Interannual Variability of the Normalized Difference Vegetation Index on the Tibetan Plateau and Its Relationship with Climate Change

The Qinghai-Xizang Plateau, or Tibetan Plateau, is a sensitive region for climate change, where the manifestation of global warming is particularly noticeable. The wide climate variability in this region significantly affects the local land ecosystem and could consequently lead to notable vegetation changes. In this paper, the interannual variations of the plateau vegetation are investigated using a 21-year normalized difference vegetation index （NDVI） dataset to quantify the consequences of climate warming for the regional ecosystem and its interactions. The results show that vegetation coverage is best in the eastern and southern plateau regions and deteriorates toward the west and north. On the whole, vegetation activity demonstrates a gradual enhancement in an oscillatory manner during 1982-2002. The temporal variation also exhibits striking regional differences： an increasing trend is most apparent in the west, south, north and southeast, whereas a decreasing trend is present along the southern plateau boundary and in the central-east region. Covariance analysis between the NDVI and surface temperature/precipitation suggests that vegetation change is closely related to climate change. However, the controlling physical processes vary geographically. In the west and east, vegetation variability is found to be driven predominantly by temperature, with the impact of precipitation being of secondary importance. In the central plateau, however, temperature and precipitation factors are equally important in modulating the interannual vegetation variability.     

Projections of climate change impacts on central America tropical rainforest

Tropical rainforest plays an important role in the global carbon cycle, accounting for a large part of global net primary productivity and contributing to CO₂ sequestration. The objective of this work is to simulate potential changes in the rainforest biome in Central America subject to anthropogenic climate change under two emissions scenarios, RCP4.5 and RCP8.5. The use of a dynamic vegetation model and climate change scenarios is an approach to investigate, assess or anticipate how biomes respond to climate change. In this work, the Inland dynamic vegetation model was driven by the Eta regional climate model simulations. These simulations accept boundary conditions from HadGEM2-ES runs in the two emissions scenarios. The possible consequences of regional climate change on vegetation properties, such as biomass, net primary production and changes in forest extent and distribution, were investigated. The Inland model projections show reductions in tropical forest cover in both scenarios. The reduction of tropical forest cover is greater in RCP8.5. The Inland model projects biomass increases where tropical forest remains due to the CO₂ fertilization effect. The future distribution of predominant vegetation shows that some areas of tropical rainforest in Central America are replaced by savannah and grassland in RCP4.5. Inland projections under both RCP4.5 and RCP8.5 show a net primary productivity reduction trend due to significant tropical forest reduction, temperature increase, precipitation reduction and dry spell increments, despite the biomass increases in some areas of Costa Rica and Panama. This study may provide guidance to adaptation studies of climate change impacts on the tropical rainforests in Central America.     

植被覆盖对暴雨型滑坡影响的初步分析

根据遥感资料、地形数据和历史观测资料等,以江西省为例,分析了森林植被覆盖率、森林生物量和暴雨型滑坡的空间分布,以及森林植被类型对大气降水的截留作用。分析结果初步揭示了植被覆盖对滑坡的影响,认为植被覆盖程度高、生物量多和植被覆盖差、生物量低的中低山区,都可能发生滑坡灾害。不同林冠对降水的截留作用,减缓了降水对斜坡的冲刷,但当降水强度达到或超过暴雨强度时,森林对降水的截留率减小。同等地质环境条件下,植被覆盖率低,滑坡较易发生,但当降水强度较大时,特别是达到诱发滑坡灾害发生的临界值时,植被对滑坡体的重力作用则更加重了滑坡的发生。植被覆盖对滑坡的影响主要取决于降水强度。高森林覆盖区发生滑坡的雨量临界值大于森林覆盖率差的区域。     

Vegetation and climate variability: a GCM modelling study

Vegetation is known to interact with the other components of the climate system over a wide range of timescales. Some of these interactions are now being taken into account in models for climate prediction. This study is an attempt to describe and quantify the climate–vegetation coupling at the interannual timescale, simulated with a General Circulation Model (HadSM3) coupled to a dynamic global vegetation model (TRIFFID). Vegetation variability is generally strongest in semi-arid areas, where it is driven by precipitation variability. The impact of vegetation variability on climate is analysed by using multivariate regressions of boundary layer fluxes and properties, with respect to soil moisture and vegetation fraction. Dynamic vegetation is found to significantly increase the variance in the surface sensible and latent heat fluxes. Vegetation growth always causes evapotranspiration to increase, but its impact on sensible heat is less straightforward. The feedback of vegetation on sensible heat is positive in Australia, but negative in the Sahel and in India. The sign of the feedback depends on the competing influences, at the gridpoint scale, of the turbulent heat exchange coefficient and the surface (stomatal) water conductance, which both increase with vegetation growth. The impact of vegetation variability on boundary layer potential temperature and relative humidity are shown to be small, implying that precipitation persistence is not strongly modified by vegetation dynamics in this model. We discuss how these model results may improve our knowledge of vegetation–atmosphere interactions and help us to target future model developments.     

Hiatus of wetland methane emissions associated with recent La Niña episodes in the Asian monsoon region

The variability of methane emissions from wetlands in the tropics and northern temperate regions can explain more than 70% of the interannual variation in global wetland methane emissions, which are largely driven by climate variability. We use climate reanalysis, remote sensing wetland area dataset and simulations from 11 land models contributing to Global Methane Budget to investigate the interannual variation and anomalies of wetland methane emissions in the Asian Monsoon region. Methane emissions in this region steadily increased over 2000–2012. However, abnormally low methane emissions were found in equatorial fully humid (Af), warm temperate winter dry (Cw), and warm temperate fully humid (Cf) Asian Monsoon climate sub-regions in 2008, 2009 and 2011, respectively. These spatially-shifting low emissions occurred simultaneously with observed wetland area shrinkage due to abnormally low precipitation. Interannual variability of wetland methane emissions in Asian Monsoon region are primarily driven by South Asian Monsoon system. However, the abnormally low emissions are related to strong La Niña events, and its accompanying effect of weakened East Asian Monsoon system and eastward Western Pacific subtropical high, which drives the shifting pattern of rainfall, and thus the spatial pattern of methane emission anomalies.     

Climate Variability-Observations, Reconstructions, and Model Simulations for the Atlantic-European and Alpine Region from 1500-2100 AD

A detailed analysis is undertaken of the Atlantic-European climate using data from 500-year-long proxy-based climate reconstructions, a long climate simulation with perpetual 1990 forcing, as well as two global and one regional climate change scenarios. The observed and simulated interannual variability and teleconnectivity are compared and interpreted in order to improve the understanding of natural climate variability on interannual to decadal time scales for the late Holocene. The focus is set on the Atlantic-European and Alpine regions during the winter and summer seasons, using temperature, precipitation, and 500 hPa geopotential height fields. The climate reconstruction shows pronounced interdecadal variations that appear to “lock” the atmospheric circulation in quasi-steady long-term patterns over multi-decadal periods controlling at least part of the temperature and precipitation variability. Different circulation patterns are persistent over several decades for the period 1500 to 1900. The 500-year-long simulation with perpetual 1990 forcing shows some substantial differences, with a more unsteady teleconnectivity behaviour. Two global scenario simulations indicate a transition towards more stable teleconnectivity for the next 100 years. Time series of reconstructed and simulated temperature and precipitation over the Alpine region show comparatively small changes in interannual variability within the time frame considered, with the exception of the summer season, where a substantial increase in interannual variability is simulated by regional climate models.     

Sensitivity of the Terrestrial Ecosystem to Precipitation and Temperature Variability over China

In this study, the sensitivities of net primary production （NPP）, soil carbon, and vegetation carbon to precipitation and temperature variability over China are discussed using the state-of-the-art Lund-Potsdam-Jena dynamic global vegetation model （LPJ DGVM）. The im- pacts of the sensitivities to precipitation variability and temperature variability on NPP, soil carbon, and vegeta- tion carbon are discussed. It is shown that increasing pre- cipitation variability, representing the frequency of ex- treme precipitation events, leads to losses in NPP, soil carbon, and vegetation carbon over most of China, espe- cially in North and Northeast China where the dominant plant functional types （i.e., those with the largest simu- lated areal cover） are grass and boreal needle-leaved for- est. The responses of NPP, soil carbon, and vegetation carbon to decreasing precipitation variability are opposite to the responses to increasing precipitation variability. The variations in NPP, soil carbon, and vegetation carbon in response to increasing and decreasing precipitation variability show a nonlinear asymmetry. Increasing pre- cipitation variability results in notable interannual variation of NPP. The sensitivities of NPP, soil carbon, and vegetation carbon to temperature variability, whether negative or positive, meaning frequent hot and cold days, are slight. The present study suggests, based on the LPJ model, that precipitation variability has a more severe impact than temperature variability on NPP, soil carbon, and vegetation carbon.     

On the relationship between vegetation and climate in tropical and northern Africa

Vegetation cover is a crucial component of the Earth’s climate system but, still, our understanding of the mechanisms governing the reciprocal influence between atmosphere and vegetation is limited. In this study, we investigate the unilateral atmospheric impact on vegetation cover in tropical and northern Africa, differentiated into regions with different circulation regimes and into detailed land-cover classes. In contrast to former studies, climate predictors from a regional climate model are used as input for a multiple regression model. Climate models provide consistent data without gaps at high spatial resolution, a considerably larger set of available climate variables and the perspective to transfer the statistical relationships to future projections, e.g., in the context of anthropogenic climate change. Indeed, robust climate predictors which drive up to 70 % of observed interannual vegetation variability could be extracted from the climate model. Besides precipitation and temperature, global radiation, and relative humidity play an important role. The statistical transfer functions are plausible in terms of the affected regions and land-cover classes and draw a rather complex picture of the atmosphere–vegetation relation in Africa.     

A transient climate change simulation with greenhouse gas and aerosol forcing: projected climate to the twenty-first century

 The potential climatic consequences of increasing atmospheric greenhouse gas (GHG) concentration and sulfate aerosol loading are investigated for the years 1900 to 2100 based on five simulations with the CCCma coupled climate model. The five simulations comprise a control experiment without change in GHG or aerosol amount, three independent simulations with increasing GHG and aerosol forcing, and a simulation with increasing GHG forcing only. Climate warming accelerates from the present with global mean temperatures simulated to increase by 1.7 °C to the year 2050 and by a further 2.7 °C by the year 2100. The warming is non-uniform as to hemisphere, season, and underlying surface. Changes in interannual variability of temperature show considerable structure and seasonal dependence. The effect of the comparatively localized negative radiative forcing associated with the aerosol is to retard and reduce the warming by about 0.9 °C at 2050 and 1.2 °C at 2100. Its primary effect on temperature is to counteract the global pattern of GHG-induced warming and only secondarily to affect local temperatures suggesting that the first order transient climate response of the system is determined by feedback processes and only secondarily by the local pattern of radiative forcing. The warming is accompanied by a more active hydrological cycle with increases in precipitation and evaporation rates that are delayed by comparison with temperature increases. There is an “El Nino-like” shift in precipitation and an overall increase in the interannual variability of precipitation. The effect of the aerosol forcing is again primarily to delay and counteract the GHG-induced increase. Decreases in soil moisture are common but regionally dependent and interannual variability changes show considerable structure. Snow cover and sea-ice retreat. A PNA-like anomaly in mean sea-level pressure with an enhanced Aleutian low in northern winter is associated with the tropical shift in precipitation regime. The interannual variability of mean sea-level pressure generally decreases with largest decreases in the tropical Indian ocean region. Changes to the ocean thermal structure are associated with a spin-down of the Atlantic thermohaline circulation together with a decrease in its variability. The effect of aerosol forcing, although modest, differs from that for most other quantities in that it does not act primarily to counteract the GHG forcing effect. The barotropic stream function in the ocean exhibits modest change in the north Pacific but accelerating changes in much of the Southern Ocean and particularly in the north Atlantic where the gyre spins down in conjunction with the decrease in the thermohaline circulation. The results differ in non-trivial ways from earlier equilibrium 2 × CO₂ results with the CCCma model as a consequence of the coupling to a fully three-dimensional ocean model and the evolving nature of the forcing. Received: 24 September 1998 / Accepted: 8 October 1999     

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.     

Variability in global land surface energy budgets during 1987–1988 simulated by an off-line land surface model

The International Satellite Land-Surface Climatology Project (ISLSCP) Initiative-I 1-degree 1987–1988 data were used to drive a land surface model (LSM) to simulate global surface energy budgets. Simulated surface heat fluxes show remarkable spatial variability and seem to capture well their annual and interannual variability. A shift of maximum evaporation across the equator is more closely related to the seasonal shifting of precipitation pattern than to surface radiation changes. The NCEP/NCAR reanalysis did not reflect this shift, presumably due to its dominant rainfall maximum in the Southern Hemisphere. To assess the “reliability” of these fields, both Global Soil Wetness Project (GSWP) and reanalysis were verified against observations, at two sites. Monthly mean ISLSCP forcing conditions agree fairly well with observations, but its precipitation is usually lower during spring and summer. Low summer GSWP evaporation may be due to low precipitation and incorrect specification of vegetation and soil conditions. The reanalysis had larger seasonal variability than GSWP and observations, and overestimated summer heat fluxes because of its large rainfall and surface radiation. Despite uncertainty in ISLSCP data, an LSM with a modest treatment of vegetation was able to capture reasonably well the seasonal variations in surface heat fluxes at global scales. With some caution, these types of simulations can be used as “pseudo-observations” to evaluate climate-model simulations and to investigate global energy budgets. For the next phase of ISLSCP data development, higher resolution data, which can reflect local heterogeneity of vegetation and soil characteristics, include more rain gauge data are highly desirable to improve model simulations.     

Climate change impact on snow and soil temperature in boreal Scots pine stands

Scenarios indicate that the air temperature will increase in high latitude regions in coming decades, causing the snow covered period to shorten, the growing season to lengthen and soil temperatures to change during the winter, spring and early summer. To evaluate how a warmer climate is likely to alter the snow cover and soil temperature in Scots pine stands of varying ages in northern Sweden, climate scenarios from the Swedish regional climate modelling programme SWECLIM were used to drive a Soil-Vegetation-Atmosphere Transfer (SVAT)-model (COUP). Using the two CO₂ emission scenarios A and B in the Hadley centres global climate model, HadleyA and HadleyB, SWECLIM predicts that the annual mean air temperature and precipitation will increase at most 4.8°C and 315 mm, respectively, within a century in the study region. The results of this analysis indicate that a warmer climate will shorten the period of persistent snow pack by 73–93 days, increase the average soil temperature by 0.9–1.5°C at 10 cm depth, advance soil warming by 15–19 days in spring and cause more soil freeze–thaw cycles by 31–38%. The results also predict that the large current variations in snow cover due to variations in tree interception and topography will be enhanced in the coming century, resulting in increased spatial variability in soil temperatures.     

Agricultural Land Use Effects on Climate over China as Simulated by a Regional Climate Model

The Abdus Salam International Centre for Theoretical Physics (ICTP) Regional Climate Model version 3 (RegCM3) is used to investigate the climate effects of land use change related to agriculture over China. The model is driven by the European Center for Medium-range Weather Forecast 40-yr Re-Analysis (ERA40)data. Two sets of experiments for 15 yr (1987-2001) are conducted, one with the potential vegetation cover and the other the agricultural land use (AG). The results show that the AG effects on temperature are weak over northern China while in southern China a significant cooling is found in both winter (December-January-February) and summer (June-July-August). The mean cooling in the sub-regions of South China (SC) in winter and the sub-regions of Southeast (SE) China in summer are found to be the greatest,up to 0.5℃ and 0.8℃, respectively. In general, the change of AG leads to a decrease of annual mean temperature by 0.5-1℃ in southern China. Slight change of precipitation in western China and a decrease of precipitation in eastern China are simulated in winter, with the maximum reduction reaching -7.5% over SE. A general decrease of precipitation over northern China and an increase over southern China are simulated in summer,in particular over SE where the increase of precipitation can be up to 7.3%. The AG effects on temperature and precipitation show strong interannual variability. Comparison of the climate effects between AG and the present-day land use (LU) is also performed. In southern China, the ratio of temperature (precipitation)changes caused by AG and LU is greater than (closer to) the ratio of the number of grid cells with changed vegetation cover due to AG and LU variations.     

Mean, interannual variability and trends in a regional climate change experiment over Europe. I. Present-day climate (1961–1990)

We present an analysis of a multidecadal simulation of present-day climate (1961–1990) over Europe with the regional climate model RegCM nested within the global atmospheric model HadAMH. Climatic means, interannual variability and trends are examined, with focus on surface air temperature and precipitation. The RegCM driven by HadAMH fields is able to reproduce the basic features of the observed mean surface climate over Europe, its seasonal evolution and the regional detail due to topographic forcing. Surface air temperature biases are mostly less than 1–2 °C and precipitation biases mostly within 10–20%. The RegCM has more intense vertical transport of temperature and water vapor than HadAMH, which results in lower surface air temperatures and greater precipitation than found in the HadAMH simulation. In some cases this is in the direction of greater agreement with observations, while in others it is in the opposite direction. The simulation shows a tendency to overestimate interannual variability of temperature and precipitation compared to observations, particularly during summer and over the Mediterranean regions. It is shown that in DJF, MAM and SON the RegCM interannual variability is primarily determined by the boundary forcing from HadAMH, while in JJA the internal model physics and resolution effects dominate over many subregions of the domain, and the RegCM has higher interannual variability than HadAMH. The precipitation trends simulated by the nested modeling system for the period 1961–1990 capture some features of the observed trends, in particular the cold season drying over the Mediterranean regions. Ensembles of simulations are, however, needed for a more robust assessment of the models capability to simulate climatic trends. Overall, this simulation is of good quality compared with previous nested RegCM experiments and will constitute the basis for the generation of climate change scenarios over the European region to be reported in future work.     

Mechanisms for projected future changes in south Asian monsoon precipitation

Results are first presented from an analysis of a global coupled climate model regarding changes in future mean and variability of south Asian monsoon precipitation due to increased atmospheric CO₂ for doubled (2 × CO₂) and quadrupled (4 × CO₂) present-day amounts. Results from the coupled model show that, in agreement with previous studies, mean area-averaged south Asian monsoon precipitation increases with greater CO₂ concentrations, as does the interannual variability. Mechanisms producing these changes are then examined in a series of AMIP2-style sensitivity experiments using the atmospheric model (taken from the coupled model) run with specified SSTs. Three sets of ensemble experiments are run with SST anomalies superimposed on the AMIP2 SSTs from 1979–97: (1) anomalously warm Indian Ocean SSTs, (2) anomalously warm Pacific Ocean SSTs, and (3) anomalously warm Indian and Pacific Ocean SSTs. Results from these experiments show that the greater mean monsoon precipitation is due to increased moisture source from the warmer Indian Ocean. Increased south Asian monsoon interannual variability is primarily due to warmer Pacific Ocean SSTs with enhanced evaporation variability, with the warmer Indian Ocean SSTs a contributing but secondary factor. That is, for a given interannual tropical Pacific SST fluctuation with warmer mean SSTs in the future climate, there is enhanced evaporation and precipitation variability that is communicated via the Walker Circulation in the atmosphere to the south Asian monsoon to increase interannual precipitation variability there. This enhanced monsoon variability occurs even with no change in interannual SST variability in the tropical Pacific.     

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。     

Coupled atmosphere-ocean-vegetation simulations for modern and mid-Holocene climates: role of extratropical vegetation cover feedbacks

A full global atmosphere-ocean-land vegetation model is used to examine the coupled climate/vegetation changes in the extratropics between modern and mid-Holocene (6,000 year BP) times and to assess the feedback of vegetation cover changes on the climate response. The model produces a relatively realistic natural vegetation cover and a climate sensitivity comparable to that realized in previous studies. The simulated mid-Holocene climate led to an expansion of boreal forest cover into polar tundra areas (mainly due to increased summer/fall warmth) and an expansion of middle latitude grass cover (due to a combination of enhanced temperature seasonality with cold winters and interior drying of the continents). The simulated poleward expansion of boreal forest and middle latitude expansion of grass cover are consistent with previous modeling studies. The feedback effect of expanding boreal forest in polar latitudes induced a significant spring warming and reduced snow cover that partially countered the response produced by the orbitally induced changes in radiative forcing. The expansion of grass cover in middle latitudes worked to reinforce the orbital forcing by contributing a spring cooling, enhanced snow cover, and a delayed soil water input by snow melt. Locally, summer rains tended to increase (decrease) in areas with greatest tree cover increases (decreases); however, for the broad-scale polar and middle latitude domains the climate responses produced by the changes in vegetation are relatively much smaller in summer/fall than found in previous studies. This study highlights the need to develop a more comprehensive strategy for investigating vegetation feedbacks.     

Evaluating the influence of different vegetation biomes on the global climate

The participation of different vegetation types within the physical climate system is investigated using a coupled atmosphere-biosphere model, CCM3-IBIS. We analyze the effects that six different vegetation biomes (tropical, boreal, and temperate forests, savanna, grassland and steppe, and shrubland/tundra) have on the climate through their role in modulating the biophysical exchanges of energy, water, and momentum between the land-surface and the atmosphere. Using CCM3-IBIS we completely remove the vegetation cover of a particular biome and compare it to a control simulation where the biome is present, thereby isolating the climatic effects of each biome. Results from the tropical and boreal forest removal simulations are in agreement with previous studies while the other simulations provide new evidence as to their contribution in forcing the climate. Removal of the temperate forest vegetation exhibits behavior characteristic of both the tropical and boreal simulations with cooling during winter and spring due to an increase in the surface albedo and warming during the summer caused by a reduction in latent cooling. Removal of the savanna vegetation exhibits behavior much like the tropical forest simulation while removal of the grassland and steppe vegetation has the largest effect over the central United States with warming and drying of the atmosphere in summer. The largest climatic effect of shrubland and tundra vegetation removal occurs in DJF in Australia and central Siberia and is due to reduced latent cooling and enhanced cold air advection, respectively. Our results show that removal of the boreal forest yields the largest temperature signal globally when either including or excluding the areas of forest removal. Globally, precipitation is most affected by removal of the savanna vegetation when including the areas of vegetation removal, while removal of the tropical forest most influences the global precipitation excluding the areas of vegetation removal.     

RegCM3 regional climatologies for South America using reanalysis and ECHAM global model driving fields

To enable downscaling of seasonal prediction and climate change scenarios, long-term baseline regional climatologies which employ global model forcing are needed for South America. As a first step in this process, this work examines climatological integrations with a regional climate model using a continental scale domain nested in both reanalysis data and multiple realizations of an atmospheric general circulation model (GCM). The analysis presents an evaluation of the nested model simulated large scale circulation, mean annual cycle and interannual variability which is compared against observational estimates and also with the driving GCM for the Northeast, Amazon, Monsoon and Southeast regions of South America. Results indicate that the regional climate model simulates the annual cycle of precipitation well in the Northeast region and Monsoon regions; it exhibits a dry bias during winter (July–September) in the Southeast, and simulates a semi-annual cycle with a dry bias in summer (December–February) in the Amazon region. There is little difference in the annual cycle between the GCM and renalyses driven simulations, however, substantial differences are seen in the interannual variability. Despite the biases in the annual cycle, the regional model captures much of the interannual variability observed in the Northeast, Southeast and Amazon regions. In the Monsoon region, where remote influences are weak, the regional model improves upon the GCM, though neither show substantial predictability. We conclude that in regions where remote influences are strong and the global model performs well it is difficult for the regional model to improve the large scale climatological features, indeed the regional model may degrade the simulation. Where remote forcing is weak and local processes dominate, there is some potential for the regional model to add value. This, however, will require improvments in physical parameterizations for high resolution tropical simulations.