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Abstract
Mosses dominate the surface cover in high northern latitudes and have the potential to play a key role in modifying the thermal and hydrologic regime of Arctic soils. These modifications in turn feed back to influence surface energy exchanges and hence may affect regional climate. However, mosses are poorly represented in models of the land surface. In this study the NCAR Land Surface Model (LSM) was modified in two ways. First, additional soil texture types including mosses and lichens were added to more realistically represent northern soils. Second, the LSM was also modified so that a different soil texture type could be specified for each layer. Several experiments were performed using climate data from an Arctic tundra site in 1995. The model was run for a homogeneous loam soil column and then also for columns that included moss, lichen, peat, and sand. The addition of a surface layer of moss underlain by peat and loam had a substantial impact on modeled surface processes. First, moss acted as an insulative layer producing cooler summer temperatures (6.9°C lower at 0.5 m) and warmer winter temperatures (2.3°C higher at 0.5 m) when compared with a homogenous loam soil column. Second, a soil column with a moss surface had a greater surface infiltration, leading to greater storage of soil moisture in lower layers when compared with a homogeneous loam column. Last, moss modulated the surface energy exchanges by decreasing soil heat flux (57% in July) and increasing turbulent fluxes of heat (67% in July) and moisture (15% in July). Mosses were also more effective contributors to total latent heating than was a bare loam surface. These results suggest that the addition of moss and the ability to prescribe different soil textures for different soil layers result in a more plausible distribution of heat and water within the column and that these modifications should be incorporated into regional and global climate models.
Abstract
Mosses dominate the surface cover in high northern latitudes and have the potential to play a key role in modifying the thermal and hydrologic regime of Arctic soils. These modifications in turn feed back to influence surface energy exchanges and hence may affect regional climate. However, mosses are poorly represented in models of the land surface. In this study the NCAR Land Surface Model (LSM) was modified in two ways. First, additional soil texture types including mosses and lichens were added to more realistically represent northern soils. Second, the LSM was also modified so that a different soil texture type could be specified for each layer. Several experiments were performed using climate data from an Arctic tundra site in 1995. The model was run for a homogeneous loam soil column and then also for columns that included moss, lichen, peat, and sand. The addition of a surface layer of moss underlain by peat and loam had a substantial impact on modeled surface processes. First, moss acted as an insulative layer producing cooler summer temperatures (6.9°C lower at 0.5 m) and warmer winter temperatures (2.3°C higher at 0.5 m) when compared with a homogenous loam soil column. Second, a soil column with a moss surface had a greater surface infiltration, leading to greater storage of soil moisture in lower layers when compared with a homogeneous loam column. Last, moss modulated the surface energy exchanges by decreasing soil heat flux (57% in July) and increasing turbulent fluxes of heat (67% in July) and moisture (15% in July). Mosses were also more effective contributors to total latent heating than was a bare loam surface. These results suggest that the addition of moss and the ability to prescribe different soil textures for different soil layers result in a more plausible distribution of heat and water within the column and that these modifications should be incorporated into regional and global climate models.
Abstract
The land surface parameterization used with the community climate model (CCM3) and the climate system model (CSM1), the National Center for Atmospheric Research land surface model (NCAR LSM1), has been modified as part of the development of the next version of these climate models. This new model is known as the community land model (CLM2). In CLM2, the surface is represented by five primary subgrid land cover types (glacier, lake, wetland, urban, vegetated) in each grid cell. The vegetated portion of a grid cell is further divided into patches of up to 4 of 16 plant functional types, each with its own leaf and stem area index and canopy height. The relative area of each subgrid unit, the plant functional type, and leaf area index are obtained from 1-km satellite data. The soil texture dataset allows vertical profiles of sand and clay. Most of the physical parameterizations in the model were also updated. Major model differences include: 10 layers for soil temperature and soil water with explicit treatment of liquid water and ice; a multilayer snowpack; runoff based on the TOPMODEL concept; new formulation of ground and vegetation fluxes; and vertical root profiles from a global synthesis of ecological studies. Simulations with CCM3 show significant improvements in surface air temperature, snow cover, and runoff for CLM2 compared to LSM1. CLM2 generally warms surface air temperature in all seasons compared to LSM1, reducing or eliminating many cold biases. Annual precipitation over land is reduced from 2.35 mm day−1 in LSM1 to 2.14 mm day−1 in CLM2. The hydrologic cycle is also different. Transpiration and ground evaporation are reduced. Leaves and stems evaporate more intercepted water annually in CLM2 than LSM1. Global runoff from land increases from 0.75 mm day−1 in LSM1 to 0.84 mm day−1 in CLM2. The annual cycle of runoff is greatly improved in CLM2, especially in arctic and boreal regions where the model has low runoff in cold seasons when the soil is frozen and high runoff during the snowmelt season. Most of the differences between CLM2 and LSM1 are attributed to particular parameterizations rather than to different surface datasets. Important processes include: multilayer snow, frozen water, interception, soil water limitation to latent heat, and higher aerodynamic resistances to heat exchange from ground.
Abstract
The land surface parameterization used with the community climate model (CCM3) and the climate system model (CSM1), the National Center for Atmospheric Research land surface model (NCAR LSM1), has been modified as part of the development of the next version of these climate models. This new model is known as the community land model (CLM2). In CLM2, the surface is represented by five primary subgrid land cover types (glacier, lake, wetland, urban, vegetated) in each grid cell. The vegetated portion of a grid cell is further divided into patches of up to 4 of 16 plant functional types, each with its own leaf and stem area index and canopy height. The relative area of each subgrid unit, the plant functional type, and leaf area index are obtained from 1-km satellite data. The soil texture dataset allows vertical profiles of sand and clay. Most of the physical parameterizations in the model were also updated. Major model differences include: 10 layers for soil temperature and soil water with explicit treatment of liquid water and ice; a multilayer snowpack; runoff based on the TOPMODEL concept; new formulation of ground and vegetation fluxes; and vertical root profiles from a global synthesis of ecological studies. Simulations with CCM3 show significant improvements in surface air temperature, snow cover, and runoff for CLM2 compared to LSM1. CLM2 generally warms surface air temperature in all seasons compared to LSM1, reducing or eliminating many cold biases. Annual precipitation over land is reduced from 2.35 mm day−1 in LSM1 to 2.14 mm day−1 in CLM2. The hydrologic cycle is also different. Transpiration and ground evaporation are reduced. Leaves and stems evaporate more intercepted water annually in CLM2 than LSM1. Global runoff from land increases from 0.75 mm day−1 in LSM1 to 0.84 mm day−1 in CLM2. The annual cycle of runoff is greatly improved in CLM2, especially in arctic and boreal regions where the model has low runoff in cold seasons when the soil is frozen and high runoff during the snowmelt season. Most of the differences between CLM2 and LSM1 are attributed to particular parameterizations rather than to different surface datasets. Important processes include: multilayer snow, frozen water, interception, soil water limitation to latent heat, and higher aerodynamic resistances to heat exchange from ground.
Abstract
This paper reviews developments for the Community Land Model, version 4 (CLM4), examines the land surface climate simulation of the Community Climate System Model, version 4 (CCSM4) compared to CCSM3, and assesses new earth system features of CLM4 within CCSM4. CLM4 incorporates a broad set of improvements including additions of a carbon–nitrogen (CN) biogeochemical model, an urban canyon model, and transient land cover and land use change, as well as revised soil and snow submodels.
Several aspects of the surface climate simulation are improved in CCSM4. Improvements in the simulation of soil water storage, evapotranspiration, surface albedo, and permafrost that are apparent in offline CLM4 simulations are generally retained in CCSM4. The global land air temperature bias is reduced and the annual cycle is improved in many locations, especially at high latitudes. The global land precipitation bias is larger in CCSM4 because of bigger wet biases in central and southern Africa and Australia.
New earth system capabilities are assessed. The present-day air temperature within urban areas is warmer than surrounding rural areas by 1°–2°C, which is comparable to or greater than the change in climate occurring over the last 130 years. The snow albedo feedback is more realistic and the radiative forcing of snow aerosol deposition is calculated as +0.083 W m−2 for present day. The land carbon flux due to land use, wildfire, and net ecosystem production is a source of carbon to the atmosphere throughout most of the historical simulation. CCSM4 is increasingly suited for studies of the role of land processes in climate and climate change.
Abstract
This paper reviews developments for the Community Land Model, version 4 (CLM4), examines the land surface climate simulation of the Community Climate System Model, version 4 (CCSM4) compared to CCSM3, and assesses new earth system features of CLM4 within CCSM4. CLM4 incorporates a broad set of improvements including additions of a carbon–nitrogen (CN) biogeochemical model, an urban canyon model, and transient land cover and land use change, as well as revised soil and snow submodels.
Several aspects of the surface climate simulation are improved in CCSM4. Improvements in the simulation of soil water storage, evapotranspiration, surface albedo, and permafrost that are apparent in offline CLM4 simulations are generally retained in CCSM4. The global land air temperature bias is reduced and the annual cycle is improved in many locations, especially at high latitudes. The global land precipitation bias is larger in CCSM4 because of bigger wet biases in central and southern Africa and Australia.
New earth system capabilities are assessed. The present-day air temperature within urban areas is warmer than surrounding rural areas by 1°–2°C, which is comparable to or greater than the change in climate occurring over the last 130 years. The snow albedo feedback is more realistic and the radiative forcing of snow aerosol deposition is calculated as +0.083 W m−2 for present day. The land carbon flux due to land use, wildfire, and net ecosystem production is a source of carbon to the atmosphere throughout most of the historical simulation. CCSM4 is increasingly suited for studies of the role of land processes in climate and climate change.
Abstract
The Community Earth System Model, version 1 (CESM1) is evaluated with two coupled atmosphere–land simulations. The CTRL (control) simulation represents crops as unmanaged grasses, while CROP represents a crop managed simulation that includes special algorithms for midlatitude corn, soybean, and cereal phenology and carbon allocation. CROP has a more realistic leaf area index (LAI) for crops than CTRL. CROP reduces winter LAI and represents the spring planting and fall harvest explicitly. At the peak of the growing season, CROP simulates higher crop LAI. These changes generally reduce the latent heat flux but not around peak LAI (late spring/early summer). In midwestern North America, where corn, soybean, and cereal abundance is high, simulated peak summer precipitation declines and agrees better with observations, particularly when crops emerge late as is found from a late planting sensitivity simulation (LateP). Differences between the CROP and LateP simulations underscore the importance of simulating crop planting and harvest dates correctly. On the biogeochemistry side, the annual cycle of net ecosystem exchange (NEE) also improves in CROP relative to Ameriflux site observations. For a global perspective, the authors diagnose annual cycles of CO2 from the simulated NEE (CO2 is not prognostic in these simulations) and compare against representative GLOBALVIEW monitoring stations. The authors find an increased (thus also improved) amplitude of the annual cycle in CROP. These regional and global-scale refinements from improvements in the simulated plant phenology have promising implications for the development of the CESM and particularly for simulations with prognostic atmospheric CO2.
Abstract
The Community Earth System Model, version 1 (CESM1) is evaluated with two coupled atmosphere–land simulations. The CTRL (control) simulation represents crops as unmanaged grasses, while CROP represents a crop managed simulation that includes special algorithms for midlatitude corn, soybean, and cereal phenology and carbon allocation. CROP has a more realistic leaf area index (LAI) for crops than CTRL. CROP reduces winter LAI and represents the spring planting and fall harvest explicitly. At the peak of the growing season, CROP simulates higher crop LAI. These changes generally reduce the latent heat flux but not around peak LAI (late spring/early summer). In midwestern North America, where corn, soybean, and cereal abundance is high, simulated peak summer precipitation declines and agrees better with observations, particularly when crops emerge late as is found from a late planting sensitivity simulation (LateP). Differences between the CROP and LateP simulations underscore the importance of simulating crop planting and harvest dates correctly. On the biogeochemistry side, the annual cycle of net ecosystem exchange (NEE) also improves in CROP relative to Ameriflux site observations. For a global perspective, the authors diagnose annual cycles of CO2 from the simulated NEE (CO2 is not prognostic in these simulations) and compare against representative GLOBALVIEW monitoring stations. The authors find an increased (thus also improved) amplitude of the annual cycle in CROP. These regional and global-scale refinements from improvements in the simulated plant phenology have promising implications for the development of the CESM and particularly for simulations with prognostic atmospheric CO2.
Abstract
Several multidecadal simulations have been carried out with the new version of the Community Climate System Model (CCSM). This paper reports an analysis of the land component of these simulations. Global annual averages over land appear to be within the uncertainty of observational datasets, but the seasonal cycle over land of temperature and precipitation appears to be too weak. These departures from observations appear to be primarily a consequence of deficiencies in the simulation of the atmospheric model rather than of the land processes. High latitudes of northern winter are biased sufficiently warm to have a significant impact on the simulated value of global land temperature. The precipitation is approximately doubled from what it should be at some locations, and the snowpack and spring runoff are also excessive. The winter precipitation over Tibet is larger than observed. About two-thirds of this precipitation is sublimated during the winter, but what remains still produces a snowpack that is very large compared to that observed with correspondingly excessive spring runoff. A large cold anomaly over the Sahara Desert and Sahel also appears to be a consequence of a large anomaly in downward longwave radiation; low column water vapor appears to be most responsible. The modeled precipitation over the Amazon basin is low compared to that observed, the soil becomes too dry, and the temperature is too warm during the dry season.
Abstract
Several multidecadal simulations have been carried out with the new version of the Community Climate System Model (CCSM). This paper reports an analysis of the land component of these simulations. Global annual averages over land appear to be within the uncertainty of observational datasets, but the seasonal cycle over land of temperature and precipitation appears to be too weak. These departures from observations appear to be primarily a consequence of deficiencies in the simulation of the atmospheric model rather than of the land processes. High latitudes of northern winter are biased sufficiently warm to have a significant impact on the simulated value of global land temperature. The precipitation is approximately doubled from what it should be at some locations, and the snowpack and spring runoff are also excessive. The winter precipitation over Tibet is larger than observed. About two-thirds of this precipitation is sublimated during the winter, but what remains still produces a snowpack that is very large compared to that observed with correspondingly excessive spring runoff. A large cold anomaly over the Sahara Desert and Sahel also appears to be a consequence of a large anomaly in downward longwave radiation; low column water vapor appears to be most responsible. The modeled precipitation over the Amazon basin is low compared to that observed, the soil becomes too dry, and the temperature is too warm during the dry season.
Abstract
Version 1 of the Community Earth System Model, in the configuration where its full carbon cycle is enabled, is introduced and documented. In this configuration, the terrestrial biogeochemical model, which includes carbon–nitrogen dynamics and is present in earlier model versions, is coupled to an ocean biogeochemical model and atmospheric CO2 tracers. The authors provide a description of the model, detail how preindustrial-control and twentieth-century experiments were initialized and forced, and examine the behavior of the carbon cycle in those experiments. They examine how sea- and land-to-air CO2 fluxes contribute to the increase of atmospheric CO2 in the twentieth century, analyze how atmospheric CO2 and its surface fluxes vary on interannual time scales, including how they respond to ENSO, and describe the seasonal cycle of atmospheric CO2 and its surface fluxes. While the model broadly reproduces observed aspects of the carbon cycle, there are several notable biases, including having too large of an increase in atmospheric CO2 over the twentieth century and too small of a seasonal cycle of atmospheric CO2 in the Northern Hemisphere. The biases are related to a weak response of the carbon cycle to climatic variations on interannual and seasonal time scales and to twentieth-century anthropogenic forcings, including rising CO2, land-use change, and atmospheric deposition of nitrogen.
Abstract
Version 1 of the Community Earth System Model, in the configuration where its full carbon cycle is enabled, is introduced and documented. In this configuration, the terrestrial biogeochemical model, which includes carbon–nitrogen dynamics and is present in earlier model versions, is coupled to an ocean biogeochemical model and atmospheric CO2 tracers. The authors provide a description of the model, detail how preindustrial-control and twentieth-century experiments were initialized and forced, and examine the behavior of the carbon cycle in those experiments. They examine how sea- and land-to-air CO2 fluxes contribute to the increase of atmospheric CO2 in the twentieth century, analyze how atmospheric CO2 and its surface fluxes vary on interannual time scales, including how they respond to ENSO, and describe the seasonal cycle of atmospheric CO2 and its surface fluxes. While the model broadly reproduces observed aspects of the carbon cycle, there are several notable biases, including having too large of an increase in atmospheric CO2 over the twentieth century and too small of a seasonal cycle of atmospheric CO2 in the Northern Hemisphere. The biases are related to a weak response of the carbon cycle to climatic variations on interannual and seasonal time scales and to twentieth-century anthropogenic forcings, including rising CO2, land-use change, and atmospheric deposition of nitrogen.
Abstract
To assess the climate impacts of historical and projected land cover change in the Community Climate System Model, version 4 (CCSM4), new time series of transient Community Land Model, version 4 (CLM4) plant functional type (PFT) and wood harvest parameters have been developed. The new parameters capture the dynamics of the Coupled Model Intercomparison Project phase 5 (CMIP5) land cover change and wood harvest trajectories for the historical period from 1850 to 2005 and for the four representative concentration pathway (RCP) scenarios from 2006 to 2100. Analysis of the biogeochemical impacts of land cover change in CCSM4 reveals that the model produced a historical cumulative land use flux of 127.7 PgC from 1850 to 2005, which is in general agreement with other global estimates of 156 PgC for the same period. The biogeophysical impacts of the transient land cover change parameters were cooling of the near-surface atmosphere over land by −0.1°C, through increased surface albedo and reduced shortwave radiation absorption. When combined with other transient climate forcings, the higher albedo from land cover change was counteracted by decreasing snow albedo from black carbon deposition and high-latitude warming. The future CCSM4 RCP simulations showed that the CLM4 transient PFT parameters can be used to represent a wide range of land cover change scenarios. In the reforestation scenario of RCP 4.5, CCSM4 simulated a drawdown of 67.3 PgC from the atmosphere into the terrestrial ecosystem and product pools. By contrast the RCP 8.5 scenario with deforestation and high wood harvest resulted in the release of 30.3 PgC currently stored in the ecosystem.
Abstract
To assess the climate impacts of historical and projected land cover change in the Community Climate System Model, version 4 (CCSM4), new time series of transient Community Land Model, version 4 (CLM4) plant functional type (PFT) and wood harvest parameters have been developed. The new parameters capture the dynamics of the Coupled Model Intercomparison Project phase 5 (CMIP5) land cover change and wood harvest trajectories for the historical period from 1850 to 2005 and for the four representative concentration pathway (RCP) scenarios from 2006 to 2100. Analysis of the biogeochemical impacts of land cover change in CCSM4 reveals that the model produced a historical cumulative land use flux of 127.7 PgC from 1850 to 2005, which is in general agreement with other global estimates of 156 PgC for the same period. The biogeophysical impacts of the transient land cover change parameters were cooling of the near-surface atmosphere over land by −0.1°C, through increased surface albedo and reduced shortwave radiation absorption. When combined with other transient climate forcings, the higher albedo from land cover change was counteracted by decreasing snow albedo from black carbon deposition and high-latitude warming. The future CCSM4 RCP simulations showed that the CLM4 transient PFT parameters can be used to represent a wide range of land cover change scenarios. In the reforestation scenario of RCP 4.5, CCSM4 simulated a drawdown of 67.3 PgC from the atmosphere into the terrestrial ecosystem and product pools. By contrast the RCP 8.5 scenario with deforestation and high wood harvest resulted in the release of 30.3 PgC currently stored in the ecosystem.
Abstract
Most evapotranspiration over land occurs through vegetation. The fraction of net radiation balanced by evapotranspiration depends on stomatal controls. Stomates transpire water for the leaf to assimilate carbon, depending on the canopy carbon demand, and on root uptake, if it is limiting. Canopy carbon demand in turn depends on the balancing between visible photon-driven and enzyme-driven steps in the leaf carbon physiology. The enzyme-driven component is here represented by a Rubisco-related nitrogen reservoir that interacts with plant–soil nitrogen cycling and other components of a climate model. Previous canopy carbon models included in GCMs have assumed either fixed leaf nitrogen, that is, prescribed photosynthetic capacities, or an optimization between leaf nitrogen and light levels so that in either case stomatal conductance varied only with light levels and temperature.
A nitrogen model is coupled to a previously derived but here modified carbon model and includes, besides the enzyme reservoir, additional plant stores for leaf structure and roots. It also includes organic and mineral reservoirs in the soil; the latter are generated, exchanged, and lost by biological fixation, deposition and fertilization, mineralization, nitrification, root uptake, denitrification, and leaching. The root nutrient uptake model is a novel and simple, but rigorous, treatment of soil transport and root physiological uptake. The other soil components are largely derived from previously published parameterizations and global budget constraints.
The feasibility of applying the derived biogeochemical cycling model to climate model calculations of evapotranspiration is demonstrated through its incorporation in the Biosphere–Atmosphere Transfer Scheme land model and a 17-yr Atmospheric Model Inter comparison Project II integration with the NCAR CCM3 GCM. The derived global budgets show land net primary production (NPP), fine root carbon, and various aspects of the nitrogen cycling are reasonably consistent with past studies. Time series for monthly statistics averaged over model grid points for the Amazon evergreen forest and lower Colorado basin demonstrate the coupled interannual variability of modeled precipitation, evapotranspiration, NPP, and canopy Rubisco enzymes.
Abstract
Most evapotranspiration over land occurs through vegetation. The fraction of net radiation balanced by evapotranspiration depends on stomatal controls. Stomates transpire water for the leaf to assimilate carbon, depending on the canopy carbon demand, and on root uptake, if it is limiting. Canopy carbon demand in turn depends on the balancing between visible photon-driven and enzyme-driven steps in the leaf carbon physiology. The enzyme-driven component is here represented by a Rubisco-related nitrogen reservoir that interacts with plant–soil nitrogen cycling and other components of a climate model. Previous canopy carbon models included in GCMs have assumed either fixed leaf nitrogen, that is, prescribed photosynthetic capacities, or an optimization between leaf nitrogen and light levels so that in either case stomatal conductance varied only with light levels and temperature.
A nitrogen model is coupled to a previously derived but here modified carbon model and includes, besides the enzyme reservoir, additional plant stores for leaf structure and roots. It also includes organic and mineral reservoirs in the soil; the latter are generated, exchanged, and lost by biological fixation, deposition and fertilization, mineralization, nitrification, root uptake, denitrification, and leaching. The root nutrient uptake model is a novel and simple, but rigorous, treatment of soil transport and root physiological uptake. The other soil components are largely derived from previously published parameterizations and global budget constraints.
The feasibility of applying the derived biogeochemical cycling model to climate model calculations of evapotranspiration is demonstrated through its incorporation in the Biosphere–Atmosphere Transfer Scheme land model and a 17-yr Atmospheric Model Inter comparison Project II integration with the NCAR CCM3 GCM. The derived global budgets show land net primary production (NPP), fine root carbon, and various aspects of the nitrogen cycling are reasonably consistent with past studies. Time series for monthly statistics averaged over model grid points for the Amazon evergreen forest and lower Colorado basin demonstrate the coupled interannual variability of modeled precipitation, evapotranspiration, NPP, and canopy Rubisco enzymes.
Abstract
The magnitude and evolution of parameters that characterize feedbacks in the coupled carbon–climate system are compared across nine Earth system models (ESMs). The analysis is based on results from biogeochemically, radiatively, and fully coupled simulations in which CO2 increases at a rate of 1% yr−1. These simulations are part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). The CO2 fluxes between the atmosphere and underlying land and ocean respond to changes in atmospheric CO2 concentration and to changes in temperature and other climate variables. The carbon–concentration and carbon–climate feedback parameters characterize the response of the CO2 flux between the atmosphere and the underlying surface to these changes. Feedback parameters are calculated using two different approaches. The two approaches are equivalent and either may be used to calculate the contribution of the feedback terms to diagnosed cumulative emissions. The contribution of carbon–concentration feedback to diagnosed cumulative emissions that are consistent with the 1% increasing CO2 concentration scenario is about 4.5 times larger than the carbon–climate feedback. Differences in the modeled responses of the carbon budget to changes in CO2 and temperature are seen to be 3–4 times larger for the land components compared to the ocean components of participating models. The feedback parameters depend on the state of the system as well the forcing scenario but nevertheless provide insight into the behavior of the coupled carbon–climate system and a useful common framework for comparing models.
Abstract
The magnitude and evolution of parameters that characterize feedbacks in the coupled carbon–climate system are compared across nine Earth system models (ESMs). The analysis is based on results from biogeochemically, radiatively, and fully coupled simulations in which CO2 increases at a rate of 1% yr−1. These simulations are part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). The CO2 fluxes between the atmosphere and underlying land and ocean respond to changes in atmospheric CO2 concentration and to changes in temperature and other climate variables. The carbon–concentration and carbon–climate feedback parameters characterize the response of the CO2 flux between the atmosphere and the underlying surface to these changes. Feedback parameters are calculated using two different approaches. The two approaches are equivalent and either may be used to calculate the contribution of the feedback terms to diagnosed cumulative emissions. The contribution of carbon–concentration feedback to diagnosed cumulative emissions that are consistent with the 1% increasing CO2 concentration scenario is about 4.5 times larger than the carbon–climate feedback. Differences in the modeled responses of the carbon budget to changes in CO2 and temperature are seen to be 3–4 times larger for the land components compared to the ocean components of participating models. The feedback parameters depend on the state of the system as well the forcing scenario but nevertheless provide insight into the behavior of the coupled carbon–climate system and a useful common framework for comparing models.
The Common Land Model (CLM) was developed for community use by a grassroots collaboration of scientists who have an interest in making a general land model available for public use and further development. The major model characteristics include enough unevenly spaced layers to adequately represent soil temperature and soil moisture, and a multilayer parameterization of snow processes; an explicit treatment of the mass of liquid water and ice water and their phase change within the snow and soil system; a runoff parameterization following the TOPMODEL concept; a canopy photo synthesis-conductance model that describes the simultaneous transfer of CO2 and water vapor into and out of vegetation; and a tiled treatment of the subgrid fraction of energy and water balance. CLM has been extensively evaluated in offline mode and coupling runs with the NCAR Community Climate Model (CCM3). The results of two offline runs, presented as examples, are compared with observations and with the simulation of three other land models [the Biosphere-Atmosphere Transfer Scheme (BATS), Bonan's Land Surface Model (LSM), and the 1994 version of the Chinese Academy of Sciences Institute of Atmospheric Physics LSM (IAP94)].
The Common Land Model (CLM) was developed for community use by a grassroots collaboration of scientists who have an interest in making a general land model available for public use and further development. The major model characteristics include enough unevenly spaced layers to adequately represent soil temperature and soil moisture, and a multilayer parameterization of snow processes; an explicit treatment of the mass of liquid water and ice water and their phase change within the snow and soil system; a runoff parameterization following the TOPMODEL concept; a canopy photo synthesis-conductance model that describes the simultaneous transfer of CO2 and water vapor into and out of vegetation; and a tiled treatment of the subgrid fraction of energy and water balance. CLM has been extensively evaluated in offline mode and coupling runs with the NCAR Community Climate Model (CCM3). The results of two offline runs, presented as examples, are compared with observations and with the simulation of three other land models [the Biosphere-Atmosphere Transfer Scheme (BATS), Bonan's Land Surface Model (LSM), and the 1994 version of the Chinese Academy of Sciences Institute of Atmospheric Physics LSM (IAP94)].
