Impact of increasing CO2 on monthly-to-annual precipitation extremes: analysis of the CMIP2 experiments

The impact of increasing atmospheric CO₂ on high and low extremes of monthly-to-annual precipitation is studied using 20 model experiments participating in the second phase of the coupled model intercomparison project (CMIP2). In marked contrast with previous research on daily precipitation extremes, the simulated changes in extremes on these longer time scales are well correlated with the changes in the long-term mean precipitation: wet extremes become more severe especially where the mean precipitation increases, and dry extremes where the mean precipitation decreases. Changes in relative variability play a smaller but discernible role. In an ensemble-mean sense, the variability increases slightly in most areas, so that the contrast between the high and low precipitation extremes grows larger with increasing CO₂. The changes in the frequency of extremes (fraction of cases with precipitation above a high or below a low predefined threshold) are much larger than the changes in their magnitude. Most of the ensemble-averaged changes in the frequency of extremes can be reconstructed by using the changes in time mean precipitation alone, provided that the variation in time mean precipitation change between different models is taken into account. The nonlinear relationship between the mean precipitation and the frequency of extremes complicates the interpretation of the frequency changes, especially when averaging frequencies over different models.     

Changes in temperature and precipitation extremes in the CMIP5 ensemble

Twenty-year temperature and precipitation extremes and their projected future changes are evaluated in an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), updating a similar study based on the CMIP3 ensemble. The projected changes are documented for three radiative forcing scenarios. The performance of the CMIP5 models in simulating 20-year temperature and precipitation extremes is comparable to that of the CMIP3 ensemble. The models simulate late 20th century warm extremes reasonably well, compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes. Simulated late 20th century precipitation extremes are plausible in the extratropics but uncertainty in extreme precipitation in the tropics and subtropics remains very large, both in the models and the observationally-constrained datasets. Consistent with CMIP3 results, CMIP5 cold extremes generally warm faster than warm extremes, mainly in regions where snow and sea-ice retreat with global warming. There are tropical and subtropical regions where warming rates of warm extremes exceed those of cold extremes. Relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation. The corresponding waiting times for late 20th century extreme precipitation events are reduced almost everywhere, except for a few subtropical regions. The CMIP5 planetary sensitivity in extreme precipitation is about 6 %/°C, with generally lower values over extratropical land.     

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.     

A Projection of the Effects of the Climate Change Induced by Increased CO2 on Extreme Hydrologic Events in the Western U.S.

The effects of increased atmospheric CO₂ on the frequency of extreme hydrologic events in the Western United States (WUS) for the 10-yr period of 2040–2049 are examined using dynamically downscaled regional climate change signals. For assessing the changes in the occurrence of hydrologic extremes, downscaled climate change signals in daily precipitation and runoff that are likely to indicate the occurrence of extreme events are examined. Downscaled climate change signals in the selected indicators suggest that the global warming induced by increased CO₂ is likely to increase extreme hydrologic events in the WUS. The indicators for heavy precipitation events show largest increases in the mountainous regions of the northern California Coastal Range and the Sierra Nevada. Increased cold season precipitation and increased rainfall-portion of precipitation at the expense of snowfall in the projected warmer climate result in large increases in high runoff events in the Sierra Nevada river basins that are already prone to cold season flooding in todays climate. The projected changes in the hydrologic characteristics in the WUS are mainly associated with higher freezing levels in the warmer climate and increases in the cold season water vapor influx from the Pacific Ocean.     

Multimodel ensemble projections of future climate extreme changes in the Haihe River Basin,China

Exploring the characteristic of the extreme climatic events, especially future projection is considerably important in assessing the impacts of climatic change on hydrology and water resources system. We investigate the future patterns of climate extremes (2001–2099) in the Haihe River Basin (HRB) derived from Coupled General Circulation Model (CGCM) multimodel ensemble projections using the Bayesian Model Average (BMA) approach, under a range of emission scenarios. The extremes are depicted by three extreme temperature indices (i.e., frost days (FD), growing season length (GSL), and T _min >90th percentile (TN90)) and five extreme precipitation indices (i.e., consecutive dry days (CDD), precipitation ≥10 mm (R10), maximum 5-day precipitation total (R5D), precipitation >95th percentile (R95T), and simple daily intensity index (SDII)). The results indicate frost days display negative trend over the HRB in the 21st century, particularly in the southern basin. Moreover, a greater season length and more frequent warm nights are also projected in the basin. The decreasing CDD, together with the increasing R10, R5D, R95T, and SDII in the 21st century indicate that the extreme precipitation events will increase in their intensity and frequency in the basin. Meanwhile, the changes of all eight extremes climate indices under A2 and A1B scenarios are more pronounced than in B1. The results will be of practical significance in mitigation of the detrimental effects of variations of climatic extremes and improve the regional strategy for water resource and eco-environment management, particularly for the HRB characterized by the severe water shortages and fragile ecological environment.     

SIMULATING THE RESPONSE OF NON-UNIFORMITY OF PRECIPITATION EXTREMES OVER CHINA TO CO2 INCREASING BY MIROC_HIRES MODEL

The response of non-uniformity of precipitation extremes over China to doubled CO2has been analyzed using the daily precipitation simulated by a coupled general circulation model,MIROC_Hires.The major conclusions are as follows:under the CO2increasing scenario(SRES A1B),the climatological precipitation extremes are concentrated over the southern China,while they are uniformly distributed over the northern China.For interannual variability,the concentration of precipitation extremes is small over the southern China,but it is opposite over the northern China.The warming effects on the horizontal and vertical scales are different over the northern and southern part of China.Furthermore,the atmospheric stability is also different between the two parts of China.The heterogeneous warming is one of the possible reasons for the changes in non-uniformity of precipitation extremes over China.     

Very extreme seasonal precipitation in the NARCCAP ensemble: model performance and projections

Seasonal extreme daily precipitation is analyzed in the ensemble of NARCAPP regional climate models. Significant variation in these models’ abilities to reproduce observed precipitation extremes over the contiguous United States is found. Model performance metrics are introduced to characterize overall biases, seasonality, spatial extent and the shape of the precipitation distribution. Comparison of the models to gridded observations that include an elevation correction is found to be better than to gridded observations without this correction. A complicated model weighting scheme based on model performance in simulating observations is found to cause significant improvements in ensemble mean skill only if some of the models are poorly performing outliers. The effect of lateral boundary conditions are explored by comparing the integrations driven by reanalysis to those driven by global climate models. Projected mid-century future changes in seasonal precipitation means and extremes are presented and discussions of the sources of uncertainty and the mechanisms causing these changes are presented.     

Assessment of indices of temperature extremes simulated by multiple CMIP5 models over China

Given that climate extremes in China might have serious regional and global consequences, an increasing number of studies are examining temperature extremes in China using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. This paper investigates recent changes in temperature extremes in China using 25 state-of-the-art global climate models participating in CMIP5. Thirteen indices that represent extreme temperature events were chosen and derived by daily maximum and minimum temperatures, including those representing the intensity (absolute indices and threshold indices), duration (duration indices), and frequency (percentile indices) of extreme temperature. The overall performance of each model is summarized by a "portrait" diagram based on relative root-mean-square error, which is the RMSE relative to the median RMSE of all models, revealing the multi-model ensemble simulation to be better than individual model for most indices. Compared with observations, the models are able to capture the main features of the spatial distribution of extreme temperature during 1986-2005. Overall, the CMIP5 models are able to depict the observed indices well, and the spatial structure of the ensemble result is better for threshold indices than frequency indices. The spread amongst the CMIP5 models in different subregions for intensity indices is small and the median CMIP5 is close to observations; however, for the duration and frequency indices there can be wide disagreement regarding the change between models and observations in some regions. The model ensemble also performs well in reproducing the observational trend of temperature extremes. All absolute indices increase over China during 1961-2005.     

Mediterranean climate extremes in synoptic downscaling assessments

The behaviour of precipitation and maximum temperature extremes in the Mediterranean area under climate change conditions is analysed in the present study. In this context, the ability of synoptic downscaling techniques in combination with extreme value statistics for dealing with extremes is investigated. Analyses are based upon a set of long-term station time series in the whole Mediterranean area. At first, a station-specific ensemble approach for model validation was developed which includes (1) the downscaling of daily precipitation and maximum temperature values from the large-scale atmospheric circulation via analogue method and (2) the fitting of extremes by generalized Pareto distribution (GPD). Model uncertainties are quantified as confidence intervals derived from the ensemble distributions of GPD-related return values and described by a new metric called “ratio of overlapping”. Model performance for extreme precipitation is highest in winter, whereas the best models for maximum temperature extremes are set up in autumn. Valid models are applied to a 30-year period at the end of the twenty-first century (2070–2099) by means of ECHAM5/MPI-OM general circulation model data for IPCC SRES B1 scenario. The most distinctive future changes are observed in autumn in terms of a strong reduction of precipitation extremes in Northwest Iberia and the Northern Central Mediterranean area as well as a simultaneous distinct increase of maximum temperature extremes in Southwestern Iberia and the Central and Southeastern Mediterranean regions. These signals are checked for changes in the underlying dynamical processes using extreme-related circulation classifications. The most important finding connected to future changes of precipitation extremes in the Northwestern Mediterranean area is a reduction of southerly displaced deep North Atlantic cyclones in 2070–2099 as associated with a strengthened North Atlantic Oscillation. Thus, the here estimated future changes of extreme precipitation are in line with the discourse about the influence of North Atlantic circulation variability on the changing climate in Europe.     

CO2倍增对我国东部极端降水的影响

 利用GFDL-CM2.1耦合模式控制试验和CO₂增长试验逐日降水输出结果,评估了CO₂浓度加倍对我国极端降水变化的影响。结果表明：CO₂浓度加倍导致我国东部地区年极端降水的强度增强、降水量显著增多及降水频次显著增加（除华北南部外）; CO₂浓度加倍对我国春夏季极端降水影响较大,导致东部多数地区春夏季极端降水频次增加,强度增强;而CO₂浓度加倍导致华北南部和长江中下游春夏季雨日减少以及小雨、中雨减少,从而导致年总降水量减少。     

CO2倍增对我国东部极端降水的影响

利用GFDL-CM2.1耦合模式控制试验和CO₂增长试验逐日降水输出结果,评估了CO₂浓度加倍对我国极端降水变化的影响。结果表明：CO₂浓度加倍导致我国东部地区年极端降水的强度增强、降水量显著增多及降水频次显著增加（除华北南部外）; CO₂浓度加倍对我国春夏季极端降水影响较大,导致东部多数地区春夏季极端降水频次增加,强度增强;而CO₂浓度加倍导致华北南部和长江中下游春夏季雨日减少以及小雨、中雨减少,从而导致年总降水量减少。     

Annual and seasonal climate and climatic changes in the Canadian prairies simulated by the CCC GCM

Abstract

As part of a study on the effects of climatic variability and change on the sustainability of agriculture in Alberto, the modelling performance of the second‐generation Canadian Climate Centre GCM (general circulation model) is examined. For the region in general, the simulation of 1 × CO₂ mean temperature is generally better than that for mean precipitation, and summer is the season best modelled for each variable. At the scale of individual grid squares, DJF (December, January, February) (temperature) and JJA (June, July, August) (precipitation) are the seasons best modelled. The GCM‐simulated increases in mean annual temperature resulting from a doubling of CO₂ are of the order of 5 to 6°C in the Prairie region, with much of this increase resulting from substantial warming in the winter and spring. Increases in mean annual precipitation are of the order of 50 to 150 mm (changes of +5 to +15%), with the greatest changes again occurring in winter and spring. As far as the limited GCM run durations allow, temperature and precipitation variance generally show no significant changes from a 1 × CO₂ to a 2 × CO₂ climate. Increased precipitation in winter and spring does not result in greater snow accumulations owing to the magnitude of warming; and significant decreases in soil moisture content occur in summer and fall. The resulting effects on the growing season and moisture regime have the potential to affect agricultural practices in the area.     

Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections

A fast simple climate modelling approach is developed for predicting and helping to understand general circulation model (GCM) simulations. We show that the simple model reproduces the GCM results accurately, for global mean surface air temperature change and global-mean heat uptake projections from 9 GCMs in the fifth coupled model inter-comparison project (CMIP5). This implies that understanding gained from idealised CO₂ step experiments is applicable to policy-relevant scenario projections. Our approach is conceptually simple. It works by using the climate response to a CO₂ step change taken directly from a GCM experiment. With radiative forcing from non-CO₂ constituents obtained by adapting the Forster and Taylor method, we use our method to estimate results for CMIP5 representative concentration pathway (RCP) experiments for cases not run by the GCMs. We estimate differences between pairs of RCPs rather than RCP anomalies relative to the pre-industrial state. This gives better results because it makes greater use of available GCM projections. The GCMs exhibit differences in radiative forcing, which we incorporate in the simple model. We analyse the thus-completed ensemble of RCP projections. The ensemble mean changes between 1986–2005 and 2080–2099 for global temperature (heat uptake) are, for RCP8.5: 3.8 K (2.3 × 10²⁴ J); for RCP6.0: 2.3 K (1.6 × 10²⁴ J); for RCP4.5: 2.0 K (1.6 × 10²⁴ J); for RCP2.6: 1.1 K (1.3 × 10²⁴ J). The relative spread (standard deviation/ensemble mean) for these scenarios is around 0.2 and 0.15 for temperature and heat uptake respectively. We quantify the relative effect of mitigation action, through reduced emissions, via the time-dependent ratios (change in RCPx)/(change in RCP8.5), using changes with respect to pre-industrial conditions. We find that the effects of mitigation on global-mean temperature change and heat uptake are very similar across these different GCMs.     

用区域气候模式模拟人为硫酸盐气溶胶在气候变化中的作用

使用新版RegCM2区域气候模式，单向嵌套澳大利亚CSIROR21L9全球海-气耦合模式，在C02加倍情况下引人人为硫酸盐气溶胶直接气候效应，进行了其对中国气候变化影响的试验。结果表明，硫酸盐气溶胶的直接气候效应，对地面气温为降温作用，其中在冬半年和在南方更明显；对降水的影响为全国各月平均降水将以减少为主，年平均降水变化的基本特点为在中国东部以减少为主，西部以增加为主。但无论温度还是降水变化的数值都很小。     

Risk assessment of precipitation extremes in northern Xinjiang,China

This study was conducted using daily precipitation records gathered at 37 meteorological stations in northern Xinjiang, China, from 1961 to 2010. We used the extreme value theory model, generalized extreme value (GEV) and generalized Pareto distribution (GPD), statistical distribution function to fit outputs of precipitation extremes with different return periods to estimate risks of precipitation extremes and diagnose aridity–humidity environmental variation and corresponding spatial patterns in northern Xinjiang. Spatiotemporal patterns of daily maximum precipitation showed that aridity–humidity conditions of northern Xinjiang could be well represented by the return periods of the precipitation data. Indices of daily maximum precipitation were effective in the prediction of floods in the study area. By analyzing future projections of daily maximum precipitation (2, 5, 10, 30, 50, and 100 years), we conclude that the flood risk will gradually increase in northern Xinjiang. GEV extreme value modeling yielded the best results, proving to be extremely valuable. Through example analysis for extreme precipitation models, the GEV statistical model was superior in terms of favorable analog extreme precipitation. The GPD model calculation results reflect annual precipitation. For most of the estimated sites’ 2 and 5-year T for precipitation levels, GPD results were slightly greater than GEV results. The study found that extreme precipitation reaching a certain limit value level will cause a flood disaster. Therefore, predicting future extreme precipitation may aid warnings of flood disaster. A suitable policy concerning effective water resource management is thus urgently required.     

Effects of increased CO2 levels on monsoons

Increased atmospheric carbon dioxide concentration provided warmer atmospheric temperature and higher atmospheric water vapor content, but not necessarily more precipitation. A set of experiments performed with a state-of-the-art coupled general circulation model forced with increased atmospheric CO₂ concentration (2, 4 and 16 times the present-day mean value) were analyzed and compared with a control experiment to evaluate the effect of increased CO₂ levels on monsoons. Generally, the monsoon precipitation responses to CO₂ forcing are largest if extreme concentrations of carbon dioxide are used, but they are not necessarly proportional to the forcing applied. In fact, despite a common response in terms of an atmospheric water vapor increase to the atmospheric warming, two out of the six monsoons studied simulate less or equal summer mean precipitation in the 16×CO₂ experiment compared to the intermediate sensitivity experiments. The precipitation differences between CO₂ sensitivity experiments and CTRL have been investigated specifying the contribution of thermodynamic and purely dynamic processes. As a general rule, the differences depending on the atmospheric moisture content changes (thermodynamic component) are large and positive, and they tend to be damped by the dynamic component associated with the changes in the vertical velocity. However, differences are observed among monsoons in terms of the role played by other terms (like moisture advection and evaporation) in shaping the precipitation changes in warmer climates. The precipitation increase, even if weak, occurs despite a weakening of the mean circulation in the monsoon regions (??precipitation-wind paradox??). In particular, the tropical east-west Walker circulation is reduced, as found from velocity potential analysis. The meridional component of the monsoon circulation is changed as well, with larger (smaller) meridional (vertical) scales.     

North Atlantic cyclones in CO2-induced warm climate simulations: frequency, intensity, and tracks

The effect of CO₂-induced climate change on the North Atlantic storm and cyclone tracks in winter is analysed using time slice experiments of the Hamburg atmospheric general circulation model (ECHAM3) with triangular truncation at wave number 42 (T42) and 19 levels. The sea surface temperature (SST) and sea ice boundary conditions for these experiments are taken from a transient Intergovernmental Panel on Climate Change (IPCC) scenario A run of ECHAM1/LSG at the times where the 1×CO₂ (control run), the 2×CO₂ and the 3×CO₂ concentrations are reached. Using a cyclone identification and tracking scheme, we detect the low pressure systems as relative minima in the 1000 hPa geopotential height field and connect them to cyclone tracks. The results of the Eulerian analysis of the storm track using filtered variances and the Lagrangian analysis of the cyclone trajectories from the three climate runs are discussed and compared with each other. In the 2×CO₂ experiment, the storm track shifts eastward, whereas the cyclone density shifts northeastward. In the 3×CO₂ experiment the storm track shows a southeastward shift, whereas the cyclone density shifts northward. The variability of the cyclone tracks is determined by a cluster analysis of their relative trajectories considering the first three days of the cyclones. The relative cyclone tracks are grouped into stationary, zonal and northeastward travelling cyclones. This analysis provides a method to assess the model quality and to detect changes of the cyclone trajectories in different climates. In the 2×CO₂ (but not in the 3×CO₂) run the occupation number of northeastward cyclones increases. Received: 27 January 1998 / Accepted: 19 May 1998     

Climate projections of future extreme events accounting for modelling uncertainties and historical simulation biases

A methodology is presented for providing projections of absolute future values of extreme weather events that takes into account key uncertainties in predicting future climate. This is achieved by characterising both observed and modelled extremes with a single form of non-stationary extreme value (EV) distribution that depends on global mean temperature and which includes terms that account for model bias. Such a distribution allows the prediction of future “observed” extremes for any period in the twenty-first century. Uncertainty in modelling future climate, arising from a wide range of atmospheric, oceanic, sulphur cycle and carbon cycle processes, is accounted for by using probabilistic distributions of future global temperature and EV parameters. These distributions are generated by Bayesian sampling of emulators with samples weighted by their likelihood with respect to a set of observational constraints. The emulators are trained on a large perturbed parameter ensemble of global simulations of the recent past, and the equilibrium response to doubled CO₂. Emulated global EV parameters are converted to the relevant regional scale through downscaling relationships derived from a smaller perturbed parameter regional climate model ensemble. The simultaneous fitting of the EV model to regional model data and observations allows the characterisation of how observed extremes may change in the future irrespective of biases that may be present in the regional models simulation of the recent past climate. The clearest impact of a parameter perturbation in this ensemble was found to be the depth to which plants can access water. Members with shallow soils tend to be biased hot and dry in summer for the observational period. These biases also appear to have an impact on the potential future response for summer temperatures with some members with shallow soils having increases for extremes that reduce with extreme severity. We apply this methodology for London, using the A1B future emissions scenario to obtain projections of the 50 year return values for the 20 year period centred on 2050. We obtain 10th to 90th percentile ranges of 35.9–42.1 °C for summer daily maximum temperature, 35.5–52.4 mm for summer daily rainfall and 79.2, 97.0 mm for autumn 5 day total rainfall, compared to observed estimates for 1961–1990 of 35.7 °C, 42.1 and 78.4 mm respectively.     

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

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

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.