Biosphere-Atmosphere Transfer Scheme Research Articles

Sensitivity analysis of the biosphere‐atmosphere transfer scheme

The biosphere‐atmosphere transfer scheme (BATS) land surface parameterization was developed to provide a realistic representation of hydrometeorology at the atmosphere‐land interface for coupling with general circulation models. This paper presents the results of a comprehensive sensitivity analysis of BATS for the conditions of midlatitude land surface and climatology. The analysis employs visual “feature‐curve” representations to study the sensitivity of key model outputs to variations over a range of model parameters, atmospheric forcings, and model initialization conditions. The analysis provides insights into the behavior of the model and indicates that (1) the dominant energy flux shifts from being the soil sensible heat flux in arid/semiarid regions to evapotranspiration in rain forest regions; (2) in off‐line studies the absence of important feedback mechanisms may result in unrealistic results at extreme climatic conditions; (3) the model functions which determine the atmosphere‐controlled and soil moisture limited latent heat fluxes from soil and vegetation may need to be refined in order to obtain a more realistic modeling of the energy fluxes from the land surface; and (4) certain components of the model can possibly be simplified. The results also show that the influence of errors in the initial state estimates can persist for several years, indicating that caution should be exercised when attempting to validate or calibrate BATS using incomplete observation data and short‐term simulation runs.

Sensitivity of a general circulation model to global changes in leaf area index

Methods have recently become available for estimating the amount of leaf area at the surface of the Earth using satellite data. Also available are modeled estimates of what global leaf area patterns would look like should the vegetation be in equilibrium with current local climatic and soil conditions. The differences between the actual vegetation distribution and the potential vegetation distribution may reflect the impact of human activity on the Earth's surface. To examine model sensitivity to changes in leaf area index (LAI), global distributions of maximum LAI were used as surface boundary conditions in the National Center for Atmospheric Research community climate model (NCAR CCM2) coupled with the biosphere atmosphere transfer scheme (BATS). Results from 10‐year ensemble averages for the months of January and July indicate that the largest effects of the decreased LAI in the actual LAI simulation occur in the northern hemisphere winter at high latitudes despite the fact that direct LAI forcing is negligible in these regions at this time of year. This is possibly a result of LAI forcing in the tropics which has long‐ranging effects in the winter of both hemispheres. An assessment of the Asian monsoon region for the month of July shows decreased latent heat flux from the surface, increased surface temperature, and decreased precipitation with the actual LAI distribution. While the statistical significance of the results has not been unambiguously established in these simulations, we suspect that an effect on modeled general circulation dynamics has occurred due to changes of maximum LAI suggesting that further attention needs to be paid to the accurate designation of vegetation parameters. The incorporation of concomitant changes in albedo, vegetation fractional coverage, and roughness length is suggested for further research.

Sensitivity of Global Climate Model Simulations to Increased Stomatal Resistance and C02Increases*

Abstract Increasing levels of atmospheric CO2 will not only modify climate, they will also likely increase the water-use efficiency of plants by decreasing stomatal openings. The effect of the imposition of “doubled stomatal resistance” on climate is investigated in off-line simulations with the Biosphere–Atmosphere Transfer Scheme (BATS) and in two sets of global climate model simulations: for present-day and doubled atmospheric CO2, concentrations. The anticipated evapotranspiration decrease is seen most clearly in the boreal forests in the summer although, for the present-day climate (but not at 2 × CO2), there are also noticeable responses in the tropical forests in South America. In the latitude zone 44°N to 58°N, evapotranspiration decreases by −15 W m−2, temperatures increase by +2 K, and the sensible heat flux by +15 W m−2. Soil moisture is often, but less extensively, increased, which can cause increases in runoff. The responses at 2 × CO2 are larger in the 44°N to 58°N zone than elsewhere. Globa...

Development of a Regional Climate Model of the Western Arctic

Abstract An Arctic region climate system model has been developed to simulate coupled interactions among the atmosphere, sea ice, ocean, and land surface of the western Arctic. The atmospheric formulation is based upon the NCAR regional climate model RegCM2, and includes the NCAR Community Climate Model Version 2 radiation scheme and the Biosphere–Atmosphere Transfer Scheme. The dynamic–thermodynamic sea ice model includes the Hibler–Flato cavitating fluid formulation and the Parkinson–Washington thermodynamic scheme linked to a mixed-layer ocean. Arctic winter and summer simulations have been performed at a 63 km resolution, driven at the boundaries by analyses compiled at the European Centre for Medium-Range Weather Forecasts. While the general spatial patterns are consistent with observations, the model shows biases when the results are examined in detail. These biases appear to be consequences in part of the lack of parameterizations of ice dynamics and the ice phase in atmospheric moist processes in ...

Global climate sensitivity to tropical deforestation

Regional to global-scale climate sensitivity to tropical deforestation is simulated using a modified version of the NCAR Community Climate Model (CCM1-Oz) which includes a mixed-layer ocean model, a 3-layer sea-ice model and BATS (the Biosphere-Atmosphere Transfer Scheme). A fourteen-year control integration is followed by a six year deforestation experiment in which the tropical moist forest throughout the Amazon Basin, S.E. Asia and tropical Africa is replaced by scrub grassland. The three deforested regions sustain different impacts on their regional climates. The largest disturbances occur in the Amazon Basin where total precipitation decreases by −437 mm yr −1, evaporation decreases by −231 mm yr −1 and a marked decrease in moisture convergence is clear, although the surface temperature increases by 0.3 K. In S.E. Asia, surface temperature decreases in 11 months with an annual average cooling of −0.7 K; total evaporation decreases all the year by 130 mm yr −1; while the sign of the precipitation changes is strongly seasonal. The African region is least affected by deforestation, although surface net radiation decreases year-round and there is a detectable decrease in moisture convergence in the dry season. Regional responses to deforestation differ because regional circulation patterns are affected differently. For example, while ground surface temperatures increase in the Southern Amazon and over this basin as a whole, the northern Amazon, S.E. Asia and Africa all exhibit decreases in ground surface temperatures. The modification of atmospheric circulation patterns over deforested tropical regions prompts climate responses distant from the disturbance. Impacts of tropical deforestation include a disturbance of the Asian monsoon and small but statistically significant changes in climate in the middle and high latitudes.

Assessing the Sensitivity of a Land-Surface Scheme to the Parameter Values Using a Single Column Model

The sensitivity of a land-surface scheme (the Biosphere Atmosphere Transfer Scheme, BATS) to its parameter values was investigated using a single column model. Identifying which parameters were important in controlling the turbulent energy fluxes, temperature, soil moisture, and runoff was dependent upon many factors. In the simulation of a nonmoisture-stressed tropical forest, results were dependent on a combination of reservoir terms (soil depth, root distribution), flux efficiency terms (roughness length, stomatal resistance), and available energy (albedo). If moisture became limited, the reservoir terms increased in importance because the total fluxes predicted depended on moisture availability and not on the rate of transfer between the surface and the atmosphere. The sensitivity shown by BATS depended on which vegetation type was being simulated, which variable was used to determine sensitivity, the magnitude and sign of the parameter change, the climate regime (precipitation amount and frequency), and soil moisture levels and proximity to wilting. The interactions between these factors made it difficult to identify the most important parameters in BATS. Therefore, this paper does not argue that a particular set of parameters is important in BATS, rather it shows that no general ranking of parameters is possible. It is also emphasized that using “stand-alone” forcing to examine the sensitivity of a land-surface scheme to perturbations, in either parameters or the atmosphere, is unreliable due to the lack of surface-atmospheric feedbacks.

Land‐surface characterization in greenhouse climate simulations

AbstractA simplified Holdridge‐type vegetation prediction scheme has been coupled to a version of the NCAR community climate model (CCM1‐Oz) that includes the biosphere‐atmosphere transfer scheme (BATS) and a mixed‐layer ocean. This interactive vegetation climate model has been used to conduct two complementary CO2‐doubling experiments: an instantaneous 2 x CO2 simulation (15 years in total) and a fast, transiently increasing CO2 simulation (45 years in total). There are some differences in the predicted vegetation distributions and areas. However, there is agreement that in a warmed world the vegetation type termed ‘agriculture’ increases in area at the expense of deciduous needle‐leaf trees and short grass; and the tundra extent, already underestimated, decreases further whereas deserts and the deciduous broadleaf tree areas expand. The overall vegetation areas predicted are not particularly sensitive to initialization, although effects of different initialization can be monitored for 1–2 years. On the other hand, when the sensitivity of the modelled climate to the inclusion of some aspects of an interactive biosphere is examined, it is found that annually updated continental characteristics do not disrupt the climate simulation but do modify zonal temperatures and precipitation and increase continental evaporation. The latter intensifies the Hadley circulation, especially in July, and, thus, leads to increased evaporation globally. These results, if corroborated by other similar studies, indicate that simple, post facto application of vegetation diagnostic schemes once climatic equilibrium is achieved may be diagnosing vegetation from an incorrect climatic state.

Simulating fluxes from heterogeneous land surfaces: Explicit subgrid method employing the biosphere‐atmosphere transfer scheme (BATS)

A vectorized version of the biosphere‐atmosphere transfer scheme (VBATS) is used to study moisture, energy, and momentum fluxes from heterogeneous land surfaces at the scale of an atmospheric model (AM) grid cell. To incorporate subgrid scale inhomogeneity, VBATS includes two important features: (1) characterization of the land surface (vegetation and soil parameters) at N subgrid points within an AM grid cell and (2) explicit distribution of climatic forcing (precipitation, clouds, etc.) over the subgrid. In this study, VBATS is used in stand‐alone mode to simulate a single AM grid cell and to evaluate the effects of subgrid scale vegetation and climate specification on the surface fluxes and hydrology. It is found that the partitioning of energy can be affected by up to 30%, runoff by 50%, and surface stress in excess of 60%. Distributing climate forcing over the AM grid cell increases the Bowen ratio, as a result of enhanced sensible heat flux and reduced latent heat flux. The combined effect of heterogeneous vegetation and distribution of climate is found to be dependent on the dominant vegetation class in the AM grid cell. Development of this method is part of a larger program to explore the importance of subgrid scale processes in regional and global climate simulations.

Sensitivity Properties of a Biosphere Model Based on BATS and a Statistical-Dynamical Climate Model

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover, soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations.

Comparison of the land surface climatology of the National Center for Atmospheric Research community climate model 2 at R15 and T42 resolutions

Land surface climatologies averaged over the last 5 years of 10‐year seasonal cycle integrations of the National Center for Atmospheric Research community climate model 2 (CCM2) with the Biosphere‐Atmosphere Transfer Scheme (BATS) land surface option configured for R15 and T42 resolutions were compared. Both simulations had a large warm‐temperature bias over northern hemisphere land regions in July. The CCM2 without BATS has a similar bias, which BATS, with its interactive hydrology, accentuated. Both simulations had too much precipitation, which is also a feature of CCM2 without BATS. Most differences in continental‐averaged hydrologic and surface energy fluxes between the R15 and T42 simulations were minor for January and July (<0.4 mm d−1 and <11 W m−1). Only 5 of 14 continental‐scale comparisons showed larger differences. In two of these, differences in land surface hydrology and energy exchange between the R15 and T42 simulations were related to precipitation differences, possibly from changes in the cloud fraction parameterization of CCM2 in its R15 and T42 configurations. The spatial resolution of the model was also important for the Mississippi Basin, where the T42 model was hotter and drier than the R15 model. These analyses show that improved spatial resolution does not necessarily result in continental‐averaged land surface climatologies substantially different from those of lower‐resolution models but that the improved resolution can be important at regional scales.

Simulation of Summer Monsoon Climate over East Asia with an NCAR Regional Climate Model

Abstract A summertime season climate over east Asia is simulated with a regional climate model (RegCM) developed at the National Center for Atmospheric Research (NCAR) to validate the model's capability to produce the basic characteristics of monsoon climate over the region. The RegCM used here is a modified version of the NCAR-Pennsylvania State University Mesoscale Model (MM4), in which the Biosphere-Atmosphere Transfer Scheme and a detailed radiative transfer package have been implemented for climate application. The model horizontal resolution is 50 km, and the domain covers a 5200 km × 4700 km area encompassing eastern Asia and adjacent ocean regions. The simulation period is June–August 1990, and the model-driving initial and lateral boundary conditions are from European Centre for Medium-Range Weather Forecasts analyses of observations. The simulated patterns of the monsoon circulation, precipitation, and land-surface temperature are in general agreement with observations, although the model is som...

Continental vegetation as a dynamic component of a global climate model: a preliminary assessment

A simplified vegetation distribution prediction scheme is used in combination with the Biosphere-Atmosphere Transfer Scheme (BATS) and coupled to a version of the NCAR Community Climate Model (CCM1) which includes a mixed-layer ocean. Employed in an off-line mode as a diagnostic tool, the scheme predicts a slightly darker and slightly rougher continental surface than when BATS' prescribed vegetation classes are used. The impact of tropical deforestation on regional climates, and hence on diagnosed vegetation, differs between South America and S.E. Asia. In the Amazon, the climatic effects of removing all the tropical forest are so marked that in only one of the 18 deforested grid elements could the new climate sustain tropical forest vegetation whereas in S.E. Asia in seven of the 9 deforested elements the climate could continue to support tropical forest. Following these off-line tests, the simple vegetation scheme has been coupled to the GCM as an interactive (or two-way) submodel for a test integration lasting 5.6 yr. It is found to be a stable component of the global climate system, producing only ~ 3% (absolute) interannual changes in the predicted percentages of continental vegetation, together with globally-averaged continental temperature increases of up to + 1.5 °C and evaporation increases of 0 to 5 W m−2 and no discernible trends over the 67 months of integration. On the other hand, this interactive land biosphere causes regional-scale temperature differences of ± 10 °C and commensurate disturbances in other climatic parameters. Tuning, similar to the q-flux schemes used for ocean models, could improve the simulation of the present-day surface climate but, in the longer term, it will be important to focus on predicting the characteristics of the continental surface rather than simple vegetation classes. The coupling scheme will also have to allow for vegetation responses occurring over longer timescales so that the coupled system is buffered from sudden shocks.

Estimation of surface heat and moisture fluxes over a prairie grassland: 4. Impact of satellite remote sensing of slow canopy variables on performance of a hybrid biosphere model

Herein, we present the results of a series of numerical experiments using the Ex‐BATS biosphere model, which is an adaptation of Dickinson's biosphere‐atmosphere transfer scheme (BATS). These simulations are used to assess how the model performs when remotely sensed data are used to estimate three key canopy variables. These canopy variables, which effectively represent the slowly changing boundary conditions of a vegetated surface, consist of the total surface albedo, leaf area index, and the nondiurnally varying component of stomatal resistance, referred to as stressed stomatal resistance. The surface albedo is retrieved from NOAA‐AVHRR (advanced very high resolution radiometer) channel 1 spectral reflectance information in conjunction with a directional reflectance model which accounts for the strong diurnal variations in surface reflectance. A 4‐channel vegetation index also retrieved from AVHRR measurements is used to estimate the leaf area index. A similar index derived from high‐resolution SPOT visible and near‐infrared information has been used to describe the spatial variations in such indices which impact the retrieval of the leaf area index. Satellite retrieval of stomatal resistance is based on split‐window skin temperatures from AVHRR channels 4 and 5 from the afternoon overpass (∼1630 LT). Variables derived from the hourly skin temperature observations of GOES‐VISSR have also been examined with respect to retrieval of stomatal resistance. It was found that although stomatal resistance has little correlation with the diurnal amplitude of skin temperature, it is closely related to the daily maximum of skin temperature. Numerical experiments have been conducted to examine model sensitivity to each of these canopy variables. Results indicate that Ex‐BATS is not sensitive to small variations of surface albedo or leaf area index within the range of estimation uncertainty. The rms measurement‐model flux differences in every numerical trial were within 6 W m−2 of the rms differences obtained for the simulations performed using measured albedo and leaf area index. Measured stomatal resistance values were obtained using an inversion form of the model. The resulting stomatal resistances were used to perform a control experiment simulating an ideal satellite retrieval scenario involving one observation per day. The control experiment resulted in improvements of approximately 20 W m−2 in the rms flux differences over the model using a purely hypothetical formulation for stomatal resistance. Simulations using the remotely retrieved stomatal resistances produced significantly reduced rms differences for latent and sensible heat fluxes over the model using the hypothetical formulation. Based on a 55‐day composite involving all days from the four FIFE intensive field campaigns, the sensible and latent heat flux improvements are approximately 25 and 20%, respectively (11 and 8 W m−2). The satellite retrievals are only 20 and 30% less accurate (7 and 10 W m−2) than the idealized results of the control experiment.

Estimation of surface heat and moisture fluxes over a prairie grassland: 3. Design of a hybrid physical/remote sensing biosphere model

This is the third in a series of papers describing a measurement program and modeling approach to the estimation of surface heat and moisture fluxes over a tallgrass prairie. We describe the design and formulation of an experimental biosphere model (Ex‐BATS) which follows the development of Dickinson's biosphere‐atmosphere transfer scheme (BATS). Ex‐BATS has been designed to incorporate in situ measurements and satellite parameterizations of certain canopy variables which are slowly varying in the course of a growing season. All components of a multistage biosphere process model used to simulate the exchange of heat and moisture between the canopy and the atmosphere are presented here. The remote sensing aspects of the model are described in a companion paper. The procedures used to optimize the model and the validation of the model against First ISLSCP Field Experiment (FIFE) observations taken during 1987 are described. Validation was carried out for three of the four intensive field campaigns (IFCs): 1, 2 and 3. The validation intercomparison shows that the Ex‐BATS model reproduces the diurnal behavior of the surface fluxes very closely. The rms differences between in situ measurements of sensible and latent heat fluxes and their model counterparts are of the order of 35 W m−2. Biases over the three IFCs, which ranged in duration from 10 to 17 days, are typically less than 20 W m −2. The overall bias for the 44 days within the first three IFCs is less than 10 W m −2. The biases and rms differences are of the same order as the accuracy and precision uncertainties of the measured fluxes, therefore the model provides a useful experimental tool to explain radiative, hydrological, and physiological controls on surface fluxes over vegetated canopies and the explicit sources of water flux to the atmosphere from transpiration, foliage evaporation, and soil evaporation.

A Factorial Assessment of the Sensitivity of the BATS Land-Surface Parameterization Scheme

Abstract Land-surface schemes developed for incorporation into global climate models include parameterizations that are not yet fully validated and depend upon the specification of a large (20–50) number of ecological and soil parameters, the values of which are not yet well known. There are two methods of investigating the sensitivity of a land-surface scheme to prescribed values: simple one-at-a-time changes or factorial experiments. Factorial experiments offer information about interactions between parameters and are thus a more powerful tool. Here the results of a suite of factorial experiments are reported. These are designed (i) to illustrate the usefulness of this methodology and (ii) to identify factors important to the performance of complex land-surface schemes. The Biosphere-Atmosphere Transfer Scheme (BATS) is used and its sensitivity is considered (a) to prescribed ecological and soil parameters and (b) to atmospheric forcing used in the off-line tests undertaken. Results indicate that the mo...

Assessing the Sensitivity of A Land‐Surface Scheme to Parameters Used In Tropical‐Deforestation Experiments

AbstractA series of factorial experiments is used to elucidate the factors and multifactor interactions important for the performance of one complex land‐surface scheme in a tropical environment. the BATS (Biosphere‐Atmosphere Transfer Scheme) is found to be sensitive to atmospheric factors which are currently poorly predicted by global climate models (GCMs) and, more importantly, to combinations of factors rendering tuning for good performance when coupled into today's global models (a worthless practice if the tropical area is subjected to different conditions such as those induced by deforestation). Similarly, two‐factor interactions, between coded ecological parameters (here roughness length and short wave, <0.7 μm, vegetation albedo), mean even if the BATS characterization and its driving GCM perform well in today's tropical‐forest environment, altering either or both parameters, as will occur in a deforestation simulation, must greatly diminish confidence in representations of future climate.

Bayesian relative information measure: A tool for analyzing the outputs of general circulation models

Mathematical models that generate scenarios containing no temporal correspondence to time series of actual occurrences are difficult to evaluate. One such class of models consists of atmospheric General Circulation Models (GCM), which have an additional drawback that the temporal and spatial scales of their outputs do not match those of the actual observations of the simulated phenomena. The problem of disparate scales can be ameliorated by aggregating both the model output and the observed data to commensurate scales. However, this approach does not permit quantitative testing at scales less than the least common level of aggregation. The lack of paired observations in the aggregated time series makes standard statistical methods either invalid or ineffective in testing the validity of a GCM. One approach to resolving this quandary is the use of a relative information measure, which is based on the uncertainties contained in the histograms of the aggregations of both the model output and the data base. Each interval of each histogram is analyzed, from a Bayesian perspective, as a binomial probability. For the data‐based histogram, the reciprocal of the sum of the variances of the posterior distributions of probability in each interval is denoted as its information content. For the model‐based histogram, the reciprocal of the sum of the expected mean squared errors of the posterior distributions in each interval likewise is its information content. The expected mean squared error, which accounts for potential biases in the GCM, is computed as the expectation of the squared differences between the data‐based and the model‐based posterior distributions for each interval. The ratio of the information content of the model‐based histogram to that of the data‐based histogram is the relative information of the model. A 5‐year monthly precipitation time series for January at a single node of the current version of the Community Climate Model including the Biosphere Atmosphere Transfer Scheme contains 7.5 % of the information in the most recent 30 years of data in the Climatological Data Set assembled by the National Climate Data Center (NCDC). If the 5‐year simulation were extended, its relative information content could be expected to approach 11.5 %. For July monthly precipitation, the 5‐year simulation contained 13.7 % of the information of the NCDC data base and had a limit of 39.3 % for extremely long simulations. Aggregation of two adjacent cells at the same latitude showed some improvements in relative information, but longitudinal aggregation with two additional adjacent cells showed improvement for January precipitation, but degraded information for July precipitation.

Land surface hydrology in a General Circulation Model N-global and regional fields needed for validation

Treatments of land surface processes in General Circulation Models are presently limited by the realism of the simulations of precipitation and surface radiation. We explore this thesis by examination of some of the climatological fields of a 6-year model simulation, using the Community Climate Model version 1 of the National Center for Atmospheric Research with addition of a diurnal cycle and coupled to a detailed treatment of land surface processes referred to as the Biosphere-Atmosphere Transfer Scheme. We examine July climatological surface fields over North America and note an excess of surface solar radiation over Eastern United States. Comparison with satellite derived cloud forcing suggests that the model underestimates the reduction of solar radiation by clouds over Eastern United States and in high latitudes, and so probably largely explaining the excess surface radiation. We consider the annual cycle of model hydrological fields (soil moisture, runoff, precipitation, evapotranspiration, net radiation) averaged over a box covering the central part of the United States (roughtly the Mississippi basin). The seasonal cycle of evapotranspiration over this box appears to be dominated by the variation of surface solar radiation and less related to that of precipitation.

Developing an interactive biosphere for global climate models

A highly generalised (five classes) grouping of Holdridge life zones, has been used to derive predicted ‘natural’ ecosystems for the present day climate using temperature and precipitation derived from two experiments undertaken with the NCAR Community Climate Model. These predictions differ from one another and both differ significantly from the prescribed classification groupings of ecosystem complexes used with a state-of-the-art land surface parameterization submodel, the Biosphere-Atmosphere Transfer Scheme. The highly generalised groupings show relatively little sensitivity to the temperature changes induced by doubling atmospheric CO2 but greater response when precipitation is also modified. All the doubled-CO2 scenarios predict increased ‘desert’ areas although these future climatically-induced changes to the global-scale ecology are very much smaller than the extensive disturbances already caused by mankind's land clearance and poor agriculture. Land-use change rendered 13% of the Earth's land surface ‘desert’ whereas the most pessimistic doubled-CO2 result gives rise to only a 2% increase in ‘desert’ area.

Predicting Generalized Ecosystem Groups with the NCAR CCM: First Steps towards an Interactive Biosphere

Canopy-plus-soil “big-leaf” models of the land surface now exist and are being incorporated in global climate models. These big-leaf models could be the basis for the incorporation of an interactive land biosphere into global models. However, their use depends upon satisfactory specification of the distribution of plants (and soils), and while such distributions can be obtained for the present-day, they must be manufactured for all other climatic scenarios. Thus, one prerequisite for the incorporation of an interactive land biosphere into global climate models is the successful prediction of the natural vegetation (or “climax” vegetation) for climatic scenarios such as the doubling of atmospheric carbon dioxide. (It is also necessary to predict agricultural land-use classes, but that is outside the scope of this paper.) A highly generalized (nine classes) grouping of Holdridge life zones has been used here as a means of investigating three-step “coupling” of a land-surface scheme into a global climate model. The investigation includes the derivation of nine “natural” ecosystems for the present day climate using temperature and precipitation derived from three experiments undertaken with the NCAR community climate model. These predictions differ from one another and both differ significantly from the prescribed classification groupings of ecosystem complexes used with one big-leaf, land-surface scheme—the Biosphere Atmosphere Transfer Scheme (BATS). On the other hand, these highly generalized groupings show relatively little sensitivity to the temperature changes induced by doubling atmospheric CO2 and even the inclusion of the precipitation disturbances in the doubled-CO2 scenario causes changes in the ecosystem “predictions” that are only of similar degree, or smaller, than the differences between sets of life-zone classes generated from present-day or doubled-CO2 climates. This result implies that the combined global field of “annual bio-temperature and precipitation” is not yet consistently predicted by GCMS, not that vegetation is likely to be insensitive to climate change.