Atmospheric general circulation models used for climate simulation and weather forecasting require the fluxes of radiation, heat, water vapor, and momentum across the land-atmosphere interface to be specified. These fluxes are calculated by submodels called land surface parameterizations. Over the last 20 years, these parameterizations have evolved from simple, unrealistic schemes into credible representations of the global soil-vegetation-atmosphere transfer system as advances in plant physiological and hydrological research, advances in satellite data interpretation, and the results of largescale field experiments have been exploited. Some modern schemes incorporate biogeochemical and ecological knowledge and, when coupled with advanced climate and ocean models, will be capable of modeling the biological and physical responses of the Earth system to global change, for example, increasing atmospheric carbon dioxide.Until the early 1980s, global atmospheric general circulation models (AGCMs) incorporated very simple land surface parameterizations (LSPs) to estimate the exchanges of energy, heat, and momentum between the land surface and the atmosphere. These have since evolved into a family of schemes that can realistically describe a comprehensive range of land-atmosphere interactions. These advanced schemes will be needed to understand the response of the biosphere and the climate system to global change, for example, increasing atmospheric CO 2 (1-3).Three generations of models have taken us from the early LSPs to where we stand now. The first, developed in the late 1960s and 1970s, was based on simple aerodynamic bulk transfer formulas and often uniform prescriptions of surface parameters (albedo, aerodynamic roughness, and soil moisture availability) over the continents (4). In the early 1980s, a second generation of models explicitly recognized the effects of vegetation in the calculation of the surface energy balance (5, 6). At the same time, global, spatially varying data of land surface properties were assembled from ecological and geographical surveys published in the scientific literature (7). The latest (third generation) models use modern theories relating photosynthesis and plant water relations to provide a consistent description of energy exchange, evapotranspiration, and carbon exchange by plants (8-10). Some are beginning to incorporate treatments of nutrient dynamics and biogeography, so that vegetation systems can move in response to climate shifts. A series of largescale field experiments have been executed to validate the process models and scaling assumptions involved in land-atmosphere schemes (3). These experiments have also accelerated the development of methods for translating satellite data into global surface parameter sets for the models. Theoretical Background and the First-Generation ModelsIt has been understood for nearly 200 years that the continents and the atmosphere exchange energy, water, and carbon with each other. However, it was not until the late 1960s with the construct...

A new global archive of soil type and land cover data derived for use in GCM climate mode--is (-;scribe1 The data are archived at a resolution of 1" latitude X 1" longitude. The method of construction of the component data sets is given together with 'reliability estimates'. The soils data form the only published data set designed specifically for use in climate studies. The land cover data are compatible with the soils data, forming a coherent and complete data set and seem to be comparable with other land cover information. Recommendations are made about combining and coarsening the data to the grid of any general circulation climate model. Methods of parameterizing surface radiative and hydrological properties in climate models are proposed.

Twenty-one land surface schemes (LSSs) performed simulations forced by 18 yr of observed meteorological data from a grassland catchment at Valdai, Russia, as part of the Project for the Intercomparison of Land-Surface Parameterization Schemes (PILPS) Phase 2(d). In this paper the authors examine the simulation of snow. In comparison with observations, the models are able to capture the broad features of the snow regime on both an intra-and interannual basis. However, weaknesses in the simulations exist, and early season ablation events are a significant source of model scatter. Over the 18-yr simulation, systematic differences between the models' snow simulations are evident and reveal specific aspects of snow model parameterization and design as being responsible. Vapor exchange at the snow surface varies widely among the models, ranging from a large net loss to a small net source for the snow season. Snow albedo, fractional snow cover, and their interplay have a large effect on energy available for ablation, with differences among models most evident at low snow depths. The incorporation of the snowpack within an LSS structure affects the method by which snow accesses, as well as utilizes, available energy for ablation. The sensitivity of some models to longwave radiation, the dominant winter radiative flux, is partly due to a stability-induced feedback and the differing abilities of models to exchange turbulent energy with the atmosphere. Results presented in this paper suggest where weaknesses in macroscale snow modeling lie and where both theoretical and observational work should be focused to address these weaknesses.

Tropical deforestation, by changing land surfaces, may have important consequences for the climate system. Predicting even the local, immediate effects of replacing tropical broadleaf forest with impoverished grassland has been difficult, because the land-surface parametrization schemes used previously in climate models have been inadequate. The forest canopy is particularly important for the surface-energy budget in tropical regions, and models neglecting the occurrence of such a canopy may give an unrealistic partitioning between various surface-energy fluxes. Inclusion of a land-surface scheme with a vegetation canopy into a version of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM) with a diurnal as well as a seasonal cycle permits an exploratory study of the possible effects of tropical deforestation. In a 13-month integration that assumes that all of the Amazon tropical forest in South America is replaced by impoverished grassland, surface hydrological and temperature effects dominate the response. Reduced mixing and less interception and evaporation from the canopy cause runoff to increase and surface temperatures to rise by 3-5 K. The period of driest soil is increased in the model from one month to several, but the possibility that this change is random cannot be excluded. Increased temperatures and drier soil could have a detrimental impact on survival of the remaining forest and on attempts at cultivation in deforested areas. The land-surface model, driven in a stand-alone mode by prescribed atmospheric conditions and with an imposed seasonal cycle of rainfall, mimics the seasonal cycle of soil moisture and runoff found in the CCM. Hence, it is used to estimate the relative contribution of the various changes imposed to simulate deforestation in the CCM with respect to the model's response at the surface. The change in surface roughness interacting with the canopy hydrology is evidently a major factor in determining the surface response to deforestation. However, the response to change in roughness is less pronounced for simpler models.

The very limited instrumental record makes extensive analyses of the natural variability of global tropical cyclone activities difficult in most of the tropical cyclone basins. However, in the two regions where reasonably reliable records exist (the North Atlantic and the western North Pacific), substantial multidecadal variability (particularly for intense Atlantic hurricanes) is found, but there is no clear evidence of long-term trends. Efforts have been initiated to use geological and geomorphological records and analysis of oxygen isotope ratios in rainfall recorded in cave stalactites to establish a paleoclimate of tropical cyclones, but these have not yet produced definitive results. Recent thermodynamical estimation of the maximum potential intensities (MPI) of tropical cyclones shows good agreement with observations. Although there are some uncertainties in these MPI approaches, such as their sensitivity to variations in parameters and failure to include some potentially important interactions such as ocean spray feedbacks, the response of upperoceanic thermal structure, and eye and eyewall dynamics, they do appear to be an objective tool with which to predict present and future maxima of tropical cyclone intensity. Recent studies indicate the MPI of cyclones will remain the same or undergo a modest increase of up to 10%-20%. These predicted changes are small compared with the observed natural variations and fall within the uncertainty range in current studies. Furthermore, the known omissions (ocean spray, momentum restriction, and possibly also surface to 300-hPa lapse rate changes) could all operate to mitigate the predicted intensification. A strong caveat must be placed on analysis of results from current GCM simulations of the "tropical-cyclone-like" vortices. Their realism, and hence prediction skill (and also that of "embedded" mesoscale models), is greatly limited by the coarse resolution of current GCMs and the failure to capture environmental factors that govern cyclone intensity. Little, therefore, can be said about the potential changes of the distribution of intensities as opposed to maximum achievable intensity. Current knowledge and available techniques are too rudimentary for quantitative indications of potential changes in tropical cyclone frequency. The broad geographic regions of cyclogenesis and therefore also the regions affected by tropical cyclones are not expected to change significantly. It is emphasized that the popular belief that the region of cyclogenesis will expand with the 26°C SST isotherm is a fallacy. The very modest available evidence points to an expectation of little or no change in global frequency. Regional and local frequencies could change substantially in either direction, because of the dependence of cyclone genesis and track on other phenomena (e.g., ENSO) that are not yet predictable. Greatly improved skills from coupled global ocean-atmosphere models are required before improved predictions are possible.