Atmospheric Models
Atmospheric models were the earliest models to be developed due to interest
in numerical weather prediction. Both numerical weather prediction models and
atmospheric general circulation models (AGCMs) used for climate modeling are
designed similarly.
Atmospheric processes have to be divided into two classes—model
dynamics and model physics —not to be confused with
dynamics and physics. Model dynamics are processes that can be characterized
by the grid-scale mean quantities, while model physics occur in spatial scales
smaller than the grid box. Thus, dynamics can be resolved explicitly by the
model, while physics cannot.
The part of the model code that describes the model dynamics is called the
dynamical core. The dynamical core models the large-scale dynamics,
or movement of air, and thermodynamics, or movement of heat, through the
atmosphere. The dynamics are described by Sir Isaac Newton's second law which
states that
the total acceleration of an object = the sum of forces acting on an object
/ the mass of the object
In the atmosphere, one can consider the object to be a parcel or small blob
of air. The forces acting on a parcel include the force exerted by a
horizontal pressure difference which would accelerate it towards lower
pressure, gravity downwards towards the center of the Earth, and frictional
drag. The rotation of the Earth also affects an air parcel. This can be
explained by imagining a ball moving away from the center of a rotating plate.
From above, the ball moves in a straight line, but an observer on the periphery
of the plate would notice that it moved away from him/her to the right. This
apparent misdirection of an object in a rotating environment is known as the
Coriolis effect. A constraint on what the dynamical core does is the
conservation of mass—no mass can be created or destroyed. For the
atmosphere that means that the same amount of mass coming into a grid volume
has to go out.
After the dynamics are completed, the model goes to the model physics. Even
though these are the processes that occur at scales smaller than the model grid
box, the grid mean quantities have to be used to find them. This is done
through parameterizations, a set of equations that are usually
empirical in nature to relate the sub-grid quantities to grid-scale quantities.
The processes that are parameterized in this way include convection that
generates cumulus clouds and thunderstorms, large-scale condensation and
evaporation of water, conversion of cloud water droplets to precipitation,
transmission and absorption of radiation through the atmosphere, the transfer
of heat, water vapor, and momentum at the surface, and atmospheric turbulence.
Ocean and Sea Ice Models
Like the atmosphere, the oceans are a fluid, so dynamics plays a key role in
the oceans as well. In fact, the same dynamical equations can be applied to
the oceans (Washington and Parkinson 2005). Like in the atmosphere, these
describe the large-scale motions. And there are processes that occur on scales
smaller than the model grid box. These include eddies which mix temperature in
the horizontal, vertical turbulence, and absorption of solar radiation.
However, there are some differences between ocean and atmospheric models.
Besides upper and lower boundaries, there are also lateral boundaries. Plus at
the upper boundary, the wind pushes the ocean currents. The ocean grid also
poses a unique problem. The ocean dynamics would become unstable at the North
Pole. So, the grid is adjusted so that the North Pole is located over a land
mass like Greenland.
Wind also pushes sea ice around, but because sea ice floats on top of sea
water, it also experiences a drag from ocean currents. The horizontal
transport can cause sea ice to diverge or to come together. When sea ice
collides together, it often compresses upward in ridges. Thus, there needs to
be vertical transport of ice. Ice can also grow from the bottom due to
freezing of sea water. The ice can also grow from above from snow falling on
top. In the summer, the ice can melt from the top with the meltwater
collecting in small pools called melt ponds. Thus, the thermodynamics within the
ice are fundamentally important. This is complicated by the presence of brine
pockets within the ice. The point of the sea ice model is to find two
quantities: sea ice area or fraction and ice thickness.
Land Models
The remaining model, the land model, has to model vegetation
characteristics, the infiltration of soil water and the movement of groundwater
horizontally, snow processes, and the diffusion of heat within the soil. The
ultimate goal is to determine the exchange of heat, moisture, and momentum
between the land surface and the air and the surface albedo, all of which are
affected by vegetation as pointed out in the first chapter.
In order for the land surface to be modeled, it has to be characterized.
How much of the surface within a grid cell is covered by vegetation? What type
of vegetation is it? Such characterizations start with global
land cover maps derived from satellite measurements like that of the
European Space Agency (ESA). Such maps differentiate between needle-leaf and
broadleaf forests, deciduous and evergreen forests, grassland, cropland,
shrubland, deserts, tundra, and ice-covered areas. Each one of these is then
assigned a characteristic roughness and albedo or the fraction of solar
radiation incident on the surface that is reflected.
The ESA map is very high resolution, and model grid boxes are much larger.
So, multiple land types have to be accounted for within a single grid box.
Therefore, a land grid box has to be divided into subboxes for each land type
that is contained within the whole grid box. Then, separate surface fluxes and
surface temperatures are calculated for each subbox, and the grid box average
is a weighted average of the subbox values.
There is added complexity in that the subboxes are inhomogeneous. Each
vegetated subbox has a vegetated and a bare ground fraction. Again, separate
fluxes and surface temperatures are calculate for the vegetated and bare ground
fractions. The vegetation canopy is another complication. The air below the
canopy is much different than the air above. Thus, the atmosphere really
interacts with the canopy not the ground. Also, the seasonal cycle of the
canopy has to be accounted for in deciduous forests.
Offline Mode
While each of these components make up a coupled global climate model, each
of these components except sea ice can be run offline or uncoupled. When they
are run offline, the model is forced by data that represents some or all of
the other components. For instance, the atmospheric model which is usually
still coupled to a land model is usually forced by observed sea surface
temperatures. The land and ocean models can be run completely uncoupled. They
are forced from near-surface quantities that are taken from an atmospheric
model run, from observations, or from reanalyses.
The purpose for running a model in offline mode is to ease a process study
or sensitivity test. By taking the other components out of the picture, you
standardize things, and any change in the results are due to changes made to
the model component and not to the response from other components. Of course,
the changes to the entire system have to be eventually simulated into the
fully coupled model.
References
Washington, W. M., and C. L. Parkinson, 2005: An Introduction to
Three-Dimensional Climate Modeling. University Science Books:
Sausalito, Calif.
