Sensitivity of a coupled climate model to canopy interception capacity

The canopy interception capacity is a small but key part of the surface hydrology, which affects the amount of water intercepted by vegetation and therefore the partitioning of evaporation and transpiration. However, little research with climate models has been done to understand the effects of a range of possible canopy interception capacity parameter values. This is in part due to the assumption that it does not significantly affect climate. Near global evapotranspiration products now make evaluation of canopy interception capacity parameterisations possible. We use a range of canopy water interception capacity values from the literature to investigate the effect on climate within the climate model HadCM3. We find that the global mean temperature is affected by up to ?0.64 K globally and ?1.9 K regionally. These temperature impacts are predominantly due to changes in the evaporative fraction and top of atmosphere albedo. In the tropics, the variations in evapotranspiration affect precipitation, significantly enhancing rainfall. Comparing the model output to measurements, we find that the default canopy interception capacity parameterisation overestimates canopy interception loss (i.e. canopy evaporation) and underestimates transpiration. Overall, decreasing canopy interception capacity improves the evapotranspiration partitioning in HadCM3, though the measurement literature more strongly supports an increase. The high sensitivity of climate to the parameterisation of canopy interception capacity is partially due to the high number of light rain-days in the climate model that means that interception is overestimated. This work highlights the hitherto underestimated importance of canopy interception capacity in climate model hydroclimatology and the need to acknowledge the role of precipitation representation limitations in determining parameterisations.     

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。     

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     

Modelling of the OASIS Energy Flux Measurements Using Two Canopy Concepts

Two land surface schemes, SCAM and CSIRO9, were used to model the measured energy fluxes during the OASIS (Observations At Several Interacting Scales) field program. The measurements were taken at six sites along a 100 km rainfall gradient. Two types of simulations were conducted: (1) offline simulations forced with measured atmospheric input data at each of the six sites, and (2) regional simulations with the two land surface schemes coupled to the regional climate model DARLAM.The two land surface schemes employ two different canopy modelling concepts: in SCAM the vegetation is conceptually above the ground surface, while CSIRO9 employs the more commonly used `horizontally tiled' approach in which the vegetation cover is modelled by conceptually placing it beside bare ground. Both schemes utilize the same below-ground components (soil hydrological and thermal models) to reduce the comparison to canopy processes only. However, the ground heat flux, soil evaporation and evapotranspiration are parameterised by the two canopy treatments somewhat differently.Both canopy concepts reproduce the measured energy fluxes. SCAM has a slightly higher root-mean standard error in the model-measurement comparison for the ground heat flux. The mean surface radiative temperature simulated by SCAM is approximately 1K lower than in the CSIRO9 simulations. However, the soil and vegetation temperatures (which contribute to the radiative temperature) varied more in the CSIRO9 simulations. These larger variations are due to the absence of a representation of the aerodynamic interactions between vegetation and ground.     

气候与植被覆盖变化对中国西南亚高山区流域碳水循环的影响模拟

正确认识气候变化对流域森林植被和水文的影响对于林业经营管理与流域生态修复具有重要意义。为了揭示气候与植被覆盖变化对西南亚高山区流域碳水循环过程的影响,用生物物理/动态植被模型SSiB4/TRIFFID（Simplified Simple Biosphere model version 4, coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics model）与流域地形指数水文模型TOPMODEL（Topographic Index Model）的耦合模型（以下记为SSiB4T/TRIFFID）模拟了不同气候情景下西南亚高山区的梭磨河流域植被演替和碳水循环过程。结果表明,所有试验流域植被经历了从C3到苔原灌木最后到森林的变化;控制试验流域蒸散在流域植被主要为苔原灌木时达到最大而径流深最小;增温5 ℃并且增雨40%试验[记为T+5, (1+40%) P试验]流域蒸散在流域为森林覆盖时达到最大而径流深最小。随着温度增加,森林蒸腾、冠层截留蒸发和蒸散的增加幅度明显大于草和苔原灌木,导致森林从控制试验的增加径流量变为减小径流量。从控制试验到T+5, (1+40%) P试验,温度增加使森林净初级生产力有所增加,但对草和苔原灌木的净初级生产力影响很小;植被水分利用效率随温度增加明显减小。西南山区随着海拔高度降低（温度升高）,森林从增加径流量转变为减少径流量,植被水分利用效率也相应明显减小。西南山区气候的垂直地带性对森林—径流关系和水分利用效率的空间变化有着重要的影响。     

The contribution of the land surface energy balance complexity to differences in means, variances and extremes using the AMIP-II methodology

This paper explores the relationship between the complexity of the land surface energy balance parameterization and the simulation of means, variances and extremes in a climate model. We used the BMRC climate model combined with the protocol of AMIP-II to perform six ensemble simulations for each of four levels of surface energy balance complexity. Our results were then compared with other AMIP-II results in terms of the mean, variance and extremes of temperatures and precipitation. In terms of the zonally-averaged mean and the maximum temperatures and precipitation, the surface energy balance complexity did not systematically affect the BMRC climate model results. The zonal minimum temperature was affected by the inclusion of tiling and/or a temporally variable canopy conductance. We found no evidence that surface energy balance complexity affected the globally- or zonally-averaged variances. Some quite large differences were identified in the probability density functions of maximum (10 K) and minimum (4 K) temperature caused by surface tiling and/or the inclusion of a time-varying canopy conductance. With these included, the model simulated a higher probability of cooler minima and warmer maxima and therefore a different diurnal temperature range. Adding interception of precipitation led to an increase in the likelihood of more extreme precipitation. Thus, provided interception, surface tiling and a time-variable stomatal conductance are included in a land surface model, the impact of other uncertainties in the parameterization of the surface energy balance are unlikely to limit the use of climate models for simulating changes in the extremes. Most published results indicating changes to precipitation and temperature extremes due to increasing carbon dioxide are therefore unlikely to be significantly limited by uncertainty in how to parameterize the surface energy balance. Given that the variations in surface energy balance complexity included in our experiments approximates the range included in the AMIP-II models, we conclude that it this is unlikely to explain the differences found between the AMIP-II simulations. This does not mean that AMIP-II differences are not caused to a significant degree by differences in their respective LSMs, rather it limits the potential role of the land surface to non-surface energy balance components, or components (such as carbon) that are not considered here.     

Validation of IPCC AR4 models over the Iberian Peninsula

This paper reports analysis of the ability of 24 coupled global climate models that were used in the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change to simulate the current monthly seasonal cycle of sea level pressure, surface air temperature and precipitation over the Iberian Peninsula in the last two decades of the twentieth century. The period investigated runs from 1979 to 1998. In order to assess the performance of the models, averaged seasonal cycles and probability density functions (PDFs) calculated from model simulations are compared with the corresponding seasonal cycles, whilst PDFs are also obtained using the data from the ERA40 reanalysis and the Global Precipitation Climatology Project. We found that simulated PDFs generally provided a better fit to actual PDFs than seasonal cycles do. This conclusion indicates that when evaluating model performance, the climate variability as measured by means of PDFs is not the only climatic element that should be tested. Regarding the comparison based on the seasonal cycle, results also show that the root mean square skill score is more useful than the r skill score. To rank the AR4 models, sea level pressure, surface air temperature and precipitation variables were selected and a group of five AR4 models were identified as the models which best reproduce current climate in the area: MIROC3.2-HIRES, MPI-ECHAM5, GFDL-CM2.1, BCCR-BCM2.0 and UKMO-HADGEM1. The rank obtained should not be understood in a hierarchical manner because there is a certain degree of internal variability in the model ensembles. Finally, it should be noted that these results are in good agreement with other classifications found in the scientific literature.     

Dependence of Indian monsoon rainfall on moisture fluxes across the Arabian Sea and the impact of coupled model sea surface temperature biases

The Arabian Sea is an important moisture source for Indian monsoon rainfall. The skill of climate models in simulating the monsoon and its variability varies widely, while Arabian Sea cold sea surface temperature (SST) biases are common in coupled models and may therefore influence the monsoon and its sensitivity to climate change. We examine the relationship between monsoon rainfall, moisture fluxes and Arabian Sea SST in observations and climate model simulations. Observational analysis shows strong monsoons depend on moisture fluxes across the Arabian Sea, however detecting consistent signals with contemporaneous summer SST anomalies is complicated in the observed system by air/sea coupling and large-scale induced variability such as the El Ni?o-Southern Oscillation feeding back onto the monsoon through development of the Somali Jet. Comparison of HadGEM3 coupled and atmosphere-only configurations suggests coupled model cold SST biases significantly reduce monsoon rainfall. Idealised atmosphere-only experiments show that the weakened monsoon can be mainly attributed to systematic Arabian Sea cold SST biases during summer and their impact on the monsoon-moisture relationship. The impact of large cold SST biases on atmospheric moisture content over the Arabian Sea, and also the subsequent reduced latent heat release over India, dominates over any enhancement in the land-sea temperature gradient and results in changes to the mean state. We hypothesize that a cold base state will result in underestimation of the impact of larger projected Arabian Sea SST changes in future climate, suggesting that Arabian Sea biases should be a clear target for model development.     

Past and future polar amplification of climate change: climate model intercomparisons and ice-core constraints

Climate model simulations available from the PMIP1, PMIP2 and CMIP (IPCC-AR4) intercomparison projects for past and future climate change simulations are examined in terms of polar temperature changes in comparison to global temperature changes and with respect to pre-industrial reference simulations. For the mid-Holocene (MH, 6,000 years ago), the models are forced by changes in the Earth’s orbital parameters. The MH PMIP1 atmosphere-only simulations conducted with sea surface temperatures fixed to modern conditions show no MH consistent response for the poles, whereas the new PMIP2 coupled atmosphere–ocean climate models systematically simulate a significant MH warming both for Greenland (but smaller than ice-core based estimates) and Antarctica (consistent with the range of ice-core based range). In both PMIP1 and PMIP2, the MH annual mean changes in global temperature are negligible, consistent with the MH orbital forcing. The simulated last glacial maximum (LGM, 21,000 years ago) to pre-industrial change in global mean temperature ranges between 3 and 7°C in PMIP1 and PMIP2 model runs, similar to the range of temperature change expected from a quadrupling of atmospheric CO₂ concentrations in the CMIP simulations. Both LGM and future climate simulations are associated with a polar amplification of climate change. The range of glacial polar amplification in Greenland is strongly dependent on the ice sheet elevation changes prescribed to the climate models. All PMIP2 simulations systematically underestimate the reconstructed glacial–interglacial Greenland temperature change, while some of the simulations do capture the reconstructed glacial–interglacial Antarctic temperature change. Uncertainties in the prescribed central ice cap elevation cannot account for the temperature change underestimation by climate models. The variety of climate model sensitivities enables the exploration of the relative changes in polar temperature with respect to changes in global temperatures. Simulated changes of polar temperatures are strongly related to changes in simulated global temperatures for both future and LGM climates, confirming that ice-core-based reconstructions provide quantitative insights on global climate changes. An erratum to this article can be found at     

Climate change simulated by full and mixed-layer ocean versions of CSIRO Mk3.5 and Mk3.0: The Asia-Pacific region

The patterns of climate change in the Asia-Pacific region simulated by versions of the CSIRO Mk3.5 and Mk3.0 climate models are examined and compared with those from 23 CMIP3 models. Using fields standardized by global warming, it is seen that both CSIRO coupled models simulate larger surface warming in the tropical western Pacific Ocean, and smaller warming in the eastern Indian Ocean, than the CMIP3 average, and also model versions with a mixed-layer ocean. Corresponding differences in the changes in the pressure, winds, rainfall and other quantities were simulated. Introducing the coupled Mk3.5’s sea surface temperature field for the present climate, which has a warm bias, as the base climate for the MLO version had only a minor effect on the MLO version’s pattern of climate change. A Pacific-Indian Dipole index quantifying the amplitude of the warming pattern explains much of the variation in rainfall change simulated by the CMIP3 models over Australia and the Indonesian and Melanesian regions. It relates more strongly to Australian average rainfall than several other indices representing southern hemispheric circulation changes. The decline in Australian rainfall produced by the full ocean coupling is largest in summer, but occurs in each season, and extends across the continent. Further assessment of the importance of the dipole change pattern in new simulations is warranted. Analyses aimed at reducing the uncertainty in its potential amplitude could help narrow the range of projections for change in the Australasian region.     

玉米冠层对降水的截留模型构建

降水资源是农作物的主要水分来源,农作物通过吸收土壤中的水分维持正常的生长发育,但由于未考虑农作物冠层对降水截留作用,在水资源评估和农田水分平衡研究中往往高估降水作用。该文通过2018年玉米生长季在辽宁锦州农业气象试验站开展的降水模拟试验系统分析了玉米冠层对降水的截留效应,结果表明:在降水量一定条件下,玉米冠层截留量与叶面积指数的二次多项式拟合相关最佳;在叶面积指数一定条件下,玉米冠层截留量与降水量的幂函数拟合相关最佳。综合叶面积指数和降水量分析表明:玉米冠层截留量与叶面积指数平方及降水量对数函数拟合呈正相关。根据我国玉米传统种植方式,高产玉米的叶面积指数最大一般为5~6,因此,对一次降水的最大截留量通常约为1.5~2.3 mm,当叶面积指数小于1时,对降水的截留可忽略不计。     

Impact of ocean model resolution on CCSM climate simulations

The current literature provides compelling evidence suggesting that an eddy-resolving (as opposed to eddy-permitting or eddy-parameterized) ocean component model will significantly impact the simulation of the large-scale climate, although this has not been fully tested to date in multi-decadal global coupled climate simulations. The purpose of this paper is to examine how resolved ocean fronts and eddies impact the simulation of large-scale climate. The model used for this study is the NCAR Community Climate System Model version 3.5 (CCSM3.5)—the forerunner to CCSM4. Two experiments are reported here. The control experiment is a 155-year present-day climate simulation using a 0.5° atmosphere component (zonal resolution 0.625 meridional resolution 0.5°; land surface component at the same resolution) coupled to ocean and sea-ice components with zonal resolution of 1.2° and meridional resolution varying from 0.27° at the equator to 0.54° in the mid-latitudes. The second simulation uses the same atmospheric and land-surface models coupled to eddy-resolving 0.1° ocean and sea-ice component models. The simulations are compared in terms of how the representation of smaller scale features in the time mean ocean circulation and ocean eddies impact the mean and variable climate. In terms of the global mean surface temperature, the enhanced ocean resolution leads to a ubiquitous surface warming with a global mean surface temperature increase of about 0.2?°C relative to the control. The warming is largest in the Arctic and regions of strong ocean fronts and ocean eddy activity (i.e., Southern Ocean, western boundary currents). The Arctic warming is associated with significant losses of sea-ice in the high-resolution simulation. The sea surface temperature gradients in the North Atlantic, in particular, are better resolved in the high-resolution model leading to significantly sharper temperature gradients and associated large-scale shifts in the rainfall. In the extra-tropics, the interannual temperature variability is increased with the resolved eddies, and a notable increases in the amplitude of the El Ni?o and the Southern Oscillation is also detected. Changes in global temperature anomaly teleconnections and local air-sea feedbacks are also documented and show large changes in ocean–atmosphere coupling. In particular, local air-sea feedbacks are significantly modified by the increased ocean resolution. In the high-resolution simulation in the extra-tropics there is compelling evidence of stronger forcing of the atmosphere by SST variability arising from ocean dynamics. This coupling is very weak or absent in the low-resolution model.     

A further assessment of vegetation feedback on decadal Sahel rainfall variability

The effect of vegetation feedback on decadal-scale Sahel rainfall variability is analyzed using an ensemble of climate model simulations in which the atmospheric general circulation model ICTPAGCM (“SPEEDY”) is coupled to the dynamic vegetation model VEGAS to represent feedbacks from surface albedo change and evapotranspiration, forced externally by observed sea surface temperature (SST) changes. In the control experiment, where the full vegetation feedback is included, the ensemble is consistent with the observed decadal rainfall variability, with a forced component 60 % of the observed variability. In a sensitivity experiment where climatological vegetation cover and albedo are prescribed from the control experiment, the ensemble of simulations is not consistent with the observations because of strongly reduced amplitude of decadal rainfall variability, and the forced component drops to 35 % of the observed variability. The decadal rainfall variability is driven by SST forcing, but significantly enhanced by land-surface feedbacks. Both, local evaporation and moisture flux convergence changes are important for the total rainfall response. Also the internal decadal variability across the ensemble members (not SST-forced) is much stronger in the control experiment compared with the one where vegetation cover and albedo are prescribed. It is further shown that this positive vegetation feedback is physically related to the albedo feedback, supporting the Charney hypothesis.     

An estimate of future climate change for western France using a statistical downscaling technique

A statistical downscaling procedure based on an analogue technique is used to determine projections for future climate change in western France. Three ocean and atmosphere coupled models are used as the starting point of the regionalization technique. Models' climatology and day to day variability are found to reproduce the broad main characteristics seen in the reanalyses. The response of the coupled models to a similar CO₂ increase scenario exhibit marked differences for mean sea-level pressure; precipitable water and temperature show arguably less spread. Using the reanalysis fields as predictors, the statistical model parameters are set for daily extreme temperatures and rain occurrences for seventeen stations in western France. The technique shows some amount of skill for all three predictands and across all seasons but failed to give reliable estimates of rainfall amounts. The quality of both local observations and large-scale predictors has an impact on the statistical model skill. The technique is partially able to reproduce the observed climatic trends and inter annual variability, showing the sensitivity of the analogue approach to changed climatic conditions albeit an incomplete explained variance by the statistical technique. The model is applied to the coupled model control simulations and the gain compared with direct model grid-average outputs is shown to be substantial at station level. The method is then applied to altered climate conditions; the impact of large-scale model uncertain responses and model sensitivities are quantified using the three coupled models. The warming in the downscaled projections are reduced compared with their global model counterparts.     

Indian Ocean SST, evaporation, and precipitation during the South Asian summer monsoon in IPCC-AR4 coupled simulations

The veracity of modeled air–sea interactions in the Indian Ocean during the South Asian summer monsoon is examined. Representative simulations of the twentieth century climate, produced by coupled general circulation models as part of the Intergovernmental Panel on Climate Change Fourth Assessment Report, are the analysis targets along with observational data. The analysis shows the presence of large systematic biases in coupled simulations of boreal summer precipitation, evaporation, and sea surface temperature (SST) in the Indian Ocean, often exceeding 50% of the climatological values. Many of the biases are pervasive, being common to most simulations. The representation of air–sea interactions is also compromised. Coupled models tend to emphasize local forcing in the Indian Ocean as reflected by their large precipitation–SST correlations, at odds with the weak links in observations which suggest the importance of non-local controls. The evaporation–SST correlations are also differently represented, indicating atmospheric control on SST in some models and SST control on evaporation in others. The Indian monsoon rainfall–SST links are also misrepresented: the former is essentially uncorrelated with antecedent and contemporaneous Indian Ocean SSTs in nature, but not so in most of the simulations. Overall, coupled models are found deficient in portraying local and non-local air–sea interactions in the Indian Ocean during boreal summer. In our opinion, current models cannot provide durable insights on regional climate feedbacks nor credible projections of regional hydroclimate variability and change, should these involve ocean–atmosphere interactions in the Indian basin.     

Uncertainties in modelling future hydrological change over West Africa

The aim of this paper is to evaluate current knowledge and uncertainties associated with the impact of increasing greenhouse gas and aerosol concentrations on the West African monsoon. For this purpose, coupled and time-slice simulations are used. A global measure of the monsoon changes is defined in order to avoid regional biases and to try and obtain significant results. The position and width of the monsoon in latitude are the main focuses. There is almost no agreement between the Coupled General Circulation models from the Coupled models Inter-Comparison project—Phase II in regard to the impact of climate change on the monsoon. Moreover, very simple discriminations between the models seem inappropriate to get a better signal. The role of the different forcings in time-slice simulations is then investigated. The sea surface temperature (SST) and particularly the pattern of the SST are shown to be the most important forcing. This accounts for the diversity of the results either from the coupled or the forced simulations with different SST changes. With a fixed SST, but of a smaller magnitude in AMJ, there are still uncertainties, coming first from the Atmospheric General Circulation models and the way they balance greenhouse gas and global SST increase. Finally the uncertainty due to the Land Surface models (LSMs) is not negligible. The greenhouse gas and the LSMs are shown to have more impact in August, when the monsoon is at its highest latitude on the continent.     

The sensitivity of the water balance of a wet multilayer model pine canopy to variations in meteorological input

A multilayer canopy model of a pine forest is used to investigate the sensitivity of the water balance of the wet canopy to variations in meteorological input. The multilayer model does not take into account large-scale eddies, which are now considered to be of importance to canopy transport. It does, however, provide realistic simulations of wet canopy water balance and often predicts interception loss rates higher than those predicted by a unilayer model for the same meteorological input. Stable layers both within and above the canopy are often simulated during rainfall events, and these may help to spontaneously generate large-scale eddies or waves within forest canopies. The sensitivity study for a wet canopy suggests that low vapour pressure deficits and low wind speeds are associated with unstable surface conditions, and increasing values of both variables are associated with decreasing canopy drainage values and increasing evaporative losses. Low short- or long-wave radiation inputs are associated with stable surface conditions, and increasing values of both variables are associated with decreasing canopy drainage values and increasing evaporative losses. Increasing temperature is associated with increasing surface stability and increasing canopy drainage and decreasing evaporative losses. In real situations the tendency for increasing temperature to cause surface stability and decreased evaporative loss is probably compensated by the opposite effects of increasing short- or long-wave radiation. The model simulations suggest that wet forest canopies may be better ventilated at low temperatures, if other meteorological conditions are constant.     

Surface energy balance complexity in GCM land surface models

 A large number of land surface models (LSMs) have been designed for use in atmospheric general circulation models (GCMs) and GCM modellers therefore have a large number of options when selecting an LSM for their GCM. This study provides information to aid LSM design choices. A framework within which sensitivity to LSM design can be tested is presented and a series of experiments carried out to investigate how general aspects of surface energy balance parametrisation affect land-atmosphere evaporation. Firstly, it is shown that a combination of surface energy balance complexity and aerodynamic parametrisation can be used to explain the gross simulation differences obtained in the Project for Intercomparison of Land-surface Parameterization Schemes (PILPS). Secondly, a simple surface energy balance parametrisation with a constant surface resistance is found to be as appropriate as more complex method for simulating annual, monthly and seasonally averaged diurnal cycles of evaporation. However, complex aspects of surface energy balance parametrisation (canopy interception, bare ground evaporation and canopy resistance) are shown to contain substantial geographic and daily functionality that is not present in the simpler parametrisation. Received: 12 June 1998/Accepted: 24 December 1998     

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