Abstract:
The Conformal-Cubic Atmospheric Model (CCAM) has been developed at
CSIRO over a number of years. CCAM is formulated on the conformal-cubic
grid, and employs 2-time-level semi-Lagrangian semi-implicit numerics.
The model is quite mature. It has mainly been used in dynamical
downscaling studies of climate change, but is also used for specialized
numerical weather prediction applications. CCAM employs reversible
staggering for the wind components (McGregor, MWR, 2005), producing
good wave dispersion behavior and also good behaviour for the kinetic
energy spectra. For treatment of non-hydrostatic flow, CCAM utilizes
the highly efficient equations of Miller and White (QJRMS, 1984).
Recently the CCAM code has been generalized to utilize the Uniform
Jacobian (UJ) variation of the cubed-sphere grid. This grid is derived
from the conformal-cubic grid to provide equal area for every grid
cell. Since the grid lines are no longer orthogonal, covariant and
contravariant velocity components are required. Apart from the
complications of the velocity components, most of the CCAM
semi-Lagrangian approach may be used, including reversible staggering
of the contravariant velocity components to switch between values at
cell centres and cell edges. The solver for the Helmholtz equation is a
little more complicated than for CCAM. A split-explicit version of CCAM
has also been developed, solving the primitive equations in flux form.
A major application of CCAM is for downscaling climate change
simulations of coupled atmosphere-ocean GCMs. The CSIRO downscaling
strategy utilizes forcing from the sea-ice and Sea Surface Temperatures
(SSTs) provided by chosen GCMs. Because the GCMs may have some
significant biases in their SSTs, the SSTs from each GCM are corrected
for their monthly biases in both mean value and variance, as calculated
from their 30-year present-day climatologies. The same monthly SST
corrections are applied throughout the simulations from each GCM. The
talk will include results from some recent CORDEX regional climate
downscaling simulations