Coupled GCM

The Challenges of linking the atmosphere and ocean

circulation

Brief History of LRF

Statistical and Analog - earliest Simple models and

Teleconnections Coupled Models with dynamic and

statistical components Dynamic Coupled Atmosphere-

Ocean Models

GCM Model Matters

Grid Spacing• dependent on

coordinate system for globe

• dependent on computer space

Time Step• dependent on

resolution and length of forecst

Terrain and Ocean Mapping• generally rough

with little detail Parameterize

• solar radiation• convection• heat flux• wind stress

The Interface

Oceans• Sea Surface

Temperature• evaporation

• Mixed Layer• heat flux/transport

• Annual cycles• upwelling• Pacific circulation

Atmosphere• Solar Energy

• sun angle• cloud cover

• Wind Stress• mixing layer

• estimate profile

• Heat & Moisture Transport

• shallow and deep convection

Coupled GCM’s Focus

Tropical Oceans - Pacific• Initial Conditions

• Atmosphere• inferred from spotty observations and detailed

satellite analysis

• Ocean• uses a data set developed by Florida State

University which shows climatology of temperature and wind stress

CGCM’s - Many Models

Center for Ocean-Land-Atmosphere Std

Geophysical Fluid Dynamics Lab (GFDL)

NASA-Lamont Doherty (Columbia Univ)

Scripps Institute UCLA NCEP Max Plank

Institute Bureau of

Meteorology Research Centre

The COLA’s Model

The Ocean Portion• Adapted from GFDL - for Pacific

Domain from 30S-45N &130E-80W• Resolution: x=1.5 y=.5 (20S-20N) 1.5

degrees elsewhere• 20 vertical levels to 4000m - 1-16 are

within the top 40m• non-linear vertical mixing of heat,

salinity and momentum

The COLA’s Model

The Atmosphere Portion• Global Spectral Model with 30 wave limit• 18 layers on a sigma coordinate• Solar radiation is parameterized• Deep convection - modified Kuo• Shallow convection - Tiedtke • Complex scheme for exchange of heat,

moisture and momentum

Coupling Strategy

Several Methods• Interpolated Exchange• Anomaly Coupling • Mixed Methods

Significance of Ocean-Atmosphere Exchange is especially important in the Tropics

Coupling Strategy

Interpolated Exchange• Daily mean values are exchanged

• OGCM produces SST for Atmosphere• AGCM produces surface heat flux,

momentum and freshwater (rainfall) for the Oceans

• These values are parameterized and interpolated for grid points in each model

Coupling Strategy

Anomaly Coupling• Each part of the model predicts and

anomaly component compared with a set model climatology.

• Atmosphere climatology - 45 years (1949-94)

• Ocean climatology - 30 years (1964-94)

Coupling Strategy

Start with Atmosphere (AGCM) predicts solar-radiation to estimate SST for Ocean

SST is used to predict a wind profile in the tropical boundary layer - the anomaly component of this profile is used for adding to the wind stress on the ocean.

Experimental Long Lead Models

Coupled GCM from COLA - now uses anomaly of initial conditions from an in-house ocean data assimilation analysis

Coupled GCM from COLA using interpolated values from AGCM and OCM

Hybrid Coupled Ocean-Atmos Model - Scripps-Max Plank

2004 Model Forecast

CPC/EMC• GFDL Ocean• MRF reduced• Ensemble-16• updated wkly

• http://www.emc.ncep.noaa.gov/cmb/sst-forecasts/

2004 Model Forecasts

Scripps Plank

• Hybrid • 30S-30N• 13 vertical• AGM - Stat• mainly wind

stress

2004 Model Forecasts

Japan Meteo Agency

AGCM (T42/40 levels)

OGCM (T 20 levels)• 2.5 x 2.0• Flux Exchanges

every 24 hrs for mean values

2004 Model Forecast

LDEO Model - wind stress Focus on

initialization Ensemble of

3 wind stresses • FSU,NCEP,QUIKSCAT

2004 Model Forecast

Markov Model of SST - CPC

Linear Statistics trained 1980-95

Verified by 1964-1979

2004 Model Forecast

LIM (Linear Inverse Model) from CIRES/CDC - Boulder

Uses a specific Stat function (Green)

2004 Model Forecast

Constructed Analog (Van Den Dool)

Uses past anomalies as predictors

2004 Model Forecast

IRI Summary All Models;

Statistical & Dynamic

Long Lead Predictions

Summary of 2004 Model Forecasts

Long Lead Predictions

Forecast of SST in Tropical Pacific with a Markov Model - NCEP (linear statistical)

Tropical SST’s using a Linear Inverse Model- CIRES - Boulder

Tropical Pacific SST using and intermediate ocean and statistical atmosphere model - Earth Environmental Studies - Seoul

Further Readings

http://grads.iges.org/ellfb/contents.htm • - (updated every 3 months)