中国地区黑碳气溶胶直接辐射效应的数值模拟研究

利用意大利国际理论物理研究中心（ICTP）提供的2000年各月气溶胶资料（包括人类活动和生物质燃烧所产生的气溶胶）,使用并行版本区域气候模式RegCM3,研究了黑碳气溶胶对中国区域气候的影响。结果表明,引入黑碳气溶胶后,冬、夏季中国大部分地区大气顶出现了正辐射强迫,其分布与垂直负荷分布基本相似。在仅考虑黑碳气溶胶的直接辐射效应时,中国大部分地区冬、夏季地面气温呈下降趋势,降温的高值区均位于中国东南部,冬季最大降温幅度约为0．9℃,夏季最大降幅约为2．4℃,夏季降温幅度明显大于冬季。相对于温度变化,黑碳气溶胶引起的降水变化较为复杂,无论是冬季还是夏季,降水量减小的区域均大于增加区。冬季降水量最大减幅约为20mm,夏季降水量最大减幅超过100mm,夏季降水量减幅明显大于冬季。冬、夏季仅西北和华南部分地区降水量有所增加。冬季中国大部分地区痕量降水和弱降水日数呈增加趋势;夏季黄河以北中国北方地区痕量降水和弱降水日数也是以增加为主。     

CCSM4模式对东北气温和降水的模拟及预估

利用东北地区162个气象观测站逐月气温和降水资料对CCSM4模式的模拟性能进行了评价,并预估了2021—2050年东北地区的气候变化情景。结果表明:CCSM4模式长期历史气候模拟实验模拟的1961—2005年月平均气温、降水量值能较好地再现东北区域年平均气温、降水量的空间分布形态,但气温模拟值比观测偏低,91. 4%站点误差在1. 5℃以内;降水中心比观测略偏北,全区平均偏多35. 18 mm。2021—2050年东北区域年平均气温呈增温趋势,高纬度地区的增温幅度明显大于低纬度地区,与基准年相比,RCP2. 6、RCP4. 5和RCP8. 5情景下全区分别偏高6. 00℃、5. 86℃和6. 42℃。年降水量分布呈东南向西北递减的形态,降水大值中心出现在东南部吉林与辽宁交界处,RCP2. 6、RCP4. 5和RCP8. 5情景下全区分别偏多15. 2%、3. 1%和2. 0%。     

1951～2007年南疆地区气温异常的时空变化特征

采用1951～2007年南疆地区站点月平均气温资料和NCAR/NCEP气候月平均资料,运用二项式系数加权平均法、Morlet小波变换等方法分析了南疆地区冬季和夏季气温的季节—年际气候变化特征,及气温异常的时空变化特征.结论如下:南疆地区冬季和夏季气温在气候态上差异明显,1980年代以前的冬季主要为气温负异常,1980年代以后呈现气温异常升高,到2000年以后又开始出现偏冷趋势;夏季气温偏差小于冬季,57 a间南疆夏季气温大致出现两波振荡,异常偏热期大致处于1950年代、1970年代后期和21世纪初,呈20～25 a振荡.冷冬年的频次多于暖冬年,热夏年的频次多于凉夏年.偏冷年在57a时间段内所占比例最多,气温异常低的幅度大于气温异常高的幅度.南疆冬季气温存在2个显著振荡:6～10 a的年际周期和18～20 a的年代际周期;夏季气温有1个最显著的振荡,稳定的20 a为中心的周期.不同的年代和季节气温及气温偏差分布各不相同.从气温长期演变趋势来看不论冬夏南疆北部(天山山脉以南)气温升高,塔里木盆地以及南疆南部地区气温降低.冬季升温区的升温幅度比夏季升温区大,夏季降温区的降温幅度比冬季降温区大.     

El Nio事件次年中国东部夏季气温分布特征研究

利用Had ISST和NCEP/NCAR再分析资料,采用统计学方法分析了1949年以来El Nio事件次年夏季中国东部气温分布特征。结果表明,混合型El Nio次年夏季,中国东部气温距平表现为山东—淮河流域及华南沿海出现负距平,其余地区为正距平;东部型,则表现为中国东部地区整体的负距平气温,且北方降温幅度明显大于长江以南地区;中部型,主要表现为长江以北气温负距平远大于长江以南。结合环流形势分析发现,三类El Nio事件次年夏季的赤道地区(5°S~5°N)异常纬向垂直环流均表现为三圈型,但3类异常Walker环流不仅强度有差异,纬向范围也有所不同。500 h Pa上西太平洋副高的强度和范围,是造成三类El Nio事件次年夏季中国东部地区气温距平分布差异的主要原因之一,850 h Pa上西南暖湿气流的输送对其也存在明显影响。     

长江三角洲近46a气温和降水的变化趋势

利用长江三角洲地区84个气象站观测数据,分析了长江三角洲1961—2006年气温和降水的时空变化趋势。结果表明,46a间长江三角洲地区年平均气温上升趋势显著,冬季平均气温的增温幅度最大,春、秋次之。增温显著区域与城市带分布区域吻合。极端最低气温有明显上升,而年极端低温事件日数的下降趋势显著。部分地区的极端最高气温呈上升趋势,在城市密集带尤为突出。年降水量没有明显的变化趋势,但降水的季节分配有所变化,冬、夏季降水量呈现显著上升趋势,秋季降水量明显下降,春季没有明显变化。     

长江三角洲近46 a气温和降水的变化趋势

利用长江三角洲地区84个气象站观测数据,分析了长江三角洲1961—2006年气温和降水的时空变化趋势。结果表明,46 a间长江三角洲地区年平均气温上升趋势显著,冬季平均气温的增温幅度最大,春、秋次之。增温显著区域与城市带分布区域吻合。极端最低气温有明显上升,而年极端低温事件日数的下降趋势显著。部分地区的极端最高气温呈上升趋势,在城市密集带尤为突出。年降水量没有明显的变化趋势,但降水的季节分配有所变化,冬、夏季降水量呈现显著上升趋势,秋季降水量明显下降,春季没有明显变化。     

CCSM4.0的长期积分试验及其对东亚和中国气候模拟的评估

本文利用通用气候系统模式CCSM4.0的低分辨率 (T31, 约3.75° × 3.75°) 版本进行了700年的长期积分试验, 将中国地表气温、降水及东亚海平面气压、500 hPa和100 hPa位势高度、850 hPa风场的最后100年模拟结果与观测和再分析资料进行了定性比较, 并对前三个要素的不同统计量值进行了定量计算, 系统评估了CCSM4.0对东亚及我国气候的模拟能力。结果表明, 模式能够合理模拟各变量的基本分布形态, 但幅度与观测有所差别, 其中地表气温的模拟效果最好, 降水的相对最差。具体而言, 地表气温空间分布型与观测一致, 但全年青藏高原地表气温模拟值偏高, 位于塔里木盆地的暖中心未能模拟出来; 降水空间分布型模拟较差, 除冬季不明显之外, 我国中南部全年都存在一个虚假降水中心, 并在夏季达到最强; 冬季东亚地区海陆热力对比大于观测, 夏季海平面气压场整体模拟效果不如冬季; 模式对冬、夏季500 hPa东亚大槽和西北太平洋副热带高压的主要特征刻画较好, 但模拟结果整体比观测偏强; 夏季100 hPa南亚高压强度与观测接近, 但高压范围及中心位置存在偏差; 850 hPa东亚冬季风和夏季风环流模拟较好, 但冬季西北气流偏强, 夏季索马里越赤道气流偏弱、我国东部西南气流偏强。总的来说, CCSM4.0对东亚和我国大尺度气候特征具备合理的模拟能力, 尽管在定量上还存在着不足。     

广东兴宁地区近46年气候变化特征

利用1961～2006年兴宁机场的逐日信息化资料,分析了兴宁地区46年来气温、降水变化特征。结果表明：兴宁地区年,冬、夏季平均温度以及最低、最高气温均呈明显上升趋势,平均增温率为0．015℃年;综合来看,20世纪60～90年代冬季增温幅度大于夏季,21世纪初夏季增温幅度高于冬季;年平均降水量为1488．9mm,季节性显著,其中夏季最多,占年平均降水量的45．4％,秋季降水量最少。降水量呈逐渐减少的趋势并不明显,其气候倾向率为-2．89mm／年。     

2009/2010年北半球冬季异常低温分析

分析了2009/2010年冬季(2009年12月1日至2010年2月28日,简称09/10年冬季)北半球地面气温异常特征及同期的水平与垂直环流场的异常结构。结果表明地面气温的异常呈现出带状的分布,表现为在低纬度为正异常、中纬度负异常及高纬度正异常的"正负正"的分布特征,最大的降温区在欧亚大陆和美国东部,其中局部的降温超过了-4℃。09/10年冬季北半球中纬度的地面气温相比过去15年冬季的平均值下降了近1℃,而在欧亚大陆的局部地区降温超过了-8℃。水平环流场的异常特征为:海平面气压和位势高度均表现为高纬度正异常而中纬度负异常的"北高南低"的分布特征,与此同时,中纬度出现气旋式的异常环流而高纬出现反气旋式的异常环流,这种分布形势在高低层表现得较为一致。经圈环流异常特征为:费雷尔环流减弱,中纬度出现异常的上升运动而高纬度出现异常的下沉运动,与此同时,中纬度对流层气温降低,而低纬度和高纬度的对流层气温升高,副热带急流增强,而极地急流减弱。09/10年冬季北半球环流的异常特征与北半球环状模(NAM)负位相时的极为相似。对多年冬季北半球地面气温和NAM指数进行合成和相关分析,结果表明当NAM处于正(负)位相时,北半球中纬度地面气温出现正(负)异常带,并且在欧亚大陆和美国东部最为显著,局部升温(降温)的幅度达到2℃。在热带外地区,经向温度平流是控制温度局地变化的关键因子。NAM影响北半球地面气温的物理机制分析表明,NAM主要是通过影响经向温度平流来影响北半球中纬度气温的。当NAM为正位相时,北半球费雷尔环流加强,中纬度带和高纬度带发生大气质量的交换,海平面气压场表现为中纬度异常高压而高纬度异常低压的"南高北低"的分布特征,中纬度地表出现异常的南风,进而经向暖平流加强,最终导致中纬度地面气温升高,NAM负位相年时与之相反。这个结果揭示了NAM作为自然变率对中纬度地面气温的调控作用。     

中国气温异常的区域特征研究

用REOF法对中国的年和春、夏、秋、冬季平均气温年际变化进行了分区,并研究了各区气温的变化趋势。结果表明,中国年平均气温可分为8个变化区,春季7区,夏季9区,秋季7区,冬季5区。从年平均气温看,近46a来中国的主要升温区为东北、华北北部和新疆自治区,升温幅度为1．2℃左右。降温区为四川、贵州,幅度为0．3～0．4℃。东南部、西北东部、西藏和云南地区1970年代初以前降温,以后升温,与北半球气温变化一致。各季节升降温区与年平均有一定的差异。升温区范围和升温幅度最大的为冬季。降温主要集中在春季西部、华南地区和夏季长江流域和新疆南部。降温幅度最大的为夏季。秋冬季全国则无降温趋势。     

A regional climate model downscaling projection of China future climate change

Climate changes over China from the present (1990–1999) to future (2046–2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility.     

不同热盐环流平均强度下北大西洋气候响应的差异

基于美国大气研究中心的CCSM3（Community Climate System Model version3）模式,对淡水扰动试验中不同热盐环流（thermohline circulation,THC）平均强度下,北大西洋气候响应的差异进行研究。结果表明：1）在不同平均强度下,北大西洋海洋、大气要素的气候态差异显著。相对于高平均强度,在低平均强度下,北大西洋地区海表温度（sea surface temperature,SST）、海表盐度（sea surface salinity,SSS）、海表密度（sea surface density,SSD）、表面气温（surface air temperature）异常减弱,最大负异常位于GIN（Greenland sea--Iceland sea--Norwegiansea）海域;海平面气压（sealev—elpressure,SLP）异常升高,相应于北大西洋海域降温,表现为异常冷性高压的响应特征;海冰分布区域向南扩大;北大西洋西部热带海域降水减少,导致热带辐合带（intertropical convergence zone,ITCZ）南移。2）在不同THC平均强度下,SST、SSS和SSD年际异常最显著的区域不同;在高平均强度下,最显著区域位于GIN海域,而在低平均强度下则位于拉布拉多海海域。3）在高平均强度下,北大西洋SST主导变率模态的变率极大区域位于GIN海,而在低平均强度下该极大区域不存在;北大西洋SLP的主导变率模态表现为类NAO型,但在高平均强度下,类NAO型表现得更明显。     

不同大西洋经圈翻转环流平均强度下中国气候的年代际响应特征

基于美国大气研究中心的CCSM3(Community Climate System Model version 3)模式,对淡水扰动试验中不同大西洋经圈翻转环流(Atlantic Meridional Overturning Circulation,AMOC)平均强度下,中国气候的年代际响应特征进行研究。结果表明:在年代际尺度上,中国区域地表气温和降水强度变化与AMOC强度变化的关系紧密,然而,不同平均强度下,中国气候的年代际响应特征不同。高平均强度下,中国区域地表气温升高,中国北部降水增多、南部降水减少;低平均强度下,则反之。不同平均强度下,中国区域年平均地表气温和降水EOF第一特征向量的空间分布存在显著差异:高平均强度下,地表气温呈现中国全区域一致的分布型,降水呈现自北向南的"-+-"型的雨带分布;低平均强度下,地表气温呈现中国区域南北反相的偶极子分布型,降水呈现自北向南的"-+"型的雨带分布。与低平均强度相比,在高平均强度下,EOF第一模态的时间系数的年代际变化尺度均更长。     

Evaluation of a WRF dynamical downscaling simulation over California

This paper presents results from a 40 year Weather Research and Forecasting (WRF) based dynamical downscaling experiment performed at 12 km horizontal grid spacing, centered on the state of California, and forced by a 1° × 1.25° finite-volume current-climate Community Climate System Model ver. 3 (CCSM3) simulation. In-depth comparisons between modeled and observed regional-average precipitation, 2 m temperature, and snowpack are performed. The regional model reproduces the spatial distribution of precipitation quite well, but substantially overestimates rainfall along windward slopes. This is due to strong overprediction of precipitation intensity; precipitation frequency is actually underpredicted by the model. Moisture fluxes impinging on the coast seem to be well-represented over California, implying that precipitation bias is caused by processes internal to WRF. Positive-definite moisture advection and use of the Grell cumulus parameterization result in some decrease in precipitation bias, but other sources are needed to explain the full bias magnitude. Surface temperature is well simulated in all seasons except summer, when overly-dry soil moisture results in a several degree warm bias in both CCSM3 and WRF. Additionally, coastal temperatures appear to be too warm due to a coastal sea surface temperature bias inherited from CCSM3. Modeled snowfall/snowmelt agrees quite well with observations, but snow water equivalent is found to be much too low due to monthly reinitialization of all regional model fields from CCSM3 values.     

Projected Changes in Surface Air Temperature and Surface Wind in the Gulf of St. Lawrence

Abstract

The impacts of climate change on surface air temperature (SAT) and winds in the Gulf of St. Lawrence (GSL) are investigated by performing simulations from 1970 to 2099 with the Canadian Regional Climate Model (CRCM), driven by a five-member ensemble. Three members are from Canadian Global Climate Model (CGCM3) simulations following scenario A1B from the Intergovernmental Panel on Climate Change (IPCC); one member is from the Community Climate System Model, version 3 (CCSM3) simulation, also following the A1B scenario; and one member is from the CCSM4 (version 4) simulation following the Representative Concentration Pathway (RCP8.5) scenario. Compared with North America Regional Reanalysis (NARR) data, it is shown that CRCM can reproduce the observed SAT spatial patterns; for example, both CRCM simulations and NARR data show a warm SAT tongue along the eastern Gulf; CRCM simulations also capture the dominant northwesterly winds in January and the southwesterly winds in July. In terms of future climate scenarios, the spatial patterns of SAT show plausible seasonal variations. In January, the warming is 3°–3.5°C in the northern Gulf and 2.5°–3°C near Cabot Strait during 2040–2069, whereas the warming is more uniform during 2070–2099, with SAT increases of 4°–5°C. In summer, the warming gradually decreases from the western side of the GSL to the eastern side because of the different heat capacities between land and water. Moreover, the January winds increase by 0.2–0.4?m?s^?1 during 2040–2069, related to weakening stability in the atmospheric planetary boundary layer. However, during 2070–2099, the winds decrease by 0.2–0.4?m?s^?1 over the western Gulf, reflecting the northeastward shift in northwest Atlantic storm tracks. In July, enhanced baroclinicity along the east coast of North America dominates the wind changes, with increases of 0.2–0.4?m?s^?1. On average, the variance for the SAT changes is about 10% of the SAT increase, and the variance for projected wind changes is the same magnitude as the projected changes, suggesting uncertainty in the latter.     

CCSM4.0模式及其驱动下RegCM4.4模式对中国夏季气候的回报分析

使用区域气候模式Reg CM4.4(Regional Climate Model version 4.4)单向嵌套CCSM4.0(Community Climate System Model version 4.0)气候系统模式输出结果,进行了2001~2010年逐年2月1日至9月1日共10年长度的季节尺度气候预测回报试验,针对平均气温和降水,分析了两个模式对中国地区夏季(6~8月)气候的回报能力。首先对气候态的分析表明,Reg CM4.4对气温和降水的回报/模拟效果均较CCSM4.0有所改进,特别是在提供更详细可靠的局地信息方面,其中降水回报与观测的空间相关系数,由CCSM4.0的0.39提高到Reg CM4.4的0.53,但同时Reg CM4.4对中国东部季风降水的回报表现出类似CCSM4.0北方偏多的偏差。对两个模式2001~2010年逐年气温和降水距平的回报能力,通过回报与观测空间和时间距平相关系数(ACCs和ACCt)、回报与观测空间和时间距平符号一致率(PCs和PCt)以及趋势异常综合评分(PS)进行了考察,结果表明两个模式的表现在整体分布上有一定相似的同时,Reg CM4.4能够提供更多的空间分布细节,并对降水的回报结果有一定的改善,如CCSM4.0和Reg CM4.4回报降水的ACCs多年平均分别为0.03和0.10,PS分别为70.4和71.4。同时给出了两个具体年份(2003年和2009年)的个例分析。     

Future changes and uncertainties in temperature and precipitation over China based on CMIP5 models

Climate changes in future 21 st century China and their uncertainties are evaluated based on 22 climate models from the Coupled Model Intercomparison Project Phase 5(CMIP5). By 2081–2100, the annual mean surface air temperature(SAT) is predicted to increase by 1.3℃± 0.7℃, 2.6℃± 0.8℃ and 5.2℃± 1.2℃ under the Representative Concentration Pathway(RCP) scenarios RCP2.6, RCP4.5 and RCP8.5, relative to 1986–2005, respectively. The future change in SAT averaged over China increases the most in autumn/winter and the least in spring, while the uncertainty shows little seasonal variation.Spatially, the annual and seasonal mean SAT both show a homogeneous warming pattern across China, with a warming rate increasing from southeastern China to the Tibetan Plateau and northern China, invariant with time and emissions scenario.The associated uncertainty in SAT decreases from northern to southern China. Meanwhile, by 2081–2100, the annual mean precipitation increases by 5% ± 5%, 8% ± 6% and 12% ± 8% under RCP2.6, RCP4.5 and RCP8.5, respectively. The national average precipitation anomaly percentage, largest in spring and smallest in winter, and its uncertainty, largest in winter and smallest in autumn, show visible seasonal variations. Although at a low confidence level, a homogeneous wetting pattern is projected across China on the annual mean scale, with a larger increasing percentage in northern China and a weak drying in southern China in the early 21 st century. The associated uncertainty is also generally larger in northern China and smaller in southwestern China. In addition, both SAT and precipitation usually show larger seasonal variability on the sub-regional scale compared with the national average.     

Estimation of the economic impact of temperature changes induced by a shutdown of the thermohaline circulation: an application of <Emphasis Type="Italic">FUND</Emphasis>

The integrated assessment model FUND 2.8n is applied in an assessment to estimate the magnitude of the general market and non-market impacts of temperature changes caused by a possible shutdown of the thermohaline circulation (THC). The monetized impacts of this change in environmental conditions are determined for 207 individual countries for two scenarios: one warming scenario in which the THC weakens but remains intact, and another in which the THC breaks down. Eight different response patterns are identified. The dominant pattern is that a THC shutdown has an offsetting effect on the underlying warming trend. Depending on whether the impacts of warming are initially beneficial or detrimental, the economic effects of a THC shutdown show distinct regional variability. Key economic sectors affected are water resources and energy consumption, as well as cardiovascular and respiratory diseases among health impacts. The maximum national impact of a shutdown of the THC turns out to be of the magnitude of a few per cent of GDP, but the average global impact is much smaller. The results indicate that the temperature effect of a THC shutdown does not create an insurmountable economic threat on a global scale, but may cause severe damages to individual countries. However, a consideration of other climatic impacts such as precipitation and sea level changes is likely to alter the identified trends in economic development.     

青藏高原与中国其他地区气候突变时间的比较

基于1961～2006年中国地面观测气温和降水资料,对青藏高原地区以及中国其他6个地区地表气温、降水的变化趋势和突变时间进行了检测和比较。结果发现,(1)地表气温:1961～2006年青藏高原地区年和四季的地表气温都呈增加趋势。年平均地表气温在20世纪80年代中期开始变暖,但显著快速增暖的突变发生在90年代中期,该时间比东北、华北、西北和淮河地区晚,与长江中下游和华南地区接近,不同季节青藏高原地区与其他地区变暖突变时间的差别也各有不同,但所有季节快速变暖突变的时间都比东北地区晚,中国东部陆地地区年和冬季平均地表气温表现出北早南晚的经向差异;(2)降水:1961～2006年青藏高原地区年降水量没有检测到显著的变化趋势,冬春降水量显著增加,而夏季降水有微弱的减少,秋季降水显著减少。降水突变的信号明显比温度突变的信号弱,年降水量和春季降水都没有检测到突变的发生,降水突变方向(增或减)和突变时间在区域与区域之间以及不同季节之间都存在较大差异。由上可见,青藏高原气候的显著快速变化比中国东部长江以北地区有明显的滞后现象,尤其是冬春温度变化,这可能是由于青藏高原地区积雪增加导致的反照率增加和冰川融化吸热对青藏高原变暖的减弱作用所致。     

Influence of SST biases on future climate change projections

We use a quantile-based bias correction technique and a multi-member ensemble of the atmospheric component of NCAR CCSM3 (CAM3) simulations to investigate the influence of sea surface temperature (SST) biases on future climate change projections. The simulations, which cover 1977?C1999 in the historical period and 2077?C2099 in the future (A1B) period, use the CCSM3-generated SSTs as prescribed boundary conditions. Bias correction is applied to the monthly time-series of SSTs so that the simulated changes in SST mean and variability are preserved. Our comparison of CAM3 simulations with and without SST correction shows that the SST biases affect the precipitation distribution in CAM3 over many regions by introducing errors in atmospheric moisture content and upper-level (lower-level) divergence (convergence). Also, bias correction leads to significantly different precipitation and surface temperature changes over many oceanic and terrestrial regions (predominantly in the tropics) in response to the future anthropogenic increases in greenhouse forcing. The differences in the precipitation response from SST bias correction occur both in the mean and the percent change, and are independent of the ocean?Catmosphere coupling. Many of these differences are comparable to or larger than the spread of future precipitation changes across the CMIP3 ensemble. Such biases can affect the simulated terrestrial feedbacks and thermohaline circulations in coupled climate model integrations through changes in the hydrological cycle and ocean salinity. Moreover, biases in CCSM3-generated SSTs are generally similar to the biases in CMIP3 ensemble mean SSTs, suggesting that other GCMs may display a similar sensitivity of projected climate change to SST errors. These results help to quantify the influence of climate model biases on the simulated climate change, and therefore should inform the effort to further develop approaches for reliable climate change projection.