Coupled GCM The Challenges of linking the atmosphere and ocean circulation.
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Transcript of Coupled GCM The Challenges of linking the atmosphere and ocean circulation.
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)