Hydrologic Response to Future Climate Change in the Dulong-Irra-waddy River Basin Based on Coupled Model Intercomparison Project 6

Within the context of the Belt and Road Initiative(BRI)and the China-Myanmar Economic Corridor(CMEC),the Dulong-Ir-rawaddy(Ayeyarwady)River,an international river among China,India and Myanmar,plays a significant role as both a valuable hydro-power resource and an essential ecological passageway.However,the water resources and security exhibit a high degree of vulnerabil-ity to climate change impacts.This research evaluates climate impacts on the hydrology of the Dulong-Irrawaddy River Basin(DIRB)by using a physical-based hydrologic model.We crafted future climate scenarios using the three latest global climate models(GCMs)from Coupled Model Intercomparison Project 6(CMIP6)under two shared socioeconomic pathways(SSP2-4.5 and SSP5-8.5)for the near(2025-2049),mid(2050-2074),and far future(2075-2099).The regional model using MIKE SHE based on historical hydrologic processes was developed to further project future streamflow,demonstrating reliable performance in streamflow simulations with a val-idation Nash-Sutcliffe Efficiency(NSE)of 0.72.Results showed that climate change projections showed increases in the annual precip-itation and potential evapotranspiration(PET),with precipitation increasing by 11.3%and 26.1%,and PET increasing by 3.2%and 4.9%,respectively,by the end of the century under SSP2-4.5 and SSP5-8.5.These changes are projected to result in increased annual streamflow at all stations,notably at the basin’s outlet(Pyay station)compared to the baseline period(with an increase of 16.1%and 37.0%at the end of the 21st century under SSP2-4.5 and SSP5-8.5,respectively).Seasonal analysis for Pyay station forecasts an in-crease in dry-season streamflow by 31.3%-48.9%and 22.5%-76.3%under SSP2-4.5 and SSP5-8.5,respectively,and an increase in wet-season streamflow by 5.8%-12.6%and 2.8%-33.3%,respectively.Moreover,the magnitude and frequency of flood events are pre-dicted to escalate,potentially impacting hydropower production and food security significantly.This research outlines the hydrological response to future climate change during the 21st century and offers a scientific basis for the water resource management strategies by decision-makers.

Projections of changes in marine environment in coastal China seas over the 21^st century based on CMIP5 models

The increases of atmospheric carbon dioxide and other greenhouse gases have caused fundamental changes to the physical and biogeochemical properties of the oceans,and it will continue to occur in the foreseeable future.Based on the outputs of nine Earth System Models from the fifth phase of the Coupled Model Intercomparison Project(CMIP5),in this study,we provided a synoptic assessment of future changes in the sea surface temperature(SST),salinity,dissolved oxygen(DO),seawater pH,and marine net primary productivity(NPP)in the coastal China seas over the 21st century.The results show that the mid-high latitude areas of the coastal China seas(East China Seas(ECS),including the Bohai Sea,Yellow Sea,and East China Sea)will be simultaneously exposed to enhanced warming,deoxygenation,acidification,and decreasing NPP as a consequence of increasing greenhouse gas emissions.The magnitudes of the changes will increase as the greenhouse gas concentrations increase.Under the high emission scenario(Representative Concentration Pathway 8.5),the ECS will experience an SST increase of 3.24±1.23℃,a DO concentration decrease of 10.90±3.92μmol/L(decrease of 6.3%),a pH decline of 0.36±0.02,and a NPP reduction of-17.7±6.2 mg/(m2·d)(decrease of 12.9%)relative to the current levels(1980-2005)by the end of this century.The co-occurrence of these changes and their cascade effects are expected to induce considerable biological and ecological responses,thereby making the ECS among the most vulnerable ocean areas to future climate change.Despite high uncertainties,our results have important implications for regional marine assessments.

Projected Regional 1.50℃and 2.00℃Warming Threshold-crossing Time Worldwide Using the CMIP6 Models

The Paris Agreement aims to limit global warming to well below 2.00℃and pursue efforts to limit the temperature increase to 1.50℃.However,the response of climate change to unbalanced global warming is affected by spatial and temporal sensitivities.To better understand the regional warming response to global warming at 1.50℃and 2.00℃,we detected the 1.50℃and 2.00℃warming threshold-crossing time(WTT)above pre-industrial levels globally using the Coupled Model Intercomparison Project phase 6(CMIP6)models.Our findings indicate that the 1.50℃or 2.00℃WTT differs substantially worldwide.The warming rate of land would be approximately 1.35–1.46 times that of the ocean between 60°N–60°S in 2015–2100.Consequently,the land would experience a 1.50℃(2.00℃)warming at least 10–20 yr earlier than the time when the global mean near-surface air temperature reaches 1.50℃(2.00℃)WTT.Meanwhile,the Southern Ocean between 0°and 60°S considerably slows down the global 1.50℃and 2.00℃WTT.In 2040–2060,over 98.70%(77.50%),99.70%(89.30%),99.80%(93.40%),and 100.00%(98.00%)of the land will have warmed by over 1.50℃(2.00℃)under SSP(Shared Socioeconomic Pathway)1–2.6,SSP2-4.5,SSP3-7.0,and SSP5-8.5,respectively.We conclude that regional 1.50℃(2.00℃)WTT should be fully considered,especially in vulnerable high-latitude and high-altitude regions.

Relationships of Interannual Variability Between the Equatorial Pacific and Tropical Indian Ocean in 17 CMIP5 Models

Seventeen coupled general circulation models from the Coupled Model Intercomparison Project Phase 5 （CMIP5） are employed to assess the relationships of interannual variations of sea surface temperature （SST） between the tropical Pacific （TP） and tropical Indian Ocean （TIO）. The eastern/central equatorial Pacific features the strongest SST interannual variability in the models except for the model CSIRO-Mk3-6-0, and the simulated maximum and minimum are produced by models GFDL-ESM2M and GISS-E2-H respectively. However, It remains a challenge for these models to simulate the correct climate mean SST with the warm pool-cold tongue structure in the equatorial Pacific. Almost all models reproduce E1 Nifio-Southem Oscillation （ENSO）, Indian Ocean Dipole mode （IOD） and Indian Ocean Basin-wide mode （lOB） together with their seasonal phase lock features being simulated; but the relationship between the ENSO and IOD is different for different models. Consistent with the observation, an Indian Ocean basin-wide warming （cooling） takes place over the tropical Indian Ocean in the spring following an E1 Nifio （La Nifia） in almost all the models. In some models （e.g., GFDL-ESM2G and MIROC5）, positive ENSO and IOB events are stronger than the negative events as shown in the observation. However, this asymmetry is reversed in some other models （e.g., HadGEM2-CC and HadGEM2-ES）.

An assessment of the CMIP5 models in simulating the Argo geostrophic meridional transport in the North Pacifi c Ocean

Eleven climate system models that participate in the Coupled Model Intercomparison Project phase 5(CMIP5)were evaluated based on an assessment of their simulated meridional transports in comparison with the Sverdrup transports.The analyses show that the simulated North Pacifi c Ocean circulation is essentially in Sverdrup balance in most of the 11 models while the Argo geostrophic meridional transports indicate signifi cant non-Sverdrup gyre circulation in the tropical North Pacifi c Ocean.The climate models overestimated the observed tropical and subtropical volume transports signifi cantly.The non-Sverdrup gyre circulation leads to non-Sverdrup heat and salt transports,the absence of which in the CMIP5 simulations suggests defi ciencies of the CMIP5 model dynamics in simulating the realistic meridional volume,heat,and salt transports of the ocean.

A comparison of the CMIP5 models on the historical simulation of the upper ocean heat content in the South China Sea

Seventeen models participating in the Coupled Model Intercomparison Project phase 5（CMIP5） activity are compared on their historical simulation of the South China Sea（SCS） ocean heat content（OHC） in the upper 300 m. Ishii＇s temperature data, based on the World Ocean Database 2005（WOD05） and World Ocean Atlas 2005（WOA05）, is used to assess the model performance by comparing the spatial patterns of seasonal OHC anomaly（OHCa） climatology, OHC climatology, monthly OHCa climatology, and interannual variability of OHCa. The spatial patterns in Ishii＇s data set show that the seasonal SCS OHCa climatology, both in winter and summer, is strongly affected by the wind stress and the current circulations in the SCS and its neighboring areas. However, the CMIP5 models present rather different spatial patterns and only a few models properly capture the dominant features in Ishii＇s pattern. Among them, GFDL-ESM2 G is of the best performance. The SCS OHC climatology in the upper 300 m varies greatly in different models. Most of them are much greater than those calculated from Ishii＇s data. However, the monthly OHCa climatology in each of the 17 CMIP5 models yields similar variation and magnitude as that in Ishii＇s. As for the interannual variability, the standard deviations of the OHCa time series in most of the models are somewhat larger than those in Ishii＇s. The correlation between the interannual time series of Ishii＇s OHCa and that from each of the 17 models is not satisfactory. Among them, BCC-CSM1.1 has the highest correlation to Ishii＇s, with a coefficient of about 0.6.

Multidecadal Trends in Large-Scale Annual Mean SATa Based on CMIP5 Historical Simulations and Future Projections

Based on observations and Coupled Model lntercomparison Project Phase 5 （CMIP5） results, multidecadal variations and trends in annual mean surface air temperature anomalies （SATa） at global, hemispheric, and hemispheric land and ocean scales in the past and under the future scenarios of two representative concentration pathways （RCPs） are analyzed. Fifteen models are selected based on their performances in capturing the temporal variability, long-term trend, multidecadal variations, and trends in global annual mean SATa. Observational data analysis shows that the multidecadal variations in annual mean SATa of the land and ocean in the northern hemisphere （NH） and of the ocean in the southern hemisphere （SH） are similar to those of the global mean, showing an increase during the 1900-1944 and 1971-2000 periods, and flattening or even cooling during the 1945-1970 and 2001-2013 periods. These observed characteristics are basically reproduced by the models. However, SATa over SH land show an increase during the 1945-1970 period, which differs from the other hemispheric scales, and this feature is not captured well by the models. For the recent hiatus period （2001-2013）, the projected trends of BCC-CSM1-1-m, CMCC-CM, GFDL-ESM2M, and NorESM1-ME at the global and hemispheric scales are closest to the observations based on RCP4.5 and RCP8.5 scenarios, suggesting that these four models have better projection capability in SATa. Because these four models are better at simulating and projecting the multidecadal trends of SATa, they are selected to analyze future SATa variations at the global and hemispheric scales during the 2006-2099 period. The selected multi-model ensemble （MME） projected trends in annual mean SATa for the globe, NH, and SH under RCP4.5 （RCP8.5） are 0.17 （0.29） ℃, 0.22 （0.36） ℃, and 0.11 （0.23） ℃-decade-1 in the 21st century, respectively. These values are significantly lower than the projections of CMIP5 MME without model selection.

CMIP 6 models simulation of the connection between North/South Pacific Meridional Mode and ENSO

The subtropical North and South Pacific Meridional Modes(NPMM and SPMM)are well known precursors of El Niño-Southern Oscillation(ENSO).However,relationship between them is not constant.In the early 1980,the relationship experienced an interdecadal transition.Changes in this connection can be attributed mainly to the phase change of the Pacific decadal oscillation(PDO).During the positive phase of PDO,a shallower thermocline in the central Pacific is responsible for the stronger trade wind charging(TWC)mechanism,which leads to a stronger equatorial subsurface temperature evolution.This dynamic process strengthens the connection between NPMM and ENSO.Associated with the negative phase of PDO,a shallower thermocline over southeastern Pacific allows an enhanced wind-evaporation-SST(WES)feedback,strengthening the connection between SPMM and ENSO.Using 35 Coupled Model Intercomparison Project Phase 6(CMIP6)models,we examined the NPMM/SPMM performance and its connection with ENSO in the historical runs.The great majority of CMIP6 models can reproduce the pattern of NPMM and SPMM well,but they reveal discrepant ENSO and NPMM/SPMM relationship.The intermodal uncertainty for the connection of NPMM-ENSO is due to different TWC mechanism.A stronger TWC mechanism will enhance NPMM forcing.For SPMM,few models can simulate a good relationship with ENSO.The intermodel spread in the relationship of SPMM and ENSO owing to SST bias in the southeastern Pacific,as WES feedback is stronger when the southeastern Pacific is warmer.

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°C（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°C（10 a）-1,为全球陆地最大,2000年后陡降至-0.17°C（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°C（10a）-1,而秋季升高了0.86°C（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°C左右,2020年后跃至2°C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。

GLDAS和CMIP5产品的中国土壤湿度-降水耦合分析及变化趋势

利用GLDAS同化产品和12个CMIP5模式的输出结果,从土壤湿度对降水影响的两个中间环节出发,通过分析陆面耦合指数ILH、潜热通量—抬升凝结高度耦合指数ILCL以及抬升凝结高度ZLCL间接研究中国区域土壤湿度与降水间耦合特征,并对1958～2013年及RCP4.5辐射强迫情景下50年（2006～2055年）的4个代表性区域夏季耦合强度的年代际变化特征进行分析。研究发现：1958～2013年期间,内蒙古阴山山脉附近、新疆和青海的部分地区为夏季中国土壤湿度与降水耦合的最强区域;陆面耦合指数ILH变化幅度从高到低依次出现在华北、华南、内蒙古中部和西北地区,并在20世纪70年代中到80年代中发生转折。2006～2055年的平均而言,预估内蒙古阴山山脉附近仍为耦合最强区;与历史时期（1958～2005年）比较,新疆中部和内蒙古阴山山脉附近的耦合指数ILH增大,而广西和广东地区的则减小;对于耦合指数ILH的年代际变化（2006～2055年）,2026～2035年间华北最大而华南最小,西北地区变化不大,而内蒙古中部地区的耦合强度逐渐增大。

未来50a中国地区冻土面积分布变化

在检验CMIP3模式比较计划中模式在中国地区的温度模拟效果的基础上,选取模拟效果相对较好的HadCM3、EACHE5模拟结果,采用Kudryavtsev方法,应用数字化土壤和植被资料,借助ArcGIS,对未来50 a中国地区在A2情景下的冻土空间变化趋势进行了模拟计算.结果表明,在A2情景下,未来50 a中国地区的冻土呈现出退缩趋势,在2050年,多年冻土在青藏高原地区的巴颜喀拉山-唐古拉山之间、冈底斯山地区出现退化,中国的冻土面积较2006年减少约10.7%.

新疆北部地区积雪深度变化特征及未来50a的预估

分析比较参加CMIP3计划的全球气候模式,在20C3M下各模式1961-1999年平均积雪深度和观测资料比较的基础上,检验了模式对积雪深度的模拟能力.在此基础上,选用INM-CM3.0和CGCM-T47_1模式对北疆地区未来50 a的积雪变化进行了预估.由于受GCM的空间分辨率和新疆北部地区地形、盆地沙漠下垫面、水汽来源和干旱气候环境的影响,CMIP3模式的GCM在新疆北部地区的模拟能力有限.通过相关系数和均方差误差的双重检验,选取了在新疆地区模拟能力较好的INM-CM3.0和CGCM-T47_1模式的模拟结果对新疆地区未来的积雪变化进行了预测.结果表明,在A1B、B1情景下,2002-2050年,总体上新疆北部地区的积雪深度均呈减少趋势;A2情景下,INM-CM3.0、CGCM-T47-1模式在准葛尔盆地地区积雪变化的模拟结果存在差异,但未来40 a新疆地区除天山附近外,积雪深度变化呈减少趋势.

未来气候情景下长江上游区域积雪时空变化分析——基于CMIP5多模式集合数据

基于21个CMIP5全球气候模式集合数据，耦合VIC模型，预估了未来30年（2011—2040年）RCP2．6、RCP4．5和RCP8．5三个情景下长江上游区域积雪的时空变化。结果表明：与基准期1970—1999年相比，长江上游区域未来30年的多年平均气温和各月平均气温都将升高1～2℃，其中冬季和春季升温较大；平均年降水量将增加3％～4％，但秋、冬季降水有所减小。未来30年平均积雪深相对于基准期将减小37．8％左右，在积雪过程中达到最大积雪深的时间与基准期基本相同，而融雪开始的时间略有延后；从空间变化来看，冬季（1月份）长江上游区域大部分地区的积雪深都呈现减小趋势，部分地区积雪深减小超过了50％。

2006-2013年CMIP5模式中国降水预估误差分析

用第五次耦合模式比较计划（CMIP5）的10个模式模拟结果与英国东安格利亚大学（UEA）气候研究机构（CRU）的最新降水格点分析资料比较,评估了三种典型浓度路径（RCPs）排放情景下模式集合对2006-2013年中国降水预估误差,结果发现模式间年降水预估在西北和东部沿海地区差异较明显,在沿海地区模式降水估计偏少,在西部和北方大部分地区偏多;冬半年大部分地区模式降水明显偏多,部分地区甚至偏多一倍以上;夏半年东部季风区降水估计偏少,但西部仍然偏多。模式降水误差随时间变化,夏半年误差变化明显的区域主要集中在北方和东部地区,冬半年在东北南部、华东及华南等地。此外,提高排放情景对年降水量估计影响明显的地区主要集中在我国西部的部分地区,加剧了西北模式降水估计偏多程度,但对东部地区影响不大。El Ni？o与La Ni？a年的模式降水误差分布相似,仅在沿海部分地区和华北北部差异较明显,逐年误差分布特征也与此相似。各种误差的对比分析表明,模式降水误差可能多来自模式本身存在的问题,如积云对流参数化、固体降水物理过程、地形处理及分辨率等。这些误差特征说明,直接使用CMIP5模式集合情景输出资料估计未来降水的方法存在较大的不确定性,必须对其进行评估,以降低潜在用户或决策者们制定未来规划的风险。

CMIP5气候模式对东亚夏季平均环流场模拟能力的评估

利用第五次耦合模式比较计划（Phase 5 of Coupled Model Intercomparison Project,CMIP5）提供的30个全球气候模式模拟的1961~2005年的夏季逐月环流场资料及同期NCEP再分析资料,引入泰勒图及各种评估指标,探讨全球气候模式对东亚夏季平均大气环流场的模拟能力,寻求具有较好东亚夏季环流场模拟能力的气候模式。结果表明：1）全球气候模式能够模拟出东亚夏季平均大气环流的基本特征,CMIP5模式的总体模拟能力较第三次耦合模式比较计划（CMIP3）有较大程度的提高,如CMIP5模式对东亚大部分地区夏季海平面气压（Sea Level Pressure,SLP）场的模拟偏差在6 h Pa以内。2）模式对不同层次环流场的模拟能力存在差异,500 h Pa高度场的模拟能力最强,其次为100 h Pa高度场、850 h Pa风场,SLP场最弱;对东亚夏季主要环流系统的模拟对比发现,模式对印度热低压及东伸槽强度指数的模拟能力最好。3）综合CMIP5模式对东亚夏季各层次平均环流场以及主要环流系统的模拟能力,发现模拟较好的5个模式为CESM1-CAM5、MPI-ESM-MR、MPI-ESM-LR、MPI-ESM-P和Can ESM2。4）相对于单一模式,多模式集合平均（MME）模拟能力较强,但较优选的前5个模式集合平均的模拟能力弱。

CMIP5/6模式对PDO调制ENSO爆发频率不对称的模拟评估

利用第五次和第六次国际间耦合模式比较计划(CMIP)中piControl情景下的模拟结果,结合观测资料,对比评估了19个CMIP5模式和23个CMIP6模式对太平洋年代际振荡(PDO)调制厄尔尼诺-南方涛动事件爆发频率不对称的模拟能力,并进一步揭示了PDO的调制过程。结果表明:在观测中,PDO正(负)位相下厄尔尼诺(El Niño)的爆发频率比拉尼娜(La Niña)多300%(少73%),53%(78%)的CMIP5(6)模式模拟出这一特征;尽管两个模式整体都低(高)估了PDO正(负)位相的调制能力,但CMIP6模式对PDO调制能力的模拟有所改进。进一步研究发现,在PDO正(负)位相下,赤道太平洋中西部会产生较强的西(东)风异常,风场通过平流的作用使得暖水向东流动,从而在太平洋中东部的海表面温度背景场中出现正(负)异常变化,而这有利于PDO正(负)位相下El Niño(La Niña)事件的发生。

CMIP5模式对春季北极涛动影响后期冬季ENSO不对称性的模拟能力分析

根据观测资料的研究指出春季北极涛动(Arctic Oscillation, AO)对随后冬季厄尔尼诺-南方涛动(El Nino–Southern Oscillation, ENSO)的影响具有明显不对称性。春季AO处于正位相时,它对随后冬季厄尔尼诺(El Nino)事件的影响显著,然而春季AO负位相对随后冬季拉尼娜(La Nina)的影响不明显。本研究分析了30个来自CMIP5的耦合模式对春季AO与随后冬季ENSO不对称性关系的模拟能力。30个CMIP5耦合模式中,只有CNRM-CM5和GISS-E2-H-CC模式能较好地抓住春季AO与冬季ENSO的联系。进一步分析这两个模式中春季AO与冬季ENSO的不对称性关系,发现CNRM-CM5模式能较好地再现春季AO与冬季ENSO的非对称关系,即春季AO正(负)位相会导致赤道中东太平洋出现El Nino(La Nina)型海表温度增暖(冷却)。然而,GISS-E2-H-CC模式的模拟结果显示,春季AO对随后冬季ENSO的影响是对称的。本文随后解释了CNRM-CM5(GISS-E2-H-CC)模式能(不能)模拟出春季AO与冬季ENSO不对称关系的原因。对于CNRMCM5模式,在春季AO正位相年,副热带西北太平洋上空存在明显的异常气旋和正降水异常,正降水异常通过Gill型大气响应对赤道西太平洋异常西风的形成和维持起着重要作用,异常西风通过激发向东传播的暖赤道Kelvin波对随后冬季El Nino事件的发生产生显著的影响;然而,在春季AO负位相年,副热带北太平洋的异常反气旋和负降水异常较弱,导致赤道西太平洋的异常东风不明显,因此,春季AO负异常对随后冬季La Nina的影响不显著。所以,CNRM-CM5模式能够较好地抓住春季AO对随后冬季ENSO事件的非对称性影响。相比之下,对于GISS-E2-H-CC模式,春季AO正(负)位相年副热带西北太平洋上存在显著的正(负)降水异常,通过Gill型大气响应在赤道西太平洋激发出明显的异常西(东)风从而影响随后冬季的El Nino(La Nina)事件。因此,在GISS-E2-H-CC模式中,春季AO对随后冬季ENSO具有对称性影响。另外,模式捕捉春季AO对随后冬季ENSO非对称性影响的能力与模式对春季AO空间结构的模拟能力有一定的联系。

模式内部变率引起的1.5℃和2℃升温阈值出现时间模拟的不确定性研究

模式内部变率是模拟结果不确定性的重要来源,然而它对于1.5℃和2℃升温阈值出现时间不确定性的影响尚不清楚。因此,基于耦合模式比较计划第五阶段(CMIP5)的多模式数据研究了模式内部变率对1.5℃和2℃升温阈值出现时间不确定性的影响以及对未来排放情景的敏感性。结果表明,模式内部变率对升温阈值出现时间模拟的影响与外强迫的影响相当,单个模式内部不同成员达到全球平均1.5℃或2℃增温的年份相差2 ~ 12 年;其影响具有明显的空间差异,影响极大值出现在欧亚大陆以北洋面、白令海峡周围区域、北美东北部及其与格陵兰岛之间的海域、南半球高纬地区等;低排放情景下模式内部变率的影响大于高排放情景。

CMIP6与CMIP5对历史大气层顶和地表辐射收支模拟的时空对比

基于云和地球辐射能量系统观测数据集(CERES),对比分析了耦合模式比较计划第五(CMIP5)和第六阶段(CMIP6)模拟的历史大气层顶和地表辐射收支的年际变化和空间分布,明确了多模式间不确定性大的关键区域。结果表明:在年际尺度上,除地表向上长波辐射外,CMIP6的辐射分量的集合均值较CMIP5更接近于CERES观测值,全球地表向下短波辐射的高估和大气逆辐射的低估在CMIP6中分别降低了1.9 W/m~2和3.3 W/m~2。除大气逆辐射外,CMIP6的辐射分量在多模式间的一致性较CMIP5提高。在北极,CMIP6对大气层顶反射短波、大气层顶出射长波和地表向下短波辐射的模拟偏差较CMIP5大。在南北纬60°,CMIP6对大气逆辐射的模拟偏差较CMIP5大。其他区域CMIP6的辐射分量更接近CERES观测值。CMIP6模拟的地表向下短波辐射和大气逆辐射的不确定性较大区域面积较CMIP5减小,但不确定性极大区域面积无变化。地表净辐射的不确定性空间分布在两代CMIP间变化甚小。青藏高原、赤道太平洋、热带雨林、阿拉伯半岛和南极洲沿海依然是地球系统模式模拟辐射收支不确定性极大的关键区域。

Development of Earth/Climate System Models in China:A Review from the Coupled Model Intercomparison Project Perspective

The development of coupled earth/climate system models in China over the past 20 years is reviewed, including a comparison with other international models that participated in the Coupled Model Intercom- parison Project （CMIP） from phase 1 （CMIP1） to phase 4 （CMIP4）. The Chinese contribution to CMIP is summarized, and the major achievements from CMIP1 to CMIP3 are listed as a reference for assessing the strengths and weaknesses of Chinese models. After a description of CMIP5 experiments, the five Chinese models that participated in CMIP5 are then introduced. Furthermore, following a review of the current status of international model development, both the challenges and opportunities for the Chinese climate modeling community are discussed. The development of high-resolution climate models, earth system mod- els, and improvements in atmospheric and oceanic general circulation models, which are core components of earth/climate system models, are highlighted. To guarantee the sustainable development of climate system models in China, the need for national-level coordination is discussed, along with a list of the main compo- nents and supporting elements identified by the US National Strategy for Advancing Climate Modeling.