Basics of numerical oceanic and coupled modelling
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Transcript of Basics of numerical oceanic and coupled modelling
Basics of numerical oceanic and coupled modelling
Antonio NavarraIstituto Nazionale di Geofisica e Vulcanologia
Italy
Simon MasonScripps Institution ofOceanography
USA
Sea Ice
Oceans
The Climate System
Biosphere
Soil MoistureRun-off
Atmosphere
PrecipitationEvaporation
Oceans -- Soil -- Cyosphere -- Biosphere
COOLING
HEATING
Latent Heat
Win
d St
ress
RAINEVAPORATION
Sensible Heat
REFL ECT IONEM
ISSI
ON
EMIS
SION
ABSO
RPTI
ONTRAN
SPORT
PRES
SIO
NE
Radiation
Temperature WaterVapor
TRANSPORT
Solar Radiation
EarthRadiationWind
Ocean Models
• All atmospheric GCMs have some form of ocean component, and all ocean models have some form of atmospheric component.
• Hierarchy of complexity: swamp ocean slab ocean detailed mixed-layer dynamical ocean
Atmosphere
Latent Heat Flux
Wind Stress
RAINEVAPORATION
Sensible Heat
Temperature
Currents
TRANSPORT
Solar Radiation
Salinity
TRANSPO
RT
Atmosphericradiation
Density
Swamp Slab Mixed-layer
Dynamicalnon-eddyresolving
Dynamicaleddy-resolving
Moistureexchange withatmosphereSea-surfacetemperaturecalculatedVerticaltransfer ofheatOceancurrents
Dynamical Models
• Important differences between ocean and atmosphere:
Dynamical Models
• Important differences between ocean and atmosphere:
Confined to only certain areas of the earth’s surface. Spectral representation is not used.
Dynamical Models
• Important differences between ocean and atmosphere:
Confined to only certain areas of the earth’s surface. Many of the important ocean models in climate prediction
are basin or sub-basin scale. Spectral representation is not used.
Smaller spatial scale of oceanic eddies compared to atmospheric eddies; also most transport is in relatively narrow ocean currents. Grid resolution needs to be much finer than in atmospheric GCMs.
Dynamical Models
• Important differences between ocean and atmosphere:
Confined to only certain areas of the earth’s surface. Spectral representation is not used.
Smaller spatial scale of oceanic eddies compared to atmospheric eddies; also most transport is in relatively narrow ocean currents. Grid resolution needs to be much finer than in atmospheric GCMs.
Much poorer observational data. Problems for initialization, verification, and parameterization
Dynamical Models
• Spatial scale:
eddy resolving models less than 0.25 resolution. non-eddy resolving models are at about 2. higher resolution required near equator, and near the
poles where currents are narrower. the coarser models are used in the fully coupled
models.
Dynamical Models
• Initialization: Problematic because of lack of observations (mainly
SSTs and surface height), very little sub-surface measurements, cf. atmospheric initialization given only surface data.
Spin-up the model using observed wind stress. Need to improve assimilation schemes – many
ocean models initialized with zero motion.
The BMRC Coupled Model
t=0
Forced Ocean Modelobs, SSTobs, ...
Assimilate Ocean
Data: T(z), , ...
FSU/BoM Winds BoM SST, SLEV
O G C MO G C MO G C MO G C M
A G C MA G C M
F O R E C A S TF O R E C A S T
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Integrate the coupled model for a period, e.g. two years, but impose observed surface temperature and salinity
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Robust Diagnostic
Spin-up
But sometimes the models are simply started from climatological conditions or, in the case of climate change experiments, theprocedure may become much more sophisticated to account for effectsfrom soil and ice.
Oceans -- Sea Ice
Atmosphere
Wind Stress Precipitation Solar Radiation
AtmosphericRadiation
AirTemperature
SeaSurface
TemperatureSensible Heat Flux Latent Heat Flux
Wind Stress Fresh Water Flux
Surface Temperature
COUPLER: (1) Interpolate from the atmospheric grid tothe ocean grid and vice versa.(2) Compute fluxes
Very Large Compiuters are
needed
Project of the Earth Simulator Computer (Japan) : objective, a globalcoupled model with 5km resolution
The main problem is how to synchronize the time evolution of the atmosphere with the evolution of the ocean. The most natural choice is to have a complete synchronization (synchronous coupling):
This choice would require to have similar time steps forboth models, for instance 30min for the atmospheric model and 2 hours for the ocean model.Computationally very expensive
Atmosphere
Ocean
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Another possibility is to exploit the different time scales using the fact that the ocean changes much more slowly than the atmosphere (asynchronous coupling):
Atmosphere
Ocean
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Integrate for a very long time
This choice save computational time at the expenseof accuracy, but for very long simulations (thousandsof years) may be the only choice.
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Integrate for avery long time
Sea Surface Temperature
High marine temperatures in the model are too narrowly confined to the equator, in the observations the warm pool is wider
Observations
Model
Coupled models can reproduce the over-all pattern, but they tend to be warmer than observations in the eastern oceans and colder in the western portions of the oceans
Dynamical Models
• Systematic bias is a major problem with dynamical ocean models (including coupled models).
Errors in the annual cycle Climate drift - the systematic bias depends on the
forecast lead-time.
Forecast model bias
• A comparison of the coupled model 12 month Nino3 forecasts [top panel] for February (blue), May (red), August (green), and November (brown) initial conditions average over all years, compared with climatology (purple). The bottom panel show the bias relative to this climatology.
ConclusionReally, there should be no conclusion. We have only started to understand the behaviour of coupled models and there is still a long way to go.