Sensitivity of high-resolution Arctic regional climate model projections to different implementations of land surface processes

This paper discusses the effects of vegetation cover and soil parameters on the climate change projections of a regional climate model over the Arctic domain. Different setups of the land surface model of the regional climate model HIRHAM were realized to analyze differences in the atmospheric circulation caused by (1) the incorporation of freezing/thawing of soil moisture, (2) the consideration of top organic soil horizons typical for the Arctic and (3) a vegetation shift due to a changing climate. The largest direct thermal effect in 2 m air temperature was found for the vegetation shift, which ranged between −1.5 K and 3 K. The inclusion of a freeze/thaw scheme for soil moisture shows equally large sensitivities in spring over cool areas with high soil moisture content. Although the sensitivity signal in 2 m air temperature for the experiments differs in amplitude, all experiments show changes in mean sea level pressure (mslp) and geopotential height (z) throughout the troposphere of similar magnitude (mslp: −2 hPa to 1.5 hPa, z: −15 gpm to 5 gpm). This points to the importance of dynamical feedbacks within the atmosphere-land system. Land and soil processes have a distinct remote influence on large scale atmospheric circulation patterns in addition to their direct, regional effects. The assessment of induced uncertainties due to the changed implementations of land surface processes discussed in this study demonstrates the need to take all those processes for future Arctic climate projections into account, and demonstrates a clear need to include similar implementations in regional and global climate models.     

The role of land surface dynamics in glacial inception: a study with the UVic Earth System Model

The first results of the UVic Earth System Model coupled to a land surface scheme and a dynamic global vegetation model are presented in this study. In the first part the present day climate simulation is discussed and compared to observations. We then compare a simulation of an ice age inception (forced with 116 ka BP orbital parameters and an atmospheric CO₂ concentration of 240 ppm) with a preindustrial run (present day orbital parameters, atmospheric [CO₂] = 280 ppm). Emphasis is placed on the vegetations response to the combined changes in solar radiation and atmospheric CO₂ level. A southward shift of the northern treeline as well as a global decrease in vegetation carbon is observed in the ice age inception run. In tropical regions, up to 88% of broadleaf trees are replaced by shrubs and C₄ grasses. These changes in vegetation cover have a remarkable effect on the global climate: land related feedbacks double the atmospheric cooling during the ice age inception as well as the reduction of the meridional overturning in the North Atlantic. The introduction of vegetation related feedbacks also increases the surface area with perennial snow significantly.     

Boreal forest and tundra ecosystems as components of the climate system

The effects of terrestrial ecosystems on the climate system have received most attention in the tropics, where extensive deforestation and burning has altered atmospheric chemistry and land surface climatology. In this paper we examine the biophysical and biogeochemical effects of boreal forest and tundra ecosystems on atmospheric processes. Boreal forests and tundra have an important role in the global budgets of atmospheric CO₂ and CH₄. However, these biogeochemical interactions are climatically important only at long temporal scales, when terrestrial vegetation undergoes large geographic redistribution in response to climate change. In contrast, by masking the high albedo of snow and through the partitioning of net radiation into sensible and latent heat, boreal forests have a significant impact on the seasonal and annual climatology of much of the Northern Hemisphere. Experiments with the LSX land surface model and the GENESIS climate model show that the boreal forest decreases land surface albedo in the winter, warms surface air temperatures at all times of the year, and increases latent heat flux and atmospheric moisture at all times of the year compared to simulations in which the boreal forest is replaced with bare ground or tundra. These effects are greatest in arctic and sub-arctic regions, but extend to the tropics. This paper shows that land-atmosphere interactions are especially important in arctic and sub-arctic regions, resulting in a coupled system in which the geographic distribution of vegetation affects climate and vice versa. This coupling is most important over long time periods, when changes in the abundance and distribution of boreal forest and tundra ecosystems in response to climatic change influence climate through their carbon storage, albedo, and hydrologic feedbacks.     

The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming

Summary A suite of simulations with the HadCM3LC coupled climate-carbon cycle model is used to examine the various forcings and feedbacks involved in the simulated precipitation decrease and forest dieback. Rising atmospheric CO₂ is found to contribute 20% to the precipitation reduction through the physiological forcing of stomatal closure, with 80% of the reduction being seen when stomatal closure was excluded and only radiative forcing by CO₂ was included. The forest dieback exerts two positive feedbacks on the precipitation reduction; a biogeophysical feedback through reduced forest cover suppressing local evaporative water recycling, and a biogeochemical feedback through the release of CO₂ contributing to an accelerated global warming. The precipitation reduction is enhanced by 20% by the biogeophysical feedback, and 5% by the carbon cycle feedback from the forest dieback. This analysis helps to explain why the Amazonian precipitation reduction simulated by HadCM3LC is more extreme than that simulated in other GCMs; in the fully-coupled, climate-carbon cycle simulation, approximately half of the precipitation reduction in Amazonia is attributable to a combination of physiological forcing and biogeophysical and global carbon cycle feedbacks, which are generally not included in other GCM simulations of future climate change. The analysis also demonstrates the potential contribution of regional-scale climate and ecosystem change to uncertainties in global CO₂ and climate change projections. Moreover, the importance of feedbacks suggests that a human-induced increase in forest vulnerability to climate change may have implications for regional and global scale climate sensitivity.     

Relative contribution of soil moisture and snow mass to seasonal climate predictability: a pilot study

Land surface hydrology (LSH) is a potential source of long-range atmospheric predictability that has received less attention than sea surface temperature (SST). In this study, we carry out ensemble atmospheric simulations driven by observed or climatological SST in which the LSH is either interactive or nudged towards a global monthly re-analysis. The main objective is to evaluate the impact of soil moisture or snow mass anomalies on seasonal climate variability and predictability over the 1986–1995 period. We first analyse the annual cycle of zonal mean potential (perfect model approach) and effective (simulated vs. observed climate) predictability in order to identify the seasons and latitudes where land surface initialization is potentially relevant. Results highlight the influence of soil moisture boundary conditions in the summer mid-latitudes and the role of snow boundary conditions in the northern high latitudes. Then, we focus on the Eurasian continent and we contrast seasons with opposite land surface anomalies. In addition to the nudged experiments, we conduct ensembles of seasonal hindcasts in which the relaxation is switched off at the end of spring or winter in order to evaluate the impact of soil moisture or snow mass initialization. LSH appears as an effective source of surface air temperature and precipitation predictability over Eurasia (as well as North America), at least as important as SST in spring and summer. Cloud feedbacks and large-scale dynamics contribute to amplify the regional temperature response, which is however, mainly found at the lowest model levels and only represents a small fraction of the observed variability in the upper troposphere.     

Impact of vegetation changes on the dynamics of the atmosphere at the Last Glacial Maximum

Much work is under way to identify and quantify the feedbacks between vegetation and climate. Palaeoclimate modelling may provide a mean to address this problem by comparing simulations with proxy data. We have performed a series of four simulations of the Last Glacial Maximum (LGM, 21,000 years ago) using the climate model HadSM3, to test the sensitivity of climate to various changes in vegetation: a global change (according to a previously discussed simulation of the LGM with HadSM3 coupled to the dynamical vegetation model TRIFFID); a change only north of 35°N; a change only south of 35°N; and a variation in stomatal opening induced by the reduction in atmospheric CO₂ concentration. We focus mainly on the response of temperature, precipitation, and atmosphere dynamics. The response of continental temperature and precipitation mainly results from regional interactions with vegetation. In Eurasia, particularly Siberia and Tibet, the response of the biosphere substantially enhances the glacial cooling through a positive feedback loop between vegetation, temperature, and snow-cover. In central Africa, the decrease in tree fraction reduces the amount of precipitation. Stomatal opening is not seen to play a quantifiable role. The atmosphere dynamics, and more specifically the Asian summer monsoon system, are significantly altered by remote changes in vegetation: the cooling in Siberia and Tibet act in concert to shift the summer subtropical front southwards, weaken the easterly tropical jet and the momentum transport associated with it. By virtue of momentum conservation, these changes in the mid-troposphere circulation are associated with a slowing of the Asian summer monsoon surface flow. The pattern of moisture convergence is slightly altered, with moist convection weakening in the western tropical Pacific and strengthening north of Australia.     

Climate Change Scenarios for the Hudson Bay Region: An Intermodel Comparison

General circulation models (GCMs) are unanimous in projecting warmer temperatures in an enhanced CO₂ atmosphere, with amplification of this warming in higher latitudes. The Hudson Bay region, which is located in the Arctic and subarctic regions of Canada, should therefore be strongly influenced by global warming. In this study, we compare the response of Hudson Bay to a transient warming scenario provided by six-coupled atmosphere-ocean models. Our analysis focuses on surface temperature, precipitation, sea-ice coverage, and permafrost distribution. The results show that warming is expected to peak in winter over the ocean, because of a northward retreat of the sea-ice cover. Also, a secondary warming peak is observed in summer over land in the Canadian and Australian-coupled GCMs, which is associated with both a reduction in soil moisture conditions and changes in permafrost distribution. In addition, a relationship is identified between the retreat of the sea-ice cover and an enhancement of precipitation over both land and oceanic surfaces. The response of the sea-ice cover and permafrost layer to global warming varies considerably among models and thus large differences are observed in the projected regional increase in temperature and precipitation. In view of the important feedbacks that a retreat of the sea-ice cover and the distribution of permafrost are likely to play in the doubled and tripled CO₂ climates of Hudson Bay, a good representation of these two parameters is necessary to provide realistic climate change scenarios. The use of higher resolution regional climate model is recommended to develop scenarios of climate change for the Hudson Bay region.     

Hydrological changes in the climate system from leaf responses to increasing CO2

Vegetation is a major component of the climate system because of its controls on the energy and water balance over land. This functioning changes because of the physiological response of leaves to increased CO₂. A climate model is used to compare these changes with the climate changes from radiative forcing by greenhouse gases. For this purpose, we use the Community Earth System Model coupled to a slab ocean. Ensemble integrations are done for current and doubled CO₂. The consequent reduction of transpiration and net increase of surface radiative heating from reduction in cloudiness increases the temperature over land by a significant fraction of that directly from the radiative warming by CO₂. Large-scale atmospheric circulation adjustments result. In particular, over the tropics, a low-level westerly wind anomaly develops associated with reduced geopotential height over land, enhancing moisture transport and convergence, and precipitation increases over the western Amazon, the Congo basin, South Africa, and Indonesia, while over mid-latitudes, land precipitation decreases from reduced evapotranspiration. On average, land precipitation is enhanced by 0.03 mm day^?1 (about 19 % of the CO₂ radiative forcing induced increase). This increase of land precipitation with decreased ET is an apparent negative feedback, i.e., less ET makes more precipitation. Global precipitation is slightly reduced. Runoff increases associated with both the increased land precipitation and reduced evapotranspiration. Examining the consistency of the variations among ensemble members shows that vegetation feedbacks on precipitation are more robust over the tropics and in mid to high latitudes than over the subtropics where vegetation is sparse and the internal climate variability has a larger influence.     

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.     

Sensitivity experiments performed with an energy balance atmosphere model coupled to an advection-diffusion ocean model

Summary In this paper a simple climate model is presented which is used to perform some sensitivity experiments. The atmospheric part is represented by a vertically and zonally averaged layer in which the surface air temperature, radiative fluxes at the surface and at the top of the atmosphere, the turbulent fluxes between atmosphere and surface and the snow cover are calculated. This atmospheric layer is coupled to a two-dimensional advection-diffusion ocean model in which the zonal overturning pattern is prescribed. The ocean model evaluates the temperature distribution, the amount of sea-ice and the meridional and vertical heat fluxes. The present-day climate simulated by the model compares reasonably well with observations of the seasonal and latitudinal distribution of temperature, radiation, surface alebdo, sea-ice and snow cover and meridional energy fluxes. Then, the sensitivity of the model-simulated present-day climate to perturbations in the incident solar radiation at the top of the atmosphere is investigated. The temperature response displays large latitudinal and seasonal variations, which is in qualitative agreement with results obtained with other climate models. It is found that the seasonal variation of sea-ice cover (and hence, the effective oceanic heat capacity) is one of the most important elements determining seasonal variations in climate sensitivity. Differences in sensitivity between the seasonal and annual mean version of the model are discussed. Finally, the equilibrium response to perturbations in some selected model variables is presented; these variables include meridional diffusion coefficients, drag coefficient, sea-ice thickness, atmospheric CO₂-concentration and cloud optical thickness.With 13 Figures     

Aridity and the Potential Physiological Response of C 3 Crops to Doubled Atmospheric Co 2 : A Simple Demonstration of the Sensitivity of the Canadian Prairies

Since cultivated annual C₃ field crops cover about50% of the land surface of the Canadian Prairie grassland eco-climatic zone, this vegetationinfluences the aridity of the climate during the growing season. The physiological response of these cropsto a doubling of the atmospheric concentration of CO₂ may be a doubling of canopyresistance. If this physiological effect is not counteracted by interactive feedbacks, such as increasedleaf area, evapotranspiration rates could be reduced. To demonstrate the sensitivity of thearidity of the Prairie climate to this potential physiological effect, representative spring wheatgrowing-season soil moisture and Bowen ratio curves for a doubled canopy resistance(2 × CO₂) scenario were compared with a control (1 × CO₂) scenario.Lower evapotranspiration in the 2 × CO₂ scenario: (1) Increased root-zone soilmoisture levels, and (2) weakened the atmospheric component of the hydrologic cycle by raisingBowen ratios, which reduces the convective available energy, and reduces the regionalcontribution to the atmospheric water vapour over the Prairies. A weakened hydrologic cycleimplies less rainfall, and possibly, lower soil moisture levels. Thus, the net impact of a doublingof the atmospheric concentration of CO₂ on the aridity of the Canadian Prairies is uncertain.This simple sensitivity demonstration did not consider most of the potential feedback mechanisms,nor interactions of other processes. Nevertheless, the result illustrates that the physiologicaleffect should be explicitly included in climate change models for the Canadian Prairies.     

Modeling the eco-hydrologic response of a Mediterranean type ecosystem to the combined impacts of projected climate change and altered fire frequencies

Global Climate Models (GCMs) project moderate warming along with increases in atmospheric CO₂ for California Mediterranean type ecosystems (MTEs). In water-limited ecosystems, vegetation acts as an important control on streamflow and responds to soil moisture availability. Fires are also key disturbances in semi-arid environments, and few studies have explored the potential interactions among changes in climate, vegetation dynamics, hydrology, elevated atmospheric CO2 concentrations and fire. We model ecosystem productivity, evapotranspiration, and summer streamflow under a range of temperature and precipitation scenarios using RHESSys, a spatially distributed model of carbon–water interactions. We examine the direct impacts of temperature and precipitation on vegetation productivity and impacts associated with higher water-use efficiency under elevated atmospheric CO2. Results suggest that for most climate scenarios, biomass in chaparral-dominated systems is likely to increase, leading to reductions in summer streamflow. However, within the range of GCM predictions, there are some scenarios in which vegetation may decrease, leading to higher summer streamflows. Changes due to increases in fire frequency will also impact summer streamflow but these will be small relative to changes due to vegetation productivity. Results suggest that monitoring vegetation responses to a changing climate should be a focus of climate change assessment for California MTEs.     

Climate feedback efficiency and synergy

Earth’s climate sensitivity to radiative forcing induced by a doubling of the atmospheric CO₂ is determined by feedback mechanisms, including changes in atmospheric water vapor, clouds and surface albedo, that act to either amplify or dampen the response. The climate system is frequently interpreted in terms of a simple energy balance model, in which it is assumed that individual feedback mechanisms are additive and act independently. Here we test these assumptions by systematically controlling, or locking, the radiative feedbacks in a state-of-the-art climate model. The method is shown to yield a near-perfect decomposition of change into partial temperature contributions pertaining to forcing and each of the feedbacks. In the studied model water vapor feedback stands for about half the temperature change, CO₂-forcing about one third, while cloud and surface albedo feedback contributions are relatively small. We find a close correspondence between forcing, feedback and partial surface temperature response for the water vapor and surface albedo feedbacks, while the cloud feedback is inefficient in inducing surface temperature change. Analysis suggests that cloud-induced warming in the upper tropical troposphere, consistent with rising convective cloud anvils in a warming climate enhances the negative lapse-rate feedback, thereby offsetting some of the warming that would otherwise be attributable to this positive cloud feedback. By subsequently combining feedback mechanisms we find a positive synergy acting between the water vapor feedback and the cloud feedback; that is, the combined cloud and water vapor feedback is greater than the sum of its parts. Negative synergies surround the surface albedo feedback, as associated cloud and water vapor changes dampen the anticipated climate change induced by retreating snow and ice. Our results highlight the importance of treating the coupling between clouds, water vapor and temperature in a deepening troposphere.     

The impact of ecosystem functional type changes on the La Plata Basin climate

In this paper, the effects of land cover changes on the climate of the La Plata Basin in southern South America are investigated using the Weather and Research Forecasting (WRF) Model configured on a 30/10km two-way interactive nested grid. To assess the regional climate changes resulting from land surface changes, the standard land cover types are replaced by time-varying Ecosystem Functional Types (EFTs), which is a newly devised land-cover classification that characterizes the spatial and interannual variability of surface vegetation dynamics. These variations indicate that natural and anthropogenic activities have caused changes in the surface physical parameters of the basin, such as albedo and roughness length, that contributed to regional climate changes. EFTs are obtained from functional attributes of vegetation computed from properties of the Normalized Difference Vegetation Index (NDVI) to represent patches of the land surface with homogeneous energy and gas exchanges with the atmosphere. Four simulations are conducted, each experimental period ranging from September to November in two contrasting years, 1988 and 1998. The influence of an identical EFT change on the surface heat fluxes, 2-m temperature and humidity, 10-m winds, convective instabilities and large-scale moisture fluxes and precipitation are explored for 1988 (a dry year) and 1998 (a wet year). Results show that the surface and atmospheric climate has a larger response to the same EFT changes in a dry year for 2-m temperature and 10-m wind; the response is larger in a wet year for 2-m water vapor mixing ratio, convective available potential energy, vertically integrated moisture fluxes and surface precipitation. For EFTs with high productivity and a weak seasonal cycle, the nearsurface temperature during the spring of 1988 and 1998 increased by as much as 1℃ in the central and western portions of La Plata Basin. Additionally, for higher productivity EFTs, precipitation differences were generally positive in both dry and wet years, although the patterns are not uniform and exhibit certain patchiness with drier conditions.     

Climate�Csoil�Cvegetation control on groundwater table dynamics and its feedbacks in a climate model

Among the three dynamically linked branches of the water cycle, including atmospheric, surface, and subsurface water, groundwater is the largest reservoir and an active component of the hydrologic system. Because of the inherent slow response time, groundwater may be particularly relevant for long time-scale processes such as multi-years or decadal droughts. This study uses regional climate simulations with and without surface water?Cgroundwater interactions for the conterminous US to assess the influence of climate, soil, and vegetation on groundwater table dynamics, and its potential feedbacks to regional climate. Analyses show that precipitation has a dominant influence on the spatial and temporal variations of groundwater table depth (GWT). The simulated GWT is found to decrease sharply with increasing precipitation. Our simulation also shows some distinct spatial variations that are related to soil porosity and hydraulic conductivity. Vegetation properties such as minimum stomatal resistance, and root depth and fraction are also found to play an important role in controlling the groundwater table. Comparing two simulations with and without groundwater table dynamics, we find that groundwater table dynamics mainly influences the partitioning of soil water between the surface (0?C0.5?m) and subsurface (0.5?C5?m) rather than total soil moisture. In most areas, groundwater table dynamics increases surface soil moisture at the expense of the subsurface, except in regions with very shallow groundwater table. The change in soil water partitioning between the surface and subsurface is found to strongly correlate with the partitioning of surface sensible and latent heat fluxes. The evaporative fraction (EF) is generally higher during summer when groundwater table dynamics is included. This is accompanied by increased cloudiness, reduced diurnal temperature range, cooler surface temperature, and increased cloud top height. Although both convective and non-convective precipitation are enhanced, the higher EF changes the partitioning to favor more non-convective precipitation, but this result could be sensitive to the convective parameterization used. Compared to simulations without groundwater table dynamics, the dry bias in the summer precipitation is slightly reduced over the central and eastern US Groundwater table dynamics can provide important feedbacks to atmospheric processes, and these feedbacks are stronger in regions with deeper groundwater table, because the interactions between surface and subsurface are weak when the groundwater table is deep. This increases the sensitivity of surface soil moisture to precipitation anomalies, and therefore enhances land surface feedbacks to the atmosphere through changes in soil moisture and evaporative fraction. By altering the groundwater table depth, land use change and groundwater withdrawal can alter land surface response and feedback to the climate system.     

Atmosphere-land surface interactions and their influence on extreme rainfall and potential abrupt climate change over southern Africa

In a changing climate, changes in rainfall variability and, in particular, extreme rainfall events are likely to be highly significant for environmentally vulnerable regions such as southern Africa. It is generally accepted that sea-surface temperatures play an important role in modulating rainfall variability, thus the majority work to date has focused on these mechanisms. However past research suggests that land surface processes are also critical for rainfall variability. In particular, work has suggested that the atmosphere-land surface feedback has been important for past abrupt climate changes, such as those which occurred over the Sahara during the mid-Holocene or, more recently, the prolonged Sahelian drought. Therefore the primary aim of this work is to undertake idealised experiments using both a regional and global climate model, to test the sensitivity of rainfall variability to land surface changes over a location where such abrupt climate changes are projected to occur in the future, namely southern Africa. In one experiment, the desert conditions currently observed over southwestern Africa were extended to cover the entire subcontinent. This is based on past research which suggests a remobilisation of sand dune activity and spatial extent under various scenarios of future anthropogenic global warming. In the second experiment, savanna conditions were imposed over all of southern Africa, representing an increase in vegetation for most areas except the equatorial regions. The results suggest that a decrease in rainfall occurs in the desert run, up to 27% of total rainfall in the regional model (relative to the control), due to a reduction in available moisture, less evaporation, less vertical uplift and therefore higher near surface pressure. This result is consistent across both the regional and global model experiments. Conversely an increase in rainfall occurs in the savanna run, because of an increase in available moisture giving an increase in latent heat and therefore surface temperature, increasing vertical uplift and lowering near surface pressure. These experiments, however, are only preliminary, and form the first stage of a wider study into how the atmosphere-land surface feedback influences rainfall extremes over southern Africa in the past (when surface i.e. vegetation conditions were very different) and in the future under various scenarios of future climate change. Future work will examine how other climate models simulate the atmosphere-land surface feedback, using more realistic vegetation types based on past and future surface conditions.     

Effects of crop growth and development on regional climate: a case study over East Asian monsoon area

In this study, the CERES phenological growth and development functions were implemented into the regional climate model, RegCM3 to give a model denoted as RegCM3_CERES. This model was used to represent interactions between regional climate and crop growth processes. The effects of crop growth and development processes on regional climate were then studied based on two 20-year simulations over the East Asian monsoon area conducted using the original regional climate model RegCM3, and the coupled RegCM3_CERES model. The numerical experiments revealed that incorporating the crop growth and development processes into the regional climate model reduced the root mean squared error of the simulated precipitation by 2.2–10.7% over north China, and the simulated temperature by 5.5–30.9% over the monsoon region in eastern China. Comparison of the simulated results obtained using RegCM3_CERES and RegCM3 showed that the most significant changes associated with crop modeling were the changes in leaf area index which in turn modify the aspects of surface energy and water partitions and lead to moderate changes in surface temperature and, to some extent, rainfall. Further analysis revealed that a robust representation of seasonal changes in plant growth and developmental processes in the regional climate model changed the surface heat and moisture fluxes by modifying the vegetation characteristics, and that these differences in simulated surface fluxes resulted in different structures of the boundary layer and ultimately affected the convection. The variations in leaf area index and fractional vegetation cover changed the distribution of evapotranspiration and heat fluxes, which could potentially lead to anomalies in geopotential height, and consequently influenced the overlying atmospheric circulation. These changes would result in redistribution of the water and energy through advection. Nevertheless, there are significant uncertainties in modeling how monsoon dynamics responds to crop modeling and more research is needed.     

Role of dynamic vegetation in regional climate predictions over western Africa

This study examines the role of vegetation dynamics in regional predictions of future climate change in western Africa using a dynamic vegetation model asynchronously coupled to a regional climate model. Two experiments, one for present day and one for future, are conducted with the linked regional climate-vegetation model, and the third with the regional climate model standing alone that predicts future climate based on present-day vegetation. These simulations are so designed in order to tease out the impact of structural vegetation feedback on simulated climate and hydrological processes. According to future predictions by the regional climate-vegetation model, increase in LAI is widespread, with significant shift in vegetation type. Over the Guinean Coast in 2084–2093, evergreen tree coverage decreases by 49% compared to 1984–1993, while drought deciduous tree coverage increases by 56%. Over the Sahel region in the same period, grass cover increases by 31%. Such vegetation changes are accompanied by a decrease of JJA rainfall by 2% over the Guinean Coast and an increase by 23% over the Sahel. This rather small decrease or large increase of precipitation is largely attributable to the role of vegetation feedback. Without the feedback effect from vegetation, the regional climate model would have predicted a 5% decrease of JJA rainfall in both the Guinean Coast and the Sahel as a result of the radiative and physiological effects of higher atmospheric CO₂ concentration. These results demonstrate that climate- and CO₂-induced changes in vegetation structure modify hydrological processes and climate at magnitudes comparable to or even higher than the radiative and physiological effects, thus evincing the importance of including vegetation feedback in future climate predictions.     

Terrestrial vegetation dynamics and global climate controls

Monthly data from the moderate resolution imaging spectroradiometer (MODIS) and its predecessor satellite sensors was used to reconstruct vegetation dynamics in response to climate patterns over the period 1983–2005. Results suggest that plant growth over extensive land areas of southern Africa and Central Asia were the most closely coupled of any major land area to El Niño–southern oscillation (ENSO) effects on regional climate. Others land areas strongly tied to recent ENSO climate effects were in northern Canada, Alaska, western US, northern Mexico, northern Argentina, and Australia. Localized variations in precipitation were the most common controllers of monthly values for the fraction absorbed of photosynthetically active radiation (FPAR) over these regions. In addition to the areas cited above, seasonal FPAR values from MODIS were closely coupled to rainfall patterns in grassland and cropland areas of the northern and central US. Historical associations between global vegetation FPAR and atmospheric carbon dioxide (CO₂) anomalies suggest that the terrestrial biosphere can contribute major fluxes of CO₂ during major drought events, such as those triggered by 1997–1998 El Niño event.