Japan Meteorological Agency: Model JMA GSM8911 (T42 L21) 1993

AMIP Representative(s)

Dr. Nobuo Sato, Dr. Toshiki Iwasaki, and Dr. Tadashi Tsuyuki, Numerical Prediction Division, Japan Meteorological Agency, 1-3-4 Ote-machi, Chiyoda-ku, Tokyo 100 Japan; Phone: + 81-03-3212-8341; Fax: +81-03-3211-8407; e-mail: /PN=N.SATO/O=JMA/ADMD=ATI/C=JP/@sprint.com (Sato) /PN=T.IWASAKI/O=JMA/ADMD=ATI/C=JP/@sprint.com (Iwasaki) /PN=T.TSUYUKI/O=JMA/ADMD=ATI/C=JP/@sprint.com (Tsuyuki)

Model Designation

JMA GSM8911 (T42 L21) 1993

Model Lineage

The JMA GSM8911 model first became operational in November 1989. This version is derived from an earlier global spectral model that is described by Kanamitsu (1983) [1].

Model Documentation

Key documentation of the model is provided by the Numerical Prediction Division's 1993 Outline of Operational Numerical Weather Prediction at Japan Meteorological Agency (hereafter Numerical Prediction Division 1993) [2] and by Sugi et al. (1989) [3].

Numerical/Computational Properties

Horizontal Representation

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

Horizontal Resolution

Spectral triangular 42 (T42), roughly equivalent to a 2.8 x 2.8 degree latitudelongitude grid.

Vertical Domain

Surface to 10 hPa. For a surface pressure of 1000 hPa, the lowest atmospheric level is at a pressure of 995 hPa.

Vertical Representation

Hybrid vertical coordinates which approximate conventional sigma coordinates at low levels and constant-pressure coordinates at upper levels (cf. Simmons and Burridge 1981) [4].

Vertical Resolution

There are 21 unevenly spaced hybrid levels. For a surface pressure of 1000 hPa, 6 levels are below 800 hPa and 7 levels are above 200 hPa.

Computer/Operating System

The AMIP simulation was run on a HITAC S-810 computer using a single processor in the HITAC VOS3/HAP/ES operational environment.

Computational Performance

For the AMIP experiment, about 2 minutes of HITAC S-810 computation time per simulated day.

Initialization

For the AMIP simulation, the initial model atmospheric state is specified from the ECMWF FGGE III-B analysis for 1 January 1993, with a nonlinear normal-mode initialization also applied (cf. Kudoh 1984) [5]. Soil moisture is initialized according to estimates of Willmott et al. (1985) [6], and snow cover/depth according to data of Dewey (1987) [7].

Time Integration Scheme(s)

Semi-implicit leapfrog time integration with an Asselin (1972) [8] time filter (cf. Jarraud et al. 1982) [9]. The length of the time step is not fixed, but is reset every 6 hours to satisfy the Courant-Friedrichs-Lewy (CFL) condition for the advection terms. Shortwave radiation is recalculated hourly, and longwave radiation every 3 hours.

Smoothing/Filling

Orography is truncated at the T42 model resolution (see Orography). When the atmospheric moisture content of a grid box becomes negative due to spectral truncation, its value is reset to zero without any other modification of the local or global moisture budgets.

Sampling Frequency

For the AMIP simulation, the model history is written every 6 hours, but some diagnostic variables are stored only once per month because of limited storage resources.

Dynamical/Physical Properties

Atmospheric Dynamics

Primitive equation dynamics are expressed in terms of vorticity, divergence, temperature, specific humidity, and surface pressure, as formulated by Simmons and Burridge (1981) [4] for hybrid vertical coordinates.

Diffusion

Fourth order linear (del^4) horizontal diffusion is applied to vorticity, divergence, temperature, and specific humidity on the hybrid vertical surfaces, but with a first-order correction of the temperature and moisture equations to approximate diffusion on constant-pressure surfaces (thereby reducing spurious mixing along steep mountain slopes). Diffusion coefficients are chosen so that the enstrophy power spectrum coincides with that expected from two-dimensional turbulence theory.
Stability-dependent vertical diffusion of momentum, heat, and moisture in the planetary boundary layer (PBL) as well as in the free atmosphere follows the Mellor and Yamada (1974) [10] level-2 turbulence closure scheme. The eddy diffusion coefficient is diagnostically determined from a mixing length formulated after the method of Blackadar (1962)[11]. See also Planetary Boundary Layer and Surface Fluxes.

Gravity-wave Drag

Orographic gravity-wave drag is parameterized by two schemes that differ mainly in the vertical partitioning of the momentum deposit, depending on the wavelength of the gravity waves. Long waves (wavelengths >100 km) are assumed to exert drag mainly in the stratosphere (type A scheme), and short waves (wavelengths approximately 10 km) to deposit momentum only in the troposphere (type B scheme). In both schemes the gravity-wave drag stress is a function of atmospheric density, wind, the Brunt-Vaisalla frequency, and subgrid-scale orographic variance (see Orography). (For the type B scheme, orographic variance is computed as an average difference of maximum and minimum heights within each 10-minute mesh.) In the type A scheme, the deposition of vertical momentum is determined from a modified Palmer et al. (1986) [12] amplitude saturation hypothesis. Because the momentum stress of short gravity waves decreases with altitude as a result of nonhydrostatic effects (cf. Wurtele et al. 1987) [13], the type B scheme assumes the wave stress to be quadratic in pressure and to vanish around the tropopause. Cf. Iwasaki et al. (1989a [14], b [15]) for further details.

Solar Constant/Cycles

The solar constant is the AMIP-prescribed value of 1365 W/(m^2). Both seasonal and diurnal cycles in solar forcing are simulated.

Chemistry

The carbon dioxide concentration is the AMIP-prescribed value of 345 ppm. Monthly averaged zonal ozone distributions are specified from data of McPeters et al. (1984) [16]. Radiative effects of water vapor, but not of aerosols, are also included (see Radiation).

Radiation

Shortwave radiation is parameterized differently for wavelengths <0.9 micron (visible) and >0.9 micron (near-infrared). In the visible, absorption by ozone, Rayleigh scattering by air molecules, and Mie scattering by cloud droplets are treated. In the near-infrared, water vapor absorption is modeled after Lacis and Hansen (1974) [17]. Near-infrared scattering and absorption by cloud droplets are calculated by the delta-Eddington approximation with constant single-scattering albedo.
Longwave absorption by water vapor, ozone, and carbon dioxide is determined from transmission functions of Rodgers and Walshaw (1966) [18], Goldman and Kyle (1968) [19], and Houghton (1977) [20], respectively; pressure broadening effects are also included. Continuum absorption by water vapor is treated by the method of Roberts et al. (1976) [21]. Transmission in four spectral bands (with boundaries at 4.0 x 10^3, 5.5 x 10^4, 8.0 x 10^4, 1.2 x 10^5, and 2.2 x 10^5 m^-1) includes overlapping effects of different absorbers. Longwave emissivity of cirrus cloud is set at 0.80, and that of all other clouds at 1.0 (blackbody emission). For purposes of the radiation calculations, all clouds are assumed to be randomly overlapped in the vertical. Cf. Sugi et al. (1989) [3] for further details. See also Cloud Formation.

Convection

A modified Kuo (1974) [22] parameterization is used to simulate deep convection. The criteria for the occurrence of convection include conditionally unstable stratification and positive moisture convergence between the cloud base and top. The cloud base is at the lifting condensation level for surface air, and the top is at a level where the cloud and environmental temperatures are identical. The cloud temperature is determined from the moist adiabatic lapse rate modified by height-dependent entrainment, as proposed by Simpson and Wiggard (1969) [23]. 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 moistening paramenter b is a cubic function of the ratio of the mean relative humidity of the cloud layer to a prescribed critical relative humidity threshold value (70 percent); if cloud relative humidity is less than this threshold, b is set to unity (no heating of the environment).
Shallow convection occurs where the vertical stratification is conditionally unstable but moisture convergence is negative. It is parameterized by enhancing the vertical diffusion coefficients after the method of Tiedtke (1983) [24].

Cloud Formation

No explicit convective cloud fraction is determined (see Convection). The stratiform cloud fraction is a quadratic function of the difference between the local relative humidity and a critical value that is empirically obtained from satellite observations, and that varies for low, middle, and high clouds (cf. Saito and Baba 1988) [25]. See also Radiation for treatment of cloud-radiative interactions.

Precipitation

The convective precipitation rate is determined from the variable moistening parameter b in the modified Kuo (1974) [22] convection scheme (see Convection). Any remaining supersaturation is removed by large-scale condensation. No subsequent evaporation of precipitation is simulated. See also Snow Cover.

Planetary Boundary Layer

The Mellor and Yamada (1974) [10] level-2 turbulence closure scheme (see Diffusion) represents the effects of the PBL through the determination of the Richardson number and the vertical wind shear. The PBL top is not explicitly computed. See also Surface Fluxes.

Orography

Orography is obtained from a U.S. Navy dataset (cf. Joseph 1980 [26] with resolution of 10 minutes arc on a latitude-longitude grid. These data are expressed as a series of spherical harmonics that are truncated at the T42 model resolution. Orographic variances that are also obtained from this dataset are used in the parameterization of gravity-wave drag (see Gravity-wave Drag).

Ocean

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

Sea Ice

Monthly AMIP sea ice extents are prescribed. The ice surface temperature is predicted by the force-restore method of Deardorff (1978) [27]. The forcing includes the net balance of surface energy fluxes (see Surface Fluxes) as well as conduction heating from the ocean below, which is computed assuming the ice to be a uniform 2-m thick and the ocean to be at the temperature for sea ice formation (about -2 degrees C). Snow is not allowed to accumulate on sea ice (see Snow Cover).

Snow Cover

Precipitation falls as snow if the temperature at the lowest atmospheric level (see Vertical Domain) is <0 degrees C. Snow may accumulate on land, but not on sea ice. The fractional coverage of a grid box is proportional to the water-equivalent snow depth up to 0.02 m; at greater depths, the proportionality constant varies with vegetation type. Snow cover alters the roughness and the albedo of bare and vegetated ground as well as the heat capacity and conductivity of soil, but sublimation from snow is not included in the surface evaporative flux. Snow melts (and contributes to soil moisture) if the ground surface temperature is >0 degrees C. See also Surface Characteristics, Surface Fluxes, and Land Surface Processes.

Surface Characteristics

Over land, the 12 vegetation/surface types of the Simple Biosphere (SiB) model of Sellers et al. (1986) [28] are specified at monthly intervals.
The local roughness length over land varies monthly according to vegetation type (cf. Dorman and Sellers 1989) [29]; it decreases with increasing snow depth, the minimum value being 5 percent of that without snow cover. The surface roughness of sea ice is a uniform 1 x 10^-3 m. Over oceans, the roughness length for momentum is a function of the surface wind stress after Charnock (1955) [30], while the roughness length for surface heat and moisture fluxes is specified as a constant 1.52 x 10^-4 m (cf. Kondo 1975) [31].
Over land, surface albedos vary monthly according to seasonal changes in vegetation (cf. Dorman and Sellers 1989) [29]. The albedo is specified separately for visible (0.0-0.7 micron) and near-infrared (0.7-4.0 microns) spectral intervals, and is also a function of solar zenith angle. Following Sellers et al. (1986) [28], snow cover alters the surface albedo. Over oceans and sea ice, albedos are functions of solar zenith angle but are independent of spectral interval.
Longwave emissivity is prescribed to be unity (blackbody emission) for all surfaces. See also Surface Fluxes and Land Surface Processes.

Surface Fluxes

Solar absorption at the surface is determined from the albedo, and longwave emission from the Planck equation with prescribed emissivity of 1.0 (see Surface Characteristics).
The representation of turbulent surface fluxes of momentum, heat, and moisture follows Monin-Obukhov similarity theory as expressed by bulk formulae. The wind, temperature, and humidity required for these formulae are taken to be the values at the lowest atmospheric level (at 995 hPa for a surface pressure of 1000 hPa). The associated drag/transfer coefficients are functions of the surface roughness (see Surface Characteristics) and vertical stability, following Louis et al. (1981) [32].
Over vegetated surfaces, the temperature and specific humidity of the vegetation canopy space of the SiB model of Sellers et al. (1986) [28] are used as surface atmospheric values. Over land, the surface moisture flux includes evapotranspiration from dry vegetation (reflecting the presence of stomatal and canopy resistances) as well as direct evaporation from the wet canopy and from bare soil (see Land Surface Processes).

Land Surface Processes

Land surface processes are simulated by the SiB model of Sellers et al. (1986) [28], as implemented by Sato et al. (1989a [33], b [34]). Vegetation in each grid box may consist both of ground cover and an upper-story canopy, with the spatial pattern of the ground cover varying monthly. Within the canopy, evaporative fluxes are computed by the Penman-Monteith method (cf. Monteith 1973) [35]. Evapotranspiration from dry leaves includes the detailed modeling of stomatal and canopy resistances. Direct evaporation from the wet canopy and from bare soil is also treated (see Surface Fluxes). Precipitation interception by the canopy (with large-scale and convective precipitation distinguished) is simulated, and infiltration of moisture into the ground is limited to less than the local hydraulic conductivity of the soil.
Soil temperature is predicted in four layers by the force-restore method of Deardorff (1978) [27]. Soil liquid moisture is predicted from budget equations in three layers, and snow and soil ice in four layers. This moisture is increased by infiltrated precipitation and snowmelt, and is depleted by evapotranspiration and direct evaporation. Both surface runoff and deep runoff from gravitational drainage are simulated. See also Surface Characteristics and Surface Fluxes.

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