the PMIP models (Bonfils et al. 1998)
PMIP Documentation for GEN1
National Center for Atmospheric
Research / Pennsylvania State University: Model GENESIS 1.02A (R15 L12)
Dr. Karl E. Taylor, Program for Climate Model Diagnosis and Intercomparison
(PCMDI), Lawrence Livermore National Laboratory, Livermore, CA, 94550,
USA, Phone: 925 423 3623, Fax: 925 422 7675; email: firstname.lastname@example.org
Dr. Lisa C. Sloan, Earth Sciences Department, University of California,
Santa Cruz, CA, 95064, USA, Phone: 408 459 3693, Fax: 408 459 3074; email:
Dr. Starley L. Thompson, P.O. Box 3000, National Center for Atmospheric
ResearchC0 80307, USA, Phone: 303 497 1628; Fax: 303 497 1348; email: email@example.com
Dr. David Pollard, Earth System Science Center, Pennsylvania State University,
University Park, PA 16802, USA, Phone: 814 863 3673; Fax: 814 865-2022;
GENESIS 1.02A (R15 L12) 1992
Model Identification for PMIP
Number of days in each month: 31 28 31 30 31 30 31 31 30 31 30 31
The global climate model used for PMIP is Version 1.02A of GENESIS (Global
ENvironmental and Ecological Simulation of Interactive Systems). It has
been developed at NCAR Interdisciplinary Climate Systems Section. The model
consists of an AGCM coupled to multilayer models of vegetation, soil or
ice land, snow, sea ice, and 50-m slab oceanic layer. The AGCM originated
from NCAR Community Climate Model version 1 (CCM1, described in Williamson
et al. 1987), but the physics schemes differ significantly from those of
Pollard, D., and S.L. Thompson, 1992: Users' guide to the GENESIS Global
Climate Model Version 1.02. Interdisciplinary Climate Systems Section,
National Center for Atmospheric Research, Boulder, Colorado, 58 pp.
Pollard, D., and S.L. Thompson, 1995: Use of a land-surface-transfer
scheme (LSX) in a global climate model: the response to doubling stomatal
resistance. Glob. Plan. Change, 10, 129-161.
Thompson, S.L., and D. Pollard, 1995: A global climate model (GENESIS)
with a land-surface-transfer scheme
(LSX). Part 1: Present climate simulation. J. Climate, 8, 732-761.
Spectral (spherical harmonic basis functions) with transformation to an
appropriate nonuniform Gaussian grid for calculation of nonlinear atmospheric
quantities. The surface variables (see Ocean, Sea Ice, Snow Cover, Surface
Characteristics, Surface Fluxes, and Land Surface Processes) are computed
on a uniform latitude-longitude grid of finer resolution (see Horizontal
Resolution). Exchanges from the surface to the atmosphere are calculated
by area-averaging within the coarser atmospheric Gaussian grid, while bilinear
interpolation is used for atmosphere-to-surface exchanges. Atmospheric
advection of water vapor (and, on option, other tracers) is via semi-Lagrangian
transport (SLT) on the Gaussian grid using cubic interpolation in all directions
with operator-splitting between horizontal and vertical advection (cf.
Williamson and Rasch 1989 and Rasch and Williamson 1990).
Spectral rhomboidal 15 (R15), roughly equivalent to 4.5 x 7.5 degrees latitude-longitude.
The spectral orography (see Orography) is present at the same resolution,
but other surface characteristics and variables are prescribed or calculated
on a uniform 2 x 2-degree latitude-longitude grid. See also Horizontal
dim_longitude*dim_latitude:48*40 for AGCM
dim_longitude*dim_latitude: 180*90 for surface
Surface to ??? hPa; for a surface pressure of 1000 hPa, the lowest atmospheric
level is at 991 hPa and the uppermost level is at 9 hPa.
Finite-difference sigma coordinates are used for all atmospheric are employed.
Energy-conserving vertical finite-difference approximations are utilized,
following Williamson (1983 , 1988).See also Horizontal Representation and
There are 12 unevenly spaced sigma-coordinate in the vertical with the
following levels: 0.009, 0.025, 0.060, 0.110, 0.165, 0.245, 0.355, 0.500,
0.664, 0.811, 0.926, 0.991 (or, for water vapor, hybrid sigma-pressure
levels--see Vertical Representation). For a surface pressure of 1000 hPa,
3 levels are below 800 hPa and 5 levels are above 200 hPa.
The PMIP simulations were run on Cray Y/MP ??? computers in a UNICOS???
For the PMIP experiment, the model used about 2 minutes of Cray Y/MP computer
time per simulated day.
The PMIP experiments were started from a previous multi-decadal present-day
simulation and were spun up for at least 2 decades.
Time Integration Scheme(s)
Time integration is by a semi-implicit Hoskins and Simmons (1975) scheme
with an Asselin (1972) frequency filter. The time step is 30 minutes for
dynamics and physics, except for full radiation calculations. The longwave
fluxes are calculated every 30 minutes, but with absorptivities/emissivities
updated only once every 24 hours. Shortwave fluxes are computed at 1.5-hour
intervals. See also Radiation.
Orography is area-averaged (see Orography). Because of the use of the SLT
scheme for transport of atmospheric moisture (see Horizontal Representation),
spurious negative specific humidity values do not arise, and moisture filling
procedures are therefore unnecessary.
For the PMIP simulation, monthly averages of model variables are saved.
Primitive-equation dynamics are expressed in terms of vorticity, divergence,
potential temperature, specific humidity, and the logarithm of surface
In the model troposphere, there is linear biharmonic (Ñ4)
horizontal diffusion of vorticity, divergence, temperature, and specific
humidity. In the model stratosphere (top three vertical levels), linear
second-order (Ñ2) diffusion
operates, and the diffusivities increase with height. The horizontal dvection
of all fields is on constant sigma surfaces (see Vertical Representation).
The vertical diffusion of heat, momentum, and moisture is simulated
by the explicit modeling of subgrid-scale vertical plumes (see Planetary
Boundary Layer and Surface Fluxes).
For the PMIP experiments, the solar constant is the AMIP-prescribed value
of 1365 W/(m2). The orbital parameters and seasonal insolation
distribution are calculated after PMIP recommendations. Both seasonal and
diurnal cycles in solar forcing are simulated.
The carbon dioxide concentration is the PMIP-prescribed value of 276 ppm
for control and 197 ppm for 21 cal. Zonally symmetric ozone concentrations
are prescribed versus latitude, pressure level and season (as for CCM1;
Bath et al, 1991).
Shortwave radiation is treated by a modified Thompson et al. (1987) scheme
in ultraviolet/visible (0.0 to 0.90 micron) and near-infrared (0.90 to
4.0 microns) spectral bands. Gaseous absorption is calculated from broadband
formulas of Ramanathan et al. (1983) , with ultraviolet/visible absorption
by ozone and near-infrared absorption by water vapor, oxygen, and carbon
dioxide treated. Reflectivities from multiple Rayleigh scattering are determined
from a polynomial fit in terms of the gaseous optical depth and the solar
zenith angle. A delta-Eddington approximation is used to calculate shortwave
albedos and transmissivities of aerosol (see Chemistry) and of cloudy portions
of each layer. Cloud optical properties depend on liquid water content
(LWC), which is predicted as a prognostic variable (see Cloud Formation).
Clouds that form in individual layers (see Cloud Formation) are assumed
to be randomly overlapped in the vertical. The effective cloud fraction
depends on solar zenith angle (cf. Henderson-Sellers and McGuffie 1990)
to allow for the three-dimensional blocking effect of clouds at low sun
Longwave radiation is calculated in 5 spectral intervals (with wavenumber
boundaries at 0.0, 5.0 x 104, 8.0 x 104, 1.0 x 105, 1.2 x 105, and 2.2
x 105 m-1). Broadband absorption and emission by water vapor
(cf. Ramanathan and Downey 1986), carbon dioxide (cf. Kiehl and Briegleb
1991), and ozone (cf. Ramanathan and Dickinson 1979) are included. In addition,
there is explicit treatment of individual greenhouse trace gases (methane,
nitrous oxide, and chlorofluorocarbon compounds CFC-11 and CFC-12: cf.
Wang et al. 1991a , b). Cloud emissivity depends on prescribed LWC (see
above). See also Cloud Formation.
Dry and moist convection as well as vertical mixing in the planetary boundary
layer (PBL) are treated by an explicit model of subgrid-scale vertical
plumes following the approach of Kreitzberg and Perkey (1976) and Anthes
(1977) , but with simplifications. A plume may originate from any layer,
and accelerate upward if buoyantly unstable; the plume radius and fractional
coverage of a grid box are prescribed as a function of height. Mixing with
the large-scale environmental air (entrainment and detrainment) is proportional
to the plume vertical velocity. From solution of the subgrid-scale plume
model for each vertical column, the implied grid-scale vertical fluxes,
latent heating, and precipitation are deduced. Convective precipitation
forms if the plume air is supersaturated. See also Planetary Boundary Layer.
Cloud formation follows a modified Slingo and Slingo (1991) scheme that
accounts for convective, anvil cirrus, and stratiform cloud types. In a
vertical column, the depth of convective cloud is determined by the vertical
extent of buoyant plumes (see Convection), and the cloud fraction from
a function of the instantaneous convective precipitation rate. (The convective
cloud fraction is adjusted in accord with the assumption of random vertical
overlap of cloud--see Radiation). If the convective cloud penetrates higher
than a sigma level of about 0.6, anvil cirrus also forms.
The fraction of stratiform (layer) cloud is a function of the relative
humidity excess above a threshold that depends on sigma level. In order
to predict realistic amounts of stratus cloud in winter polar regions,
a further constraint on cloud formation in conditions of low absolute humidity
is added, following Curry and Herman (1985).
Precipitation forms in association with subgrid-scale supersaturated convective
plumes (see Convection). Under stable conditions, precipitation also forms
to restore the large-scale supersaturated humidity to its saturated value.
The amount of evaporation is parameterized as a function of the large-scale
humidity and the thickness of the intervening atmospheric layers.
Planetary Boundary Layer
Vertical mixing in the PBL (and above the PBL for an unstable vertical
lapse rate) is simulated by an explicit model of subgrid-scale plumes (see
Convection) that are initiated at the center of the lowest model layer
using scaled perturbation quantities from the constant-flux region immediately
below (see Surface Fluxes). The plume vertical motion and perturbation
temperature, specific humidity, and horizontal velocity components are
solved as a function of height. The implied grid-scale fluxes are then
used to modify the corresponding mean quantities.
Raw orography obtained from the 1 x 1-degree topographic height data of
Gates and Nelson (1975) is area-averaged over each atmospheric grid box
(see Horizontal Resolution).
The ocean is represented by a thermodynamic slab (Thompson and Pollard,
1997), which crudely captures the seasonal heat capacity of the ocean mixed
layer. The thickness of the slab is 50 m. Poleward oceanic heat transport
is prescribed as a zonally symmetric function of latitude based on present-day
observations, using 0.3 times the "0.5 x OCNFLX" case of Covey and Thompson
(1989), which improves the simulation of present zonal-mean sea-surface
temperatures (SSTs). Convergence under sea ice is weighted towards 2 W
m-2 for 100% cover in the Northern Hemisphere, and towards 6
W m-2 in the Southern Hemisphere. To avoid unrealistic sea-ice
formation in the Norwegian Sea region we impose a crude local flux that
warms the mixed layer whenever it drops below 1.04 deg C, in a rectangular
region between 66 and 78 deg N and -10 and 56 deg E. This flux increases
linearly to a maximum possible value of 500 W m-2 if the ocean
were to cool to its freezing point (-1.96 deg C). This is meant to simulate
the buffering effect of the deepening winter mixed layer, and advection
by warm ocean currents, and does produce wintertime heat convergences of
about 200 W m-2 in agreement with Hibler and Bryan (1987). After
making the sea-ice and Norwegian Sea adjustments at each time step, an
additive global adjustment is made to ensure that the global integral of
the convergence is zero.
A three-layer sea-ice thermodynamic model predicts the local melting and
freezing of sea ice, essentially as in Semtner (1976). Fractional areal
cover is included as in Hibler (1979) and Harvey (1988). Sea ice advection
is included using the ``cavitating-fluid'' model of Flato and Hibler (1990,
1992) in which the ice resists compressive stresses but offers no resistance
to divergence or shear. The surface wind and ocean current fields for driving
the dynamic sea ice were prescribed (from climatology for the winds and
from an earlier OGCM run for the currents).
Precipitation falls as snow if the surface air temperature is < 0 degrees
C, with accumulation on land and continental/sea ice surfaces. Snow cover
is simulated by a three-layer model (top layer a constant 0.03 m thick,
other layers of equal thickness at each time step). Prognostic variables
include the layer temperatures and the total snow mass per unit horizontal
area (expressed as snow thickness and fractional coverage in a model grid
box). When snow falls in a previously snow-free grid box, the fractional
coverage increases from zero, with total snow thickness fixed at 0.15 m.
If snowfall continues, the fractional coverage increases up to 100 percent,
after which the snow thickness increases (the reverse sequence applies
for melting of a thick snow cover).
Heat diffuses linearly with temperature within and below the snow. The
upper boundary condition is the net balance of surface energy fluxes, and
the lower condition is the net heat flux at the snow-surface interface
(see below). If the temperature of any snow layer becomes 0 degrees C,
it is reset to 0 degrees C, snow is melted to conserve heat, and the meltwater
contributes to soil moisture. Snow cover is also depleted by sublimation
(a part of surface evaporation--see Surface Fluxes), and snow modifies
the roughness and the albedo of the surface (see Surface Characteristics).
The fractional coverage of snow is the same for both bare ground and
lower-layer vegetation (see Land Surface Processes). In order to exactly
conserve heat, temperatures are kept separately for buried and unburied
lower-layer vegetation, and are adjusted calorimetrically as the snow cover
grows/recedes. Any liquid water or snow already intercepted by the vegetation
canopy that becomes buried is immediately incorporated into the lowest
snow layer. The buried lower vegetation is included in the vertical heat
diffusion equation as an additional layer between the soil and the snow,
with thermal conduction depending on the local vegetation fractional coverage
and leaf /stem area indices. See also Sea Ice.
The land surface is subdivided according to upper- and lower-story vegetation
(trees and grass/shrubs) of 12 types. Vegetation attributes (e.g., fractional
cover and heights, leaf and stem area indices, leaf orientation, root distribution,
leaf/stem optical properties, and stomatal resistances) are specified from
a detailed equilibrium vegetation model driven by present-day climate.
Soil hydraulic properties and albedos are prescribed as in BATS from global
maps of soil-texture class and color (Dickinson et al., 1986). See also
Land Surface Processes.
The surface roughness length is a uniform 2.4 x 10-3 m over
the oceans and 1.0 x 10-2 m over bare soil, ice and snow surfaces.
The ocean surface albedo is specified after Briegleb et al. (1986) to
be 0.0244 for the direct-beam component of radiation (with sun overhead),
and a constant 0.06 for the diffuse-beam component; the direct-beam albedo
varies with solar zenith angle, but not spectral interval. The albedo of
ice surfaces depends on the topmost layer temperature (to account for the
lower albedo of melt ponds). For temperatures that are < -5 degrees
C, the ice albedos for the ultraviolet/visible and near-infrared spectral
bands (see Radiation) are 0.7 and 0.4 respectively. There is no dependence
on solar zenith angle or direct-beam vs diffuse-beam radiation. Following
Maykut and Untersteiner (1971) , a fraction 0.17 of the absorbed solar
flux penetrates and warms the ice to an e-folding depth of 0.66 m (see
Sea Ice). The background albedos of land and ice surfaces are also modified
by snow (see Snow Cover). The snow albedo depends on the temperature (wetness)
of the topmost snow layer: below -15 degrees C, the visible and near-infrared
albedos are 0.9 and 0.6, respectively; these decrease linearly to 0.8 and
0.5 as the temperature increases to 0 degrees C (cf. Harvey 1988). The
direct-beam snow albedo also depends on solar zenith angle (cf. Briegleb
and Ramanathan 1982).
Longwave emissivities of all solid body surfaces (including, ocean,
ice, and land) are unity (blackbody emission).
Surface solar absorption is determined from albedos, and longwave emission
from the Planck equation with prescribed surface emissivities (see Surface
Turbulent vertical eddy fluxes of momentum, heat, and moisture are expressed
as bulk formulae, following Monin-Obukhov similarity theory. The values
of wind, temperature, and humidity required for the bulk formulae are taken
to be those at the lowest atmospheric level (sigma = 0.993), which is assumed
to be within a constant-flux surface layer. The bulk drag/transfer coefficients
are functions of roughness length (see Surface Characteristics) and stability
(bulk Richardson number), following the method of Louis et al. (1981).
Over vegetation, the turbulent fluxes are mediated by a Land-Surface-Transfer
(LSX) model (see Land Surface Processes). The bulk formula for the surface
moisture flux also depends on the surface specific humidity, which is taken
as the saturated value over ocean, snow, and ice surfaces, but which otherwise
is a function of soil moisture.
Above the surface layer, the turbulent diffusion of momentum, heat,
and moisture is simulated by a subgrid-scale plume model (see Planetary
Land Surface Processes
Effects of interactive vegetation are simulated by the LSX model (cf. Pollard
and Thompson 1994 , Thompson and Pollard 1995), which includes canopies
in upper (trees) and lower (grasses/shrubs) layers. Prognostic variables
are the temperatures of upper-layer leaves and stems and of combined lower-layer
leaves/stems, as well as the stochastically varying rain and snow intercepted
by these three components (see Precipitation and Snow Cover). The LSX model
also includes evaporation of canopy-intercepted moisture and evapotranspiration
via root uptake, as well as soil wilting points. Air temperatures/specific
humidities within the canopies are determined from the atmospheric model
and the surface conditions; canopy aerodynamics are modeled using logarithmic
wind profiles above/between the vegetation layers, and a simple diffusive
model of air motion within each layer. Effects of vegetation patchiness
on radiation and precipitation interception are also included.
Soil temperature and fractional liquid water content are predicted in
6 layers with thicknesses 0.05, 0.10, 0.20, 0.40, 1.0, and 2.5 meters,
proceeding downward. (The near-surface temperature profile of the continental
ice sheets is predicted by the same model.) Heat diffuses linearly, but
diffusion/drainage of liquid water is a nonlinear function of soil moisture
(cf. Clapp and Hornberger 1978). Boundary conditions at the bottom soil
level include zero diffusion of heat and liquid, but nonzero gravitational
drainage (deep runoff). The upper boundary condition for heat is the net
energy flux at the soil surface computed by the LSX model; infiltration
of moisture is limited by the downward soil diffusion to the center of
the upper layer, assuming a saturated surface (cf. Abramopoulos et al.
Soil fractional ice content is also predicted. (Ice formation affects
soil hydraulics by impeding water flow, and soil thermodynamics by changing
the heat capacity/conductivity and by releasing latent heat.) The specific
humidity at the upper surface of the top soil layer (used to predict evaporation--see
Surface Fluxes) varies as the square of the composite liquid/ice fractions.
See also Snow Cover and Surface Characteristics.
Last update November 9, 1998. For further information, contact: Céline