)-ice melts early Labrador Sea-Ice melt late north of Russia

January

July

Max : +0.8

Max : +1

Max : +1.2

SST too warm in summerdue to over-estimated shoaling

SST biais 2.1 Validation of the climatology

Page 7: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

80y mean MLD for January-February-March average

Underestimatesof the MLD

Correct representationOver the main atm. Baroclinic zone

Overestimation over theTrade winds domain and no diurnal cycle

Mixed Layer Depth 2.2 Validation of the climatology

Page 8: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

Model(80y mean)

Observations

March September

Ice concentration (Northern Hemisphere) 2.3 Validation of the climatology

Realistic SI Extentbut UNrealisticSI Thickness

Page 9: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

Model(80y mean)

Observations

March September

Ice concentration (Southern Hemisphere)

2.4 Validation of the climatology

Page 10: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

EOF1 for DJF SST(contour) /Regressed precipitation (filled)

PC1 (bars)/5yr-running mean (green line)Regressed MSLP

Variability in the Indian Ocean and its links to the atmosphere 3.1 Variability

Page 11: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

SVD between SST(color) and MSLP (contour) FMA season

No significant auto-corr.for MSLP (white noise) +Quasi-biennal dominant peak

Years

SST

MSLP

MSLPSST

Reddening of the SSTspectrum

Variability in the North Pacific 3.2 Variability

Page 12: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

SVD between SST(color) and MSLP (contour) FMA season

Years

SST

MSLP

MSLPSST

No significant auto-corr.for MSLP (white noise) +Quasi-biennal dominant peak

Reddening of the SSTspectrum

Variability in the North Atlantic 3.3 Variability

Page 13: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

EOF1 for DJF MSLP(contour) Regressed SST(filled)

Regressed ice frac

More Ice Less Ice

Regressed Mixed Layer Depth

Deeper

Shallower

White spectrum with a strongquasi-biennal peakStrongly linked to the Artic Oscillation

The North Atlantic Osciallation 3.4 Variability

Page 14: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

From March (0)

May (+2)

60

30

Jan (+10)

+0.6

Oct (+7)

+0.5

Persistence of SST anomalies : Monthly Autocorrelation 3.5 Variability

Page 15: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

3D SVD between JAS Ocean Temperature[30m-400m] (color @30m) and previous FMAMSLP (contour)

Relationship between the deep ocean and the surface atmosphere 3.6 Variability

Page 16: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

From March (0)

Oct (+7) Jan (+10)

May (+2)

60

30

+0.6+0.5

Reemergence mechanism

The Reemergence mechanism 3.7 Variability

Page 17: CAM(2+) Coupled to a  Mixed Layer Ocean Model: Model Physics and Climate

Discussion

• Model has run for more than 150 years now and appears to be stable (basic climate variability structures are correctly simulated, some biais though –model and configuration)

• Originally MLM coupled to CAM2 plan is to support with newer versions of CAM (coupled with CAM3 in progress)

• Ocean can be a mix of specified SSTs and MLM (e.g. observed SSTs specified in the tropical Pacific)

• Useful for a wide variety of coupled model studies: between CAM-SOM CCSM (Reemergence experiments running right now)

• Will be used in climate@home project (See J. Hansen, MIT)