2℃全球变暖背景下中国未来气候变化预估

相对于工业化革命前期, 全球年平均地表气温上升2℃的时间和相应的气候变化受到了广泛关注, 特别是包括欧盟成员国在内的许多国家和国际组织已经将避免2℃全球变暖作为温室气体减排的首要目标。为此, 本文作者基于16个气候模式在20世纪气候模拟试验和SRES B1、A1B和A2温室气体和气溶胶排放情景下的数值模拟试验结果, 采用多模式集合方法预估研究了2℃全球变暖发生的时间、对应的大气中主要温室气体浓度以及中国气候变化情况。根据模式集合平均结果, 三种排放情景下2℃全球变暖分别发生在2064年、2046年和2049年, 大气二氧化碳当量浓度分别为625 ppm、645 ppm和669 ppm (1 ppm=10-6)。对应着2℃全球变暖, 中国气候变暖幅度明显更大。从空间分布形势上看, 变暖从南向北加强, 在青藏高原地区存在一个升温大值区; 就整体而言, 中国区域平均的年平均地表气温上升2.7～2.9℃, 冬季升温幅度 (3.1～3.2℃) 要较其他季节更大。年平均降水量在华南大部分地区减少0～5%, 而在其余地区增加0～20%, 中国区域年平均降水增加3.4%～4.4%, 各季节增加量在0.5%～6.6%之间。     

Climate Change of 4°C Global Warming above Pre-industrial Levels

Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4°C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4°C global warming will occur is 2084. Based on the median results of models that project a 4°C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-to-noise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5°C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the inter-model consistency is better for temperature than for precipitation.     

On the Response of the Global Subduction Rate to Global Warming in Coupled Climate Models简

The response of the global subduction rate to global warming was assessed based on a set of Intergovernmental Panel on Climate Change （IPCC） Fourth Assessment Report （AR4） models. It was found that the subduction rate of the global ocean could be significantly reduced under a warming climate, as compared to a simulation of the present-day climate. The reduction in the subduction volume was quantitatively estimated at about 40 Sv and was found to be= primarily induced by the decreasing of the lateral induction term due to a shallower winter mixed layer depth. The shrinking of the winter mixed layer would result from intensified stratification caused by increased heat input into the ocean under a warming climate. A reduction in subduction associated with the vertical pumping term was estimated at about 5 Sv. F~rther, in the Southern Ocean, a significant reduction in subduction was estimated at around 24 Sv, indicating a substantial contribution to the weakening of global subduction.     

Detection, Causes and Projection of Climate Change over China： An Overview of Recent Progress

This article summarizes the main results and findings of studies conducted by Chinese scientists in the past five years.It is shown that observed climate change in China bears a strong similarity with the global average.The country-averaged annual mean surface air temperature has increased by 1.1℃over the past 50 years and 0.5-0.8℃over the past 100 years,slightly higher than the global temperature increase for the same periods.Northern China and winter have experienced the greatest increases in surface air temperature.Although no significant trend has been found in country-averaged annual precipitation, interdecadal variability and obvious trends on regional scales are detectable,with northwestern China and the mid and lower Yangtze River basin having undergone an obvious increase,and North China a severe drought.Some analyses show that frequency and magnitude of extreme weather and climate events have also undergone significant changes in the past 50 years or so. Studies of the causes of regional climate change through the use of climate models and consideration of various forcings,show that the warming of the last 50 years could possibly be attributed to an increased atmospheric concentration of greenhouse gases,while the temperature change of the first half of the 20th century may be due to solar activity,volcanic eruptions and sea surface temperature change.A significant decline in sunshine duration and solar radiation at the surface in eastern China has been attributed to the increased emission of pollutants. Projections of future climate by models of the NCC(National Climate Center,China Meteorological Administration)and the IAP(Institute of Atmospheric Physics,Chinese Academy of Sciences),as well as 40 models developed overseas,indicate a potential significant warming in China in the 21st century,with the largest warming set to occur in winter months and in northern China.Under varied emission scenarios,the country-averaged annual mean temperature is projected to increase by 1.5-2.1℃by 2020,2.3-3.3℃by 2050, and by 3.9-6.0℃by 2100,in comparison to the 30-year average of 1961 1990.Most models project a 10% 12% increase in annual precipitation in China by 2100,with the trend being particularly evident in Northeast and Northwest China,but with parts of central China probably undergoing a drying trend.Large uncertainty exists in the projection of precipitation,and further studies are needed.Furthermore,anthropogenic climate change will probably lead to a weaker winter monsoon and a stronger summer monsoon in eastern Asia.     

Future Changes in Extreme High Temperature over China at 1.5℃-5℃ Global Warming Based on CMIP6 Simulations

Extreme high temperature(EHT)events are among the most impact-related consequences related to climate change,especially for China,a nation with a large population that is vulnerable to the climate warming.Based on the latest Coupled Model Intercomparison Project Phase 6(CMIP6),this study assesses future EHT changes across China at five specific global warming thresholds(1.5℃-5℃).The results indicate that global mean temperature will increase by 1.5℃/2℃ before 2030/2050 relative to pre-industrial levels(1861-1900)under three future scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5),and warming will occur faster under SSP5-8.5 compared to SSP1-2.6 and SSP2-4.5.Under SSP5-8.5,global warming will eventually exceed 5℃ by 2100,while under SSP1-2.6,it will stabilize around 2℃ after 2050.In China,most of the areas where warming exceeds global average levels will be located in Tibet and northern China(Northwest China,North China and Northeast China),covering 50%-70%of the country.Furthermore,about 0.19-0.44 billion people(accounting for 16%-41%of the national population)will experience warming above the global average.Compared to present-day(1995-2014),the warmest day(TXx)will increase most notably in northern China,while the number of warm days(TX90p)and warm spell duration indicator(WSDI)will increase most profoundly in southern China.For example,relative to the present-day,TXx will increase by 1℃-5℃ in northern China,and TX90p(WSDI)will increase by 25-150(10-80)days in southern China at 1.5℃-5℃ global warming.Compared to 2℃-5℃,limiting global warming to 1.5℃ will help avoid about 36%-87%of the EHT increases in China.     

全球变暖1.5℃和2℃阈值时青藏高原气温的变化特征

利用国际耦合模式比较计划第5阶段（CMIP5）中的21个气候模式的RCP4.5和RCP8.5情景预估结果,分析了全球变暖1.5℃和2℃阈值时青藏高原气温年和季节的变化特征。结果表明,对应1.5℃和2℃全球变暖,青藏高原变暖幅度明显更大,就整体而言,在RCP4.5/RCP8.5情景下,高原区域平均的平均、最高、最低气温变暖分别为2.11℃/2.10℃和2.96℃/2.85℃、2.02℃/2.02℃和2.89℃/2.77℃、2.34℃/2.34℃和3.20℃/3.14℃,冬季平均气温的变暖幅度（2.19℃/2.31℃和3.13℃/3.05℃）较其他季节更大;从空间分布形势上看,年变暖呈西南高东北低的分布,而春、冬变暖呈南高北低的分布,夏、秋变暖则呈西高东低的分布。到达同一温升阈值时,RCP4.5与RCP8.5情景下高原气温的响应也存在区域差异。高原年与各季平均气温对全球变暖1.5℃与2℃的响应差异均>0.5℃,其中冬季最明显,区域平均差异可达0.94℃,局地差异超过1.1℃。     

Projections of 2.0°C Warming over the Globe and China under RCP4.5

The outputs of 17 models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) are employed to investigate the temporal and spatial features of 2.0°C warming of the surface temperature over the globe and China under the Representative Concentration Pathways (RCP) 4.5 scenario. The simulations of the period 1860-1899 in the "historical" experiment are chosen as the baseline. The simulations for the 21st century in the RCP4.5 experiment are chosen as the future project. The multi-model ensemble mean (MME) shows that the global mean temperature would cross the 2.0°C warming threshold in 2047. Warming in most of the models would cross the threshold during 2030-2060. For local warming, high-latitude areas in the Northern Hemisphere show the fastest warming over the globe. Land areas warm substantially faster than the oceans. Most of the southern oceans would not exceed the 2.0°C warming threshold within the 21st century. Over China, surface warming is substantially faster than the global mean. The area-averaged warming would cross the 2.0°C threshold in 2034. Locally, Northwest China shows the fastest warming trend, followed by Central North China and Northeast China. Central China, East China, and South China are the last to cross the 2.0°C warming threshold. The diversity of the models is also estimated in this study. Generally, the spread among the models increases with time, and there is smaller spread among the models for the areas with the faster warming.     

The Impact of Global Warming on the Pacific Decadal Oscillation and the Possible Mechanism简

The response of the Pacific Decadal Oscillation （PDO） to global warming according to the Fast Ocean Atmosphere Model （FOAM） and global warming comparison experiments of 11 IPCC AR4 models is investigated. The results show that North Pacific ocean decadal variability, its dominant mode （i.e., PDO）, and atmospheric decadal variability, have become weaker under global warming, but with PDO shifting to a higher frequency. The SST decadal variability reduction maximum is shown to be in the subpolar North Pacific Ocean and western North Pacific （PDO center）. The atmospheric decadal variability reduction maximum is over the PDO center. It was also found that oceanic baroclinic Rossby waves play a key role in PDO dynamics, especially those in the subpolar ocean. As the frequency of ocean buoyancy increases under a warmer climate, oceanic baroclinic Rossby waves become faster, and the increase in their speed ratio in the high latitudes is much larger than in the low latitudes. The faster baroclinic Rossby waves can cause the PDO to shift to a higher frequency, and North Pacific decadal variability and PDO to become weaker.     

全球增温1.5和2℃下中国东部极端高温风险预估

2013年中国中东部地区经历了一次破纪录的极端高温,给社会经济及人民财产造成了严重损失。利用高分辨率的观测格点数据集以及参与CMIP5的17个全球气候模式数据,通过分位数映射的偏差订正方法对模式模拟的逐日最高温度数据进行订正;在此基础上,研究了2013年的破纪录极端高温以及多年（20、50和100 a）一遇极端高温在未来全球增温1.5和2℃下的风险。结果表明,在未来增温1.5℃（2℃）下,2013年极端高温强度的发生风险将会增加为历史时期（1986-2005年）的3.0倍（6.1倍）,极端高温日数增加为历史时期的5.6倍（12.6倍）。从1.5℃到2℃,额外的0.5℃的增温将会使2013年极端高温强度和日数在未来的发生风险分别增加到2.0倍和2.3倍。对于不同重现期的极端高温来说,越极端的极端高温在未来发生的风险越大,并且极端高温日数增加的风险要大于极端高温强度增加的风险。历史时期平均每20、50、100 a发生一次的极端高温日数在未来增温1.5℃下将会变为平均每4、8、15 a发生一次,在增温2℃下变为平均每2、3、6 a发生一次。历史时期20、50、100 a一遇的极端高温强度在未来增温1.5℃下将会变为7、14、27 a一遇,在未来增温2℃下变为4、6、8 a一遇。     

1.5和2℃升温阈值下中国温度和降水变化的预估

基于CMIP5耦合气候模式模拟结果对1.5和2℃升温阈值时中国温度和降水变化的分析表明,1.5℃升温阈值时,中国年平均升温由南向北加强且在青藏高原地区有所放大,季节尺度上升温的空间分布与其类似,就区域平均而言,RCP2.6、RCP4.5和RCP8.5情景下中国年平均气温分别升高1.83、1.75和1.88℃,气温的季节变幅以冬季升高最为显著;除华南和西南地区外中国大部分地区年平均降水量增多,降水的季节差异明显,以夏季降水的分布模态与年平均降水量的分布最为相似,区域平均的年降水量分别增加5.03%、2.82%和3.27%,季节尺度上以冬季降水增幅最大。2℃升温阈值时,RCP4.5和RCP8.5情景下中国年平均温度的空间分布与1.5℃升温阈值基本一致,中国年平均气温分别升高2.49和2.54℃,季节尺度上气温的变化以秋、冬季增幅最大;中国范围内年平均降水量基本表现为增多趋势,其中,西北和长江中下游部分地区表现为明显的季节差异,区域平均的年降水量分别增加6.26%和5.86%。与1.5℃升温阈值相比较,2℃升温阈值时中国年平均温度在RCP4.5和RCP8.5情景下分别升高0.74和0.76℃,降水则分别增加3.44%和2.59%,空间上温度升高以东北、西北和青藏高原最为显著,降水则在东北、华北、青藏高原和华南地区增加最为明显。      

结合模式性能和独立性加权的全球增暖1.5/2℃下中国区域气候的未来预估

基于耦合模式比较计划第6阶段(CMIP6)中的全球气候模式的模拟结果,采用考虑模式性能和独立性结合(Climate model Weighting by Independence and Performance,ClimWIP)的加权方案进行中国区域气候的多模式集合预估及不确定性研究。结果表明,ClimWIP方案在历史阶段的模拟优于等权重方案,降低了多模式模拟的气候态偏差。温度指数的未来预估不确定性较大的区域主要集中在中国北方和青藏高原,而降水指数主要集中在华北和西北地区。ClimWIP方案的预估不确定性与等权重方案相比有所降低。ClimWIP方案预估的温度指数的增温大值区主要集中在中国北方和青藏高原;降水指数在西北和青藏高原增加最为显著。全球额外0.5 ℃增暖时,中国区域平均的温度指数变化更强,平均高于全球0.2 ℃,最低温在东北部分地区的额外增温甚至是全球平均的3倍;总降水额外增加5.2％;强降水额外增加10.5％。全球增暖2 ℃下,中国大部分区域温度指数较当前气候态增加可能超过1.5 ℃(概率>50％),在中国北方和青藏高原的部分地区增温超过1.5 ℃的可能性更大(概率>90％);总降水,强降水和连续干日在西北和华北增加幅度有可能超过10％、25％和-5 d(概率>50％)。     

Multi-Model Ensemble Projection of Precipitation Changes over China under Global Warming of 1.5 and 2℃with Consideration of Model Performance and Independence

A weighting scheme jointly considering model performance and independence(PI-based weighting scheme)is em-ployed to deal with multi-model ensemble prediction of...     

1.5°C与2°C温升目标下“一带一路”主要陆域气温和降水变化的CMIP6多模式预估

基于CMIP6的16个全球模式试验数据,多模式集合预估了《巴黎协定》1.5°C/2°C温升目标下“一带一路”倡议的主要陆域未来气温和降水变化。与观测相比较,多模式集合能够比较准确地刻画“一带一路”主要陆域1995～2014年气温和降水的空间结构特征。在SSP2-4.5、SSP3-7.0和SSP5-8.5三种不同路径情景下,相对于工业革命前（1850～1900年）,全球升温1.5°C与2°C分别将发生在2020年代中后期与2040年左右。全球1.5°C与2°C温升目标下,预计“一带一路”陆域平均的气温分别显著升高1.84°C和2.43°C,两者相差0.59°C,模式间标准差分别为0.18°C和0.21°C;区域平均的降水分别显著增加20.14 mm/a和30.02 mm/a,相差9.88 mm/a,模式间标准差分别为10.79 mm/a和13.72 mm/a。两种温升目标下,“一带一路”主要陆域气温空间上均表现为一致性显著增暖,高纬度的增温幅度普遍比低纬度大;降水变化具有明显的空间差异性,地中海与黑海地区、中国南部至中南半岛地区减少,其他地区的降水普遍增加。P-E指数表征的干旱化未来在欧洲地区、中国南部至中南半岛地区、南亚印度东部地区、东南亚和赤道非洲中部地区达到最大。     

CMIP5模式对辽宁省气温模拟能力及未来2℃升温阈值出现时间评估

利用全球气候模式、多模式集合和辽宁省气象观测数据,评估了不同典型浓度路径下19个全球气候模式和多模式集合对辽宁省气温变化模拟能力和可信度。结果表明:最优模式模拟结果优于多模式集合,具有较高的可信度。随着全球二氧化碳排放浓度增加,气温变化率和可信度呈增加趋势,首次达到2℃年份呈提前趋势,大部分站点出现在2011年之前,且出现年份越晚,升幅往往越高,反之亦然。大部分站点首次稳定到达2℃阈值开始年份在2022年之前,结束年份出现在2019—2026年,持续时间在13 a以下,开始年份均呈西早—东晚分布形势,结束时间和持续时间分布较均匀,且随着全球二氧化碳排放浓度增加,升温幅度呈上升趋势。不同典型浓度路径下各区域最高温、最低温和平均气温出现年份和变化特征均比较一致。     

Why Does FGOALS-gl Reproduce But a Reasonable Little Ice Age a Weak Medieval Warm Period and 20th Century Warming？

To understand the strengths and limitations of a low-resolution version of Flexible Global Ocean Atmosphere-Land-Sea-ice （FGOALS-gl） to simulate the climate of the last millennium, the energy balance, climate sensitivity and absorption feedback of the model are analyzed. Simulation of last-millennium climate was carried out by driving the model with natural （solar radiation and volcanic eruptions） and anthropogenic （greenhouse gases and aerosols） forcing agents. The model feedback factors for （model sensitivity to） different forcings were calculated. The results show that the system feedback factor is about 2.5 （W m-2） K-1 in the pre-industrial period, while 1.9 （W m-2） K-1 in the industrial era. Thus, the model＇s sensitivity to natural forcing is weak, which explains why it reproduces a weak Medieval Warm Period. The relatively reasonable simulation of the Little Ice Age is caused by both the specified radiative forcing and unforced linear cold drift. The model sensitivity in the industrial era is higher than that of the pre-industrial period. A negative net cloud radiative feedback operates during whole-millennial simulation and reduces the model＇s sensitivity to specified forcing. The negative net cloud radiative forcing feedback under natural forcing in the period prior to 1850 is due to the underestimation （overestimation） of the response of cloudiness （in-cloud water path）. In the industrial era, the strong tropospheric temperature response enlarges the effective radius of ice clouds and reduces the fractional ice content within cloud, resulting in a weak negative net cloud feedback in the industrial period. The water vapor feedback in the industrial era is also stronger than that in the pre-industrial period. Both are in favor of higher model sensitivity and thus a reasonable simulation of the 20th century global warming.     

Changes in Extreme Maximum Temperature Events and Population Exposure in China under Global Warming Scenarios of 1.5 and 2.0°C: Analysis Using the Regional Climate Model COSMO-CLM

We used daily maximum temperature data (1986–2100) from the COSMO-CLM (COnsortium for Small-scale MOdeling in CLimate Mode) regional climate model and the population statistics for China in 2010 to determine the frequency, intensity, coverage, and population exposure of extreme maximum temperature events (EMTEs) with the intensity–area–duration method. Between 1986 and 2005 (reference period), the frequency, intensity, and coverage of EMTEs are 1330–1680 times yr^–1, 31.4–33.3°C, and 1.76–3.88 million km², respectively. The center of the most severe EMTEs is located in central China and 179.5–392.8 million people are exposed to EMTEs annually. Relative to 1986–2005, the frequency, intensity, and coverage of EMTEs increase by 1.13–6.84, 0.32–1.50, and 15.98%–30.68%, respectively, under 1.5°C warming; under 2.0°C warming, the increases are 1.73–12.48, 0.64–2.76, and 31.96%–50.00%, respectively. It is possible that both the intensity and coverage of future EMTEs could exceed the most severe EMTEs currently observed. Two new centers of EMTEs are projected to develop under 1.5°C warming, one in North China and the other in Southwest China. Under 2.0°C warming, a fourth EMTE center is projected to develop in Northwest China. Under 1.5 and 2.0°C warming, population exposure is projected to increase by 23.2%–39.2% and 26.6%–48%, respectively. From a regional perspective, population exposure is expected to increase most rapidly in Southwest China. A greater proportion of the population in North, Northeast, and Northwest China will be exposed to EMTEs under 2.0°C warming. The results show that a warming world will lead to increases in the intensity, frequency, and coverage of EMTEs. Warming of 2.0°C will lead to both more severe EMTEs and the exposure of more people to EMTEs. Given the probability of the increased occurrence of more severe EMTEs than in the past, it is vitally important to China that the global temperature increase is limited within 1.5°C.     

基于CMIP5耦合气候模式的1.5℃和2℃升温阈值出现时间研究

利用CMIP5耦合气候模式的模拟结果,分析了不同排放情景下1.5℃和2℃升温阈值出现的时间。多模式集合平均结果表明：RCP2.6、RCP4.5和RCP8.5排放情景下,全球地表温度将分别在2029年、2028年和2025年达到1.5℃升温阈值;RCP2.6情景下直至21世纪末期都未达到2℃升温阈值,RCP4.5和RCP8.5排放情景下达到2℃升温阈值的时间分别为2048年和2040年。伴随着排放情景的升高,完成从1.5℃升温阈值到2℃升温阈值所需要的时间缩短。区域尺度上,达到同一升温阈值的时间主要表现为陆地比海洋早,且陆地对排放情景差异的敏感性相对较差,而海洋达到升温阈值的时间则随着排放情景的升高而明显提前。中国达到相应升温阈值的时间要早于全球,且以东北和西北地区出现的时间最早。     

Mesoscale Analysis of a Heavy Rainfall Event over Hong Kong During a Pre-rainy Season in South China

During the Heavy Rainfall Experiment in South China （HUAMEX） of 1998, a record heavy rainfall event occurred in the delta of the Pearl River during the 24 hours from 1200 UTC 8 June to 1200 UTC 9 June, 1998, and a 24-hour precipitation maximum of 574 mm was reported in Hong Kong. In this paper, some mesoscale characteristics of this heavy rainfall event are studied using data from satellites, Doppler radar, wind profilers, and automatic meteorological stations collected during HUAMEX. The following conclusions are drawn： （1） During this heavy rainfall event, there existed a favorable large-scale environment, that included a front with weak baroclinity in the heavy rain area and with an upward motion branch ahead of the front. （2） Unlike most extratropical or subtropical systems, the closed low in the geopotential height field does not exited. The obvious feature was that a southerly branch trough in the westerlies existed and Hong Kong was located ahead of the trough. （3） The rainfall areas were located in the warm sector ahead of the front, rather than in the frontal zone, which is one of the characteristics of heavy rainfalls during the pre-rainy season of South China. A southerly warm and moist current contributed to the heavy rainfall formation, including the transportation of rich water vapor and the creation of strong horizontal wind convergence. （4） The observations show that the heavy rainfall in Hong Kong was directly caused by a series of meso β systems rather than a mesoscale convective complex （MCC）. These meso β systems moved with the steering current in the lower-mid troposphere, their life cycles were 3-6 hours, and their horizontal sizes were 10-100 km. （5） The disturbances in the lower and mid troposphere, especially that in the planetary boundary layer （PBL） were very shallow. However, they are a possible trigger mechanism for the occurrence and development of the mesoscale convective systems and related heavy rainfalls. Finally, a conceptual model of the heav     

Multi-Model Projection of July–August Climate Extreme Changes over China under CO_2 Doubling. Part II: Temperature

This is the second part of the authors’ analysis on the output of 24 coupled climate models from the Twentieth-Century Climate in Coupled Models (20C3M) experiment and 1% per year CO 2 increase experiment (to doubling) (1pctto2x) of phase 3 of the Coupled Model Inter-comparison Project (CMIP3). The study focuses on the potential changes of July–August temperature extremes over China. The pattern correlation coefficients of the simulated temperature with the observations are 0.6–0.9, which are higher than the results for precipitation. However, most models have cold bias compared to observation, with a larger cold bias over western China (>5°C) than over eastern China (<2°C). The multi-model ensemble (MME) exhibits a significant increase of temperature under the 1pctto2x scenario. The amplitude of the MME warming shows a northwest–southeast decreasing gradient. The warming spread among the models (～1°C– 2°C) is less than MME warming (～2°C–4°C), indicating a relatively robust temperature change under CO 2 doubling. Further analysis of Geophysical Fluid Dynamics Laboratory coupled climate model version 2.1 (GFDL-CM2.1) simulations suggests that the warming pattern may be related to heat transport by summer monsoons. The contrast of cloud effects also has contributions. The different vertical structures of warming over northwestern China and southeastern China may be attributed to the different natures of vertical circulations. The deep, moist convection over southeastern China is an effective mechanism for "transporting" the warming upward, leading to more upper-level warming. In northwestern China, the warming is more surface-orientated, possibly due to the shallow, dry convection.