UCLA atmospheric GCM is a state of the art grid point model of
the global atmosphere extending from the Earth's surface to a
height of 50 km. The model predicts the horizontal wind, potential
temperature, water vapor mixing ratio, cloud water and cloud ice
mixing ratios, planetary boundary layer (PBL) depth and the surface
pressure, as well as the surface temperature and snow depth over
land. The horizontal finite differencing of the primitive equations
is done on a staggered Arakawa "C" grid and is based
on a fourth order version of the scheme of Arakawa and Lamb (1981)
that conserves the potential enstrophy and energy when applied
to the shallow water equations (Takano and Wurtele 1982). The
differencing of the thermodynamic energy and water vapor advection
equations is also based on a fourth-order scheme. The
vertical coordinate used is the modified sigma-coordinate of Suarez
et al. (1983). In this coordinate, the lowest model layer is the
planetary boundary layer.
The vertical finite differencing is performed on a Lorenz-type
grid following Arakawa and Lamb (1977) above 100 mb and Arakawa
and Suarez (1983) below. This differencing is of second order
accuracy and is designed to conserve the global mass integrals
of potential temperature and total energy for adiabatic, frictionless
For the integration in time of the momentum,
thermodynamic energy and water vapor and cloud water/ice advection
equations, a leapfrog time-differencing scheme is used with a
Matsuno step regularly inserted. To avoid the use of the extremely
short timestep necessary to satisfy the CFL condition near the
poles, a longitudinal averaging (which takes the form of a Fourier
filter) is performed on selected terms in the prognostic equations
to increase the effective longitudinal grid size. The filter acts
poleward of 45 degrees latitude and its strength is gradually
increased towards the pole by increasing the number of affected
zonal wavenumbers and the amount by which they are damped (Arakawa
and Lamb 1977). A more localized spatial filter is applied to
the predicted PBL depths (Suarez et al. 1983) everywhere. A nonlinear
horizontal diffusion of momentum is included following Smagorinsky
(1963). The coefficient used is one order of magnitude smaller
than that used by Smagorinsky. The diffusion is applied at each
timestep, using a forward time differencing scheme. In layers
where an unstable stratification develops (potential temperature
decreasing with height), we assume that subgrid-scale dry convection
occurs and that the prognostic variables (horizontal momentum,
potential temperature and water vapor mixing ratio) in the layers
involved are mixed completely.
Planetary boundary layer processes are
parameterized using the mixed-layer approach of Suarez et al.
(1983). In this parameterization, surface fluxes are calculated
following the bulk formula proposed by Deardorff (1972). The formulation
of moist processes in the PBL and moisture exchange with the layer
above has been recently revised (Li et al. 1999, Li et al. 2002),
resulting in an improved simulation of the geographical distribution
and optical properties of PBL stratocumulus clouds. Parameterization
of cumulus convection, including its interaction with the PBL,
follows the prognostic version of Arakawa and Schubert (1974)
presented by Pan and Randall (1998). The effects of convective
downdrafts and vertical momentum and rainwater budgets are included
in the cumulus parameterization (Cheng and Arakawa 1997). The
current model version also includes an implementation of the prediction
scheme for cloud liquid water and ice due to Köhler (1999).
Parameterization of cumulus convection, including its interaction
with the PBL, follows Arakawa and Schubert (1974) and Lord et
al. (1982), with a relaxed adjustment time scale for the cloud
work function as described in Cheng and Arakawa (1994)> and
Ma et al. (1994). The parameterization of both long and shortwave
radiative heating follows Harshvardhan et al. (1987, 1989). The
ozone mixing ratios used in the radiation calculations are prescribed
as a function of latitude, height and time based on values from
a monthly UGAMP climatology (Li and Shine 1995) as used by Kim
et al. (1998). The cloud optical properties are specified following
Harshvardhan et al. (1989). This prescription makes a distinction
between stratiform clouds and "cumulus anvil"-type clouds.
"Cumulus anvil"-type clouds are assumed to exist at
each model layer above 400 mb where the cumulus mass flux is positive;
all other clouds are assumed to be stratiform-type clouds. The
effects of subgrid-scale orography are included via a gravity
wave drag parameterization and envelop orography ( Kim and Arakawa
1995, Kim 1996).
The geographical distribution of sea surface
temperature is prescribed using climatological or yearly varying
values from the Reynolds (1998) dataset; sea ice thickness and
extents are prescribed following Alexander and Mobley (1976).
Surface albedo and roughness lengths are specified following Dorman
and Sellers (1989), in which roughness lengths over land vary
according to the vegetation type. Daily values of these surface
conditions (as well as sea ice thickness) are determined from
the monthly mean values by linear interpolation.
The parallel version of the UCLA AGCM
code was designed for distributed memory multiple-instruction-multiple-data
(MIMD) computing environments (Wehner et al., 1995). It is based
on a two dimensional (longitud-latitude) domain decomposition,
message-passing strategy. Subdomains consist of vertical columns
from the Earth's surface to the top of the atmosphere. The code
is written in standard FORTRAN, including machine-architecture
independent directives that are expanded to machine-architecture
dependednt source code at pre-processing time. The has been ported
to and time in several machines including the SGI/Origin 2000,
IBM SP, CRAY T3E, Intel and Compaq Workstation clusters.
A., and W. H. Schubert, 1974: Interaction of a cumulus cloud
ensemble with the large-scale environment, Part I. J. Atmos.
Sci., 31, 674-701.
M.-D., and A. Arakawa, 1997: Inclusion of rainwater budget and
convective downdrafts in the Arakawa-Schubert cumulus parameterization.
J. Atmos. Sci. , 54, 1359-1378.
J. D., C. R. Mechoso and A. W. Robertson, 2000: Ensembles of
AGCM two-tier predictions and simulations of the circulation
anomalies during winter 1997-1998. Mon. Wea. Rev., 128, 3589-3604.
R. Davies, D. A. Randall and T. G. Corsetti, 1987: A fast radiation
parameterization for atmospheric circulation models. J. Geophys.,
Res., 92, 1009-1016.
D. A. Randall, T. G. Corsetti, and D. A. Dazlich, 1989: Earth
radiation budget and cloudiness simulations with a general circulation
model. J. Atmos. Sci., 46, 1922-1942.
Y. -J., 1996: Representation of subgrid-scale orographic effects
in a general circulation model: Part I. Impact on the dynamics
of simulated January climate. J. Climate, 9, 2698-2717.
Y.-J., J. D. Farrara and C. R. Mechoso, 1998: Sensitivity of
AGCM simulations to modifications in the ozone distribution
and refinements in selected physical parameterizations. J. Meteor.
Soc. Japan, 76, No. 5, 695-709.
J., N. Miller, J. D. Farrara and S. Hong, 2000: A numerical
study of precipitation and streamflow in the western United
States during the 1997-98 winter season. J. Hydrometeor., 1,
M., 1999: Explicit prediction of ice clouds in general circulation
models. Ph.D. Dissertation, Department of Atmospheric Sciences,
University of California, Los Angeles, 167 pp.
J.-L., A. Arakawa and C. R. Mechoso, 1999: Improved simulation
of PBL moist processes with the UCLA GCM. Proceedings, Seventh
Conference on Climate Variations, 2-7 February 1999, Long Beach,
CA, Amer. Meteor. Soc., 423-426.
C. R., A. Kitoh, S. Moorthi and A. Arakawa, 1987: Numerical
simulations of the atmospheric response to a sea surface temperature
anomaly over the equatorial eastern Pacific Ocean. Mon. Wea.
Rev., 115, 2936-2956.
C. R., S. W. Lyons and J. A. Spahr, 1990: The impact of sea
surface temperature anomalies on the rainfall over northeast
Brazil. J. Climate, 3, 812-826.
J.-L., M. Köhler, J. D. Farrara and C. R. Mechoso, 2002:
The impact of stratocumulus cloud radiative properties on surface
heat fluxes simulated with a general circulation model. Mon.
Wea. Rev., 130, 1433-1441.
C. R., L. A. Drummond, J. D. Farrara and J. A. Spahr, 1998:
The UCLA AGCM in high performance computing environments. Proceedings
of SuperComputing ’98, November, 1998, Orlando, Florida,
C. R., J.-Y. Yu and A. Arakawa, 2000: A coupled GCM pilgrimage:
From climate catastrophe to ENSO simulations. General circulation
model development: Past, present and future. Proceedings of
a Symposium in Honor of Professor Akio Arakawa, D. A. Randall,
Ed., Academic Press, pp. 539-575.
D.-M., and D. A. Randall, 1998: A cumulus parameterization with
a prognostic closure. Quart. J. Roy. Meteor. Soc., 124, 949-981.
M. J., A. Arakawa and D. A. Randall, 1983: The parameterization
of the planetary boundary layer in the UCLA general circulation
model: Formulation and results. Mon. Wea. Rev., 111, 2224-2243.