摘要
随着计算机技术的飞速发展,气候系统模式也得到了快速发展,已成为研究气候变化机理及其预测的重要工具,倍受重视,并已取得了诸多很有价值的研究成果。但仍有一些基本的或深层次的问题亟待进一步研究解决,例如,一个新开发的气候系统耦合模式,系统全面地检验与评估其模拟能力就是最基本、也是最重要的工作之一,这对于合理利用此模式进行数值模拟试验,研究揭示外强迫对气候变化的影响过程及其机理至关重要；对于认定模式所预测的未来气候变化程度的可信度更是必不可少。基于此,按照所承担的国家科技支撑计划课题“极端天气气候事件数值模拟”任务要求,本文在我国及周边区域内,检验了中国气象局国家气候中心研发的BCC_CSM气候系统模式关于模拟中国及周边地区气候状况的模拟能力,评估了其在大气环流形势场和各气象要素场方面的模拟能力,计算统计了其高度场的平均误差、均方根误差、相对均方根误差以及空间相关系数。其次,评估了该模式对我国极端温度的模拟能力,并依次分析了模式对日平均温度、日最高最低温度、极端温度指数及其长期变化趋势的模拟能力。在此基础上,利用该模式对火山灰气溶胶的气候效应进行了数值模拟试验,初步揭示了其辐射强迫及气候效应。最后,利用包括BCC_CSM模式在内CMIP5计划中的12个模式的模拟试验结果,比较分析了BCC_CSM模式与其它模式的模拟性能,并利用BCC_CSM气候系统模式,开展了长期气候模拟的三类试验(历史试验、控制试验、气候灵敏度试验),模拟研究了其它外强迫作用对气候变化的影响主要结论如下：
1、经检验,BCC CSM1.0模式能较好地模拟东亚大气环流形势及相关气象要素场,尤其对南亚高压和西太平洋副热带高压的位置和强度模拟得较准确,并对各个等压面层的温度场、湿度场、垂直运动等气象要素场都有较好的模拟,且低层的模拟效果优于高层。通过定量分析500hPa层高度场的误差发现,模式系统误差偏差不大,受季节影响,春夏秋季主要为正偏差,冬季主要为负偏差；均方根误差在低纬地区误差较小,高纬地区误差略偏大。相对均方根误差分析显示,模式系统误差主要受地形影响所致,除青藏高原以外,其余地区误差均较小。由此说明BCC_CSM1.0模式在东亚大部分地区有较好模拟能力。
检验与评估结果还显示,BCC_CSM1.0模式对中国地区的极端温度模拟效果较好,其中,日平均温度的年际变化、年变化、季节变化的模拟结果与观测值基本一致,只是在青藏高原地区存在异常低值区；最高和最低温度的模拟,在东南沿海、新疆、青藏高原地区模拟值略偏低,其它大部分地区偏差都较小。极端温度指数模拟情况也较好,模拟值和观测值均显示出极端温度指数呈上升趋势,表明此模式对极端温度及其与此相关联的气候事件也有一定的模拟能力。
2、利用检验与评估后的BCC-CSM1.0气候系统耦合模式进行了火山灰气溶胶辐射强迫作用的气候敏感性及其效应的数值模拟研究,结果表明,模式中加入火山灰气溶胶后,各个气象要素场的模拟误差都有所减小,总体模拟效果明显提高,表明加入火山灰气溶胶的模式大气更加逼近实际大气。其中,北半球比南半球的模拟误差减小明显,30°-35°N之间是模拟误差变化最敏感地区；夏季比冬季的模拟误差减小明显；高度场、海平面气压场、风场的模拟误差变化态势一致。全球模拟误差综合统计分析表明,火山灰气溶胶的综合辐射强迫作用可使高度场高层的模拟结果优于低层,而温度场和绝对湿度场的模拟结果却是低层的优于高层。
3、在BCC_CSM1.0气候系统模式中加入了火山灰气溶胶后,其模拟结果显示：火山灰气溶胶的辐射强迫作用很明显,使得近地面向下的太阳辐射减少,辐射强迫为负值；长波辐射通量,因纬度不同而异,低纬地区为正值,高纬地区为负值,辐射通量减少的地区主要为亚热带和极地区域。火山灰气溶胶也可影响大气层垂直加热率,使长波辐射冷却在对流层增加,在平流层减少；短波辐射加热在对流层减少,在平流层增加,呈现出了明显的“阳伞效应”。此外,火山灰气溶胶还改变了云的辐射强迫。
4、利用BCC_CSM1.1模式开展了三类模拟试验(工业革命前控制试验；历史试验；气候灵敏度试验)。在三类模拟试验结果中,选取中国及周边区域进行分析,结果表明,BCC_CSM1.1模式模拟的温度、降水、蒸发量的模拟值均接近12个模式模拟结果的平均值,在350N-400N区间内,BCC_CSM1.1温度模拟值与其它模式相比,变化平缓,可信度更高。综合来看,BCC_CSM模式与11个模式的模拟值变化趋势和范围大致相同,表明其模拟性能及普适性都较佳。
5、BCC_CSM1.1模式对温度场的模拟结果表明,由历史试验与工业革命前控制试验之差所反映的综合外强迫作用显示,温度年际变化总体呈降低趋势,但随纬度的变化幅度很小；但是,由气候灵敏度试验与工业革命前控制试验之差所反映的CO2突增4倍的结果显示,总体特征是增温明显,其中,陆地增温比海洋增温幅度大；春夏秋冬四季中,增温幅度都随纬度而增大,且冬季增温幅度最大。
降水变化情况表明,不论是外强迫的综合作用、还是C02突增4倍的作用,总体上对低纬地区夏季的降水影响大于中高纬地区；在低纬地区,对陆地降水的影响程度大于海洋；外强迫的综合作用使研究区内大部分地区冬夏季降水减少,而C02突增4倍的作用使研究区内大部分地区(除赤道附近外)冬夏季降水增多。
大气环流场,外强迫的综合作用使高度场的模拟值在春夏秋三季降低,冬季升高；CO2突增4倍的作用使全年的对流层高度场模拟值均增高；两种试验对高层的影响大于低层,并且对冬季高度场的影响大于其它季节。
雪盖百分比的影响情况,外强迫的综合作用使研究区内大部分地区雪盖百分比增大,尤其是秋冬季的青藏高原地区明显增大：而CO2浓度突增4倍的作用使研究区内雪盖全部减少。
综上所述,运用BCC_CSM1.1进行的三种试验结果表明,就温湿场而言,外强迫的综合作用总体上使温度降低,降水减少;C02突增4倍的作用总体上使温度升高、降水增多,增温幅度陆地比海洋大,中高纬地区升幅比低纬大,且冬季增温幅度最大。由此可揭示上世纪80年代以来,北半球中高纬地区增暖比低纬明显,冬季增温比其它季节明显的实事,主要是由C02急剧增加所致。
With the rapid development of computer technology, there has also been a rapid advance in the climate system model, which has become an important tool for studying the mechanisms and forecast of climate change and has been paid much more attention. So far, there have been many valuable research results. However, there are still some basic or deep-seated problems which are needed to be studied. For example, for a newly developed coupled climate system model, the most basic and critical work is to evaluate its simulation capabilities comprehensively and systematically, which is important for the rational numerical experimentation to study the mechanisms of the external forcing effecting on climate change and the credibility of predicting future climate change. Based on this, according to the mission requirements of the National Science and Technology Support Program project "the numerical simulation of extreme weather and climate events", the ability of the global climate system model BCC_CSM (developed by the National Climate Center) in simulating climatic conditions in China and the surrounding area has been assessed including the atmospheric circulation and meteorological elements. Firstly, the statistics of the height field, average error, the root mean square error, relative root mean square error and spatial correlation coefficient are calculated. Secondly, the capability of the model simulation in simulating the extreme temperatures, the daily average temperature, daily maximum and minimum temperatures, extreme temperature index and its long-term trend has been assessed. Based on this, a numerical experiment of the climate effects of volcanic aerosol has been conducted by using this model, and the radiation forcing and climate changes has been indicated. Finally, the capability of the BCC_CSM model and other models are assessed by comparing the simulation results of12models from CMIP5plan including BCC_CSM model. Moreover, three types of long-term climate test (historical test, controlled trial, climate sensitivity test) have been analyzed and compared, and the effect of the external forcing on climate change has been analyzed. The main conclusions are as follows,
1. Through testing, it is found that BCC_CSM1.0model has good ability in simulating the atmospheric circulation and meteorological elements in East Asia especially in simulating the location and intensity of the South Asia High and West Pacific subtropical high, and the simulation results at low levels are better than those at high levels. In addition, the model can also simulate the temperature field in every layer, humidity field and vertical movement very well. Through analyzing the system error deviation of500hPa height field, it is indicated that the model system error is small and affected by seasons, which is positive in spring, summer and autumn, and is negative in winter. Mean square root error is small in low latitudes and slightly large in the high latitudes. Analysis on the relative mean square root error shows that the model system error is mainly affected by terrain, and it is small in all the regions except Qinghai-Tibet Plateau The results stated above shows that the model BCC_CSM1.0is applicable in most of East Asia.
The results of the test and evaluation also show that BCC CSM1.0model can simulate the extreme temperature very well. Moreover, the simulation of inter-annual variation, annual variation and seasonal variation of the daily mean temperature is consistent with the observation, except an anomalously low region in the Tibetan Plateau. The simulation of the maximum and minimum temperatures is small in most regions, and the deviation of the simulated maximum and minimum temperatures are slightly low in the southeast coastal region, Xinjiang, Qinghai-Tibet Plateau. The simulation of extreme temperature index is in good agreement in the observation, and both of them show an upward tendency. Hence, it is found that this mode also has the ability to simulate the extreme temperatures evens and associated climate events.
2. The climate effects of volcanic ash aerosol are simulated by utilizing BCC_CSM1.0coupled climate system model. The results show that the simulation errors of various meteorological elements are reduced significantly with the volcanic ash aerosol put into the model, and the overall effect of simulation is improved. This indicates that the model atmosphere with the volcanic aerosol is closer to the real atmosphere, and the simulation error decreases significantly in northern hemisphere (NH) than the southern hemisphere (SH). In addition, the most sensitive area of the simulation error change is the area between30°N and35°N. The simulation error decreases more significant in summer than in winter. The trends of the simulation error of height field, sea level pressure and wind fields are consistent with each other. The comprehensive analysis of the global simulation error shows that the simulation of height field is better in low levels than in high level with the radiative forcing effects of volcanic ash aerosol, while it is opposite for temperature field and the absolute humidity field.
3. After adding volcanic ash aerosol into the model, the results show that the effects of radiative forcing of volcanic ash aerosol are obvious, which leads to the reduction of downward solar flux near the surface, and the radiative forcing (RF) is negative. The long wave radiation flux varies is different with latitude, which is positive in low latitudes, while negative in high latitudes, and the reduction of radiant flux is mainly in the subtropical and polar regions. Shortwave radiative forcing is negative at the sea ice surface and the open ocean, and the long wave radiative forcing is not obvious. The vertical atmosphere heating rate is also affected by volcanic ash aerosol, that is the long wave radiative cooling is increased in the troposphere and decreased in the stratosphere, and shortwave radiation heating is reduced in the troposphere and increased in the stratosphere. Therefore, the RF of the net radiation heating rate is negative in the troposphere and positive in the stratosphere, which is called "Parasol effect". In addition, the overall effect of the radiative forcing of volcanic aerosols on cloud is that the cloud cooling effect is enhanced. In short, due to the volcanic ash aerosols, the surface of the earth receives less radiation, resulting in that atmospheric heating rate is decreasing in the troposphere and increasing in the stratosphere, which is called "Parasol effect" restraining the troposphere atmospheric heating.
4. Three types of simulation test (controlled trial before the industrial revolution, history test; climate sensitivity test) are carried out in China and the surrounding area using BCC_CSM1.1model. The results show that the simulation of temperature, precipitation and evaporation are close to the average value of12models. In the range of35°N-40°N, the change of temperature is smooth compared to other models, and it is highly reliable. Generally speaking, BCC_CSM model has the same trends and range compared to the other11models, indicating its performance and universal is very well.
5. The simulation of temperature field from the BCC_CSM1.1model shows that the inner-annual temperature is overall decreasing with small amplitude for the function of comprehensive extra forcing of the difference between historical test and the control test before the industrial revolution. However, the inner-annual temperature is overall increasing for the function of the pre-industrial CO2four times sudden increase reflected by the difference between climate sensitivity test and the control test before the industrial revolution, and the rate of warming is larger on the land than the ocean. In the four seasons, the warming is increasing with latitude, especially in winter. It reveals the fact that the warming has been more significant in the mid-and high latitudes than the low-latitude and more obvious in winter than the other seasons mainly caused by sharp increase of CO2since the global warming which began in the1980s. The changes of precipitation show that either the function of comprehensive external forcing or CO2sudden increase four times has much more impact on summer precipitation in low latitudes than high latitudes. In low latitudes, the effect on the land is greater than that on the ocean. The effect of comprehensive external forcing leads to the increasing of precipitation in summer and winter in most areas, except the equation.
For the atmospheric circulation, the combined effects of external forcing are the reduction of the simulation value of the height field in spring, summer and autumn, but increase in winter. The effect of CO2sudden four times increase is the increasing of the simulated troposphere height filed throughout a year. The impact of the high-rise in two experiments is greater in the high levels than the low levels, and the impact on the height field is greater in winter than other seasons.
For the effects of the snow cover percentage, the percentage of snow cover increases significantly in the most area due to the combined effects of external forcing, especially in autumn and winter in the Tibetan Plateau. However, the snow cover reduces in all the research areas due to the sudden4times increase of CO2concentration.
In summary, the results of three experiments using BCC_CSM1.1show that the temperature decreases and the precipitation reduces due to the overall combined effect of external forcing. Due to the CO2sudden4times increase, both the temperature and precipitation increase. Moreover, the warming range is larger on the land than the ocean, and is larger in high latitudes than in low latitudes especially in winter. Therefore, it reveals the warming in the mid-and high latitudes has been more significant than that in the low-latitude, and the warming has been more obvious in winter than the other seasons mainly caused by sharp increase of CO2since the1980s.
引文
[1]Randall, D. A., Coauthors. Climate models and their evaluation. Climate Change[J].2007,600.
[2]Tebaldi, K. Hayhoe, JM Arblaster, GA Meehl. Going to the extremes. Clim Change[J] 2006,79 (3-4):185-211.
[3]Brown S J, Caesar J, Ferro C A T. Global changes in extreme daily temperature since 1950[J]. Journal of Geophysical Research:Atmospheres (1984-2012),2008,113(D5).
[4]Du H, Wu Z, Li M, et al. Characteristics of extreme daily minimum and maximum temperature over Northeast China,1961-2009[J]. Theoretical and Applied Climatology,2013,111(1-2): 161-171.
[5]Wang H, Chen Y, Chen Z, et al. Changes in annual and seasonal temperature extremes in the arid region of China,1960-2010[J]. Natural Hazards,2013,65(3):1913-1930.
[6]徐群.近百年北半球中纬度火山灰尘幕指数的估量[J].地球物理学报.1985,(06)：558-568.
[7]An Assessment of the Intergovernmental Panel on Climate Change 2007. Synthesis Report[M]. United Kingdom and New York, NY, USA, Cambridge:Cambridge University Press,2007:600.
[8]Hegerl, G. C., Crowley, T. J., Baum, S. K., Kim, K.-Y., Hyde, W.T..2003. Detection of volcanic, solar and greenhouse gas signals in paleo-reconstructions of Northern Hemispheric temperature[J]. Geophys. Res. Lett.30,1242.
[9]Friend, A. D.. Response of Earth's surface temperature to radiative forcing over AD 1-2009[J]. Journal of Geophysical Research-Atmospheres.2011,116.
[10]贾朋群,陆龙骅,薛正夫,石广玉.火山喷发和太阳活动对我国温度影响的研究[J].气候与环境研究1999,(02)：58-66.
[11]Hansen, J., W.-C. Wang, Lacis, A.. Mt. Agung provides test of a global climate perturbation[J]. Science.1978,199,1065-1068.
[12]Pollack, J. Ackerman, T.. Possible effects of the El Chichon cloud on the radiation budget of the northern tropics[J]. Geophys. Res. Lett.1983,10,1057-1060.
[13]Hansen, J., Sato M., Ruedy R., et al. A Pinatubo climate modeling investigation. In The Mount Pinatubo Eruption Effects on the Atmosphere and Climate[J]. eds. Fiocco, G, Fua, D., Visconti, G. NATO ASI Series, Berlin, Springer-Verlag,1996,142,233-72.
[14]Miffire, A., David, G, et al. Characterization of Iceland volcanic aerosols by UV-polarization Lidar at Lyon, SW Europe. Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing[J]. Vi. U. N. Singh and G. Pappalardo.7832.2010.
[15]杨修群,黄士松.外强迫引起的夏季大气环流异常及其机制探讨[J].大气科学.1993,(06)：697-702.
[16]徐群.太阳常数、火山灰和长期预报[J].气象.1983,(06)：7-10.
[17]Taylor, K. E., Stouffer, R. J., Meehl, G. A.. An overview of CMIP5 and theexperiment design [J]. Bull Amer Meteorol Soc,2011.
[18]辛晓歌,吴统文,张洁.BCC气候系统模式开展的CMIP5试验介绍[J].气候变化研究进展.2012,8(5)：378-382.
[19]姚遥,罗勇,黄建斌.8个CMIP5模式对中国极端气温的模拟和预估[J].气候变化研究进展.2012,8(4)：250-256.
[20]http://cmip-pcmdi.llnl.gov/cmip5/index.html.
[21]全球变化研究国家重大科学计划《基于CMIP5多模式模拟试验的气候变化集合预估和归因分析研究》项目官方网站：http://114.255.218.74/index.jsp.
[22]Houghton, J. T., Filho, L. G. M., Bruce, J., et al. IPCC Climate Change. Radiative Forcing of Climate Change and an Evaluation of the IPCC IS92 Emission Scenarios[J]. Cambridge, Cambridge University Press.1994.
[23]Kiehl, J. T., Ramanathan, V.. Frontiers of Climate modeling[M], Cambridge University Press, 2006.
[24]贾朋群,石广玉.近50年火山喷发和太阳活动对我国气候影响的研究[J].高原气象.2001,(03)：225-233.
[25]Randall, D. A., Coauthors. Climate models and their evaluation. The Physical Science Basis, Climate Change 2007[M]. United Kingdom and New York, NY, USA, Cambridge: Cambridge University Press.2007:589-662.
[26]An Assessment of the Intergovernmental Panel on Climate Change 2007:Synthesis Report [M]. United Kingdom and New York, NY, USA, Cam-bridge:Cambridge University Press. 2007:600.
[27]Meehl et al,2007G.A. Meehl, C. Covey, T. Delworth, M. Latif, B. McAvaney, J.F.B. Mitchell, R.J. Stouffer, K.E. Taylor. The WCRP CMIP3 multi-model dataset:a new era in climate change research [J]. Bulletin of the American Meteorological Society.88 (2007),:1383-1394.
[28]Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design[J]. Bulletin of the American Meteorological Society.93:485-498.
[29]Wang Bin, Xie Xin, Li Lijuan. A Review on Aspects of Climate Simulation Assessment[J]. Advances in Atmospheric Sciences.2009,26(4):736-747.
[30]高学杰,赵宗慈,丁一汇等.温室效应引起的中国区域气候变化的数值模拟模式对中国气候模拟能力的检验[J].气象学报.2003,61(1)：20-28.
[31]Gao Xuejie, Zhao Zongci, Ding Yihui, et al. Climate Change due to Greenhouse Effects in China as Simulated by a Regional Climate Model[J]. Advances in Atmospheric Sciences. 2001,18(6):1224-1230.
[32]王在志,吴国雄,刘平,吴统文.全球海-陆-气耦合模式大气模式分量的发展及其气候模拟性能I[J].热带气象学报.2005,21(3)：225-237.
[33]汤剑平,赵鸣,苏炳凯,赵得明MM5BATS对东亚夏季气候及其变化的模拟试验[J].高原气象.2005,24(1)：28-37.
[34]周天军,宇如聪,王在志,吴统文等.大气环流模式SAMIL及其耦合模式FGOALSs[M].北京：气象出版社.2005.
[35]赵天保,符淙斌.中国区域ERA40、NCEP2再分析资料与观测资料的初步比较与分析[J].气候与环境研究.2006,11(1)：14-32.
[36]刘还珠,Tibaldi, S.,吴国雄.ECMWF预报模式在不同地形方案下的系统误差检验[J].气象.1987,13(3)：3-9.
[37]黄昌兴.气候模式的误差及其可预报性研究[博士论文].北京：中国气象科学研究院.2005.
[38]Harry, Glahn, R.. Comments on "Error determination of a successive correction type objective analysis scheme[J]. Jou. Atmos. Oce. Tech.1987,4:348-349.
[39]Miyakoda, K, Sirutis, J.. Sub grid Scale Physics in 1-Month Forecasts. Part II:Systematic error and blocking forecasts[J]. Mon Wea Rea.1990,123:1065-1081.
[40]Boer, G.J. Systematic and Random Error in an Extended-Rang Forecasting Experiment[J]. Mon Wea Rev.1993,121:173-188.
[41]Koch, Steven, E., et al. Synoptic Scale Forecast Skill and Systematic Errors in the MASS 2.0 Model[J].Mon Wea Rev.1985,113:1714-1737.
[42]Farrel, B.F. Small error dynamics and the predictability of atmospheric fows[J]. J.Atmos.Sci. 1990,47:2409-2416.
[43]Ake, Johansson.1989:Simulation of Systematic Error Effects and Their Reduction in a Simple Model of the Atmosphere[J]. Mon Wea Rev.1989,117:1658-1675.
[44]徐影,丁一汇,赵宗慈.近30年人类活动对东亚地区气候变化影响的检测与评估[J].应用气象学报.2002,13(5)：513-525.
[45]赵宗慈,丁一汇,李晓东等.海气耦合模式在东亚地区的可靠性评估[J].应用气象学报.1995,6(增刊)：9-18.
[46]高学杰.实况海温强迫的CCM3模式对中国区域气候的模拟能力[J].大气科学.2004.28(1)：78-90.
[47]赵宗慈.全球环流模式在中国部分模拟效果评估[J].气象.1990,16(9)：13-17.
[48]Grotch, S.L., MacCracken, M.C.. The use of General Circulation Models to predict regional climate change[J]. J. Climate.1991,4:286-303.
[49]李巧萍,丁一汇.区域气候模式对东亚季风和中国降水的多年模拟与性能检验[J].气象学报.2004,62(2)：140-153.
[50]Nam J C. Comparison of daily extreme temperatures over eastern China and South Korea between 1996-2005[J]. Advances in Atmospheric Sciences,2009,26(2):253-264.
[51]Kharin V V, Zwiers F W. Estimating extremes in transient climate change simulations[J]. Journal of Climate,2005,18(8):1156-1173.
[52]Kharin V V, Zwiers F W, Zhang X, et al. Changes in temperature and precipitation extremes in the IPCC ensemble of global coupled model simulations[J]. Journal of Climate,2007,20(8): 1419-1444.
[53]Coppola E, Giorgi F. An assessment of temperature and precipitation change projections over Italy from recent global and regional climate model simulations[J]. International Journal of Climatology,2010,30(1):11-32.
[54]Li H, Feng L, Zhou T. Multi-model projection of July-August climate extreme changes over China under CO2 doubling. Part Ⅱ:Temperature[J]. Advances in Atmospheric Sciences,2011, 28(2):448.
[55]Rinke A, Matthes H, Dethloff K. Regional characteristics of Arctic temperature variability: comparison of observations with regional climate simulations[J]. Climate research (Open Access for articles 4 years old and older),2010,41(3):177.
[56]Russo S, Sterl A. Global changes in indices describing moderate temperature extremes from the daily output of a climate model[J]. Journal of Geophysical Research:Atmospheres (1984-2012),2011,116(D3).
[57]Rusticucci M, Marengo J, Penalba O, et al. An intercomparison of model-simulated in extreme rainfall and temperature events during the last half of the twentieth century. Part 1: mean values and variability[J]. Climatic change,2010,98(3-4):493-508.
[58]Thibeault J M, Seth A, Garcia M. Changing climate in the Bolivian Altiplano:CMIP3 projections for temperature and precipitation extremes[J]. Journal of Geophysical Research: Atmospheres (1984-2012),2010,115(D8).
[59]Zhang D F, Gao X J, Ouyang L C, et al. Simulation of present climate over East Asia by a regional climate model[J]. J Trop Meteorol,2008,14:19-23.
[60]C. Y. Li, J. Ling, X. L. Jia, M. Dong. Numerical simulation and comparison study of the atmospheric intraseasonal oscillation[J]. Acta Meteorologica Sinica.2007,21:1-8.
[61]T. W. Wu,, R. C. Yu, F. Zhang. A modified dynamic framework for the atmospheric spectral model and its application [J].Journal of the Atmospheric Sciences.2008,65:2235-2253.
[62]陈湘雅.东亚夏季风年际变化及BCC_CSM模拟分析[硕士论文].南京：南京信息工程大学.2008.
[63]Zhang L, Dong M, Wu T. Changes in precipitation extremes over Eastern China simulated by the Beijing Climate Center Climate System Model (BCC-CSM1.0)[J]. Climate Research,2012, 50(2):227.
[64]Zhang, L., Wu, T. W., Xin, X. G. Dong, M., Wang, Z. Z.. Projections of annual mean air temperature and precipitation over the globe and in China during the 21st century by the BCC Climate System Model BCC_CSM1.0[J]. Acta Meteorologica Sinica.2012, 26:362-375.
[65]Wu, T. W., Yu, R. C., Zhang, F.,Wang, Z. Z., Dong, M., Wang, L. N., Jin, X., Chen, D. L., Laurent, Li.. The Beijing Climate Center atmospheric general circulation model:description and its performance for the present-day climate[J]. Clim Dyn.2012,34:123-147.
[66]Chen, H. M., Yu, R. C., Li, J., Xin, X. G, Wang, Z. Z., Wu, T. W.. The coherent interdecadal changes of East Asia climate in mid-summer simulated by BCC_AGCM 2.0.1 [J]. Climate Dynamics.2012,39:155-163.
[67]Dong, M., Wu, T. W., Wang, Z. Z., Zhang, F.. Simulations of the Tropical Intraseasonal Oscillation by the Atmospheric General Circulation Model of the Beijing Climate Center[J]. Acta Meteorologica Sinica.2010,24:571-583.
[68]Dong, M., Wu, T. W., Wang, Z. Z., Cheng, Y. J., Zhang, F.. A simulation study on the extreme temperature events of the 20th century by using the BCC_AGCM[J]. Acta Meteorologica Sinica.2012,26:489-506.
[69]Wang, Z., Zhang, H., Shen, X., Gong, S., Zhang, X.. Modeling study of aerosol indirect effects on global climate with an AGCM[J]. Advances in Atmospheric Sciences.2010,27: 1064-1077.
[70]Wu, T. W., Coauthors. The Beijing Climate Center atmospheric general circulation model: description and its performance for the present-day climate[J]. Climate Dynamics.2010, 34:123-147.
[71]Forster P, Ramaswamy V, Artaxo P, et al. Changes in atmospheric constituents and in radiative forcing[J]. Climate change,2007,20.
[72]Gasteiger, J. G. J., Gross, S., Freudenthaler, V., Wiegner, M.. Volcanic ash from Iceland over Munich:mass concentration retrieved from ground-based remote sensing measurements[J]. Atmospheric Chemistry and Physics.2011,11:2209-2223.
[73]Timmreck, C., Lorenz, S.J., Crowley, T.J., Kinne, S., Raddatz, T.J., Thomas, M.A., Jungclaus, J.H.. Limited temperature response to the very large AD 1258 volcanic eruption[J]. Geophys. Res. Lett..2009,36, L21708.
[74]Carstea, E., Radulescu, R., Belegante, L., Radu, C.. Volcanic ash monitoring over Bucharest area using a multiwavelength Raman lidar[J]. Optoelectronics and Advanced Materials-Rapid Communications.2010,4,2162-2166.
[75]Mitchell, J. M. Jr. in S. F. Singer (ed), Global effects of environmental pollution[J]. SpringerVerlag, N. Y./D. Reidel Publ. Co, Dordrecht,1970,139-155.
[76]曲维政,黄菲,赵进平,邓声贵,杜凌,刘应辰.火山活动对北半球平流层气候异常变化的影响[J].地球物理学进展.2006,(02)：650-659.
[77]Robock, A., The dust cloud of the century[J]. Nature.1983,301,373-374.
[78]Simkin, T. et al. Volcanoes of the world[J]. Hutchison Ross. New York,1981.
[79]Newell, R. E.. Workshop on Mount. St. Helens eruptions of 1980:atmospheric effects and potential climatic impact[J]. Bull. Amer. Met. Soc..1983,64(2):154-157.
[80]Karagulian, F., Clarisse, L., Clerbaux, C., Prata, A. J., Hurtmans, D., Coheur, P. F.. Detection of volcanic SO(2), ash, and H(2)SO(4) using the Infrared Atmospheric Sounding Interferometer (IASI) [J]. Journal of Geophysical Research-Atmospheres.2010,115.
[81]Kern, C., Deutschmann, T., Vogel, L., Wohrbach, M., Wagner, T., Platt, U.. Radiative transfer corrections for accurate spectroscopic measurements of volcanic gas emissions[J]. Bulletin of Volcanology.2010,72:233-247.
[82]Miffre, A., David, G., Thomas, B., Rairoux, P.. Characterization of Iceland volcanic aerosols by UV-polarization Lidar at Lyon, SW Europe. Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing[J]. Vi, U. N. Singh, and G. Pappalardo, Eds, 2010.
[83]Nicolae, D., Nemuc, A., Belegante, L.. Mix of volcanic ash and Saharan dust over Romania, during Eyjafjallajokull eruption. Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing[J]. Vi, U. N. Singh, and G. Pappalardo, Eds,2010.
[84]Ansmann, A., Coauthors. The 16 April 2010 major volcanic ash plume over central Europe: EARLINET lidar and AERONET photometer observations at Leipzig and Munich[J]. Germany. Geophysical Research Letters.2010,37.
[85]Tesche, M., Ansmann, A., Hiebsch, A., Mattis, I., Schmidt, J., Seifert, P., Wandinger, U.. Lidar observations of the Eyjafjallajokull volcanic ash plume at Leipzig, Germany. Conference on Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing[J]. VI, Toulouse, France.2010.
[86]张先恭,张富国.火山活动与我国旱涝、冷暖的关系[J].气象学报.1985,(02)：196-207.
[87]Wang, S. W., Zhao, Z. C,, Gong, D. Y., Zhou, T. J.. Introduction to modern climate[M]. Bei Jing:Meteorological press.2006.
[88]Dyer, A. J.. The effect of volcanic eruptions on global turbidity and an attempt to detect longterm trends due to man[J], Ouart. J. Roy. Meteor. Soc..1974,100,426.
[89]Kravitz, B., Robock, A.. Climate effects of high-latitude volcanic eruptions:Role of the time of year[J]. Journal of Geophysical Research-Atmospheres.2011,116.
[90]Schmidt, A., Carslaw, K. S., Mann, G W., Wilson, M., Breider, T. J., Pickering, S. J., Thordarson, T.. The impact of the 1783-1784 AD Laki eruption on global aerosol formation processes and cloud condensation nuclei[J]. Atmospheric Chemistry and Physics.2010, 10:6025-6041.
[91]徐群.1980年夏季我国天气气候反常和St.Helens火山爆发的影响[J].气象学报.1986,(04)：426-432.
[92]贾朋群.平流层火山灰气溶胶层对全球温度影响的敏感性研究[J].气象科学研究院院刊.1989,(01)：52-59.
[93]Chou, M. D. et al.. Climate studies with a multilayer energy balance model part Ⅲ:Climatic impact of stratospheric volcanic aerosols[J]. J. Atmos. Sci..1984,41:759-767.
[94]Self, S.. The effects and consequences of very large explosive volcanic eruptions[J]. Phil. Trans. R. Soc. A.2006,364:2073-2097.
[95]侯章栓,李晓东.近百年全球气候变化与外强迫因子信号检测[J].北京大学学报(自然科学版).2000,(05)：641-650.
[96]Lamb, H. H.. Volcanic dust in the atmosphere [J]. Phil. Trans. Roy. Soc, A.1970, 266(1178):426-533, London.
[97]Taylor W J, Bartley J M, Lux D R, et al. Timing of Tertiary extension in the Railroad Valley Pioche Transect, Nevada:Constraints from 40Ar/39Ar ages of volcanic rocks[J]. Journal of Geophysical Research:Solid Earth (1978-2012),1989,94(B6):7757-7774.
[98]Vernier, J. P., Coauthors. Major influence of tropical volcanic eruptions on the stratospheric aerosol layer during the last decade[J]. Geophysical Research Letters.2011,38.
[99]Stenchikov, G., Hamilton, K., Stouffer, R. J., Robock, A., Ramaswamy, V., Santer, B., Graf, H. F.. Arctic Oscillation response to volcanic eruptions in the IPCC AR4 climate models[J]. Journal of Geophysical Research-Atmospheres.2006,111.
[100]Julian, P. R., Chervin, R. M.. A study of the Southern Oscillation and Walker circulation phenomenon[J]. Mon. Wea. Rev..1978,106:1433-1451.
[101]Robock, A.. Volcanic eruptions and climate[J]. Reviews of Geophysics.2000,38:191-219.
[102]Xu, J. J., Powell, A. M.. Uncertainty estimation of the global temperature trends for multiple radiosondes, reanalyses, and CMIP3/IPCC climate model simulations[J]. Theoretical and Applied Climatology.2012,108:505-518.
[103]Timmreck, C.. Modeling the climatic effects of large explosive volcanic eruptions[J]. Wiley Interdisciplinary Reviews-Climate Change.2012,3.
[104]Meronen, H., Henriksson, S. V., Raisanen, P., Laaksonen, A.. Climate effects of northern hemisphere volcanic eruptions in an Earth System Model[J]. Atmospheric Research.2012, 114:107-118.
[105]Ramaswamy, V., Schwarzkopf, M.D., Randel, W.J.. Fingerprint of ozone depletion in the spatial and temporal pattern of recent lower-stratospheric cooling[J]. Nature.1996. 382:616-618.
[106]Timmreck, C., Coauthors. Aerosol size confines climate response to volcanic super-eruptions [J]. Geophysical Research Letters.2010,37.
[107]Ramaswamy, V., Schwarzkopf, M. D., Randel, W. J.. Fingerprint of ozone depletion in the spatial and temporal pattern of recent lower-stratospheric cooling[J]. Nature.1996, 382:616-618.
[108]Mao, J. P., Robock, A.. Surface air temperature simulations by AMIP general circulation models:Volcanic and ENSO sisals and systematic errors[J]. Journal of Climate.1998, 11:1538-1552.
[109]Domingues, C. M., Church, J. A., White, N. J., Gleckler, P. J., Wijffels, S. E., Barker, P. M., Dunn, J. R.. Improved estimates of upper-ocean warming and multi-decadal sea-level rise[J]. Nature.2008,453:1090-U1096.
[110]Yuan, T., Remer, L. A., Yu, H.. Microphysical, macrophysical and radiative signatures of volcanic aerosols in trade wind cumulus observed by the A-Train[J]. Atmospheric Chemistry and Physics.2011,11:7119-7132.
[111]Pope, F. D., Braesicke, P., Grainger, R. G., Kalberer, M., Watson, I. M., Davidson, P. J., Cox. R. A.. Stratospheric aerosol particles and solar-radiation management[J]. Nature Climate Change.2012,2.
[112]Yuan, T. L., Remer, L. A., Pickering, K. E., Yu, H. B.. Observational evidence of aerosol enhancement of lightning activity and convective invigoration[J]. Geophysical Research Letters.2011b,38.
[113]Harrison, R. G, Nicoll, K. A., Ulanowski, Z., Mather, T. A.. Self-charging of the Eyjafjallajokull volcanic ash plume[J]. Environmental Research Letters.2010,5.
[114]徐群.皮纳图博火山云对1992年大范围气候的影响[J].应用气象学报.1995,(01)：35-42.
[115]李祖滨,肖文全,杨青,肖开提.火山爆发对新疆太阳辐射和气温的影响[J].干旱区地理.1994,(04)：15-22.
[116]Watson,R.T.等.温室气体和气溶胶,政府间气候变化专门委员会(IPCC)工作报告[M],1990.
[117]Robock. A.. The cloud of the century[J]. Nature.1983,301:373-374.
[118]Rock, A.. Volcanic Eruptions and Climate[J]. Reviews of Geophysics.2000,38(2):191-219.
[119]Harshvardhan, Cess R. D.. Stratospheric aerosols:effect upon atmospheric temperature and global climate[J]. Tellus.1976,28:1-10.
[120]Shukla, J., Wallace, J. M.. Numerical simulation of the atmospheric response to equatorial pacific sea surface temperature anomalies[J]. J. Atmos. Sci.. 1983,40:1613-1630.
[121]Keshavamurty, R. N.. Response of the atmosphere to sea surface temperature anomalies over the equatorial Pacific and the teleconnections of the Southern Oscillation[J]. J. Atmos. Sci.. 1982,39:1241-1259.
[122]Wallace, J. M., Blackmon, M. L.. Observations of low-frequency atmospheric variability, Large-scale Dynamical Processes in the Atmosphere[J]. Ed. By B. J. Hoskins and R. Pearce, Academic press,1983:55-94.
[123]汪宏七,赵高祥.火山气溶胶的辐射影响[J].大气科学.1992,(06)：755-760.
[124]施能,朱乾根,徐建军.十年际大气环流及东亚季风气候异常成因研究[J].地球科学进展.1998,(04)：95-96.
[125]任宜勇.ENSO与新疆的气温及降水[J].新疆气象.1989.(6).
[126]喻威.厄尔尼诺年新疆的气温及降水[J].新疆气象.1987.(6).
[127]Robock, A., Taylor, K.E., Stenchikov, G. L., Liu, Y.. GCM evaluation of a mechanism for El Nino triggering by the El Chichon ash cloud[J]. Geophys. Res. Lett.1995,22:2369-2372.
[128]Emile-Geay, J., Seager, R., Cane, M.A., Cook, E.C., Haug, G.H.. Volcanoes and ENSO over the past millennium [J]. J. Clim.2008,21:3134-3148.
[129]Stenchikov, G., Hamilton, K., Robock, A., Ramaswamy, V., Schwarzkopf, M.D.. Arctic oscillation response to the 1991 Pinatubo eruption in the SKYHI general circulation model with a realistic quasi-biennial oscillation[J]. J. Geophys. Res..2004,109, D03112.
[130]Stenchikov, G, Robock, A., Ramaswamy, V., Schwarzkopf, M.D., Hamilton, K., Ramachandran, S.. Arctic Oscillation response to the 1991 Mount Pinatubo eruption: effects of volcanic aerosols and ozone depletion[J]. J. Geophys. Res..2002,107,4803.
[131]Gu, G J., Adler, R. F., Precipitation and Temperature Variations on the Interannual Time Scale:Assessing the Impact of ENSO and Volcanic Eruptions [J]. Journal of Climate.2011, 24:2258-2270.
[132]Church, J. A., White, N. J., Arblaster, J. M.. Significant decadal-scale impact of volcanic eruptions on sea level and ocean heat content [J]. Nature.2005,438:74-77.
[133]Gleckler, P. J., AchutaRao, K., Gregory, J. M., Santer, B. D., Taylor, K. E., Wigley, T. M. L., Krakatoa lives:The effect of volcanic eruptions on ocean heat content and thermal expansion[J]. Geophysical Research Letters.2006,33.
[134]黄士松,汤明敏.夏季海洋上副热带高压的成长维持与青藏高压的联系[J].南京大学学报(自然科学版).1977,(01)：141-146.
[135](日)加藤久雄.The normal seasonal change of the temperature field over the Globe[J].研究时报.1980,6,325.
[136]Smagorinsky, J.. General circulation experiments with the primitive equations, I:The basic experiment[J]. Mon. Wea. Rev..1963,91:99-104.
[137]Phillips, D. W.. Significant meteorological events in 1980, Part 1, Ⅱ[J]. WMO Bulletin. 1981,30,3-4.
[138]谢倩,黄土松.1990,冬季赤道中东太平洋海温和北极海冰异常对大气环流影响的研究[J].气象科学.10,325-338.
[139]Jones, A., Slingo, A.. Predicting cloud-droplet effective radius and indirect sulphate aerosol forcing using a general circulation model[J]. Quart. J. Roy. Meteor. Soc..1996,122: 1573-1595.
[140]刘永强,李月洪,贾朋群.低纬和中高纬度火山爆发与我国旱涝的联系[J].气象.1993,(11)：3-7.
[141]Joseph, R., Zeng, N.. Seasonally Modulated Tropical Drought Induced by Volcanic Aerosol[J]. Journal of Climate,2011,24:2045-2060.
[142]Robock, A.. The Mount. St, Helens volcanic eruption of 18 May 1980[J]. Science.1981,212, 1383.
[143]Jlornhob, B. n3. N. HBOBAPOBA, OneHKa BKaa ectecTBeHH KaHTPOnoreHH XaKTOPOBB N3MeHNBOCTb COJHeHHON paHaNH Ha OBepXHOCTH 3eMH, MeTeopo AouuupoAou,1983,8:55-60.
[144]Kelly, P. M., Sear, C. B.. Climate impact of explosive volcanic eruptions[J]. Nature.1984, 311:740-743.
[145]张富国,张先恭.全球不同区域火山爆发与中国夏季旱涝的关系[J].自然灾害学报.1994,(01)：40-46.
[146]Reikard, G.. Forecasting volcanic air pollution in Hawaii:Tests of time series models[J]. Atmospheric Environment.2012,60.
[147]Zhang L. J., Deer. Impact of Volcanic Eruptions on Climate[J]. Meteorological Science and Technology.2005,33,3.
[148]Sellers. W. D.. A new global climate model[J]. J. Appl. Meteor..1973,12:241-254..
[149]Pollack, J. B. et. al. Volcanic explosions and climate change:a theoretical assessment[J]. J. Geophy. Res..1976,31:1071-1083,.
[150]King M D, Arking A. A model of the radiative properties of the El Chichon stratospheric aerosol layer[J]. Journal of climate and applied meteorology,1984,23:1121-1137.
[151]贾朋群.平流层火山灰气溶胶对全球温度影响的敏感性研究[J].气象科学研究院院刊.1989,4：52-59.
[152]Hunt, B. G.. A Simulation of the possible consequences of a volcanic eruption on the general circulation of the atmosphere[J]. Mon. Wea. Rev..1977,105,3.
[153]Chou, M. D. et al.. Climate studies with a multilayer energy balance model part 111:Climatic impact of stratospheric volcanic aerosols[J]. J. Atmos. Sci.. 1984,41,759-767.
[154]Gadian, A. M., Davies, D. R.. A mathematical climate study on the effect of dust from Mount[J]. St. Helens volcano eruptions, Weather.1981,36(5):136-138.
[155]李晓东,王绍武,黄建平.火山喷发对气候影响信号的检测[J].应用气象学报.1993, (04)：458-467.
[156]Crowley, T.J., Zielinski, G., Vinther, B., Udisti, R., Kreutz, K., Cole-Dai, J., Castellano, E.. Volcanism and the Little Ice Age[J]. PAGES News.2008,16:22-23.
[157]Oman, L., Robock, A., Stenchikov, G. L., Thordarson, T., Koch, D., Shindell, D. T., Gao, C. C.. Modeling the distribution of the volcanic aerosol cloud from the 1783-1784 Laki eruption[J]. Journal of Geophysical Research-Atmospheres.2006,111.
[158]Oppenheimer, C., Coauthors. Atmospheric chemistry of an Antarctic volcanic plume[J]. Journal of Geophysical Research-Atmospheres,2010,115.
[159]Scollo, S., Folch, A., Coltelli, M., Realmuto, V. J.. Three-dimensional volcanic aerosol dispersal:A comparison between Multiangle Imaging Spectroradiometer (MISR) data and numerical simulations[J]. Journal of Geophysical Research-Atmospheres.2010,115.
[160]Haywood, J. M., Coauthors. Observations of the eruption of the Sarychev volcano and simulations using the HadGEM2 climate model[J]. Journal of Geophysical Research-Atmospheres.2010,115.
[161]Shiogama, H., Nagashima, T., Yokohata, T., Crooks, S. A., Nozawa, T.. Influence of volcanic activity and changes in solar irradiance on surface air temperatures in the early twentieth century[J]. Geophysical Research Letters.2006,33.
[162]Anchukaitis, K. J., Buckley, B. M., Cook, E. R., Cook, B. I., D'Arrigo, R. D., Ammann. C. M.. Influence of volcanic eruptions on the climate of the Asian monsoon region[J]. Geophysical Research Letters.2010,37.
[163]Gillett, N. P., Weaver, A. J., Zwiers, F. W., Wehner, M. F.. Detection of volcanic influence on global precipitation[J]. Geophysical Research Letters.2004,31.
[164]Ammann, C. M., Naveau, P.. A statistical volcanic forcing scenario generator for climate simulations[J]. Journal of Geophysical Research-Atmospheres.2010,115.
[165]Taylor, K.E., Stouffer, R.J., Meehl, G.A.. An Overview of CMIP5 and the experiment design[J]. Bull. Amer. Meteor. Soc..2012,93:485-498.
[166]WCRP Coupled Model Intercomparison Project-Phase 5[J]. Special Issue of the CLIVAR Exchanges Newsletter.56,15.
[167]Meehl, K., Gerald A., Coauthors. Decadal Prediction[J]. Bull. Amer. Meteor. Soc.2009. 90:1467-1485.
[168]Friedlingstein P. A Strategy for Climate Change Stabilization Experiments with AOGCMs and ESMs[C]//Geophysical Research Abstracts.2007,9:03379.
[169]Friedlingstein, P., Coauthors. Climate-Carbon Cycle Feedback Analysis:Results from the CMIP Model Intercomparison [J]. J. Climate.2006,19:3337-3353.
[170]https://www.ipcc-wgl.unibe.ch/AR5/AR5.html.
[171]Rasch, P. J., et al. (2008), An overview of geoengineering the climate using stratospheric sulfate aerosols, Phil. Trans. Roy. Soc. A,366,4007-4037.
[172]Jones, A., J. Haywood, O. Boucher, B. Kravitz, and A. Robock (2010), Geoengineering by stratospheric SO 2 injection:Results from the Met Office HadGEM2 climate model and comparison with the Goddard Institute for Space Studies Model[J], Atm. Chem. Phys.,10, 5999-6006.
[173]Taylor, K. E., R. J. Stouffer, and G A. Meehl (2012), An overview of CMIP5 and the experiment design[J], Bull. Amer. Meteor. Soc.,93,485-498.
[174]Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.IPCC (2007), Climate Change 2007:The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge Univ. Press,996.
[175]T. Andrews, J. M. Gregory, P. M. Forster, and M. J. Webb, Cloud Adjustment and its Role in CO2 Radiative Forcing and Climate Sensitivity:[J], Surveys in Geophysics, vol. 33,:.619-635,Jul 2012.
[176]S. S. Hou, L. P. Lei, and Z. C. Zeng, The response of global net primary productivity (NPP) to CO2 increasing and climate change:Evaluation of coupled model simulations[J], Journal of Food Agriculture & Environment,2013,11:937-944,.
[177]Y. Kamae and M. Watanabe, On the robustness of tropospheric adjustment in CMIP5 models," Geophysical Research Letters,2012,39.
[178]O. Geoffroy, D. Saint-Martin, and A. Ribes, Quantifying the sources of spread in climate change experiments[J],Geophysical Research Letters,2012,39..
[179]A. Ahlstrom, G. Schurgers, A. Arneth, and B. Smith, Robustness and uncertainty in terrestrial ecosystem carbon response to CMIP5 climate change projections[J], Environmental Research Letters,2012,11-12(7).
[180]S. L. Stevenson, Significant changes to ENSO strength and impacts in the twenty-first century:Results from CMIP5[J], Geophysical Research Letters,2012,9(39).
[181]G. Villarini and G. A. Vecchi, Twenty-first-century projections of North Atlantic tropical storms from CMIP5 models, Nature Climate Change,2012,2:604-607.
[182]T. Kuhlbrodt and J. M. Gregory, Ocean heat uptake and its consequences for the magnitude of sea level rise and climate change[J], Geophysical Research Letters,2012,39.
[183]P. Good, J. M. Gregory, J. A. Lowe, and T. Andrews, Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections[J],Climate Dynamics,2013,40:.
[1]Collins WD et al, Description of the NCAR Community Atmosphere Model (CAM3)[M]. Technical report NCAR/TN-464+STR, National Center for Atmospheric Research, Boulder,Colorado,2004,226.
[2]Collins W D, Rasch P J, Boville B A, et al. The formulation and atmospheric simulation of the Community Atmosphere Model version 3 (CAM3)[J]. Journal of Climate,2006,19(11): 2144-2161.
[3]Berger A L. Long-term variations of daily insolation and Quaternary climatic changes[J]. Journal of the Atmospheric Sciences,1978,35(12):2362-2367.
[4]Ramanathan V, Downey P. A nonisothermal emissivity and absorptivity formulation for water vapor[J]. Journal of Geophysical Research:Atmospheres (1984-2012),1986,91(D8): 8649-8666.
[5]Joseph J H, Wiscombe W J, Weinman J A. The delta-Eddington approximation for radiative flux transfer[J]. Journal of the Atmospheric Sciences,1976,33(12):2452-2459.
[6]Coakley Jr J A, Cess R D, Yurevich F B. The effect of tropospheric aerosols on the earth's radiation budget:A parameterization for climate models[J]. Journal of Atmospheric Sciences, 1983,40:116-138.
[7]Briegleb B P. Delta-Eddington approximation for solar radiation in the NCAR Community Climate Model[J]. Journal of Geophysical Research:Atmospheres (1984-2012),1992,97(D7): 7603-7612.
[8]Collins W D. A global signature of enhanced shortwave absorption by clouds[J]. Journal of Geophysical Research:Atmospheres (1984-2012),1998,103(D24):31669-31679.
[9]Kiehl J T, Briegleb B P. The relative roles of sulfate aerosols and greenhouse gases in climate forcing[J]. Science,1993,260(5106):311-314.
[10]Wu T. The 20th century global carbon cycle from the Beijing Climate Center Climate System Model (BCC CSM)[J]. J Clim,2012.
[11]Wu T, Yu R, Zhang F. A modified dynamic framework for the atmospheric spectral model and its application[J]. Journal of the Atmospheric Sciences,2008,65(7):2235-2253.
[12]Wu T., Yu R, Zhang F, et al. (2010) The Beijing Climate Center for Atmospheric General Circulation Model (BCC-AGCM2.0.1):Description and its performance for the present-day climate[J]. Clim. Dyn.,34:123-147.
[13]Wu T. A mass-flux cumulus parameterization scheme for large-scale models:description and test whh observations[J]. Climate dynamics,2012,38(3-4):725-744.
[14]Ji J J, Huang M, Li K R. Prediction of carbon exchanges between China terrestrial ecosystem and atmosphere in 21st century[J]. Science in China Series D:Earth Sciences,2008,51(6): 885-898.
[15]Ji J. A climate-vegetation interaction model:Simulating physical and biological processes at the surface[J]. Journal of Biogeography,1995:445-451.
[16]http://www.ipsl.jussieu.fr/OCMIP/phase2/.
[17]冯婧.多全球模式对中国区域气候的模拟评估和预估[D].南京信息工程大学,2012.
[18]Dai Y, Zeng X, Dickinson R E, et al. The common land model[J]. Bulletin of the American Meteorological Society,2003,84(8):1013-1023.
[19]Gent P R, Danabasoglu G, Donner L J, et al. The community climate system model version 4[J]. Journal of Climate,2011,24(19):4973-4991.
[20]Hazeleger W, Wang X, Severijns C, et al. EC-Earth V2.2:description and validation of a new seamless earth system prediction model [J]. Climate dynamics,2012,39(11):2611-2629.
[21]Madec, G. (2008), NEMO ocean engine. Tech. Rep.27, Institut Pierre Simon Laplace des Sciences d 1'Environement Global.
[22]Schmidt G A, Ruedy R, Hansen J E, et al. Present-day atmospheric simulations using GISS ModelE:Comparison to in situ, satellite, and reanalysis data [J]. Journal of Climate.2006. 19(2):153-192.
[23]Aleinov I, Schmidt G A. Water isotopes in the GISS ModelE land surface scheme [J]. Global and Planetary Change,2006,51(1):108-120.
[24]Russell G L, Miller J R, Rind D. A coupled atmosphere-ocean model for transient climate change studies [J]. Atmosphere-ocean,1995,33(4):683-730.
[25]Gordon C, Cooper C, Senior C A, et al. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments [J]. Climate Dynamics,2000,16(2-3):147-168.
[26]Collins W J, Bellouin N, Doutriaux-Boucher M, et al. Development and evaluation of an Earth-system model-HadGEM2 [J]. Geosci Model Dev Discuss,2011,4(2):997-1062.
[27]Essery R L H, Best M J, Betts R A, et al. Explicit representation of subgrid heterogeneity in a GCM land surface scheme [J]. Journal of Hydrometeorology,2003,4(3):530-543.
[28]Whiteknights Reading U K. The HadGEM2 family of met office unified model climate configurations[J].2011.
[29]Dufresne J L, Foujols M A, Denvil S, et al. Climate change projections using the IPSL-CM5 Earth System Model:from CMIP3 to CMIP5[J]. Climate Dynamics,2012:1-43.
[30]Krinner G, Viovy N, de Noblet-Ducoudre N, et al. A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system[J]. Global Biogeochemical Cycles,2005, 19(1).
[31]Hourdin F, Foujols M A, Codron F, et al. Impact of the LMDZ atmospheric grid configuration on the climate and sensitivity of the IPSL-CM5A coupled model[J]. Climate Dynamics,2012: 1-26.
[32]Watanabe S, Hajima T, Sudo K, et al. MIROC-ESM 2010:model description and basic results of CMIP5-20c3m experiments[J]. Geoscientific Model Development,2011,4:845-872.
[33]Takata K, Emori S, Watanabe T. Development of the minimal advanced treatments of surface interaction and runoff[J]. Global and Planetary Change,2003,38(1):209-222.
[34]Watanabe S, Miura H, Sekiguchi M, et al. Development of an atmospheric general circulation model for integrated Earth system modeling on the Earth Simulator[J]. J. Earth Simulator, 2008,9:27-35.
[35]K-1 model developers (2004), K-1 Coupled GCM (MIROC) Description, K-1 Technical Report No.1 (Center for Climate System Research, National Institute for Environmental Studies, and Frontier Research Center for Global Change), available online at http://www.ccsr.u-tokyo.ac.jp/kyosei/hasumi/MIROC/tech-repo.pdf.
[36]Giorgetta M A, Jungclaus J, Reick C, et al. Climate variability and climate change in MPI-ESM CMIP5 simulations[J]. J. Adv. Model. Earth Syst, in revision,2012.
[37]Raddatz T J, Reick C H, Knorr W, et al. Will the tropical land biosphere dominate the climate-carbon cycle feedback during the twenty-first century?[J]. Climate Dynamics,2007, 29(6):565-574.
[38]Stevens B, Giorgetta M, Esch M, et al. The atmospheric component of the MPI-M earth system model:ECHAM6[J]. Journal of Advances in Modeling Earth Systems,2013.
[39]Marsland S J, Haak H, Jungclaus J H, et al. The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates[J]. Ocean Modelling,2003,5(2):91-127.
[40]JE K,(?) S. Sensitivity to deliberate sea salt seeding of marine clouds-observations and model simulations[J]. Atmospheric Chemistry and Physics,2012,12(265):2795-2807.
[41]Kirkevag A, Iversen T, Seland (?), et al. Aerosol-climate interactions in the Norwegian Earth System Model-NorESMl-M, Geosci. Model Dev.,6,207-244, doi:10.5194[J].2013.
[42]Assmann K M, Bentsen M, Segschneider J, et al. An isopycnic ocean carbon cycle model[J]. Geoscientific Model Development,2010,3:143-167.
[43]辛晓歌,吴统文,张洁.BCC气候系统模式开展的CMIP5试验介绍[J].气候变化研究进展ISTIC,2012,8(5).
[44]Kanamitsu M, Kumar A, Juang H M H, et al. NCEP dynamical seasonal forecast system 2000[J]. Bulletin of the American Meteorological Society,2002,83(7):1019-1038.
[45]Wenhua Z Q Z F G. Comparison and Analysis Between NCEP/NCAR Every-6-hours Analysis Land Surface and Air Temperature and 753 Chinese Stations'Observation in 2005 [J]. Meteorological Monthly,2008,2:013.
[46]Kanamitsu M, Ebisuzaki W, Woollen J, et al. Ncep-doe amip-ii reanalysis (r-2)[J]. Bulletin of the American Meteorological Society,2002,83(11):1631-1644.
[47]Fang Zhifang, Lei Jtm. Lfi Xiaona, Qu Xing, Li Qian. A comparison of 500 hPa field of East-Asia between the NCEP/NCAR reanalysis data and the ERA'40 of ECMWF data[J]. Acta Meteorologica Sinica.2010,68(2):270-276.
[48]Zheng Yongguang Zhang Chunxi Chen Jiong Chen Mingxuan Wang Yingchun, Climatic Background of Warm 2 Season Convective Weather in North China Based on the NCEP Analysis. Acta Scientiarum Naturalium Universitatis Pekinensis,2007,43(5) (In Chinese).
[49]Buizza R, Houtekamer P L, Pellerin G, et al. A comparison of the ECMWF, MSC, and NCEP global ensemble prediction systems[J]. Monthly Weather Review,2005,133(5):1076-1097.
[50]施晓晖,徐祥德,谢立安.NCEP/NCAR再分析风速、表面气温距平在中国区域气候变化研究中的可信度分析[J].气象学报,2006,(06)：709-722.
[51]Hines K M, Bromwich D H, Marshall G J. Artificial Surface Pressure Trends in the NCEP-NCAR Reanalysis over the Southern Ocean and Antarctica[J]. Journal of Climate, 2000,13(22):3940-3952.
[52]HE Lang,WUHong-bao, ZHAO Xiao-chuan. A Comparison of Basic Statistics Derived from NCEP/NCAR, ECMWF ReanalysisData and CMA Data [J], Journal of Nanjing Institute of Meteorology,2009,32(1):54-63.
[53]Bromwich D H, Fogt R L. Strong Trends in the Skill of the ERA-40 and NCEP-NCAR Reanalyses in the High and Midlatitudes of the Southern Hemisphere,1958-2001[J]. Journal of Climate,2004,17(23):4603-4619.
[54]Kiktev D, Sexton D M H, Alexander L, et al. Comparison of modeled and observed trends in indices of daily climate extremes[J]. Journal of Climate,2003,16(22):3560-3571.
[55]Marengo J A, Rusticucci M, Penalba O, et al. An intercomparison of observed and simulated extreme rainfall and temperature events during the last half of the twentieth century:part 2: historical trends[J]. Climatic Change,2010,98(3-4):509-529.
[56]Hofstra N, New M, McSweeney C. The influence of interpolation and station network density on the distributions and trends of climate variables in gridded daily data[J]. Climate dynamics. 2010,35(5):841-858.
[57]Price D T, McKenney D W, Nalder I A, et al. A comparison of two statistical methods for spatial interpolation of Canadian, monthly mean climate data[J]. Agricultural and Forest meteorology,2000,101(2):81-94.
[58]Giorgi F. A daily temperature dataset over China and its application in validating a RCM simulation[J]. Advances in Atmospheric Sciences,2009,26(4):763-772.
[1]董敏.《气候模式的基本原理和技术方法》[M].北京：气象出版社.1997：175.
[2]Randall, D. A., Coauthors. Climate models and their evaluation. The Physical Science Basis, Climate Change 2007[M]. United Kingdom and New York, NY, USA, Cambridge: Cambridge University Press.2007:589-662.
[3]An Assessment of the Intergovernmental Panel on Climate Change 2007:Synthesis Report [M]. United Kingdom and New York, NY, USA, Cam-bridge:Cambridge University Press.2007 600.
[4]Meehl et al,2007G.A. Meehl, C. Covey, T. Delworth, M. Latif, B. McAvaney, J.F.B. Mitchell, R.J. Stouffer, K.E. Taylor. The WCRP CMIP3 multi-model dataset:a new era in climate change research [J]. Bulletin of the American Meteorological Society.88 (2007),:1383-1394.
[5]Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design [J]. Bulletin of the American Meteorological Society.93:485-498.
[6]许崇海,沈新勇,徐影. IPCC AR4模式对东亚地区气候模拟能力的分析[J].气象变化研究进展.2007,3(5)：287-292.
[7]高学杰.实况海温强迫的CCM3模式对中国区域气候的模拟能力[J].大气科学.2004,28(1)：78-90.
[8]Gao Xuejie, Zhao Zongci, Ding Yihui, etc. Climate Change due to Greenhouse Effects in China as Simulated by a Regional Climate Model [J].Advances in Atmospheric Sciences. 2001,18(6):1224-1230.
[9]王在志,吴国雄,刘平等.全球海-陆-气耦合模式大气模式分量的发展及其气候模拟性能I[J].热带气象学报,2005,21(3)：225-237.
[10]汤剑平,赵鸣,苏炳凯等.MM5BATS对东亚夏季气候及其变化的模拟试验[J].高原气象.2005,24(1)：28-37.
[11]周天军,宇如聪,王在志等.大气环流模式SAMIL及其耦合模式FGOALSs[M].北京：气象出版社.2005.
[12]张耀存.P-σ混合坐标全球模式模拟夏季气候的性能及系统性误差分析[J].高原气象, 1997,16(3)：235-242.
[13]高学杰,周广庆,陈嘉滨.仅引入质量守恒律的T63模式对全球大气环流和中国气候的模拟[J].气候与环境研究.2003,8(3)：338-347.
[14]刘还珠,S. Tibaldi,吴国雄.ECMW预报模式在不同地形方案下的系统误差检验[J].气象.1987,13(3)：3-9.
[15]黄昌兴.气候模式的误差及其可预报性研究[M].北京：博士学位论文,2005：65.
[16]Harry R. Glahn. Comments on Error determination of a successive correction type objective analysis scheme [J], Jou. Atmos. Oce. Tech.1987,4:348-349.
[17]Miyakoda K and J. Sirutis. Sub grid Scale Physics in 1-Month Forecasts. Part Ⅱ:Systematic error and blocking forecasts[J]. Mon Wea Rea.1990,123:1065-1081.
[18]Boer, G. J.. Systematic and Random Error in an Extended-Rang Forecasting Experiment[J]. Mon Wea Rev.1993,121:173-188.
[19]Koch, Steven E., William C. Skillman, Paul J. Kocin, Peter J. Wetzel, Keith F. Brill, Dennis A. Keyser, Michael C. McCumber. Synoptic Scale Forecast Skill and Systematic Errors in the MASS 2.0 Model [J]. Mon Wea Rev,1985,113:1714-1737.
[20]Farrel, B. F. Small error dynamics and the predictability of atmospheric flows [J]. J. Atmos. Sci,1990,47:2409-2416.
[21]Ake Johansson,1989:Simulation of Systematic Error Effects and Their Reduction in a Simple Model of the Atmosphere[J]. Mon Wea Rev,1989,117:1658-1675.
[22]徐影,丁一汇,赵宗慈.近30年人类活动对东亚地区气候变化影响的检测与评估[J].应用气象学报.2002,13(5)：513-525.
[23]赵宗慈,丁一汇,李晓东等.海气耦合模式在东亚地区的可靠性评估[J].应用气象学报.1995,6(增刊)：9-18.高学杰.
[24]高学杰,赵宗慈,丁一汇等.温室效应引起的中国区域气候变化的数值模拟模式对中国气候模拟能力的检验[J].气象学报,2003,61(1)：20-28.
[25]赵宗慈.全球环流模式在中国部分模拟效果评估[J].气象.1990,(09)：13-17.
[26]Grotch S L, MacCracken M C. The use of general circulation models to predict regional climatic change [J]. Journal of Climate,1991,4(3):286-303.
[27]李巧萍,丁一汇.区域气候模式对东亚季风和中国降水的多年模拟与性能检验[J].气象学报.2004,62(2)：140-153.
[28]陈湘雅.东亚夏季风年际变化及BCC CSM模拟分析[M].南京信息工程大学.硕士学位论文.2008年.
[29]Wu T, Yu R, Zhang F, et al. The Beijing Climate Center atmospheric general circulation model: description and its performance for the present-day climate [J]. Climate dynamics,2010, 34(1):123-147.
[30]L. Zhang, M. Dong, and T. W. Wu. Changes in precipitation extremes over Eastern China simulated by the Beijing Climate Center Climate System Model (BCC_CSM1.0)[J]. Climate Research,2011,50(2-3):227-245.
[31]Zhang.L, T. W. Wu, X. G. Xin, M. Dong, and Z. Z. Wang. Projections of annual mean air temperature and precipitation over the globe and in China during the 21st century by the BCC Climate System Model BCC_CSM1.0[J]. Acta Meteorologica Sinica.2012,26:362-375.
[32]石彦军,任余龙,王式功,尚可政,李旭,周甘霖BCC_CSM气候模式对中国区域气候变化模拟能力的检验[J].高原气象.2012,(05)：1257-1267.
[33]石彦军,任余龙,张宇,周甘霖,尚可政,王式功.BCC CSM气候模式对中国区域500hPa气候要素模拟能力的检验[J].兰州大学学报(自然科学版),2012,(06)：54-62.
[1]Tebaldi C, Hayhoe K, Arblaster J M, et al. Going to the extremes[J]. Climatic Change,2006, 79(3-4):185-211.
[2]Brown S J, Caesar J, Ferro C A T. Global changes in extreme daily temperature since 1950[J]. Journal of Geophysical Research:Atmospheres (1984-2012),2008,113(D5).
[3]Du H, Wu Z, Li M, et al. Characteristics of extreme daily minimum and maximum temperature over Northeast China,1961-2009[J]. Theoretical and Applied Climatology,2013,111(1-2): 161-171.
[4]Wang H, Chen Y, Chen Z, et al. Changes in annual and seasonal temperature extremes in the arid region of China,1960-2010[J]. Natural Hazards,2013,65(3):1913-1930.
[5]Yan Z, Jones P D, Davies T D, et al. Trends of extreme temperatures in Europe and China based on daily observations[J]. Climatic Change,2002,53(1-3):355-392.
[6]Kharin V V, Zwiers F W. Estimating extremes in transient climate change simulations[J]. Journal of Climate,2005,18(8):1156-1173.
[7]Kharin V V, Zwiers F W, Zhang X, et al. Changes in temperature and precipitation extremes in the IPCC ensemble of global coupled model simulations[J]. Journal of Climate,2007,20(8): 1419-1444.
[8]Knote C, Heinemann G, Rockel B. Changes in weather extremes:Assessment of return values using high resolution climate simulations at convection-resolving scale[J]. Meteorologische Zeitschrift,2010,19(1):11-23.
[9]Li H, Feng L, Zhou T. Multi-model projection of July-August climate extreme changes over China under CO2 doubling. Part Ⅱ:Temperature[J]. Advances in Atmospheric Sciences,2011, 28(2):448.
[10]Rinke A, Matthes H, Dethloff K. Regional characteristics of Arctic temperature variability: comparison of observations with regional climate simulations [J]. Climate research (Open Access for articles 4 years old and older),2010,41(3):177.
[ll]Russo S, Sterl A. Global changes in indices describing moderate temperature extremes from the daily output of a climate model[J]. Journal of Geophysical Research:Atmospheres (1984-2012),2011,116(D3).
[12]Rusticucci M, Marengo J, Penalba O, et al. An intercomparison of model-simulated in extreme rainfall and temperature events during the last half of the twentieth century. Part 1:mean values and variability[J]. Climatic change,2010; 98(3-4):493-508.
[13]Thibeault J M, Seth A, Garcia M. Changing climate in the Bolivian Altiplano:CMIP3 projections for temperature and precipitation extremes[J]. Journal of Geophysical Research: Atmospheres (1984-2012),2010,115(D8).
[14]XJ Gao, ZC Zhao, F. Giorgi; Changes of extreme events in regional climate simulations over East Asia. Advances in Atmospheric Sciences,2002,19 (5):927-942.
[15]Zhang D F, Gao X J, Ouyang L C, et al. Simulation of present climate over East Asia by a regional climate model[J]. J Trop Meteorol,2008,14:19-23.
[16]Zhang L, Dong M, Wu T. Changes in precipitation extremes over Eastern China simulated by the Beijing Climate Center Climate System Model (BCC-CSM1.0)[J]. Climate Research, 2012,50(2):227.
[17]Kiehl J T, Gent P R. The community climate system model, version 2[J]. Journal of Climate, 2004,17(19):3666-3682.
[18]Kiktev D, Sexton D M H, Alexander L, et al. Comparison of modeled and observed trends in indices of daily climate extremes[J]. Journal of Climate,2003,16(22):3560-3571.
[19]Marengo J A, Rusticucci M, Penalba O, et al. An intercomparison of observed and simulated extreme rainfall and temperature events during the last half of the twentieth century:part 2: historical trends[J]. Climatic Change,2010,98(3-4):509-529.
[20]Hofstra N, New M, McSweeney C. The influence of interpolation and station network density on the distributions and trends of climate variables in gridded daily data[J]. Climate dynamics, 2010,35(5):841-858.
[21]Price D T, McKenney D W, Nalder I A, et al. A comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data[J]. Agricultural and Forest meteorology,2000,101(2):81-94.
[22]Giorgi F. A daily temperature dataset over China and its application in validating a RCM simulation[J]. Advances in Atmospheric Sciences,2009,26(4):763-772.
[23]Chu J T, Xia J, Xu C Y, et al. Statistical downscaling of daily mean temperature, pan evaporation and precipitation for climate change scenarios in Haihe River, China[J]. Theoretical and applied climatology,2010,99(1-2):149-161.
[1]马井会.黑碳和沙尘气溶胶光学特性及全球辐射强迫的模拟研究[D].南京信息工程大学,2007.
[2]张华,马井会,郑有飞.沙尘气溶胶辐射强迫全球分布的模拟研究[J].气象学 报,2009,(04)：510-521.
[3]陈艳.中国西北干旱半干旱区沙尘气溶胶对云特性的影响及云的辐射强迫效应[D].兰州大学,2007.
[4]王玉洁.通过卫星资料反演东亚中纬度地区沙尘云的辐射强迫[D].兰州大学,2006.
[5]苏婧.中国西北地区沙尘气溶胶辐射强迫效应的研究[D].兰州大学,2010.
[6]毛节泰,李成才.气溶胶辐射特性的观测研究[J].气象学报,2005,(05)：622-635.
[7]王宏,石广玉,T.ZAoki,王标.2001年春季东亚-北太平洋地区沙尘气溶胶的辐射强迫[J].科学通报,2004,(19)：1993-2000.
[8]周碧.黄土高原半干旱区气溶胶辐射特性观测研究[D].兰州大学,2012.
[9]宿兴涛,王汉杰,周林.中国有机碳气溶胶时空分布与辐射强迫的模拟研究[J].热带气象学报,2010,(06)：765-772.
[101马井会.黑碳和沙尘气溶胶光学特性及全球辐射强迫的模拟研究[D].南京信息工程大学,2007.
[11]薛江丽,李俊,张鑫,孙新民,王旗,王振全,王式功.新疆春季两次沙尘暴过程中大气PM2.5元素组成特征分析[J].环境与健康杂志,2010,(09)：759-763.
[12]严俊,王振全,连素琴,王式功,胡泽楠,赵春霞,王立辉.兰州大气污染对循环系统疾病日住院人数影响[J].中国公共卫生,2010,(12)：1514-1516.
[13]宁海文,王式功,杜继稳.西安沙尘天气特征及其对空气质量的影响[J].中国沙漠,2005,(06)：94-98.
[14]王建鹏,王式功,孟小绒,赵燕宁,林杨,刘小英.沙尘天气等对西安市空气污染影响的研究[J].中国沙漠,2004,(05)：42-48.
[15]王式功,杨民,祁斌,辛春兰,杨明芳.甘肃河西沙尘暴对兰州市空气污染的影响[J].中国沙漠,1999,(04)：58-62.
[16]陈永忠,肖化云.大气气溶胶的种类及其对人类的影响分析[J].江西科,2009,(06)：912-915.
[17]夏晓敏,汪建君,陈立奇,张锐.厦门市区10月份大气气溶胶中细菌群落结构的初步研究[J].厦门大学学报(自然科学版),2010,(05)：682-687.
[18]车凤翔.气溶胶对人类健康的影响[J].职业与健康,1990,(03)：4.
[191李沛,辛金元,王跃思,王式功,潘小川,李国星.北京市大气颗粒物污染对人群死亡率的影响研究[A].中国气象学会.S7气候环境变化与人体健康[C].中国气象学会：,2012：11.
[20]李德帅,孙博,王式功,罗双,张凌,刘晶晶.兰州市空气污染特征及其对呼吸系统疾病的影响研究[A].中国气象学会.S7气候环境变化与人体健康[C].中国气象学会：,2012：9.
[21]康凤琴,银燕,张逸轩.中国北方沙尘气溶胶对云和降水影响的数值模拟研究[J].气象,2009,35(6)：36-45.
[22]银燕,崔振雷,张华,辛金元,王莉莉.2006年中国地区大气气溶胶浓度分布特征的模拟研究[J].大气科学学报,2009,(05)：595-603.
[23]吉振明,高学杰,张冬峰,吴佳,徐影.亚洲地区气溶胶及其对中国区域气候影响的数值模拟[J].大气科学,2010,(02)：262-274.
[241崔振雷.中国地区和全球大气气溶胶浓度及光学厚度的数值模拟研究[D].南京信息工程大学,2008.
[25]牛生杰.沙尘气溶胶微结构及其对降水影响的观测和数值模拟研究[D].南京气象学院,2004.
[26]马晓燕,石广玉,郭裕福,张立盛.硫酸盐气溶胶辐射强迫的数值模拟研究[J].气候与环境研究,2004,(03)：454-464.
[271李晓东,王绍武,黄建平.火山活动对气候影响的数值模拟研究[J].应用气象学报,1994,(01)：90-97.
[28]周秀骥,李维亮,罗云峰.中国地区大气气溶胶辐射强迫及区域气候效应的数值模拟[J].大气科学,1998,(04)：34-43.
[291肖辉.气溶胶对云和降水影响的数值模拟研究[D].南京信息工程大学,2011.
[30]Ammann, C. M., G. A. Meehl, W. M. Washington, and C. S. Zender, A monthly and latitudinally varying volcanic forcing dataset in simulations of 20th century climate[J]. Geophysical Research Letters,2003,30.
[31]Kanamitsu, Masao, and Coauthors, NCEP Dynamical Seasonal Forecast System 2000[J]. Bull. Amer. Meteor. Soc.,2002,83:1019-1037,.
[32]Zhou Qing, Zhao Fengsheng, Gao Wenhua, Comparison and Analysis Between NCEP/NCAR Every-6-hours Analysis Land Surface and Air Temperature and 753 Chinese Stations' Observation in 2005[J], Meteorological Monthly,2008,34(2)(In Chinese).
[33]Kanamitsu, Masao, Wesley Ebisuzaki, Jack Woollen, Shi-Keng Yang, J. J. Hnilo. M. Fiorino. G. L. Potter, NCEP-DOE AMIP-II Reanalysis (R-2)[J]. Bull. Amer. Meteor. Soc., 2002,83:1631-1643,.
[34]Fang Zhifang, Lei Jtm. Lfi Xiaona,QuXing,Li Qian. A comparison of 500 hPa field of East-Asia between the NCEP/NCAR reanalysis data and the ERA'40 of ECMWF data[J]. Acta Meteorologica Sinica,2010,68(2):270-276. (In Chinese).
[35]Zheng Yongguang Zhang Chunxi Chen Jiong Chen Mingxuan Wang Yingchun, Climatic Background of Warm 2 Season Convective Weather in North China Based on the NCEP Analysis[J]. Acta Scientiarum Naturalium Universitatis Pekinensis,2007,43(5).(In Chinese).
[36]Buizza, Roberto, P. L. Houtekamer, Gerald Pellerin, Zoltan Toth, Yuejian Zhu, Mozheng Wei,A Comparison of the ECMWF, MSC, and NCEP Global Ensemble Prediction Systems[J]. Mon. Wea. Rev.,2005,133:1076-1097.
[37]徐影,丁一汇,赵宗慈.美国NCEP/NCAR近50年全球再分析资料在我国气候变化研究中可信度的初步分析[J].应用气象学报,2001,12(3)：337-347.
[38]Hines K M, Bromwich D H, Marshall G J. Artificial Surface Pressure Trends in the NCEP-NCAR Reanalysis over the Southern Ocean and Antarctica*[J]. Journal of Climate, 2000,13(22):3940-3952.
[39]HE Lang,WUHong-bao, ZHAO Xiao-chuan. A Comparison of Basic Statistics Derived from NCEP/NCAR[J], ECMWF ReanalysisData and CMA Data, Journal of Nanjing Institute of Meteorology,2009,32(1):54-63 (In Chinese).
[40]Bromwich, David H., Ryan L. Fogt, Strong Trends in the Skill of the ERA-40 and NCEP-NCAR Reanalyses in the High and Midlatitudes of the Southern Hemisphere, 1958-2001[J]. J. Climate,2004,17:4603-4619.
[41]Stenchikov, G. L., and Coauthors, Radiative forcing from the 1991 Mount Pinatubo volcanic eruption[J]. Journal of Geophysical Research-Atmospheres,1998,103:13837-13857.
[42]Huang, J. P., and Coauthors, Satellite-based assessment of possible dust aerosols semi-direct effect on cloud water path over East Asia[J]. Geophysical Research Letters,2006,33.
[43]Taylor KE. Summarizing multiple aspects of model performance in a single diagram[J]. J Geophys Res 2001,106:7183-7192.
[1]Rasch, P. J., et al., An overview of geoengineering the climate using stratospheric sulfate aerosols, Phil. Trans. Roy. Soc. A,2008,366:4007-4037.
[2]Jones, A., J. Haywood, O. Boucher, B. Kravitz, and A. Robock, Geoengineering by stratospheric SO2 injection:Results from the Met Office HadGEM2 climate model and comparison with the Goddard Institute for Space Studies ModelE[J], Atm. Chem. Phys.,2010, 10:5999-6006.
[3]Taylor, K. E., R. J. Stouffer, and G. A. Meehl, An overview of CMIP5 and the experiment design[J], Bull. Amer. Meteor. Soc.,2012,93:485-498,.
[4]Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.), IPCC (), Climate Change 2007:The Physical Science Basis. Contribution of Working Group Ⅰ to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change[J], Cambridge Univ. Press,2007:996.
[5]T.Andrews, J. M. Gregory, P. M. Forster, and M. J. Webb, Cloud Adjustment and its Role in CO2 Radiative Forcing and Climate Sensitivity:A Review[J], Surveys in Geophysics,2012, 33:619-635.
[6]S. S. Hou, L. P. Lei, and Z. C. Zeng, The response of global net primary productivity (NPP) to CO2 increasing and climate change:Evaluation of coupled model simulations[J], Journal of Food Agriculture & Environment,2013,11:937-944.
[7]Y. Kamae and M. Watanabe, On the robustness of tropospheric adjustment in CMIP5 models[J], Geophysical Research Letters,2012,39.
[8]O. Geoffroy, D. Saint-Martin, and A. Ribes, Quantifying the sources of spread in climate change experiments[J], Geophysical Research Letters,2012,39.
[9]A. Ahlstrom, G. Schurgers, A. Arneth, and B. Smith, Robustness and uncertainty in terrestrial ecosystem carbon response to CMIP5 climate change projections[J], Environmental Research Letters,2012,7.
[10]S. L. Stevenson, Significant changes to ENSO strength and impacts in the twenty-first century:Results from CMIP5[J], Geophysical Research Letters,2012,39.
[11]G. Villarini and G. A. Vecchi, Twenty-first-century projections of North Atlantic tropical storms from CMIP5 models[J], Nature Climate Change,2012:604-607.
[12]T. Kuhlbrodt and J. M. Gregory, Ocean heat uptake and its consequences for the magnitude of sea level rise and climate change[J], Geophysical Research Letters,2012,39.
[13]P. Good, J. M. Gregory, J. A. Lowe, and T. Andrews, Abrupt CO2 experiments as tools for predicting and understanding CMIP5 representative concentration pathway projections, Climate Dynamics,2013,40:1041-1053.
[14]Taylor, K. E., R. J. Stouffer, and G. A. Meehl, An overview of CMIP5 and the experiment design, Bull. Amer. Meteor. Soc.,2012,93:485-498.
[15]辛晓歌,吴统文,张洁.BCC气候系统模式开展的CMIP5试验介绍[J].气候变化研究进展,2012,(05)：69-73.
