Land Surface Modeling: A Mini-Workshop
3. Science Background
Global climate and the global carbon cycle are, in a direct sense, controlled by exchanges of water, carbon, and energy between the terrestrial biosphere and atmosphere. Thus models of these processes are essential for the purpose of developing predictive capability for the Earth's climate on all time scales, including seasonal climate prediction as well as natural climate fluctuations and human-induced climate change on decadal time scales.
Early efforts to introduce parameterizations of land processes into global climate models were driven by the understanding that development of the atmospheric planetary boundary layer (including clouds and precipitation) is strongly affected by redistribution of incoming radiative energy at the land surface into sensible and latent heat fluxes. Application of increasingly sophisticated land-surface models has shown that water-carbon-energy exchanges are tightly coupled, that large-scale interannual variations in climate produce substantial variations in atmosphere-biosphere carbon exchanges and that changes in atmospheric concentrations of CO2 can influence vegetation physiology directly. Most current land-surface models are can be associated with three broad types with respect to representation of vegetation as described by Foley (1995a): soil-vegetation-atmosphere transfer schemes (SVATS), potential vegetation models (PVMs), and terrestrial biogeochemistry models (TBMs). Development of more realistic treatment of biospheric processes in land-surface schemes for GCMs has resulted in explicit representation of biospheric carbon exchanges thereby interweaving the carbon cycle with energy and water cycles.
The first generation of soil-vegetation-atmosphere transfer schemes (SVATS) evolved from simple bucket schemes focusing on soil water availability (Manabe, 1969), through the schemes of Deardorff (1978), to the biosphere-atmosphere transfer scheme (BATS) of Dickinson et al. (1986) and the Simple Biosphere (SiB) of Sellers et al. (1986). The latter was the first land-surface scheme that explicitly modeled plant physiology in a GCM (General Circulation Model or Global Climate Model). Aside from differences in which processes were included in these schemes, some schemes focused on more complex methods for the spatial treatment of vegetation cover itself including the mosaic-of-tiles type (Avissar and Pielke, 1989; Koster and Suarez, 1992). For most SVATS, land cover is fixed, with seasonally-varying prescriptions of parameters such as reflectance, leaf area index or rooting depth. Some SVATS incorporate satellite data to characterize more realistically the seasonal dynamics in vegetation function (e.g., Sellers et al., 1994) and several simulate ecological processes such as primary productivity and plant respiration (Sellers et al., 1992; Bonan, 1994).
Biogeography, or potential vegetation, models (PVMs) comprise a suite of schemes that focus on modeling distributions of vegetation as a function of climate (e.g., Holdridge, 1947; Prentice, 1990) without influences of anthropogenic or natural disturbance. Several include more sophisticated approaches to account for competition and varying combinations of plant functional types, as well as physiological and ecological constraints on vegetation distributions (e.g. Woodward, 1987; Prentice et al., 1992). Although not merged directly with GCMs, these models have been used to simulate vegetation distributions for the present climate as well as for paleo- and future climates (Prentice, 1990; Prentice and Fung, 1990; Foley, 1995b).
Finally, terrestrial biogeochemistry models (TBMs), developed from scaling up local ecological models, are process-based models that simulate dynamics of energy, water, and carbon and nitrogen exchange among biospheric pools and the atmosphere. They typically model primary productivity/photosynthesis as a function of prescribed vegetation, soil, and climate parameters, characterize composition and turnover times of vegetation and soil components, and rely on simple parameterizations of the surface energy and water balance (e.g., Potter et al., 1993; Parton et al., 1993; Schimel et al., 1990). Because these models either rely on, or predict, static land-cover distributions, they are not applicable to transient climate change experiments.
A few of the 40 existing, free-standing, global TBMs incorporate vegetation dynamics (J. Foley, I. Woodward, A. Friend, C. Prentice). These models are designed to represent more realistically the dynamic exchanges of water, energy and carbon between the land surface and the atmosphere including seasonal-to-interannual as well as decadal-to-centennial interactions. For example, modeled processes that simulate vegetation responses on seasonal time scales (e.g., phenology of leaf area index and photosynthesis) control the cumulative response of vegetation to a multi-year drought as well as large-scale changes in vegetation distributions in response to transient climate change. Currently, dynamic vegetation models (DVMs) include components of all the schemes summarized above although their strengths lie primarily in the representation of physiological and biological processes while radiative and soil components remain quite simple.
Several model intercomparisons have focused on evaluating SVATS and terrestrial biosphere models. The Project for Intercomparison of Land-surface Parameterization Schemes was initiated to evaluate an array of land-surface schemes existing in GCMs (Pitman et al., 1993; Henderson-Sellers et al., 1993; Shao and Henderson-Sellers, 1996). About 30 terrestrial biosphere models, including DVMs, were assessed in two workshops run by the Potsdam Institute for Climate Impact Research (PIK) (Lurin, 1994). PILPS concentrated on assessing the adequacy of modeled energy and water balances at the land surface, while the PIK meetings concentrated on integrative processes like net primary productivity and biomass accumulation.
One feature absent from most land surface schemes in GCMs is anthropogenic alterations to land cover. This influence is included, albeit in a simple way, in several schemes that rely on prescribed land-cover distributions as well as those that rely on remote sensing to describe the land surface.
The strong coupling of exchanges of water, energy and carbon between the land surface and the atmosphere, along with development of models with varying representations of physical, physiological, and biogeochemical processes, has led to similar efforts among GCM groups to merge strengths of the more sophisticated SVATS (physical and some physiological processes) with those of the dynamic vegetation models (physiological and biological processes). The workshop at GISS was designed to bring together researchers working on various components of land-surface schemes, including snow, to discuss status and improvements of land-surface representations in GCMs.