气候变化是人类21世纪面临的重大挑战之一。在温室气体减排谈判日益艰难的背景下，一些科学家提议利用地球工程（geoengineering）措施人为地降低地球温度，以抑制全球变暖，并在近几年逐步发展成为国际热点问题。太阳辐射管理（Solar Radiation Management，SRM）这类地球工程由于其成本相对较低、降温快但可能带来较大负面影响的特点倍受关注。本文基于地球工程模式比较计划（Geoengineering Model Intercomparison Project, GeoMIP）中G1、G2、G3和G4这4种SRM实验展开研究，其中G1模拟的是减少太阳辐射以抵消CO2 浓度瞬间增加到工业革命前的4倍而引起的辐射强迫；G2模拟减少太阳辐射以抵消大气CO2 浓度以每年1%的速度增长而引起的辐射强迫；G3模拟在RCP 4.5 的辐射强迫背景下，在平流层中注入气溶胶以使辐射强迫维持在RCP 4.5情景下2020年的水平；G4模拟在RCP 4.5 的辐射强迫背景下，每年向平流层注入5×109 kg SO2。利用这4种SRM实验下的多模式数据，本文分析了不同SRM下气温和降水变化的稳健特征、减缓气温和降水变化的效率以及区域差异性，同时本文分析了G1下北极海冰和大气环流变化，以及造成北极海冰变化的原因。研究发现：（1） 在气温变化方面，G1和G2实验下的全球平均气温接近于工业革命前，但赤道地区的气温比工业革命前更低，而两极地区极的气温比工业革命前更高。G3和G4实验下气温变化的空间分布与G1和G2不同，赤道地区的温度也有所增加。在降水变化方面，G1和G2下的全球平均降水均显著下降，但G3和G4下的全球平均降水并没有明显减少。无论是在实施和不实施SRM的模拟实验下，亚马逊流域的降水均会减少。（2） 在减缓效率和区域差异性方面，4种SRM减缓气温变化的效率远高于减缓降水变化的效率。G1、G3 和G4 减缓气温和降水变化的区域差异性均不在背景噪音的范围内，即是显著的，但是G2减缓气温和降水变化的区域差异性均不显著。尽管许多模式中4种SRM之间的区域差异性和减缓效率没有显著差异，但超过一半的模式中太阳辐射减少情景（G1和G2）减缓温度变化的效率显著地高于SO2平流层注入情景（G3和G4）。本文凸显了模式间处理一些关键地球工程过程（如平流层气溶胶）时的较大差异，以及这些差异对评估SRM的减缓效率和区域差异性的影响。（3） 在北极海冰和大气环流变化方面，G1实验成功地将北极地区的平均升温控制在了1°C左右，并伴随着一定程度的海冰季节循环变化。夏季和秋季海冰变化的空间分布与温度变化的空间分布相关性较好，冬季和春季的相关性较小。4个季节中均有些地区的海冰变化幅度高达±20%，这将会引起大气环流形态的变化。另外，多数模式中冬季500hPa的位势高度呈现出类似于PNA负相位的变化。在夏季和秋季，各模式的结果均呈现出在波弗特海、楚科奇海、东西伯利亚海和拉普捷夫海的海冰与工业革命前相比有所减少，而有些模式显示巴伦支/喀拉海的海冰增加。G1下冬季和春季巴伦支海的海冰减少与进入该地区的气旋活动增加有关。

Climate change is one of the most challenging issues for human beings in 21st centry. As the slow progress in negotiation of greenhouse gas emission reduction, some scientists proposed to artificially cool the Earth by using geoengineering, the technology that deliberately change the planet environment to counteract the global warming and gains wide attentions in recent years. Solar radiation management (SRM), one type of geoengineering that could be deployed with a relative low cost and raise many potential side effects, concerns scientists, media and general publics. We use the multimodel results from Geoengineering Model Intercomparison Project (GeoMIP) experiments to analyze the temperature and precipitation change, compensation effectiveness and regional inequality of four SRMs and the impact of SRM on Arctic sea ice and atmospheric circulation. The four GeoMIP SRM experiments are G1 (offsetting 4×CO2 via solar reduction), G2 (offsetting CO2 that increased by 1% per year), G3 (offsetting increasing radiative forcing under RCP4.5 with increasing stratospheric aerosol) and G4 (injection of 5×109 kg SO2 a-1 into the stratosphere under RCP4.5 radiative forcing background). Our research found that,(1) The global average temperature change under G1 and G2 are close to pre-industral level,but with pattern of cooler tropics and warmer polar. Unlike G1 and G2 temperature and precpitation change pattern, there is no cooling over tropics and no reduction of global average precipitation relative to RCP4.5 2010-2019 baseline climate under the two SO2 injection scenarios(G3 and G4). (2) The regional inequalities in temperature and precipitation compensation for experiment G1, G3 and G4 are significantly different from their corresponding background noises for most models, but the regional inequalities for G2 are not significantly different from corresponding noises. Differences in the regional inequalities and the actual effectiveness among the four SRM scenarios are not significant for many models. However, in more than half of the models, the effectiveness for temperature in the solar dimming geoengineering scenarios (G1 and G2) is significantly higher than that in the SO2 geoengineering scenarios (G3 and G4). The effectiveness of the four SRM experiments in compensating for temperature change is considerably higher than for precipitation. The methodology used in this study highlights that large across-model variation in the treatment of key geoengineering processes (such as stratospheric aerosols) and the quantification of damage caused by climate change creates significant uncertainties in any strategies to achieve optimal compensation effectiveness across different regions.(3) G1 successfully moderates annually averaged Arctic temperature rise to about 1°C, with modest changes in seasonal sea ice cycle compared with the pre-industrial control simulations (piControl). Changes in summer and autumn sea ice extent are spatially correlated with temperature patterns, but much less in winter and spring seasons. However, there are changes of ±20% in sea ice concentration in all seasons, and these will induce changes in atmospheric circulation patterns. For most models under G1, winter 500 hPa geopotential height changes resemble a PNA negative phase pattern. In summer and autumn, the models consistently simulate less sea ice relative to pre-industrial simulations in the Beaufort, Chukchi, East Siberian and Laptev Seas, and some models show increased sea ice in the Barents/Kara Seas region. Sea ice extent increases in the Greenland Sea, particularly in winter and spring, and is to some extent associated with changed sea ice drift. Decreased sea ice cover in winter and spring in the Barents Sea is associated with increased cyclonic activity entering this area under G1.