The 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 flows.

    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.


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