CMIP6检测归因模式比较计划（DAMIP）概况与评述

气候变化的检测归因是历次IPCC评估报告的重要组成部分。检测归因的目标是检测并量化由外强迫引起的变化,识别人为和自然强迫对气候变化的相对贡献。有助于全面评估气候系统是如何受人类活动影响的,所得结论对未来气候变化预估的信度而言至关重要。检测归因模式比较计划(DAMIP)是第六次国际耦合模式比较计划(CMIP6)的一个子计划,共包含3个级别、多达14组不同强迫驱动下的试验。文中概述其科学背景、试验设计、参与模式情况,并评述该计划的意义、期待的产出以及中国的机遇和贡献,以期使读者迅速了解相关要点和进展,为利用这些模式模拟试验数据开展检测归因研究提供必要的参考。     

第六次国际耦合模式比较计划（CMIP6）评述

世界气候研究计划（WCRP）发起了新一轮的国际耦合模式比较计划（CMIP6),目的是回答当前气候变化领域面临的新的科学问题,为实现WCRP“大挑战”计划所确立的科学目标提供数据支撑。文中回顾了CMIP的发展历程,介绍了CMIP6的组织思路,阐述了CMIP6核心试验及23个模式比较子计划（MIPs）的科学关注点,总结了参与CMIP6的全球模式概况以及中国的贡献。最后,从继承性和创新性等角度对CMIP6进行了评述,指出了CMIP6组织和实施中存在的问题,并对CMIP未来的发展进行了展望。     

参加CMIP5计划的四个中国模式模拟的东亚地区降水结构特征及未来变化

在全球变暖的背景下, 降水特征的改变体现为降水总量和降水结构的变化。由于缺乏较为长期、覆盖范围广的较高分辨率逐日降水资料, 过去对东亚降水的研究多关注其降水量的长期趋势和时空变率, 较少涉及降水结构的变化。本文利用当前最新且分辨率最高、覆盖范围最广的逐日亚洲陆地降水数据集(简称APHRODITE)以及四个中国参加第五次国际耦合模式比较计划(简称CMIP5)的模式(BCC-CSM1-1, BNU-ESM, FGOALS-g2和FGOALS-s2), 研究了东亚地区降水结构的观测特征及四个模式的模拟能力。基于此, 通过分析四个模式的未来预估试验, 探讨东亚地区降水结构在全球变暖背景下的变化。结果表明:整个东亚地区的累积降水量呈现出随着降水强度的增加先增加后减小的分布形态;降水频率则是随着强度的增加显著减小。小雨(中雨)呈现出南少北多(南多北少)的形态;强降水则较多分布在华南沿海以及日本南部地区。长期趋势上, 整个东亚地区大体上呈现小雨和30 mm/d以上的大雨增加, 而中等强度降水减少的变化趋势。四个模式对东亚降水结构的气候态模拟能力较好。BCC-CSM1-1和FGOALS-g2能够合理再现观测中各个强度降水的变化趋势, 而其他模式模拟不出中雨的减小趋势。四个模式的未来预估表明, 在全球变暖的背景下, 东亚地区30 mm/d以上的强降水会增加。且降水强度越大, 增加越明显。以30°N为界, 小雨(中雨)在变暖背景下呈现南部增加北部减少(南部减少北部增加)的变化趋势。     

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

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

Surface Air Temperature Projection Under 1.5 ℃ Warming Threshold Based on Corrected Pattern Scaling Technique

The global mean temperature during the recent decade (2007-2016) has increased above 1 ℃ relative to the pre-industrial period (1861-1890). The climate change and impact under 1.5 ℃ warming in the future have become a great concern in global society. Temperature projections, especially in regional scale, show great uncertainty depending on used climate models. Taking advantage of pattern scaling technique and observed temperature changes during 1951-2005, we tried to project the temperature changes globally under 1.5 ℃ threshold relative to current climate state, i.e. about 1 ℃ warming around 2007-2016. The projections of 21 climate models from the Coupled Model Intercomparison Project - Phase 5 under four Representative Concentration Pathways (RCP2.6, RC4.5, RCP6.0 and RCP8.5) were used to correct the assumptions in pattern scaling. Results showed that the geographical distribution and warming amplitude of surface air temperature changes under 1.5 ℃ threshold are similar in the four scenarios. Warming over most of the land would be above 0.6 ℃, 0.3 ℃ warmer than ocean. The Northern Hemisphere would be 0.2 ℃ warmer than the Southern Hemisphere. The temperature over China region will increase by 0.7 ℃. The warming in the Northern and Central China under RCP2.6 was obviously higher than that in the other scenarios. Ignoring the impact of correction method, uncertainty in temperature projection based on pattern scaling was much smaller than that in climate models, both in global and regional scales.     

CAS-ESM2.0 Model Datasets for the CMIP6 Ocean Model Intercomparison Project Phase 1(OMIP1)

As a member of the Chinese modeling groups,the coupled ocean-ice component of the Chinese Academy of Sciences’Earth System Model,version 2.0(CAS-ESM2.0),is taking part in the Ocean Model Intercomparison Project Phase 1(OMIP1)experiment of phase 6 of the Coupled Model Intercomparison Project(CMIP6).The simulation was conducted,and monthly outputs have been published on the ESGF(Earth System Grid Federation)data server.In this paper,the experimental dataset is introduced,and the preliminary performances of the ocean model in simulating the global ocean temperature,salinity,sea surface temperature,sea surface salinity,sea surface height,sea ice,and Atlantic Meridional Overturning Circulation(AMOC)are evaluated.The results show that the model is at quasi-equilibrium during the integration of 372 years,and performances of the model are reasonable compared with observations.This dataset is ready to be downloaded and used by the community in related research,e.g.,multi-ocean-sea-ice model performance evaluation and interannual variation in oceans driven by prescribed atmospheric forcing.     

降尺度CMIP6模式对新疆降水模拟评估

基于6个CMIP6模式的日降水量数据,采用降尺度方法将其统一分辨率到0.25°×0.25°,选取5个极端降水指数从降水气候态、极端性、季节性三个角度对新疆区域1961—2014年历史期降水模拟效果评估。结果表明,降尺度CMIP6模式能较好再现新疆区域降水的空间分布特征,最大年均降水量误差小于30 mm,夏季降水模拟效果最佳相关系数均高于0.8。模式在春秋季对降水的模拟效果差异较小,标准差比值均在1.00 ~ 1.25之间,ACCESS-CM2模拟效果最佳。模式集合均值能模拟出观测降水增多趋势,但低估了降水的年际变率,模拟结果提示新疆80年代的降水转折可能与人类活动有关。在降水极端性和季节性方面,降尺度数据对新疆的极端降水和季节性降水均有较好的模拟性能,降尺度数据对季节性降水的模拟能力（与观测均值误差小于0.001）比原始分辨率的数据（与观测误差大于0.005）效果更好。     

中国地球气候系统模式研究进展：CMIP计划实施近20年回顾

在系统总结过去20年从CMIP1到CMIP4世界各国模式的综合情况基础上,回顾了中国气候模式参与CMIP科学试验的概况。在此基础上,慨述了CMIP5的试验设计,总结了参加CMIP5的5个中国气候模式的特点。随后,从高分辨率模式研发、地球系统模式研发、地球气候系统模式最为关键的分量——大气环流模式和海洋环流模式研发的角度,提出了中国地球气候系统模式发展面临的挑战,指出了中国模式发展面临的机遇。针对如何从国家层次协调以实现地球气候模式的可持续发展问题,给出了美国国家科学院最近发布的《推动气候模拟的国家战略》所提出的九条措施作为参考。     

8个CMIP5模式对中国极端气温的模拟和预估

利用8个耦合模式比较计划第五阶段（CMIP5）模式结果,采用加权平均方法进行多模式集合,并与NCEP再分析资料进行对比分析,评估了CMIP5模式对中国极端气温的模拟效果,在此基础上,对未来极端气温进行预估。CMIP5模式对中国8个极端气温指数和20年一遇最高（低）气温有模拟能力,所有极端气温指数模拟和观测结果的时间相关均达到0.10显著性水平,20年一遇最高、最低气温模拟和观测结果空间相关系数均超过0.98。在中等排放RCP4.5情景下,未来中国极暖（冷）日数增多（减少）,到21世纪中期热浪指数增加2.6倍,到21世纪末期寒潮指数减少71%,20年一遇最高（低）气温在中国地区均呈现升高趋势,局部升温幅度达到4℃。     

基于CMIP5资料的东亚夏季环流的BMA预测研究

利用CMIP5的17个全球气候系统模式对500 hPa位势高度场的年代际回报结果,采用距平相关系数、均方根误差、平均绝对误差及连续等级概率评分4种指标,评估了贝叶斯模式平均(Bayesian model average,BMA)预报方法对东亚夏季环流的回报能力,并与最优单模式MIROC5和多模式简单集合平均结果进行了比较。结果表明,BMA方法对东亚夏季500 hPa位势高度场的回报效果是最好的,优于最优单模式MIROC5和简单集合平均的回报结果。BMA模型能产生高集中度的概率密度函数,并包含了多模式集成回报不确定性的定量估计。此外,BMA方法对西太平洋副热带高压的年际变率也有较好的回报效果,对西太平洋副热带高压的预报,选取60~70%概率下的结果更为合理。