中国地球系统模式对全球地表入射短波辐射和大气逆辐射的模拟效果评估

以云和地球辐射能量系统(CERES)数据集为准,量化了中国地球系统模式对地表入射短波辐射和大气逆辐射时空变化的模拟性能,明确了多模式间模拟结果存在不确定性的区域。结果表明：中国模式均能模拟出北半球地表入射短波辐射和大气逆辐射“夏高冬低”的季节变化特征。陆地上,中国模式对两个辐射分量月均值的模拟结果与CERES相当,在海洋上低于CERES结果。中国模式能模拟出地表入射短波辐射下降、大气逆辐射上升的年际变化趋势。对于2001—2014年均值,中国模式模拟的地表入射短波辐射在海洋和陆地上较CERES分别偏低3.3和3.0 W·m^-2,模拟的大气逆辐射在海洋上与CERES结果相当,在陆地上较CERES低1.3 W·m^-2。除南北纬30°附近之外,中国模式在其他纬度均低估地表入射短波辐射,以热带和北极最为明显。模式对大气逆辐射的模拟偏差呈纬向波动特征,模拟误差大值出现在高大山脉处。中国模式模拟地表入射短波辐射不确定性极大的区域分布在热带雨林和南极洲沿海,模拟大气逆辐射不确定性极大的区域分布在格林兰岛、青藏高原、安第斯山脉和南极洲沿海。     

CMIP6全球气候模式对青藏高原中东部地表感热通量模拟能力评估

利用青藏高原（以下简称高原）气象台站常规观测资料、国家青藏高原科学数据中心的青藏高原地气相互作用过程高分辨率（逐小时）综合观测数据集（2005～2016）、国际耦合模式比较计划第六阶段（CMIP6）的历史模拟试验数据和卫星辐射资料,定量评估了12个全球气候模式对1979～2014年高原中东部地表感热通量的模拟能力,并对其模拟偏差进行了成因分析。结果表明,CMIP6模式可较好地重现高原地表感热通量的年循环和季节平均的空间分布型,但数值较计算感热通量偏低,主要表现为对感热通量大值区严重低估。区域平均而言,12个模式模拟的春季高原中东部感热通量的时间演变序列整体较计算感热通量偏低,其中偏差最大的模式为MIROC6,其多年均值仅为计算值的1/3左右。进一步分析发现多模式模拟的春季高原10 m高度处风速和地气温差分别偏强和偏弱,说明CMIP6模拟的春季高原感热通量偏低可主要归因于地气温差的模拟冷偏差。地气温差的模拟冷偏差在高原中东部地区普遍存在,且地表温度和空气温度均存在明显冷偏差,尤其地表温度偏差更大,这很大程度上可能与CMIP6多模式模拟的春季高原降水偏强有关。     

辐射和积云对流过程对大气辐射通量的影响

基于中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室发展的全球大气环流谱模式(SAMIL-R42L26),研究了澳大利亚气象局研究中心(BMRC)新辐射方案和新Zhang-McFaflane积云对流方案对大气辐射通量模拟的影响.新辐射方案相比原辐射方案在辐射计算光谱分辨率、气体吸收和计算效率等方面作了很多改进,其对大气辐射通量的模拟能力相应提高.在晴空条件下,大气顶出射长波、大气吸收短波和地表入射短波等与观测的偏差较原辐射方案明显减小,尤其是在对流活跃区域.在云天条件下大气辐射通量与观测的偏差也较原辐射方案减小,但其偏差依然较大,这与模式中积云对流参数化方案模拟能力不足引起的辐射通量偏差有关.为此,换用了新Zhang-McFarlane积云对流方案,其结果表明,对流活跃区水汽含量显著增加,原对流方案中偏强的"双赤道辐合带"现象明显减弱,赤道辐合带地区的大气辐射通量偏差有明显减小,在海洋地区晴空大气顶出射长波和地表入射短波的量值及空间分布均接近观测结果,同时大气顶全球平均能量收支的年变化和观测结果趋于一致,其中模拟的伞球年平均大气顶能量收支和观测的偏差不到0.6 W/m2.试验结果同时表明,在未来研究中引入气溶胶分布、调整相关的云物理和陆面过程等物理参数化方案是进一步提高SAMIL-R42L26辐射通最模拟性能的关键.     

RegCM4对中国东部区域气候模拟的辐射收支分析

利用卫星和再分析数据,评估了区域气候模式Reg CM4对中国东部地区辐射收支的基本模拟能力,重点关注地表净短波(SNS)、地表净长波(SNL)、大气顶净短波(TNS)、大气顶净长波(TNL)4个辐射分量。结果表明:1)短波辐射的误差值在夏季较大,而长波辐射的误差值在冬季较大。但各辐射分量模拟误差的空间分布在冬、夏季都有较好的一致性。2)对于地表辐射通量,SNS表现为正偏差(向下净短波偏多),在各分量中误差最大,区域平均误差值近50 W/m2;SNL表现为负偏差(向上净长波偏多);对于大气顶辐射通量,TNS和TNL分别表现为"北负南正"的误差分布和整体正偏差。3)利用空间相关和散点线性回归方法对4个辐射分量的模拟误差进行归因分析,发现在云量、地表反照率、地表温度三个直接影响因子中,云量模拟误差的贡献最大,中国东部地区云量模拟显著偏少。     

CMIP6模式大气中南北半球际涛动的季节循环

利用1958—2014年47个CMIP6模式输出资料和NCEP/NCAR再分析资料,研究了模式大气中南北涛动(InterHemispheric Oscillation,IHO)的季节变化特征,且评估了CMIP6对IHO季节特征的模拟能力。结果表明:47个CMIP6模式都能模拟出IHO的季节演变特征,但模式间存在一定差异。通过比较,筛选出模拟IHO季节循环较好的16个模式,它们能成功模拟出半球大气质量的时间演变和空间结构。进一步分析表明,水汽对IHO季节变化有抵消作用且半球内部水汽质量变化可驱动越赤道质量流的产生;地表净短波辐射夏高冬低,其加热造成的水汽蒸发在水汽质量变化中起到重要作用;地表净长波辐射在春秋变化幅度较大,与大气质量逐月变化吻合。对比再分析资料表明,CMIP6模式模拟的半球大气质量的峰谷值变化有明显的月份偏差,且CMIP6模式模拟的地表气压异常值的偏差主要出现在北太平洋、欧亚大陆、南半球中纬度地区和两极极区,模拟的南北半球的蒸发和降水量、赤道风场、地表净长波和短波辐射通量等均存在明显的偏差。     

中国6个CMIP5模式对全球降水年际-年代际变率模拟的定量评估

本文利用美国全球降水气候中心(GPCC)的降水资料和中国参加国际第五阶段耦合模式比较计划(CMIP5)的6个气候模式[BCC_CSM1.1、BCC_CSM1.1(m)、BNU-ESM、FGOALS-s2、FGOALS-g2和FIO-ESM]的历史模拟试验的降水数据,采用可以表征降水变率相对和绝对量级的方法,定量评估了6个模式对降水年际-年代际变率的模拟能力。研究表明,观测降水的年际变率一般占总方差的65%~80%,年代际变率占总方差的10%~35%。在CMIP5历史试验中,6个模式平均的降水年际分量方差对总方差的贡献(超过70%)较观测偏强,模拟降水年代际分量的方差对总方差的贡献较小(约为10%~20%)。模式总体低估了全球平均总降水、年际降水和年代际降水的变率,但是高估了年际降水对总降水的贡献、低估了年代际降水对总降水的贡献。与观测相比,6个模式对东亚和澳大利亚地区的年代际降水的模拟都比较好,模拟与观测年代际降水方差的比值为1左右。在非洲、南美洲和海洋性大陆,BCC_CSM1.1模式模拟的降水年代际变率最接近观测;在欧亚和北美,BNU-ESM模式模拟的降水年代际变率与观测最接近。在欧亚大陆上,BCC_CSM1.1模式模拟的降水年际分量与年代际分量的方差比最接近观测;在非洲和美洲,FGOALS-s2模式模拟的降水年际分量与年代际分量的方差比最接近观测。本文的研究结果有助于理解中国当前气候模式对降水年际-年代际变率的模拟能力,以及未来改进模式。     

CMIP5全球气候模式对1981—2005年东北地表温度的模拟分析

利用中国东北1981—2005年173个气象台站观测的月平均地表(0 cm)温度资料和参加IPCC第五次评估报告的43个全球气候模式模拟结果,对比分析了CMIP5耦合气候模式对中国东北地区地表温度的模拟性能。结果表明：大部分气候模式模拟结果都能较好的再现研究区域的地表温度时空变化,与月观测的时间相关系数均高于095,对年际变化模拟能力稍差,大部分模式模拟结果在整个研究时段均表现出冷偏差。空间分布显示,CMIP5模式能够模拟出中国东北地区地表温度南高北低的空间分布特征,但不同模式模拟结果之间差异较大,模拟能力较优模式能够较好的模拟出研究区域的冷暖中心,较优模式组和较差模式组在夏季的差距达到最大,较差模式组不能再现地表温度的分布特征。通过模式优选发现FGOALS_s2模式表现最优。总的来说,CMIP5耦合气候模式对中国东北区域地表温度的时空变化特征的模拟性能较好,对气候态年变化的模拟性能好于对年际变化的模拟。     

CMIP3与CMIP5模式对中国西北干旱区气温和降水的模拟能力比较

通过对15组CMIP3和CMIP5两代模式集合平均对中国西北干旱区气温和降水的模拟能力比较,发现CMIP5模式对气温和降水的模拟更接近观测值。CMIP5模式模拟年、春季、夏季、秋季平均气温的相关系数比CMIP3模式分别提升了0.15、0.13、0.24和0.02,冬季下降了0.07。CMIP5模式对西北干旱区的平均气温变化趋势的模拟效果比CMIP3有所提高,对年、春季、夏季、秋季、冬季趋势的模拟偏差比CMIP3分别减少了0.03℃/10a、0.10℃/10a、0.01℃/10a、0.06℃/10a、0.14℃/10a。对西北干旱区平均气温年、季的模拟偏差分布上,CMIP5模式的偏差均比CMIP3低1~2℃。但是天山区年、季节平均气温的模拟与整体模拟偏低情况相反,CMIP3和CMIP5分别偏高3~6℃和1~4℃,对夏季的模拟偏高最严重,分别达到6℃和4℃。CMIP5模式整体对西北干旱区降水量的模拟结果与观测值的平均相关系数与CMIP3相差不大,均不超过0.1,而且偏差仍然较大。CMIP5模式对西北干旱区的降水量的变化趋势模拟效果比CMIP3有所降低,对年、春季、夏季、秋季、冬季趋势的模拟偏差比CMIP3增加了0.67 mm/10a、0.23 mm/10a、0.51 mm/10a、0.11 mm/10a、0.14 mm/10a。CMIP5模式对年、春季、夏季、秋季和冬季的降水量模拟的均方根误差相比CMIP3分别减少77.6 mm、25.5 mm、25.0 mm、18.8 mm和13.9 mm。在空间上,CMIP5模式对年、季节降水模拟仍然偏高,但是比CMIP3有明显缓解;CMIP3和CMIP5模式对夏季天山区年降水量和夏季降水量的模拟也与大部分区域偏高的趋势明显相反,两代模式对夏季天山区的降水模拟均偏低50 mm左右。     

CMIP5西北太平洋气候变率的模拟评估

利用观测海温资料和CMIP5模式模拟结果分析西北太平洋(120°E~120°W,20~60°N)海表温度的气候态和年代际变化特征。结果表明,所选22个模式可以较好地模拟出西北太平洋海表温度的气候特征及其年际、年代际变化特征;模式模拟的海表温度总体标准偏差在黑潮延伸体区域最大;绝大多数模式能模拟出海表温度的第一EOF模态;西北太平洋海表温度具有较明显的年代际振荡现象,13/22的模式模拟的海表温度存在明显的年代际振荡,同时海表温度气候态的模拟偏差对其周期振荡模拟的影响较大,尤其在黑潮延伸体区域。     

CMIP模式对冬季北半球大气环流与青藏高原冬春季气温相关关系的模拟评估

本文评估了36个CMIP5模式和39个CMIP6模式对近期观测中揭示的北半球冬季大气环流与高原冬春气温之间的相关关系的模拟能力。利用最大协方差(MCA)分析方法,计算并比较了观测和模式中冬季北半球200 hPa位势高度场与同后期青藏高原近地面气温的耦合关系。整体而言,大部分CMIP模式能够模拟出显著的冬季北半球大气环流与青藏高原气温之间的相关关系,且CMIP6模式模拟相关特征和作用机制的能力较CMIP5均有所提升。与观测相比,历史情景下36个CMIP5模式中有26个能够模拟出显著的大气环流与同后期高原气温之间的相关关系,其中对于相关的位势高度场空间模态的模拟明显好于对高原气温异常场空间模态的模拟。同情景下39个CMIP6模式中有37个能模拟出显著相关关系,且CMIP6模式更能模拟出观测中MCA模态的位势高度场上北极涛动(AO)和西太平洋遥相关型(WP)反相位叠加的大气环流特征。在对MCA模态时间变率的模拟上,大部分模式都能重现青藏高原整体变暖的趋势,部分模式能够模拟出观测中位势高度场时间主成分的年际变率,并且CMIP6表现要优于CMIP5。对耦合环流型的动力诊断显示,相比CMIP5模式,CMIP6中有更多模式可以模拟出极地—高原之间的遥相关波列,且对波列结构的模拟更完整。     

Understanding the Surface Temperature Cold Bias in CMIP5 AGCMs over the Tibetan Plateau

The temperature biases of 28 CMIP5 AGCMs are evaluated over the Tibetan Plateau(TP) for the period 1979–2005. The results demonstrate that the majority of CMIP5 models underestimate annual and seasonal mean surface 2-m air temperatures(T_(as)) over the TP. In addition, the ensemble of the 28 AGCMs and half of the individual models underestimate annual mean skin temperatures(T_s) over the TP. The cold biases are larger in T_(as) than in T_s, and are larger over the western TP. By decomposing the T_s bias using the surface energy budget equation, we investigate the contributions to the cold surface temperature bias on the TP from various factors, including the surface albedo-induced bias, surface cloud radiative forcing, clear-sky shortwave radiation, clear-sky downward longwave radiation, surface sensible heat flux, latent heat flux,and heat storage. The results show a suite of physically interlinked processes contributing to the cold surface temperature bias.Strong negative surface albedo-induced bias associated with excessive snow cover and the surface heat fluxes are highly anticorrelated, and the cancelling out of these two terms leads to a relatively weak contribution to the cold bias. Smaller surface turbulent fluxes lead to colder lower-tropospheric temperature and lower water vapor content, which in turn cause negative clear-sky downward longwave radiation and cold bias. The results suggest that improvements in the parameterization of the area of snow cover, as well as the boundary layer, and hence surface turbulent fluxes, may help to reduce the cold bias over the TP in the models.     

Compensating Errors in Cloud Radiative and Physical Properties over the Southern Ocean in the CMIP6 Climate Models

The Southern Ocean is covered by a large amount of clouds with high cloud albedo. However, as reported by previous climate model intercomparison projects, underestimated cloudiness and overestimated absorption of solar radiation (ASR) over the Southern Ocean lead to substantial biases in climate sensitivity. The present study revisits this long-standing issue and explores the uncertainty sources in the latest CMIP6 models. We employ 10-year satellite observations to evaluate cloud radiative effect (CRE) and cloud physical properties in five CMIP6 models that provide comprehensive output of cloud, radiation, and aerosol. The simulated longwave, shortwave, and net CRE at the top of atmosphere in CMIP6 are comparable with the CERES satellite observations. Total cloud fraction (CF) is also reasonably simulated in CMIP6, but the comparison of liquid cloud fraction (LCF) reveals marked biases in spatial pattern and seasonal variations. The discrepancies between the CMIP6 models and the MODIS satellite observations become even larger in other cloud macro- and micro-physical properties, including liquid water path (LWP), cloud optical depth (COD), and cloud effective radius, as well as aerosol optical depth (AOD). However, the large underestimation of both LWP and cloud effective radius (regional means ~20% and 11%, respectively) results in relatively smaller bias in COD, and the impacts of the biases in COD and LCF also cancel out with each other, leaving CRE and ASR reasonably predicted in CMIP6. An error estimation framework is employed, and the different signs of the sensitivity errors and biases from CF and LWP corroborate the notions that there are compensating errors in the modeled shortwave CRE. Further correlation analyses of the geospatial patterns reveal that CF is the most relevant factor in determining CRE in observations, while the modeled CRE is too sensitive to LWP and COD. The relationships between cloud effective radius, LWP, and COD are also analyzed to explore the possible uncertainty sources in different models. Our study calls for more rigorous calibration of detailed cloud physical properties for future climate model development and climate projection.     

利用MODIS和CERES遥感数据研究青藏高原的云辐射强迫效应

准确估算青藏高原的云辐射效应,对分析该地区的近地面感热通量十分重要。本文首先利用加权平均方法,分别将中分辨率成像光谱仪(MODIS)、测云雷达(CPR)和云与地球辐射能量系统(CERES)的像元数据进行融合。利用这些数据,分析了青藏高原上多云个例(2017年5月5日)与少云个例(2017年8月2日)情况下的可见光通道和热红外通道的信号、云参数和大气长短波辐射强迫等的差异。研究表明,少云时高原地区的大气顶大气长波辐射强迫为108.3 W·m-2,多云时为104.5 W·m-2。同时少云个例中塔里木盆地的大气顶大气长波辐射强迫为200.7 W·m-2,表明该辐射强迫受到地表热力状况影响较大。深厚与浅薄云区的云顶高度相差不大,但多云个例中深厚云区的短波辐射强迫是浅薄云区的2倍多,这一比例远大于长波。这表明短波辐射强迫对云厚度较敏感。最后,本文分析了CERES观测的大气顶长短波辐射分别与MODIS热红外和可见光通道之间的关系,结果表明它们存在很好的相关性(相关系数超过0.95),MODIS的可见光通道可以用于估算大气顶的短波辐射量,而MODIS的热红外通道只可用来估算云区的大气顶长波辐射量。     

The sea ice mass budget of the Arctic and its future change as simulated by coupled climate models

Arctic sea ice mass budgets for the twentieth century and projected changes through the twenty-first century are assessed from 14 coupled global climate models. Large inter-model scatter in contemporary mass budgets is strongly related to variations in absorbed solar radiation, due in large part to differences in the surface albedo simulation. Over the twenty-first century, all models simulate a decrease in ice volume resulting from increased annual net melt (melt minus growth), partially compensated by reduced transport to lower latitudes. Despite this general agreement, the models vary considerably regarding the magnitude of ice volume loss and the relative roles of changing melt and growth in driving it. Projected changes in sea ice mass budgets depend in part on the initial (mid twentieth century) ice conditions; models with thicker initial ice generally exhibit larger volume losses. Pointing to the importance of evolving surface albedo and cloud properties, inter-model scatter in changing net ice melt is significantly related to changes in downwelling longwave and absorbed shortwave radiation. These factors, along with the simulated mean and spatial distribution of ice thickness, contribute to a large inter-model scatter in the projected onset of seasonally ice-free conditions.     

CMIP6火山强迫的气候响应模拟比较计划（VolMIP）概况与评述

为揭示造成火山强迫气候响应模拟不确定性的原因,第六次国际耦合模式比较计划（CMIP6）设立了火山强迫的气候响应模拟比较计划（VolMIP)。该计划由基于历史火山爆发的理想火山扰动试验组成,包括三组主要的试验：第一组关注短期（季节至年际）大气动力响应;第二组关注海气耦合系统的长期（年际至年代际）响应;第三组关注气候系统对火山群的响应。VolMIP旨在通过给定相同的辐射强迫并进行多成员集合模拟,揭示模式对外强迫响应的不确定性,通过设定不同的背景气候态,阐明内部变率和外强迫对气候响应的相对贡献。     

The respective roles of surface temperature driven feedbacks and tropospheric adjustment to CO2 in CMIP5 transient climate simulations

An overview of radiative climate feedbacks and ocean heat uptake efficiency diagnosed from idealized transient climate change experiments of 14 CMIP5 models is presented. Feedbacks explain about two times more variance in transient climate response across the models than ocean heat uptake efficiency. Cloud feedbacks can clearly be identified as the main source of inter-model spread. Models with strong longwave feedbacks in the tropics feature substantial increases in cloud ice around the tropopause suggestive of changes in cloud-top heights. The lifting of the tropical tropopause goes together with a general weakening of the tropical circulation. Distinctive inter-model differences in cloud shortwave feedbacks occur in the subtropics including the equatorward flanks of the storm-tracks. Related cloud fraction changes are not confined to low clouds but comprise middle level clouds as well. A reduction in relative humidity through the lower and mid troposphere can be identified as being the main associated large-scale feature. Experiments with prescribed sea surface temperatures are analyzed in order to investigate whether the diagnosed feedbacks from the transient climate simulations contain a tropospheric adjustment component that is not conveyed through the surface temperature response. The strengths of the climate feedbacks computed from atmosphere-only experiments with prescribed increases in sea surface temperatures, but fixed CO₂ concentrations, are close to the ones derived from the transient experiment. Only the cloud shortwave feedback exhibits discernible differences which, however, can not unequivocally be attributed to tropospheric adjustment to CO₂. Although for some models a tropospheric adjustment component is present in the global mean shortwave cloud feedback, an analysis of spatial patterns does not lend support to the view that cloud feedbacks are dominated by their tropospheric adjustment part. Nevertheless, there is positive correlation between the strength of tropospheric adjustment processes and cloud feedbacks across different climate models.     

Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble

Warm sea-surface temperature (SST) biases in the southeastern tropical Atlantic (SETA), which is defined by a region from 5°E to the west coast of southern Africa and from 10°S to 30°S, are a common problem in many current and previous generation climate models. The Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble provides a useful framework to tackle the complex issues concerning causes of the SST bias. In this study, we tested a number of previously proposed mechanisms responsible for the SETA SST bias and found the following results. First, the multi-model ensemble mean shows a positive shortwave radiation bias of ~20 W m^?2, consistent with models’ deficiency in simulating low-level clouds. This shortwave radiation error, however, is overwhelmed by larger errors in the simulated surface turbulent heat and longwave radiation fluxes, resulting in excessive heat loss from the ocean. The result holds for atmosphere-only model simulations from the same multi-model ensemble, where the effect of SST biases on surface heat fluxes is removed, and is not sensitive to whether the analysis region is chosen to coincide with the maximum warm SST bias along the coast or with the main SETA stratocumulus deck away from the coast. This combined with the fact that there is no statistically significant relationship between simulated SST biases and surface heat flux biases among CMIP5 models suggests that the shortwave radiation bias caused by poorly simulated low-level clouds is not the leading cause of the warm SST bias. Second, the majority of CMIP5 models underestimate upwelling strength along the Benguela coast, which is linked to the unrealistically weak alongshore wind stress simulated by the models. However, a correlation analysis between the model simulated vertical velocities and SST biases does not reveal a statistically significant relationship between the two, suggesting that the deficient coastal upwelling in the models is not simply related to the warm SST bias via vertical heat advection. Third, SETA SST biases in CMIP5 models are correlated with surface and subsurface ocean temperature biases in the equatorial region, suggesting that the equatorial temperature bias remotely contributes to the SETA SST bias. Finally, we found that all CMIP5 models simulate a southward displaced Angola–Benguela front (ABF), which in many models is more than 10° south of its observed location. Furthermore, SETA SST biases are most significantly correlated with ABF latitude, which suggests that the inability of CMIP5 models to accurately simulate the ABF is a leading cause of the SETA SST bias. This is supported by simulations with the oceanic component of one of the CMIP5 models, which is forced with observationally derived surface fluxes. The results show that even with the observationally derived surface atmospheric forcing, the ocean model generates a significant warm SST bias near the ABF, underlining the important role of ocean dynamics in SETA SST bias problem. Further model simulations were conducted to address the impact of the SETA SST biases. The results indicate a significant remote influence of the SETA SST bias on global model simulations of tropical climate, underscoring the importance and urgency to reduce the SETA SST bias in global climate models.     

CMIP6全球气候模式对中国极端降水模拟能力的评估及其与CMIP5的比较

对CMIP6全球气候模式在中国地区极端降水的模拟能力进行了综合评估。基于CN05.1观测数据集和32个CMIP6全球气候模式的降水数据,采用8个常用极端降水指数对极端降水进行了定量描述。研究结果表明,在极端降水的气候平均态方面,CMIP6多模式集合对1961—2005年中国地区区域平均的8个极端降水指数模拟的平均相对误差为29.94%,相较CMIP5降低了2.95个百分点。极端降水的气候变率方面,CMIP6多模式集合对区域平均的8个极端降水指数模拟的平均相对误差为10.10%,相较CMIP5降低5.45个百分点。此外,利用TS评分进行模式间比较,CMIP6的平均分（0.78）高于CMIP5（0.75）,且模拟能力排名前五的模式中CMIP6占4个。对比14个同源模式的TS评分可以发现,CMIP6（0.91）相对于CMIP5（0.68）的模拟能力显著提高。进一步研究发现,CMIP6相对于CMIP5对不同区域极端降水模拟能力的改进有所区别:CMIP6对干旱区平均的气候态和变率方面改进明显,而对于湿润区的改进主要表现在对极端降水空间相关模拟能力的提高。综上,在中国地区,CMIP6相较于CMIP5对极端降水的模拟能力总体上有提升。      

Asymmetry of surface climate change under RCP2.6 projections from the CMIP5 models

The multi-model ensemble (MME) of 20 models from the Coupled Model Intercomparison Project Phase Five (CMIP5) was used to analyze surface climate change in the 21st century under the representative concentration pathway RCP2.6, to reflect emission mitigation efforts. The maximum increase of surface air temperature (SAT) is 1.86°C relative to the pre-industrial level, achieving the target to limit the global warming to 2°C. Associated with the “increase-peak-decline” greenhouse gases (GHGs) concentration pathway of RCP2.6, the global mean SAT of MME shows opposite trends during two time periods: warming during 2006–55 and cooling during 2056–2100. Our results indicate that spatial distribution of the linear trend of SAT during the warming period exhibited asymmetrical features compared to that during the cooling period. The warming during 2006–55 is distributed globally, while the cooling during 2056–2100 mainly occurred in the NH, the South Indian Ocean, and the tropical South Atlantic Ocean. Different dominant roles of heat flux in the two time periods partly explain the asymmetry. During the warming period, the latent heat flux and shortwave radiation both play major roles in heating the surface air. During the cooling period, the increase of net longwave radiation partly explains the cooling in the tropics and subtropics, which is associated with the decrease of total cloud amount. The decrease of the shortwave radiation accounts for the prominent cooling in the high latitudes of the NH. The surface sensible heat flux, latent heat flux, and shortwave radiation collectively contribute to the especial warming phenomenon in the high-latitude of the SH during the cooling period.