全球变暖减缓期陆地地表气温变化特征和CMIP5多模式的未来情景预估

2000年后全球气温的增温率显著下降,全球进入变暖减缓期.本文基于CRU(Climatic Research Unit) 观测资料,分析讨论了2000年后全球及欧亚中高纬度地区全球变暖的减缓特征,评估了CMIP5(Coupled Model Intercomparison Project Phase 5)试验多模式对全球变暖减缓的模拟及未来气温变化预估.结果表明,2000年后全球陆地平均地面气温的增温率大幅下降至0.14℃ (10 a)-1,仅为1976~1999年加速期增温率的一半.全球陆地13个区域中有9个地区的增温率小于2000年前,4个地区甚至出现了降温.其中以欧亚中高纬地区最为特殊.加速期(1976~1999年)增温率达到0.50℃ (10 a)-1,为全球陆地最大,2000年后陡降至-0.17℃ (10 a)-1,为全球最强降温区,为全球变暖的减缓贡献了49.13%.并且具有显著的季节依赖,减缓期冬季增温率下降了-2.68℃ (10 a)-1,而秋季升高了0.86℃ (10 a)-1,呈现反位相变化特征.CMIP5多模式计划中仅BCC-CSM1.1在RCP2.6情景下和MRI-ESM1模式在RCP8.5下的模拟较好地预估了全球及欧亚中高纬地区在2000年后增温率的下降以及欧亚中高纬秋、冬温度的反位相变化特征.BCC-CSM1.1在RCP2.6情景下预估欧亚中高纬地区2012年后温度距平保持在1.2℃左右,2020年后跃至2℃附近振荡.而MRI-ESM1在RCP8.5情景下预估的欧亚中高纬度温度在2030年前一直维持几乎为零的增温率,之后迅速升高.     

Evaluating the formation mechanisms of the equatorial Pacific SST warming pattern in CMIP5 models

Based on the historical and RCP8.5 runs of the multi-model ensemble of 32 models participating in CMIP5, the present study evaluates the formation mechanisms for the patterns of changes in equatorial Pacific SST under global warming.Two features with complex formation processes, the zonal El Ni ?no-like pattern and the meridional equatorial peak warming(EPW), are investigated. The climatological evaporation is the main contributor to the El Ni ?no-like pattern, while the ocean dynamical thermostat effect plays a comparable negative role. The cloud–shortwave-radiation–SST feedback and the weakened Walker circulation play a small positive role in the El Ni ?no-like pattern. The processes associated with ocean dynamics are confined to the equator. The climatological evaporation is also the dominant contributor to the EPW pattern, as suggested in previous studies. However, the effects of some processes are inconsistent with previous studies. For example,changes in the zonal heat advection due to the weakened Walker circulation have a remarkable positive contribution to the EPW pattern, and changes in the shortwave radiation play a negative role in the EPW pattern.     

The Southwest Indian Ocean thermocline dome in CMIP5 models: Historical simulation and future projection

Using 20 models of the Coupled Model Intercomparison Project Phase 5 (CMIP5), the simulation of the Southwest Indian Ocean (SWIO) thermocline dome is evaluated and its role in shaping the Indian Ocean Basin (IOB) mode following El Niño investigated. In most of the CMIP5 models, due to an easterly wind bias along the equator, the simulated SWIO thermocline is too deep, which could further influence the amplitude of the interannual IOB mode. A model with a shallow (deep) thermocline dome tends to simulate a strong (weak) IOB mode, including key attributes such as the SWIO SST warming, antisymmetric pattern during boreal spring, and second North Indian Ocean warming during boreal summer. Under global warming, the thermocline dome deepens with the easterly wind trend along the equator in most of the models. However, the IOB amplitude does not follow such a change of the SWIO thermocline among the models; rather, it follows future changes in both ENSO forcing and local convection feedback, suggesting a decreasing effect of the deepening SWIO thermocline dome on the change in the IOB mode in the future.     

Projected Shifts in Kppen Climate Zones over China and Their Temporal Evolution in CMIP5 Multi-Model Simulations

Previous studies have examined the projected climate types in China by 2100. This study identified the emergence time of climate shifts at a 1?scale over China from 1990 to 2100 and investigated the temporal evolution of K o¨ppen–Geiger climate classifications computed from CMIP5 multi-model outputs. Climate shifts were detected in transition regions(7%–8% of China's land area) by 2010, including rapid replacement of mixed forest(Dwb) by deciduous forest(Dwa) over Northeast China, strong shrinkage of alpine climate type(ET) on the Tibetan Plateau, weak northward expansion of subtropical winterdry climate(Cwa) over Southeast China, and contraction of oceanic climate(Cwb) in Southwest China. Under all future RCP(Representative Concentration Pathway) scenarios, the reduction of Dwb in Northeast China and ET on the Tibetan Plateau was projected to accelerate substantially during 2010–30, and half of the total area occupied by ET in 1990 was projected to be redistributed by 2040. Under the most severe scenario(RCP8.5), sub-polar continental winter dry climate over Northeast China would disappear by 2040–50, ET on the Tibetan Plateau would disappear by 2070, and the climate types in 35.9%and 50.8% of China's land area would change by 2050 and 2100, respectively. The results presented in this paper indicate imperative impacts of anthropogenic climate change on China's ecoregions in future decades.     

Cloud Radiative Effects and Changes Simulated by the Coupled Model Intercomparison Project Phase 5 Models

Using 32 CMIP5(Coupled Model Intercomparison Project Phase 5) models, this study examines the veracity in the simulation of cloud amount and their radiative effects(CREs) in the historical run driven by observed external radiative forcing for 1850–2005, and their future changes in the RCP(Representative Concentration Pathway) 4.5 scenario runs for2006–2100. Validation metrics for the historical run are designed to examine the accuracy in the representation of spatial patterns for climatological mean, and annual and interannual variations of clouds and CREs. The models show large spread in the simulation of cloud amounts, specifically in the low cloud amount. The observed relationship between cloud amount and the controlling large-scale environment are also reproduced diversely by various models. Based on the validation metrics,four models—ACCESS1.0, ACCESS1.3, Had GEM2-CC, and Had GEM2-ES—are selected as best models, and the average of the four models performs more skillfully than the multimodel ensemble average.All models project global-mean SST warming at the increase of the greenhouse gases, but the magnitude varies across the simulations between 1 and 2 K, which is largely attributable to the difference in the change of cloud amount and distribution. The models that simulate more SST warming show a greater increase in the net CRE due to reduced low cloud and increased incoming shortwave radiation, particularly over the regions of marine boundary layer in the subtropics. Selected best-performing models project a significant reduction in global-mean cloud amount of about-0.99% K~(-1)and net radiative warming of 0.46 W m~(-2)K~(-1), suggesting a role of positive feedback to global warming.     

CMIP5多模式模拟两类El Ni(n)o海表盐度分布及与降水的关系

利用CMIP5提供的25个工业革命前控制试验(piControl)模拟数据评估了热带太平洋两类El Ni(n)o(即东部EP和中部CP型El Ni(n)o)的海表盐度(SSS)空间结构差异及其与海表温度(SST)和降水的关系.结果表明:(1)大部分模式能够模拟出EP和CP型空间结构,两类El Ni(n)o中的SST、降水和SSS的空间技巧评分依次减小,其中,EP型SST和降水水平分布的模拟能力强于CP型,SSS则为CP型强于EP型,CP型模拟的SST、SSS和降水异常中心位置较EP型偏西且强度偏弱;(2) CP型SST、降水和SSS三者空间分布的线性一致性比EP型好,即在CP型中,SST影响降水,进而影响SSS,同时SSS对SST调制的反馈机制较显著,而对于EP型,由于海洋水平平流和非局地效应等因素,使得SST与SSS空间对应较差;(3)依据多模式模拟的SSS空间技巧评分高低将CMIP5模式分为两类,技巧评分低(高)的模式模拟的SST、SSS和降水异常值的中心位置偏西(偏东),引起中心位置偏移的原因与模式模拟赤道太平洋冷舌的位置有关,即赤道太平洋冷舌西伸显著,导致发生El Ni(n)o时SST异常变暖西伸显著,进而使得降水异常和SSS异常位置偏西.同时,技巧评分低的模式还易出现向东南延伸的负SSS异常,原因是双赤道辐合带的东南分支过于明显,即降水偏多,导致SSS偏淡.SSS变化会影响ENSO的发生发展.因此,探讨两类El Ni(n)o盐度分布的差异及相关物理场的关系,为提高模式的气候模拟和预测提供有益的借鉴.     

CMIP6模式中的中国冬季气温主要区域空间模态及与观测的对比分析

利用国际耦合模式比较计划第六阶段（CMIP6）的全球气候模式历史模拟试验资料，通过旋转经验正交函数分析得到了CMIP6模式中的我国冬季气温变化主要的区域空间模态。结果表明：CMIP6多模式集合平均中我国冬季气温有4个主要的区域空间模态，分别为中原—西北型，华南型，东北型以及滇藏型。其中，东北型与滇藏型是较为稳定的空间模态，在所选CMIP6模式及观测资料中都稳定存在，这也是前人研究中一致性较高的模态。而我国新疆、西北、华中及华南地区的冬季气温在空间分型上存在分歧，这些地区的分型在以往研究中的一致性也较差。华南型在所选CMIP6模式内是一致存在的模态，中原—西北型在模式内部的差异性较大。在近40 a观测资料中，新疆及西北到我国南方为统一的空间分型，在CMIP6多模式集合平均的结果中新疆及西北地区气温空间分布与我国中原地区的联系更为紧密。CMIP6模式能较好地模拟出与低温空间分布有直接联系的对流层中层的槽的位置，当CMIP6模式和观测中的冬季气温都表现为同一个空间模态时，该模态所对应的对流层中层的主要环流系统在观测和CMIP6模式中也是一致的。     

基于CMIP6模式数据的1961—2100年青藏高原地表气温时空变化分析

基于第六次国际耦合模式比较计划（CMIP6）的22个地球气候/系统模式模拟数据,分析了1961—2100年期间青藏高原年均地表气温在不同情景下的时空变化。结果表明,多模式集合平均的模拟结果优于大多数单个模式。由于共享社会经济路径（SSP）和辐射强迫的不同,在SSP1-2.6、SSP2-4.5、SSP3-7.0和SSP5-8.5四种情景下,2015—2100年间青藏高原年均地表气温的增温趋势分别为0.10 ℃·（10a）^-1、0.29 ℃·（10a）^-1、0.53 ℃·（10a）^-1和0.69 ℃·（10a）^-1,帕米尔高原、藏北高原中西部和巴颜喀拉山区为三个升温中心。相对于1995—2014年参考时段,到本世纪中期（2041—2060年）,青藏高原区域年均地表气温将分别增加1.37 ℃、1.72 ℃、1.98 ℃和2.30 ℃,而到本世纪末期（2081—2100年）,年均地表气温将分别增加1.42 ℃、2.65 ℃、4.28 ℃和5.38 ℃。与《巴黎协定》提出的到本世纪末全球平均气温升高不超过2 ℃目标相比,无论在哪种情景下,到本世纪中期时青藏高原年均地表气温相对于工业革命前均升高超过2 ℃,这会造成极大的气候生态环境问题。     

1979—2100年青藏高原夏季大气0 ℃层高度变化分析

大气0 ℃层高度是决定青藏高原冰冻圈消融状态的重要指标。基于ERA5再分析资料,分析了1979—2019年青藏高原夏季大气0 ℃层高度时空变化,发现青藏高原夏季大气0 ℃层高度介于4 423~5 972 m之间,以高原中南部（30°~32° N,83.5°~88.5° E）为高值中心,呈纬向分带状向四周逐渐降低。过去41 a青藏高原夏季大气0 ℃层高度总体呈持续上升趋势,高原北部上升趋势大于南部,祁连山地区上升趋势最为明显,为60 m?（10a）^-1,而在高原西南部略呈下降趋势。平均而言,青藏高原夏季地面温度每升高1 ℃,大气0 ℃层高度升高122 m。利用CMIP6模式数据,预估在SSP1-2.6、SSP2-4.5、SSP3-7.0和SSP5-8.5四种社会共享路径情景下,2020—2100年期间青藏高原夏季大气0 ℃层高度都呈现升高趋势,但不同情景下升高趋势在空间上差别较大。相对于1979—2014年参考时段,在四种情景下,到2081—2100年青藏高原夏季平均大气0 ℃层高度将分别升高265 m、394 m、576 m 和729 m;相对应的是到2081—2100年,在高原上处于夏季大气0 ℃层高度以下的冰川面积分别为第二次冰川编目数据的79%、86%、94%和98%。仅从夏季大气0 ℃层高度变化角度看,在SSP5-8.5情景下,到本世纪末期,预估除帕米尔高原和昆仑山西北部地区外,青藏高原其他地区的冰川在夏季将不存在积累区。     

江淮流域梅雨期气候对全球气候变暖的响应

在全球气候变暖背景下,中国江淮流域梅雨期的气候响应趋于复杂,给江淮流域梅雨期的气候预测带来了更多的不确定因素。研究江淮梅雨期气候对全球变暖的响应,对于认识江淮梅雨变化新趋势、提高新气候背景下的汛期预报及制定防灾减灾政策均有深远意义。采用中国地面气温和降水日值数据集对近几十年来江淮地区梅雨期的气温和降水变化进行了深入分析,基于观测结果,评估了国际耦合模式比较计划第5阶段（CMIP5）的22个模式结果,并对CMIP5模式预估的21世纪中排放（RCP4.5）和高排放（RCP8.5）情景下中国江淮流域梅雨期的气温和降水变化进行了分析,并对梅雨期气候变化的机理进行了探讨。研究结果表明,在全球变暖背景下,江淮地区梅雨期气候亦发生了相应的变化,气温呈现出显著的升高趋势,降水亦发生了相应调整,在较暖年降水偏多,较冷年降水偏少。在未来全球进一步变暖的背景下,江淮地区梅雨期平均气温进一步升高,降水进一步增多,且随着排放量的增加,降水的空间分布不均匀性也在加剧。