the PMIP models (Bonfils et al. 1998)
PMIP Documentation for GEN2
National Center for Atmospheric
Research / Pennsylvania State University: Model GENESIS2 (T31 L18) 1995
Dr. David Pollard, Earth System Science Center, Pennsylvania State University,
University Park, PA 16802, USA, Phone: (814) 865-2022 ; Fax : 814 865 3191
; email : firstname.lastname@example.org
Dr. Starley L. Thompson, P.O. Box 3000, National Center for Atmospheric
ResearchC0 80307, USA, Phone : 303 497 1628 ; Fax: 303 497 1348 ; email
Dr. John E. Kutzbach, IES-Center for Climatic Research, University of
Wisconsin, 1225 W. Dayton St. Madison, Wisconsin 53706-1695, Phone: 608
262 0392 ; Fax: 608 262 5964 ; email : email@example.com
GENESIS2 (T31 L18) 1995
Model Identification for PMIP
0fix, 6fix, 21fix, 0cal, 21cal.
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 2.0 of GENESIS (Global
ENvironmental and Ecological Simulation of Interactive Systems). It has
been developed at NCAR Interdisciplinary Climate Systems Section. Its documented
predecessor is GENESIS model version 1.02. The latter version is substantially
different and has improved present-day climatology compared to version
1.02. 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 GENESIS
atmospheric models are based on the spectral dynamics of the NCAR CCM1
model (cf. Williamson et al. 1987 ), but their physics schemes differ significantly
from those of CCM1. The GENESIS models also are substantially different
from the NCAR CCM2 model.
summary of the model formulation + present day results :
Thompson, S.L. and D. Pollard. 1997. Greenland and Antarctic mass balances
for present and doubled CO2
from the GENESIS version-2 global climate model. Journal of Climate,
vol. 10, 871-900.
other gen2 papers in press:
Pollard, D., J.C. Bergengren, L.M. Stillwell-Soller, B.S. Felzer and
S.L. Thompson. 1997. Climate simulations for 10 000 and 6 000 years BP
using the GENESIS global climate model. Palaeoclimates, in press.
Pollard, D. and S.L. Thompson. 1997. Climate and ice-sheet mass balance
at the last glacial maximum from the GENESIS version 2 global climate model.
Quaternary Science Reviews, 16, 841-863.
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 triangular 31 (T31), roughly equivalent to 3.75 x 3.75 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 Representation.
dim_longitude*dim_latitude: 96*48 for AGCM
dim_longitude*dim_latitude: 180*90 for surface
Surface to 5 hPa; for a surface pressure of 1000 hPa, the lowest atmospheric
level is at 993 hPa.
Finite-difference sigma coordinates are used for all atmospheric variables
except water vapor, for which hybrid sigma-pressure coordinates (cf. Simmons
and Burridge 1981 ) are employed. Energy-conserving vertical finite-difference
approximations are utilized, following Williamson (1983 , 1988 ).See also
Horizontal Representation and Diffusion.
There are 18 unevenly spaced sigma-coordinate in the vertical with the
following levels: 0.005, 0.013, 0.033, 0.064, 0.099, 0.139, 0.189, 0.251
0.325, 0.409, 0.501, 0.598. 0.695, 0.787, 0.866, 0.929, 0.970, 0.993 (or,
for water vapor, hybrid sigma-pressure levels--see Vertical Representation).
For a surface pressure of 1000 hPa, 4 levels are below 800 hPa and 7 levels
are above 200 hPa.
The PMIP simulations were run on Cray Y/MP and J90 computers using multiple
processors (up to 4) in a UNICOS environment.
For the PMIP experiment, about 4 minutes Cray Y/MP computer time per simulated
The control (0fix) experiment was started from a previous multi-decadal
spinup using prescribed climatological sea-surface temperatures and sea-ice
extents, (Shea et al., 1992, J.Climate ,5,987-1001), in which all model
fields had reached equilibrated seasonal cycles. AMIP solar constant, AMIP
carbon dioxide and IPCC other greenhouse-gas concentrations were used.
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. In order to reduce
spurious diffusion of moisture in the stratosphere over mountains, the
specific humidity is advected on hybrid sigma-pressure surfaces, while
advection of other 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).
Orographic gravity-wave drag is parameterized after McFarlane (1987) .
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.
For 0fix, 6fix, 21 fix, 0cal and 21cal, 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 345 ppm
for control (fix and cal), 280 ppm for 6fix, 200 ppm for 21fix and 246.4
for 21 cal. Zonally symmetric ozone concentrations are prescribed versus
latitude, pressure level and season (as for CCM1; Bath et al, 1987). Radiative
effects of oxygen, water vapor, methane (1.653ppm), nitrous oxide (0.306ppm),
chlorofluorocarbon compounds CFC-11 and CFC-12, and of preindustrial tropospheric
"background" aerosol (an option) are also included (see Radiation).
We prescribe small amounts of background dust aerosols that are fixed
in time, vary latitudinally and over land versus ocean, and are the same
for all runs.
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
Additional cloud absorption of solar radiation (Cess et al., 1995; Ramanathan
et al., 1995) is included in version 2 by a prescribed decrease in cloud
single-scattering albedos, except in high southern latitudes with a linear
transition to higher albedos from 40 to 60 degrees S. The global net solar
absorption by the model atmosphere is about 86 W m-2 with about 30 W m-2
absorbed by clouds, and the ratio of the global mean cloud radiative forcing
at the surface to that at the top of the atmosphere is 1.61.
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; its subsequent evaporation in
falling toward the surface (see Precipitation) substitutes for explicit
treatment of convective downdrafts and cloud/precipitation microphysics.
See also Planetary Boundary Layer.
In version 2 clouds are predicted using prognostic 3-D water cloud amounts,
(eg., Smith, 1990; Senior and Mitchell, 1993). Three separate prognostic
cloud fields are kept for stratus, convective and anvil cirrus clouds,
which are advected by semi-Lagrangian transport, and mixed vertically by
convective plumes and background diffusion. Convective clouds are formed
within buoyant convective plumes (see Convection) if the plume air saturates,
and anvil clouds are formed in the same way at the top of the plumes. Stratus
clouds are formed by large-scale saturation if the model relative humidity
exceeeds a threshold value. The large-scale cloud water concentrations
can then be advected or mixed, evaporate into the ambient air, be converted
to falling precipitation, or intercept precipitation falling from above
(see Precipitation) Latent heat changes due to liquid vs. ice clouds are
neglected (as if all clouds are liquid), although the determination of
cloud fraction, radiative properties and microphysical parameters take
the temperature (above/below freezing) into account. Cloud fractions for
each type are proportional to the grid-box average cloud amounts.
Falling precipitation is created by conversion of the prognostic cloud
water amounts at specified e-folding rates. In addition, precipitation
can be created within the buoyant plumes (see Convection) if the within-plume
cloud concentration exceeds a certain value. Falling precipitation is subject
to re-evaporation and aggregation by lower clouds. Turbulent deposition
of owest-layer cloud particles onto the surface is also included. Subgrid-scale
spatial variability of convective precipitation falling in land grid boxes
is simulated stochastically (cf. Thomas and Henderson-Sellers 1991 ). See
also Snow Cover and Land Surface Processes.
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.
For 0fix and 6fix : Raw orography obtained from the U.S. Navy ?FNOC? dataset
(Kineman, 1985) is area-averaged over each atmospheric grid box (see Horizontal
Resolution). The subgrid-scale orographic variances required by the gravity-wave
drag parameterization (see Gravity-wave Drag) are obtained from U.S. Navy
data with resolution of 10 minutes arc (cf. Joseph 1980 ). The standard
deviation (square root of the variance) of the fine-scale U.S. Navy orography
in each model grid box is computed, and used as the surface roughness generating
upward-propagating gravity waves.
For 21k we use Peltier (1994).
For control (0 fix): SSts and sea ice extents were prescribed from the
climatological present-day monthly dataset of Shea et al.(1992,J.Climate,
5,987-1001), interpolating linearly in time between the mid-month points.
For 6 fix: SSTs and sea-ice prescribed at their present day value, as
in the control run.
For control (0 cal): SSTs and sea ice were calculated using a 50-m mixed-layer
slab ocean model (see below).
For 21 fix: SSTs and sea ice were prescribed using the CLIMAP (1981)
February and August datasets, using sinusoidal fits for the intervening
months and straightforward rules about the occurrence of sea ice. This
PMIP run uses Peltier ice sheets.
For computed SSTs experiments, the model was coupled to a mixed layer
ocean model (Thompson and Pollard, 1997). The ocean is represented by a
thermodynamic slab, which crudely captures the seasonal heat capacity of
the surface mixed layer. The thickness of the slab is 50 m. Oceanic heat
transport is treated differently in version 2, to alleviate difficulties
encountered with the earlier method of prescribing the heat convergence
(W m-2) as a function of latitude. For version 2 we first fitted the present-day
observed zonal mean transport as a linear function of the latitudinal sea-surface-temperature
(SST) gradient, but with the diffusion coefficient depending on the zonal
fraction of land vs. ocean, and on latitude itself. Those coefficients
are used to calculate the two-dimensional linear diffusion of heat vs.
SST at each model timestep. Convergence under sea ice is weighted towards
0 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.
For 0fix, 6fix, monthly sea-ice extents are prescribed from Shea et al.
(1992). Sea-ice extents are prescribed by the datasets, whereas1 sea-ice
fractional coverage and thickness are prescribed as simple functions of
For 21fix, sea ice is prescribed using the CLIMAP (1981) (See Ocean).
For computed SSTs, 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. In version 2 the annual mean
ocean currents prescribed for sea-ice dynamics are obtained from a 5-year
run of a 2x2 degree ocean GCM (E.Brady, personal communication), and the
surface winds used for sea-ice dynamics come from the AGCM itself.
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.
For the PMIP experiments with gen2, we have used the EVE vegetation model.
The EVE model predicts 110 life forms in response to various monthly climate
predictors such as air temperature and precipitation, based on present-day
observed correlations. It aslo includes parameterized effects due to disturbances
such as fire frequency. It can be used interactively driven by GCM climate,
but for the PMIP simulations, it was driven by observed present-day climatology.
In this mode, it closely reproduces observed present-day natural vegetation
(effects due to humans are not included). (See Bergengren and Thompson
(1998), Bergengren et al. (1998), Pollard et al. (1997)).
From the relative amounts of the 110 life forms in each grid cell, EVE
also computes the aggregate physical vegetation attributes needed by the
GCM, such as fractional cover, heights, leaf and stem area indices, leaf
orientation, root distribution, leaf/stem optical properties, and stomatal
resistances. Most of there are computed separately for the two canopy layers
used by LSX ("trees" and "grass"). (See Land Surface Processes).
. Soil hydraulic properties are inferred from texture data of Webb et
al. (1993) that consider 15 soil horizons, 107 soil types, and 10 continental
subtypes. See also Land Surface Processes. The surface roughness length
is a uniform 1.0 x 10-4 m over the oceans and 5.0 x 10-4
m over 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 0.8 and 0.5 respectively;
these decrease linearly to 0.7 and 0.4 as the temperature increases to
0 degrees C (cf. Harvey 1988 ). 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). Over vegetated land,
instantaneously changing (depending on solar zenith angle) spatially varying
albedos are calculated as described by Pollard and Thompson (1994) for
direct and diffuse radiation in visible (0.4-0.7 micron) and near-infrared
(0.7-4.0 microns) spectral intervals. Albedos of bare dry soil are prescribed
as a function of spectral interval and the texture of the topmost soil
layer (cf. Webb et al. 1993 ); these values are modified by the moisture
in the top soil layer (see Land Surface Processes), but they do not depend
on solar zenith angle or direct-beam vs diffuse beam radiation. 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: be low -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
Longwave emissivities of ocean and ice surfaces are unity (blackbody
emission), but over land they are a function of vegetation (the emissivity
of each canopy layer depends on leaf/stem densities).
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.
There are 20 parameters describing the vegetation canopies at each grid
point (and there are two canopies: upper and lower, for trees and grasses).
* fractional cover of canopy
* geometric height of canopy top (m)
* geometric height of canopy bottom (m)
* stem area index (m2/m2)
* aerodynamic dimension of stems (m)
* maximum root depth (m)
* green LAI, one-sided (m2/m2)
* brown (dead) LAI, one-sided (m2/m2)
* fraction of total LAI that is broadleaf
* aerodynamic length dimension for broadleaf leaves (m)
* aerodynamic length dimension for needleleaf leaves (m)
* aerodynamic width dimension for broadleaf leaves (m)
* aerodynamic width dimension for needleleaf leaves (m)
* leaf orientation (-1=vertical, 0=random, 1=horizontal)
* live leaf reflectivity, visible and near_IR wavebands
* live leaf transmissivity, visible and near_IR wavebands
* stomatal conductance, maximum (m/s)
* stomatal conductance, minimum (m/s)
* stomatal PAR constant (W/m2)
* stomatal vapor-pressure-deficit constant (N/m2)
These are aggregated from the amounts of the 110 life forms at each
grid point within the EVE model.
For soil, all properties are parameterized from sand/silt/clay fractions
as mentioned above.
From Thompson and Pollard 1997:
soil and ice-sheet surface model: A six-layer soil model extends from
the surface to 4.25-m depth, with layer thicknesses increeasing from 5cm
at the top to 2.5m at the bottom. Physical processes in the vertical soil
column include heat diffusion, liquid warer transport (Clapp and Hornberger
1978 Dickinson 1984), surface runoff and bottom drainage, uptake of liquid
water by plant roots for transpiration, and the freezing and thawing of
soil ice.Version 2 also includes a surface ponding reservoir (with a maximum
depth of 10mm), which acts as a buffer between rainfall, infitration, and
runoff. Satured soil layers are now possible by implicitly accounting for
vertical hydrostatic pressure gradients. In Version 2, soil hydrologic
properties (saturated matric potential and hydraulic conductivity, porosity,
etc.) and wet surface albedo are determined from soil sand-silt-clay texture
ratios using empirical formulae in Cosby et al. (1984). The ratios are
in turn prescribed from a new 1*1 degree global soil-texture dataset (Webb
et al. 1993), which includes variations with depth. The same six-layer
model is used for ice-sheets, with physical parameters appropriate for
ice and with no internal liquid moisture. liquid/ice fractions. See also
Snow Cover and Surface Characteristics.
Last update November 9, 1998. For further information, contact: Céline