In addition to the initial grid-point values described in the previous
section, the model also requires lower boundary conditions. The
required data are surface temperature ( at each ocean point, the
surface geopotential at each point, and a flag at each point to indicate
whether the point is land, ocean, or sea ice.
The land surface model requires its own boundary data, as described by
Bonan [22].
A surface temperature
and three subsurface temperatures must also be provided at non-ocean points.
For the uncoupled configuration of the model, a seasonally varying sea-surface temperature, and sea-ice concentration dataset is used to prescribe the time evolution of these surface quantities. This dataset prescribes analyzed monthly mid-point mean values of SST and ice concentration for the period 1950 through 2001. The dataset is a blended product, using the global HadISST OI dataset prior to 1981 and the Smith/Reynolds EOF dataset post-1981 (see Hurrell, 2002). In addition to the analyzed time series, a composite of the annual cycle for the period 1981-2001 is also available in the form of a mean ``climatological'' dataset. The sea-surface temperature and sea ice concentrations are updated every time step by the model at each grid point using linear interpolation in time. The mid-month values have been evaluated in such a way that this linear time interpolation reproduces the mid-month values.
Earlier versions of the global atmospheric model (the CCM series) included a simple land-ocean-sea ice mask to define the underlying surface of the model. It is well known that fluxes of fresh water, heat, and momentum between the atmosphere and underlying surface are strongly affected by surface type. The CAM 3.0 provides a much more accurate representation of flux exchanges from coastal boundaries, island regions, and ice edges by including a fractional specification for land, ice, and ocean. That is, the area occupied by these surface types is described as a fractional portion of the atmospheric grid box. This fractional specification provides a mechanism to account for flux differences due to sub-grid inhomogeneity of surface types.
In CAM 3.0 each atmospheric grid box is partitioned into three surface types: land, sea ice, and ocean. Land fraction is assigned at model initialization and is considered fixed throughout the model run. Ice concentration data is provided by the external time varying dataset described above, with new values determined by linear interpolation at the beginning of every time-step. Any remaining fraction of a grid box not already partitioned into land or ice is regarded as ocean.
Surface fluxes are then calculated separately for each surface type, weighted by the appropriate fractional area, and then summed to provide a mean value for a grid box:
The radiation parameterization requires monthly mean ozone volume mixing
ratios to be specified as a function of the latitude grid, 23 vertical
pressure levels, and time. The ozone path lengths are evaluated from
the mixing-ratio data. The path lengths are interpolated to the model
-layer interfaces for use in the radiation calculation. As with
the sea-surface temperatures, the seasonal version assigns the
monthly averages to the mid-month date and updates them every 12 hours
via linear interpolation. The actual mixing ratios used in the
standard version were derived by Chervin [32] from analysis of
Dütsch [52].
The sub-grid scale standard
deviation of surface orography is specified in the following manner.
The variance is first evaluated from the global Navy 10
topographic height data over an intermediate grid (e.g.
grid for T42
and lower resolutions,
for T63, and
for T106 resolution) and is assumed to be
isotropic. Once computed on the appropriate grid, the standard
deviations are binned to the CAM 3.0 grid (i.e., all
values whose latitude and longitude centers fall within each grid box
are averaged together). Finally, the standard deviation is
smoothed twice with a 1-2-1 spatial filter. Values over ocean are
set to zero.