The role of surface energy balance complexity in land surface models' sensitivity to increasing carbon dioxide

Global simulations with the Bureau of Meteorology Research Centre climate model coupled to the CHAmeleon Surface Model (CHASM) are used to explore the sensitivity of simulated changes in evaporation, precipitation, air temperature and soil moisture resulting from a doubling of carbon dioxide in the atmosphere. Five simulations, using prescribed sea surface temperatures, are conducted which are identical except in the level of complexity used to represent the surface energy balance. The simulation of air temperature, precipitation, evaporation and soil moisture at 1 2 CO₂ and at 2 2 CO₂ are generally sensitive at statistically significant levels to the complexity of the surface energy balance representation (i.e. the level of complexity used to represent these processes affects the simulated climate). However, changes in mean quantities, resulting from a doubling of atmospheric CO₂, are generally insensitive to the surface energy balance complexity. Conversely, changes in the spatial and temporal variance of evaporation and soil moisture are sensitive to the surface energy balance complexity. The addition of explicit canopy interception to the simplest model examined here enables that model to capture the change in the variance of evaporation simulated by the more complex models. In order to simulate changes in the variability of soil moisture, an explicit parameterization of bare soil evaporation is required. Overall, our results increase confidence that the simulation by climate models of the mean impact of increasing CO₂ on climate are reliable. Changes in the variability resulting from increased CO₂ on air temperature, precipitation or evaporation are also likely to be reliable since climate models typically use sufficiently complex land surface schemes. However, if the impact of increased CO₂ on soil moisture is required, then a more complex surface energy balance representation may be needed in order to capture changes in variability. Overall, our results imply that the level of complexity used by most climate models to represent the surface energy balance is appropriate and does not contribute significant uncertainty in the simulation of changes resulting from increasing CO₂. Our results only relate to surface energy balance complexity, and major uncertainties remain in how to model the surface hydrology and changes in the physiology, structural characteristics and distribution of vegetation. Future developments of land surface models should therefore focus on improving the representation of these processes.     

Surface energy balance complexity in GCM land surface models. Part II: coupled simulations

 Global coupled simulations with the Bureau of Meteorology Research Centre climate model and the CHAmeleon Surface Model (CHASM) are used to examine how four general extensions to the representation of the basic land surface energy balance affect simulated land-atmosphere interface variables: evaporation, precipitation, skin temperature and air temperature. The impacts of including separate surface energy balance calculations for: vegetated and non-vegetated portions of the land surface; an explicit parametrisation of canopy resistance; explicit bare ground evaporation; and explicit canopy interception are isolated and quantified. The hypothesis that these aspects of surface energy balance parametrisation do not contain substantial information at the monthly time scale (and are therefore not important to consider in a land surface model) is shown to be false. Considerable sensitivity to each of the four general surface energy balance extensions is identified in average pointwise monthly changes for important land-atmosphere interface variables. Average pointwise changes in monthly precipitation and land evaporation are equal to about 40 and 31–37% of the global-average precipitation and land evaporation respectively. Average pointwise changes for land surface skin temperature and lowest model layer air temperature are about 2 and 0.9 K respectively. The average pointwise change and average pointwise biases are statistically significant at 95% in all cases. Substantial changes to zonally average variables are also identified. We demonstrate how the globally averaged surface resistance parameter can vary from 150 to 25 s/m depending on which aspects of the surface energy balance are treated implicitly. We also show that if interception is treated implicitly, the effective surface resistance must vary geographically in order to capture the behaviour of a model which treats this process explicitly. The implication of these results for the design of land surface models is discussed. Received: 8 July 1999 / Accepted: 1 September 2000     

Potential impacts of land-use on climate variability and extremes

This study aims at exploring potential impacts of land-use vegetation change (LUC) on regional climate variability and extremes. Results from a pair of Australian Bureau of Meteorology Research Centre (BMRC) climate model 54-yr (1949-2002) integrations have been analysed. In the model experiments, two vegetation datasets are used, with one representing current vegetation coverage in China and the other approximating its potential coverage without human intervention. The model results show potential impacts ...     

Response of the mean global vegetation distribution to interannual climate variability

The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global fires is substantially enhanced by interannual precipitation variability. The current position of the central United States’ ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation, climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem distributions since climate models generally predict an increase in climate variability and extremes. CCR Contribution # 941     

Global and regional coupled climate sensitivity to the parameterization of rainfall interception

A coupled land?Catmosphere model is used to explore the impact of seven commonly used canopy rainfall interception schemes on the simulated climate. Multiple 30-year simulations are conducted for each of the seven methods and results are analyzed in terms of the mean climatology and the probability density functions (PDFs) of key variables based on daily data. Results show that the method used for canopy interception strongly affects how rainfall is partitioned between canopy evaporation and throughfall. However, the impact on total evaporation is much smaller, and the impact on rainfall and air temperature is negligible. Similarly, the PDFs of canopy evaporation and transpiration for six selected regions are strongly affected by the method used for canopy interception, but the impact on total evaporation, temperature and precipitation is negligible. Our results show that the parameterization of rainfall interception is important to the surface hydrometeorology, but the seven interception parameterizations examined here do not cause a statistically significant impact on the climate of the coupled model. We suggest that broad scale climatological differences between coupled climate models are not likely the result of how interception is parameterized. This conclusion is inconsistent with inferences derived from earlier uncoupled simulations, or simulations using very simplified climate models.     

CLIMBER-2: a climate system model of intermediate complexity. Part I: model description and performance for present climate

A 2.5-dimensional climate system model of intermediate complexity CLIMBER-2 and its performance for present climate conditions are presented. The model consists of modules describing atmosphere, ocean, sea ice, land surface processes, terrestrial vegetation cover, and global carbon cycle. The modules interact through the fluxes of momentum, energy, water and carbon. The model has a coarse spatial resolution, nevertheless capturing the major features of the Earth's geography. The model describes temporal variability of the system on seasonal and longer time scales. Due to the fact that the model does not employ flux adjustments and has a fast turnaround time, it can be used to study climates significantly different from the present one and to perform long-term (multimillennia) simulations. The comparison of the model results with present climate data show that the model successfully describes the seasonal variability of a large set of characteristics of the climate system, including radiative balance, temperature, precipitation, ocean circulation and cryosphere. Received: 12 January 1998 / Accepted: 2 July 1999     

Quantifying uncertainties in projections of extremes��a perturbed land surface parameter experiment

Uncertainties in the climate response to a doubling of atmospheric CO₂ concentrations are quantified in a perturbed land surface parameter experiment. The ensemble of 108 members is constructed by systematically perturbing five poorly constrained land surface parameters of global climate model individually and in all possible combinations. The land surface parameters induce small uncertainties at global scale, substantial uncertainties at regional and seasonal scale and very large uncertainties in the tails of the distribution, the climate extremes. Climate sensitivity varies across the ensemble mainly due to the perturbation of the snow albedo parameterization, which controls the snow albedo feedback strength. The uncertainty range in the global response is small relative to perturbed physics experiments focusing on atmospheric parameters. However, land surface parameters are revealed to control the response not only of the mean but also of the variability of temperature. Major uncertainties are identified in the response of climate extremes to a doubling of CO₂. During winter the response both of temperature mean and daily variability relates to fractional snow cover. Cold extremes over high latitudes warm disproportionately in ensemble members with strong snow albedo feedback and large snow cover reduction. Reduced snow cover leads to more winter warming and stronger variability decrease. As a result uncertainties in mean and variability response line up, with some members showing weak and others very strong warming of the cold tail of the distribution, depending on the snow albedo parametrization. The uncertainty across the ensemble regionally exceeds the CMIP3 multi-model range. Regarding summer hot extremes, the uncertainties are larger than for mean summer warming but smaller than in multi-model experiments. The summer precipitation response to a doubling of CO₂ is not robust over many regions. Land surface parameter perturbations and natural variability alter the sign of the response even over subtropical regions.     

Precipitation Change: Model Simulations and Paleoreconstructions

Zonal-scale patterns of precipitation change, as reconstructed for the Mid-Pliocene and the two Pleistocene optima, are compared with those generated in standard 2 × CO₂–1 × CO₂ equilibrium experiments by two high-resolution GCMs of equal sensitivities of global precipitation and temperature to CO₂ doubling. We find that the three warm paleoclimates, despite differences in boundary conditions/forcings, exhibit a similarity in zonal-scale patterns of change for precipitation over land in the Northern Hemisphere (NH); the between-epoch pattern correlation is 0.9 on the average. The two models give marked differences in zonal distribution of precipitation anomalies at mid-latitudes; the between-model pattern correlation for changes of precipitation over NH land is 0.4. The response of precipitation over the NH land area to the NH warming is about 10%/°C in the paleodata compared to 3%/°C in the models. The largest model/paleodata descrepancy refers to the present-day desert belt, where a large precipitation anomaly persists in all epochs. North of 50 N, the absolute values of the zonally-averaged precipitation anomalies simulated by both models fall in the range implied by the three warm paleoclimates, but they are systematically lower than the anomalies of the Mid-Pliocene. If our reconsructions are valid and if climate changes in the Mid-Pliocene were driven solely by CO₂ changes, then our results suggest that models are underestimating the magnitude of the precipitation response, especially in the regions of subtropical deserts; the magnitude of the simulated temperature response at high latitudes is also underestimated. At least part of the reported model/paleodata discordance appears to be due to lack of interactive land surface package in the models examined.     

北方土地利用变化对中国夏季气候可能影响的敏感性试验

为考察中国北方地区当代土地利用变化对中国夏季气候的可能影响,以区域气候模式RegCM3为模拟工具,利用1992年和1999年的土地利用资料,进行了中国地区植被覆盖变化的敏感性试验。结果表明,中国北方地区土地利用/植被覆盖的改变,将通过影响大气环流和改变陆地—大气或植被—大气之间的能量平衡状态等,对降水和气温等产生较大影响。     

Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation.The rates of change in future precipitation extremes are quantified with changes in surface air temperature.Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model,RegCM4,and 17 global climate models that participated in CMIP5.First,we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period(RF:1982-2001).The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes,as well as those based on observations:OBS and XPP.Precipitation extremes over four subregions in China are predicted to increase in the mid-future(MF:2039-58)and far-future(FF:2079-98)relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean.The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058,and the RCM results show higher interannual variability relative to that of the CMIP5 models.Then,we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature.Finally,based on the water vapor equation,changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity(significant at the p<0.1 level).     

中国区域陆面覆盖变化的气候效应模拟研究

基于MODIS和CLCV陆面覆盖资料,利用区域气候模式RegCM4分别进行两组24年（1978-2001年）的数值模拟试验,研究中国区域陆面覆盖变化对区域气候的影响。结果表明,以荒漠化和植被退化为主要特征的陆面覆盖变化通过改变陆面能量、水分平衡与大尺度环流进而对气候要素产生重要影响。夏季,中国南方地区普遍降温,季风边缘区及藏北高原气温升高,降水减少;季风边缘区与西北地区气温年际波动加剧;内蒙古中东部地区西南风增强,进而水汽输送增强,一定程度上增加了该地区降水。冬季,中国东部地区偏北气流增强,更多干燥冷空气南下,使得黄河以南地区降水减少、气温降低。     

The coupling of the Common Land Model (CLM0) to a regional climate model (RegCM)

Summary We replace the existing land surface parameterization scheme, the Biosphere-Atmosphere Transfer Scheme (BATS), in a regional climate model (RegCM) with the newly developed Common Land Model (CLM0). The main improvements of CLM0 include a detailed 10-layer soil model, the distinction between soil ice and water phases, a linked photosynthesis-stomatal conductance model, a multilayer snow model, and an improved runoff parameterization. We compare the performance of CLM0 and BATS as coupled to the RegCM in a one year simulation over East Asia. We find that the RegCM/CLM0 improves the winter cold bias present in the RegCM/BATS simulation. With respect to the surface energy balance, lower CLM0 albedos allow the absorption of more solar radiation at the surface. CLM0 tends to simulate higher sensible heat and lower latent heat fluxes than its BATS counterpart. The surface water balance also changes considerably between the two land surface schemes. Compared to BATS, CLM0 precipitation is reduced overall and surface runoff is increased, thereby allowing less water to enter the soil column. Evapotranspiration is lower in CLM0 due to lower ground evaporation, which leads to a wetter surface soil in CLM0 in spite of less precipitation input. However, transpiration is greater in CLM0 than BATS, which has an overall effect of less surface storage during the summertime. Comparison with station observations indicates that CLM0 tends to improve the simulation of root zone soil water content compared to BATS. Another pronounced difference between the two schemes is that CLM0 produces lower snow amounts than BATS because of different snow models and warmer CLM0 temperatures. In this case, BATS snow cover amounts are more in line with observations. Overall, except for the snow amounts, CLM0 appears to improve the RegCM simulation of the surface energy and water budgets compared to BATS.     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

Human activities have altered the distribution and quality of terrestrial ecosystems. Future demands for goods and services from terrestrial ecosystems will occur in a world experiencing human-induced climate change. In this study, we characterize the range in response of unmanaged ecosystems in the conterminous U.S. to 12 climate change scenarios. We obtained this response by simulating the climatically induced shifts in net primary productivity and geographical distribution of major biomes in the conterminous U.S. with the BIOME 3 model. BIOME 3 captured well the potential distribution of major biomes across the U.S. under baseline (current) climate. BIOME 3 also reproduced the general trends of observed net primary production (NPP) acceptably. The NPP projections were reasonable for forests, but not for grasslands where the simulated values were always greater than those observed. Changes in NPP would be most severe under the BMRC climate change scenario in which severe changes in regional temperatures are projected. Under the UIUC and UIUC + Sulfate scenarios, NPP generally increases, especially in the West where increases in precipitation are projected to be greatest. A CO₂-fertilization effect either amplified increases or alleviated losses in modeled NPP. Changes in NPP were also associated with changes in the geographic distribution of major biomes. Temperate/boreal mixed forests would cover less land in the U.S. under most of the climate change scenarios examined. Conversely, the temperate conifer and temperate deciduous forests would increase in areal extent under the UIUC and UIUC + Sulfate scenarios. The Arid Shrubland/Steppe would spread significantly across the southwest U.S. under the BMRC scenario. A map overlay of the simulated regions that would lose or gain capacity to produce corn and wheat on top of the projected distribution of natural ecosystems under the BMRC and UIUC scenarios (Global mean temperature increase of +2.5 °C, no CO₂ effect) helped identify areas where natural and managed ecosystems could contract or expand. The methods and models employed here are useful in identifying; (a) the range in response of unmanaged ecosystem in the U.S. to climate change and (b) the areas of the country where, for a particular scenario of climate change, land cover changes would be most likely.     

CLM4.5冠层截留方案的敏感性试验与改进

为探究陆气系统对于冠层截留过程敏的感性,研究基于NCAR CAM-CLM陆气耦合模式探讨了截留参数对于全球陆地蒸发、降水、径流及气温的可能影响,揭示了冠层截留与植被光合作用之间的潜在联系。通过GLEAMv3.0a陆面蒸散发数据评估了CLM4.5冠层截留方案,并指出该方案高估了低茎叶面积指数植被的冠层蒸发,而低估了高茎叶面积指数植被的冠层蒸发。在CLM4.5中引入冠层截留偏差校正方案则可在一定程度上提高了全球林区冠层蒸发和陆面蒸散发的模拟能力。     

NUMERICAL SIMULATIONS OF EFFECTS OF LAND SURFACE PROCESSES ON CLIMATE——IMPLEMENTING OF SSiB IN IAP/LASG AGCM AND ITS PERFORMANCE

This is an investigation of exchanges of energy and water between the atmosphere and thevegetated continents,and the impact of and mechanisms for land surface-atmosphere interactionson hydrological cycle and general circulation by implementing the Simplified Simple Biosphere(SSiB)model in a modified version of IAP/LASG global spectral general model(L9R15 AGCM).This study reveals that the SSiB model produces a better partitioning of the land surface heat andmoisture fluxes and its diurnal variations,and also gives the transport of energy and water amongatmosphere,vegetation and soil explicitly and realistically.Thus the coupled SSiB-AGCM runslead to the more conspicuous improvement in the simulated circulation,precipitation,mean watervapor content and its transport.particularly in the Asian monsoon region in the real world thanCTL-AGCM runs.It is also pointed out that both the implementation of land surfaceparameterizations and the variations in land surface into the GOALS model have greatly improvedhydrological balance over continents and have a significant impact on the simulated climate.particularly over the massive continents.Improved precipitation recycling model was employed to verify the mechanisms for landsurface hydrology parameterizations on hydrological cycle and precipitation climatology in AGCM.It can be argued that the recycling precipitation rate is significantly reduced,particularly in the aridand semi-arid region of the boreal summer hemisphere,coincident with remarkable reduction inevapotranspiration over the continental area.Therefore the coupled SSiB-AGCM runs reduce thebias of too much precipitation over land surface in most AGCMs,thereby bringing the simulatedprecipitation closer to observations in many continental regions of the world than CTL-AGCMruns.     

Possible Impacts of Global Warming on the Hydrology of the Ogallala Aquifer Region

The Ogallala or High Plains aquifer provides water for about 20% of the irrigated land in the United States. About 20 km³ (16.6 million acre-feet) of water are withdrawn annually from this aquifer. In general, recharge has not compensated for withdrawals since major irrigation development began in this region in the 1940s. The mining of the Ogallala has been pictured as an analogue to climate change in that many GCMs predict a warmer and drier future for this region. In this paper we attempt to anticipate the possible impacts of climate change on the sustainability of the aquifer as a source of water for irrigation and other purposes in the region. We have applied HUMUS, the Hydrologic Unit Model of the U.S. to the Missouri and Arkansas-White-Red water resource regions that overlie the Ogallala. We have imposed three general circulation model (GISS, UKTR and BMRC) projections of future climate change on this region and simulated the changes that may be induced in water yields (runoff plus lateral flow) and ground water recharge. Each GCM was applied to HUMUS at three levels of global mean temperature (GMT) to represent increasing severity of climate change (a surrogate for time). HUMUS was also run at three levels of atmospheric CO₂ concentration (hereafter denoted by [CO₂]) in order to estimate the impacts of direct CO₂ effects on photosynthesis and evapotranspiration. Since the UKTR and GISS GCMs project increased precipitation in the Missouri basin, water yields increase there. The BMRC GCM predicts sharply decreased precipitation and, hence, reduced water yields. Precipitation reductions are even greater in the Arkansas basin under BMRC as are the consequent water yield losses. GISS and UKTR climates lead to only moderate yield losses in the Arkansas. CO₂-fertilization reverses these losses and yields increase slightly. CO₂ fertilization increases recharge in the base (no climate change) case in both basins. Recharge is reduced under all three GCMs and severities of climate change.     

NUMERICAL SIMULATIONS OF EFFECTS OF LAND SURFACE PROCESSES ON CLIMATE--IMPLEMENTING OF SSiB IN IAP/LASG AGCM AND ITS PERFORMANCE*

This is an investigation of exchanges of energy and water between the atmosphere and the vegetated continents,and the impact of and mechanisms for land surface-atmosphere interactions on hydrological cycle and general circulation by implementing the Simplified Simple Biosphere(SSiB) model in a modified version of IAP/LASG global spectral general model(L9R15 AGCM).This study reveals that the SSiB model produces a better partitioning of the land surface heat and moisture fluxes and its diurnal variations,and also gives the transport of energy and water among atmosphere,vegetation and soil explicitly and realistically.Thus the coupled SSiB-AGCM runs lead to the more conspicuous improvement in the simulated circulation,precipitation,mean water vapor content and its transport.particularly in the Asian monsoon region in the real world than CTL-AGCM runs.It is also pointed out that both the implementation of land surface parameterizations and the variations in land surface into the GOALS model have greatly improved hydrological balance over continents and have a significant impact on the simulated climate.particularly over the massive continents.Improved precipitation recycling model was employed to verify the mechanisms for land surface hydrology parameterizations on hydrological cycle and precipitation climatology in AGCM.It can be argued that the recycling precipitation rate is significantly reduced,particularly in the arid and semi-arid region of the boreal summer hemisphere,coincident with remarkable reduction in evapotranspiration over the continental area.Therefore the coupled SSiB-AGCM runs reduce the bias of too much precipitation over land surface in most AGCMs,thereby bringing the simulatedprecipitation closer to observations in many continental regions of the world than CTL-AGCMruns.     

Formulation and verification of a land surface parameterization for atmospheric models

The need for a well-defined lower boundary condition for atmospheric numerical models is well documented. This paper describes the formulation of a land surface parameterization, which will be used in atmospheric boundary-layer and mesoscale numerical models. The land surface model has three soil layers for the prediction of soil moisture and soil temperature. Model soil properties depend on soil texture and moisture content. A homogeneous distribution of vegetation is also included, so that transpiration may be included, as well as the interception of precipitation by vegetation elements. The simulated vegetation also affects the mean surface albedo and roughness characteristics.First ISLSCP Field Experiment (FIFE) data are used to verify the model. Three cases during the growing season were chosen, each case having different amounts of vegetation cover. Stand alone simulations, where observations of atmospheric and radiation variables are input to the land surface model, were performed. These simulations show that the model is able to reproduce observed surface energy budgets and surface temperatures reasonably well. The RMS differences between modeled and obsered turbulent fluxes of heat and moisture are quite comparable to those reported by more detailed land surface models.     

Influence of modern land cover on the climate of the United States

I have used a high-resolution nested climate modeling system to test the sensitivity of regional and local climate to the modern non-urban land cover distribution of the continental United States. The dominant climate response is cooling of surface air temperatures, particularly during the warm-season. Areas of statistically significant cooling include areas of the Great Plains where crop/mixed farming has replaced short grass, areas of the Midwest and southern Texas where crop/mixed farming has replaced interrupted forest, and areas of the western United States containing irrigated crops. This statistically significant warm-season cooling is driven by changes in both surface moisture balance and surface albedo, with changes in surface moisture balance dominating in the Great Plains and western United States, changes in surface albedo dominating in the Midwest, and both effects contributing to warm-season cooling over southern Texas. The simulated changes in surface moisture and energy fluxes also influence the warm-season atmospheric dynamics, creating greater moisture availability in the lower atmosphere and enhanced uplift aloft, consistent with the enhanced warm-season precipitation seen in the simulation with modern land cover. The local and regional climate response is of a similar magnitude to that projected for future greenhouse gas concentrations, suggesting that the climatic effects of land cover change should be carefully considered when crafting policies for regulating land use and for managing anthropogenic forcing of the climate system.