Documentation of the PMIP models (Bonfils et al. 1998)

PMIP Documentation for GEN2

National Center for Atmospheric Research / Pennsylvania State University: Model GENESIS2 (T31 L18) 1995


PMIP Representative(s)

Dr. David Pollard, Earth System Science Center, Pennsylvania State University, University Park, PA 16802, USA, Phone: (814) 865-2022 ; Fax : 814 865 3191 ; 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 :


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 :

Model Designation

GENESIS2 (T31 L18) 1995

Model Identification for PMIP


PMIP run(s)

0fix, 6fix, 21fix, 0cal, 21cal.

Number of days in each month: 31 28 31 30 31 30 31 31 30 31 30 31

Model Lineage

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.

Model Documentation

main reference:

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.

secondary reference(s):

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.

Numerical/Computational Properties

Horizontal Representation

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 ).

Horizontal Resolution

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

Vertical Domain

Surface to 5 hPa; for a surface pressure of 1000 hPa, the lowest atmospheric level is at 993 hPa.

Vertical Representation

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.

Vertical Resolution

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.

Computer/Operating System

The PMIP simulations were run on Cray Y/MP and J90 computers using multiple processors (up to 4) in a UNICOS environment.

Computational Performance

For the PMIP experiment, about 4 minutes Cray Y/MP computer time per simulated day.


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.

Sampling Frequency

For the PMIP simulation, monthly averages of model variables are saved.

Dynamical/Physical Properties

Atmospheric Dynamics

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


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).

Gravity-wave Drag

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.

Solar Constant/Cycles

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 angles.

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.

Cloud Formation

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.

Sea Ice

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 latitude.

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.

Snow Cover

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.

Surface Characteristics

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 1982 ).

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 Fluxes

Surface solar absorption is determined from albedos, and longwave emission from the Planck equation with prescribed surface emissivities (see Surface Characteristics).

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 Boundary Layer).

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 Bonfils ( )