Main Geophysical Observatory: Model MGO AMIP92 (T30 L14) 1992

AMIP Representative(s)

Dr. Valentin Meleshko, Voeikov Main Geophysical Observatory, 7 Karbyshev Str., 194018 St. Petersburg, Russia; Phone: +7-812-247-01-03; Fax: +7-812-247-01-03; e-mail: vmeleshk@mgo.spb.su

The MGO model was first employed in research in 1983 (cf. Meleshko et al. 1980 [1] and Sokolov 1986 [2]). The current third generation model includes enhancements in the simulation of radiative transfer; vertical turbulent exchange of heat, moisture, and momentum between the surface and the atmosphere; and heat and moisture exchange in the soil.

Model Documentation

Key documentation of the model is provided by Meleshko et al. (1991) [3].

Numerical/Computational Properties

Horizontal Representation

Spectral (spherical harmonic basis functions) with transformation to a Gaussian grid for calculation of nonlinear quantities and some physics.

Horizontal Resolution

The spectral triangular truncation is at total wave number 30 (T30), roughly equivalent to a 3.75 x 3.75-degree 1atitude-longitude grid.

Vertical Domain

Surface to 12.5 hPa. For a surface pressure of 1000 hPa, the lowest atmospheric level is at 992 hPa.

Vertical Representation

Thermodynamically consistent finite difference formulation in sigma coordinates with momentum conservation (cf. Sheinin 1987 [4] and Magazenkov and Sheinin 1988 [5]).

Vertical Resolution

There are 14 irregularly spaced sigma levels. For a surface pressure of 1000 hPa, 5 levels are below 800 hPa and 4 levels are above 200 hPa.

Computer/Operating System

The AMIP simulation was run on a Cray 2 computer using a single processor in a UNICOS environment.

Computational Performance

For the AMIP experiment, about 6 minutes of Cray 2 computation time per simulated day.

Initialization

For the AMIP simulation, the model atmosphere is initialized for 1 January 1979 from ECMWF analyses. Initial conditions for soil moisture and snow cover/mass are taken from mean-January ECMWF climatologies.

Time Integration Scheme(s)

The main time integration is done by a two-step semi-implicit method (cf. Sheinin 1983) [6], but an Euler-backward scheme is used for the vertical transport of momentum, heat, and moisture, which are split from other physical processes (see Surface Fluxes). The time step length is 30 minutes for dynamics and physics, except for full radiation calculations which are done once every 12 hours.

Smoothing/Filling

High-resolution topography is adjusted to the model's resolution by means of a special filter (see Orography). Negative values of moisture are filled by a horizontal and vertical borrowing procedure.

Sampling Frequency

For the AMIP simulation, the model history is written once every 24 hours.

Dynamical/Physical Properties

Atmospheric Dynamics

Primitive-equation dynamics are expressed in terms of vorticity, divergence, virtual temperature, specific humidity, and surface pressure.

Diffusion

There is second-order horizontal diffusion of vorticity, divergence, temperature, and specific humidity on sigma surfaces for total spectral wave numbers >23 (cf. Laursen and Eliasen 1989) [7].
Stability-dependent vertical diffusion of atmospheric momentum, temperature, and specific humidity is modeled (cf. Louis 1979) [8].

Gravity-wave Drag

The formulation of gravity-wave drag follows McFarlane (1987) [9]. Deceleration of the resolved flow by dissipation of orographically excited gravity waves is a function of the rate at which the parameterized vertical component of the gravity-wave momentum flux decreases in magnitude with height. This momentum-flux term is the product of local air density, the component of the local wind in the direction of that at the near-surface reference level, and a displacement amplitude. At the surface, this amplitude is specified in terms of the subgrid-scale orographic variance, and in the free atmosphere by linear theory, but it is bounded everywhere by wave saturation values. See also Orography.

Solar Constant/Cycles

The solar constant is the AMIP-prescribed value of 1365 W/(m^2). A seasonal, but not a diurnal cycle in solar forcing, is simulated.

Chemistry

The carbon dioxide concentration is the AMIP-prescribed value of 345 ppm. The ozone concentration is prescribed as a function of latitude and season from Nimbus 7 data (cf. McPeters et al. 1984) [10]. Radiative effects of water vapor and trace gases (methane, nitrous oxide, and chlorofluorocarbon compounds CFC-11 and CFC-12) are also included, but not those of aerosols (see Radiation). Global vertical profiles for the trace gases are specified from the U.S. Standard Model Atmosphere Profiles.

Radiation

The shortwave fluxes are computed in three subranges: ultraviolet (0.2 to 0.31 micron), visible (0.31 to 0.75 micron), and near-infrared (0.75 to 4.0 microns). Fluxes in the ultraviolet and visible subranges are computed following Karol (1986) [11]. In the ultraviolet subrange, only ozone absorption is considered, and the effects of scattering are neglected. Within the visible subrange, absorption by ozone and Rayleigh scattering are accounted for using the delta-Eddington approximation. In the near-infrared sub-range, absorption by water vapor in 12 spectral bands and by carbon dioxide in 6 bands is determined using a Goody statistical band model (cf. Rozanov and Frolkis 1988) [12].
The longwave fluxes are computed in 9 spectral intervals over the range 0 to 2.2 x 10^5 m^-1, accounting for absorption by water vapor, carbon dioxide, ozone, and trace gases (see Chemistry). The flux computation is based on the Goody statistical band model, and its parameters depend on temperature (cf. Karol 1986). Water vapor continuum absorption is by the method of Roberts et al. (1976) [13].
The optical properties of clouds are prescribed (cf. Gordon et al. 1984) [14], with cloud albedo depending on solar zenith angle. Convective cloud is assigned the same optical characteristics as the lower stratiform cloud. The longwave emissivity of high stratiform cloud depends on cloud temperature; it ranges linearly between 0.5 and 1.0 for temperatures from -30 degrees C to -20 degrees C, and is fixed for temperatures beyond this range. All other clouds emit as blackbodies (emissivity of 1.0). For purposes of the radiation calculations, stratiform clouds of different types are assumed to be randomly overlapped in the vertical, and convective clouds to be fully overlapped. See also Cloud Formation.

Convection

A Kuo (1974) [15] scheme is used for simulation of deep convection (cf. also Louis 1984) [16]. Convection is assumed to occur only in the presence of conditionally unstable layers in the vertical and large-scale net moisture convergence in the horizontal. The associated convective cloud formed at the lifting condensation level is assumed to dissolve instantaneously through lateral mixing, thereby imparting heat and moisture to the environment. In a vertical column, the total moisture available from convergence is divided between a fraction b that moistens the environment and the remainder (1 - b) that contributes to the latent heating (rainfall) rate. The value of (1 - b) is taken to be the ratio of the integral moisture content in a convective layer to the integral saturation moisture content of this layer (cf. Meleshko et al. 1991) [3].
Shallow convection is formulated as a convective adjustment process for moisture only.

Cloud Formation

Cloud formation follows the diagnostic technique of Slingo (1987) [17]. There are three types of layer clouds (low, middle, and high) that are associated with large-scale disturbances. These clouds are present only when the relative humidity exceeds threshold values of 90, 93, and 98 percent for high, middle, and low layers, respectively. The layer cloud amount is a quadratic function of this humidity excess.
The vertical depth of convective cloud is determined from the thickness of the unstable layers, and the areal extent from the logarithm of the convective precipitation rate (cf. Slingo 1987) [17]. Of the total cloud amount, 25 percent is assigned to the convective column clouds in the unstable layers, while 75 percent is assigned to the lowest unstable layer. Convective anvil cloud forms when the instability extends above the 400 hPa level and the convective cloud fraction exceeds 0.20; the anvil cloud fraction cannot exceed 0.80. See also Radiation for treatment of cloud-radiative interactions.

Precipitation

Large-scale precipitation forms when the local relative humidity exceeds 100 percent. Convective precipitation is determined from the complement of the moistening parameter b in the Kuo scheme (see Convection). Subsequent evaporation of precipitation is not simulated. See also Snow Cover.

Planetary Boundary Layer

The top of the boundary layer is assumed to coincide with the middle of the lowest atmospheric layer (sigma = 0.992). In computing surface fluxes of momentum, heat, and moisture from bulk formulae (see Surface Fluxes), the surface wind is assigned the same value as at this lowest model level. The surface air temperature and specific humidity are determined from a surface heat balance equation and from surface wetness and soil moisture. See also Diffusion, Surface Characteristics, and Land Surface Processes.

Orography

1 x 1-degree topography of Gates and Nelson (1975) [18] is smoothed with a special filter (cf. Hoskins 1980) [19] and truncated at the model's spectral T30 resolution (see Horizontal Resolution). High-resolution (6 x 6 minutes arc) topographic data are used for computation of orographic variances that are required for the gravity-wave drag parameterization (see Gravity-wave Drag).

Ocean

AMIP monthly sea surface temperatures are prescribed, with daily values determined by linear interpolation.

Sea Ice

AMIP monthly sea ice extents are prescribed. Ice thickness is specified from the climatology of Bourke and Garrett (1987) [20] and Jacka (1983) [21], and snow is allowed to accumulate on sea ice (see Snow Cover). A two-layer scheme is used for predicting the temperatures of sea ice/snow layers from the surface energy balance (see Surface Fluxes) with the inclusion of a heat flux from the ocean below.

Snow Cover

Precipitation falls as snow if the surface air temperature is <273 K. Snow thickness is determined from the prognostic value of snow mass and density, assumed to be 200 kg/(m^3); fractional coverage of a grid box by snow is not allowed. Snow cover affects the surface albedo of land and of sea ice (see Surface Characteristics), as well as the soil heat conductivity (see Land Surface Processes). Snowmelt contributes to soil moisture (see Land Surface Processes), and sublimation of snow is included in the surface evaporative flux (see Surface Fluxes).

Surface Characteristics

Different surface types (land/ocean/ice) may coexist in a grid box, and composite averages of surface quantities are computed in these cases (see Surface Fluxes and Land Surface Processes).
The roughness length over land is a prescribed function of orography and vegetation type (cf. Louis 1984) [16]. Over ice surfaces, the roughness length is uniformly specified as 0.01 m. Over the oceans, the dependence of roughness length on surface wind stress follows Charnock (1955) [22], with a dimensionless factor of 0.018 (cf. Ariel and Murashova 1981) [23]. For a surface wind speed <1 m/s, a minimum ocean roughness is determined from an asymptotic relationship (cf. Zilitinkevich 1970) [24].
Annual mean surface albedos are prescribed for bare soil and vegetation after data of Wilson and Henderson-Sellers (1985) [25]. The ocean surface albedo is 0.06, independent of solar zenith angle. The albedo of glacial ice on Greenland and Antarctica is 0.80, while the albedo of sea ice is a function of surface temperature (cf. Wilson and Mitchell 1987) [26]. The albedo of snow-covered land depends on the annual mean background albedo, the liquid snow equivalent, and the maximum snow albedo.
Longwave emissivity is prescribed as unity (blackbody emission) for all surfaces.

Surface Fluxes

Shortwave absorption is determined from surface albedos, and long wave emission from the Planck equation with emissivity of 1.0 (see Surface Characteristics).
Simulation of the vertical turbulent exchange of heat, moisture, and momentum is based on Monin-Obukhov similarity theory. The values of the momentum, heat, and moisture fluxes over an inhomogenous surface are area-weighted averages of the flux from each surface type in the grid box (see Surface Characteristics), and the surface drag and transfer coefficients depend on roughness length and vertical stability (cf. Louis 1979) [8]. The surface moisture flux includes sublimation from snow-covered surfaces; it also depends on the evapotranspiration efficiency beta, which is prescribed as unity over ocean, snow, and ice surfaces, but which over land is a function of soil moisture (see Land Surface Processes).
Time integration of the vertical turbulence equations is performed using the Euler-backward scheme with splitting (see Time Integration Scheme(s)).

Land Surface Processes

Soil temperature is computed by a three-layer model with thicknesses 0.1, 0.9, and 2.0 m, from top to bottom. The thickness of the top soil layer (0.1 m) is increased when snow accumulates (see Snow Cover). The thermodynamic properties of this layer are calculated as thickness-weighted averages of those of the two media; otherwise, the properties of the soil are assumed to be spatially uniform. When snow melts, the surface temperature remains constant (273 K) until all the snow disappears. Heating of the soil is computed from an energy-balance equation with the net surface heat fluxes (see Surface Fluxes) as the upper boundary condition and with zero heat flux assumed at the lower boundary of the bottom soil layer (at 3 m depth).
Soil moisture is prognostically determined in two layers, with thicknesses the same as those of the two upper layers of the soil heat model (0.1 and 0.9 m). Moisture from precipitation and snowmelt can accumulate in either layer, and can diffuse upward from the bottom layer (with constant diffusion coefficient 2.5 x 10^6 m^2/s). The hydraulic conductivity is computed by the method of Milly and Eagleson (1982) [27]. The field capacity for moisture in the upper layer is a function of soil and vegetation types (cf. Wilson and Henderson-Sellers 1985 [25]), and soil moisture is depleted by evapotranspiration and runoff. The evapotranspiration efficiency beta (see Surface Fluxes) depends on the ratio of soil moisture to the spatially uniform field capacity. Following Warrilow et al. (1986) [28], the surface runoff from the upper layer is a function of the precipitation type (large-scale or convective), while runoff from the lower layer is computed assuming that its moisture holding capacity cannot exceed the field capacity (cf. Meleshko et al. 1991) [3].

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