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...     

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。     

CMIP6全球气候模式对中亚极端降水模拟能力的评估

本文基于NOAA再分析逐日降水数据和22个CMIP6模式的降水模拟数据,选取了6个极端降水指数,从气候态和相对变率两个角度对CMIP6模式在中亚地区极端降水方面的模拟能力开展了评估。结果表明,在气候态方面,中亚地区降水的空间分布表现为由西南向东北递增,其东南部山地迎风侧降水偏多;多模式集合对SDII(简单降水强度)和CDD(最大无雨期)模拟的平均误差分别为-5.43%和0.45%,对PRCPTOT(年总降水量)、R1mm(有雨日数)、Rx5day(最大连续五日降水)和CWD(最大雨期)的模拟结果存在明显高估,且在中亚东南部高海拔地区误差偏高。在相对变率方面,多模式集合模拟的中亚极端降水的相对变率偏小,其中对CWD的模拟效果相对较好,平均误差为-4.78%;对R1mm的模拟效果最差,平均误差为-36.16%。模式间进行比较,TaiESM1、EC-Earth3-Veg-LR和GFDL-ESM为22个CMIP6模式中模拟能力最好的前3个模式。     

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。     

21世纪前期中国降水预估及其订正

用全球格点分析数据集（CRU TSv4.0）月降水资料和24个CMIP5（Coupled Model Intercomparison Project Phase 5）模式历史模拟数据以及RCP4.5情景下的预估数据,分析了多模式集合平均降水的偏差特征并进行了扣除模式气候漂移和一元对数差分回归订正。结果表明,模式降水在西部和北部明显偏多,东南沿海偏少;冷季（11月至次年4月）在全国大部分地区模式降水偏多,暖季（5～10月）东南沿海季风区偏少。1956～2005年多模式集合平均历史模拟降水偏差中84%属于气候漂移,其余是偏差的非定常模态。扣除气候漂移后,RCP4.5情景下2006～2015年中国模式降水预估偏差减小90%以上,大部分地区降水偏差百分率分布在±5%以内,仅在青藏高原西部和西北中部等地区模式降水偏多10%～40%;暖季降水偏差分布与年降水量类似;冷季偏差较大,北方降水偏多,南方偏少。检验表明,一元线性对数差分回归方程订正后,模式降水对于2006～2015年期间西南和江南中部的干旱少雨气候均能再现,且距平同号率高于多模式集合平均和扣除气候漂移的结果。用该方法对RCP4.5情景下2016～2035年模式预估降水进行订正,结果显示,南方（淮河以南）降水减少5%～20%,河套、内蒙古和华北北部减少20%～40%,东北南部、淮河流域、西北大部增加10%～40%及以上,东南沿海和台湾省降水增加10%～20%。以上降水预估结果说明,在RCP4.5情景下,21世纪前期持续十年的西南干旱会略有缓解,但南方降水偏少格局变化不大,淮河流域和三江源区及其以西等地降水可能明显增加。中国降水异常分布总体呈现南北少、中间多的格局,但北方和西部高山地带的降水预估存在较大的不确定性。     

CMIP5模式对中国东北气候模拟能力的评估

利用CN05观测资料和参与IPCC第五次评估报告的45个全球气候系统模式的模拟结果,分析了新一代全球气候模式对中国东北三省(1961~2005年)气温和降水的模拟能力。结果表明:1)绝大多数模式都能较好地模拟出研究区内显著增温的趋势,对气温的年际变化模拟能力则相对有限;2)所有模式均能很好地再现气温气候态的空间分布特征,且多模式集合模拟结果优于绝大多数单个模式,空间相关系数达到了0.96;3)对于降水的模拟结果,模式间差异较大,多模式集合能较好地再现其空间分布规律(空间相关系数为0.86),对降水年际变化及线性变化趋势的模拟能力则较差。总体来说,多模式集合对东北气候的时空变化特征具有一定的模拟能力,且对气温模拟效果优于降水,对空间分布的模拟能力优于时间变化。     

CMIP6模式对青藏高原气候的模拟能力评估与预估研究

利用国际耦合模式比较计划第六阶段(CMIP6)模拟试验数据,首先评估了45个全球气候模式对1985-2014年青藏高原地表气温和降水的模拟能力,表明CMIP6模式能合理地模拟地表气温的空间分布,但大部分模式对年和季节平均地表气温的模拟值偏低,年均偏冷2.1℃,冷偏差在冬季和春季相对更大.CMIP6模式对青藏高原降水的模...     

基于国际大气化学—气候模式比较计划模式数据评估未来气候变化对中国东部气溶胶浓度的影响

气候变化引起的地面气溶胶浓度变化与区域空气质量密切相关。本文利用“国际大气化学—气候模式比较计划”（Atmospheric Chemistry and Climate Model Intercomparison Project, ACCMIP）中4个模式的试验数据分析了RCP8.5情景下2000~2100年气候变化对中国气溶胶浓度的影响。结果显示,在人为气溶胶排放固定在2000年、仅考虑气候变化的影响时,2000~2100年气候变化导致中国北部地区（31°N~45°N, 105°E~122°E）硫酸盐、有机碳和黑碳气溶胶分别增加28%、21%和9%,硝酸盐气溶胶在中国东部地区减少30%。气候变化对细颗粒物（PM_2.5）浓度的影响有显著的季节变化特征,冬季PM_2.5浓度在中国东部减少15%,这主要是由硝酸盐气溶胶在冬季的显著减少造成的;夏季PM_2.5浓度在中国北部地区增加16%,而长江以南地区减少为9%,这可能与模式模拟的未来东亚夏季风环流的增强有关。     

CMIP6模式对青藏高原极端气温指数模拟能力评估及预估

利用第六次国际耦合模式比较计划（CMIP6）28个全球气候模式模拟的历史和多SSP排放情景下的模拟结果以及国家气候中心制作的CN05.1格点化的观测数据,在评估28个全球气候模式对青藏高原极端气温相关指数模拟效果的基础上,预估了多个SSP情景下青藏高原未来极端气温指数的变化趋势。评估结果表明多模式集合平均模拟结果更稳定,且能模拟出极端气温指数的时间分布以及空间分布特征,但与观测相比,不同指数存在不同偏差。预估结果表明,相对于1995-2014年,青藏高原上日最高气温最高值（TXx）、日最低气温最低值（TNn）、暖昼指数（TX90p）未来呈上升趋势,霜冻日数（FD）、冰冻日数（ID）、冷夜指数（TN10p）呈减少趋势,其中高原极端低温比极端高温增温明显,暖昼指数在高原西南部增加明显,霜冻日数、冰冻日数、冷夜指数在高原东南部减少明显。SSP1-1.9情景下,极端气温指数在21世纪的变化幅度较小,随着辐射强迫增大,指数的变化趋势也增大。SSP1-2.6情景下,2030年前中国实现碳达峰时,青藏高原地区TXx、 TNn、 TX90p增长分别不超过1.12℃、0.84℃、 8.4%, FD、 I...     

CMIP5全球气候模式对中国地区降水模拟能力的评估

使用多种观测资料和43个参加耦合模式比较计划第五阶段（CMIP5）的全球气候模式模拟数据,评估分析了全球气候模式对中国地区1980-2005年降水特征的模拟能力。结果表明：多数CMIP5模式能够模拟出中国降水由西北向东南递增的分布特点,这与耦合模式比较计划第三阶段（CMIP3）的模式模拟结果类似,但华南地区降水模拟偏少,西部高原地区降水模拟偏多。模式能够较好地模拟出降水冬弱夏强的季节变化特征,但降水模拟系统性偏多。从EOF分析结果来看,多数CMIP5模式可以再现中国地区年平均降水的时空变化特征,集合平均的表现优于CMIP3。多模式集合在月、季、年时间尺度下模拟的平均值优于大部分单个模式的结果。CMIP5中6个中国模式的模拟能力与其他模式相当,其中FGOALS-g2、BCC-CSM1-1-m的模拟能力相对较好。     

Differences between CMIP6 and CMIP5 Models in Simulating Climate over China and the East Asian Monsoon

We compare the ability of coupled global climate models from the phases 5 and 6 of the Coupled Model Intercomparison Project(CMIP5 and CMIP6, respectively) in simulating the temperature and precipitation climatology and interannual variability over China for the period 1961–2005 and the climatological East Asian monsoon for the period1979–2005. All 92 models are able to simulate the geographical distribution of the above variables reasonably well.Compared with earlier CMIP5 models, current CMIP6 models have nationally weaker cold biases, a similar nationwide overestimation of precipitation and a weaker underestimation of the southeast–northwest precipitation gradient, a comparable overestimation of the spatial variability of the interannual variability, and a similar underestimation of the strength of winter monsoon over northern Asia. Pairwise comparison indicates that models have improved from CMIP5 to CMIP6 for climatological temperature and precipitation and winter monsoon but display little improvement for the interannual temperature and precipitation variability and summer monsoon. The ability of models relates to their horizontal resolutions in certain aspects. Both the multi-model arithmetic mean and median display similar skills and outperform most of the individual models in all considered aspects.     

CMIP6模式对中国气温日较差的模拟能力评估北大核心CSCD

利用CRU_TS v4.04观测数据作为验证,对28个CMIP6(Coupled Model Intercomparison Project 6)模式模拟中国区域内气温日较差(Diurnal Temperature Range,DTR)年际变化、气候平均态变化以及不同区域和不同季节尺度变化的能力进行评估。结果表明:在百年尺度上,CMIP6模式能够反映出年际变化中DTR下降的演变趋势,模式与观测之间的相关系数在0.1~0.7,均方根误差在0.6~1.5,Taylor评分(Taylor Score,TS)在0.2~0.7,MRI-ESM2-0模式与观测之间的相关系数(0.65)最大,均方根误差(0.8)最小,TS(0.67)最高,模拟能力最好;在30年气候平均态尺度上,CMIP6模式符合观测呈现的DTR北方地区高、南方地区低,西部地区高、东部地区低,内陆地区高、沿海地区低,高原地区高、平原盆地地区低的空间分布特征,基本可以再现中国大范围区域内DTR下降的空间分布特征,对不同区域和不同季节DTR变化也有较好的模拟,以EC-Earth3模式的模拟能力最好。然而,单模式存在不同程度的高估或低估DTR变化的现象,多模式中位数集合能够模拟出DTR在年际变化和气候平均态变化中的一些特征,对于春季和冬季的模拟,多模式集合优于单模式模拟。     

CMIP6 Evaluation and Projection of Temperature and Precipitation over China

This article evaluates the performance of 20 Coupled Model Intercomparison Project phase 6(CMIP6)models in simulating temperature and precipitation over China through comparisons with gridded observation data for the period of 1995–2014,with a focus on spatial patterns and interannual variability.The evaluations show that the CMIP6 models perform well in reproducing the climatological spatial distribution of temperature and precipitation,with better performance for temperature than for precipitation.Their interannual variability can also be reasonably captured by most models,however,poor performance is noted regarding the interannual variability of winter precipitation.Based on the comprehensive performance for the above two factors,the“highest-ranked”models are selected as an ensemble(BMME).The BMME outperforms the ensemble of all models(AMME)in simulating annual and winter temperature and precipitation,particularly for those subregions with complex terrain but it shows little improvement for summer temperature and precipitation.The AMME and BMME projections indicate annual increases for both temperature and precipitation across China by the end of the 21st century,with larger increases under the scenario of the Shared Socioeconomic Pathway 5/Representative Concentration Pathway 8.5(SSP585)than under scenario of the Shared Socioeconomic Pathway 2/Representative Concentration Pathway 4.5(SSP245).The greatest increases of annual temperature are projected for higher latitudes and higher elevations and the largest percentage-based increases in annual precipitation are projected to occur in northern and western China,especially under SSP585.However,the BMME,which generally performs better in these regions,projects lower changes in annual temperature and larger variations in annual precipitation when compared to the AMME projections.     

Comparison of precipitation projections of CMIP5 and CMIP6 global climate models over Yulin,China

Theoretical and Applied Climatology - This study compared precipitation projections of CMIP5 and CMIP6 GCMs over Yulin City, China. The performance of CMIP5 and CMIP6 GCMs in replicating Global...     

Preliminary Assessment of Simulations of Climate Changes over China by CMIP5 Multi-Models

Based on 18 global climate models’ simulations of the 20th century climate, a set of experiments within phase five of the Coupled Model Inter-comparison Project (CMIP5), the performances of simulating the present climate over China are assessed. Compared with observations, models can capture the dominant features of the geographic distributions of temperature and precipitation during 1961-2005. For the temporal changes of temperature, models appear to have a good performance on reproducing the warming tendency but show limited skills for precipitation. For the regional mean temperature and precipitation over the whole of China, most models underestimate the actual temperature and overestimate precipitation. Concerning the standard deviations of simulations by the 18 models, they are larger for temperature in the western part of China, while the standard deviations are larger for precipitation in the South.     

Assessment of Snow Depth over Arctic Sea Ice in CMIP6 Models Using Satellite Data

Snow depth over sea ice is an essential variable for understanding the Arctic energy budget.In this study,we evaluate snow depth over Arctic sea ice during 1993-2014 simulated by 31 models from phase 6 of the Coupled Model Intercomparison Project(CMIP6)against recent satellite retrievals.The CMIP6 models capture some aspects of the observed snow depth climatology and variability.The observed variability lies in the middle of the models’simulations.All the models show negative trends of snow depth during 1993-2014.However,substantial spatiotemporal discrepancies are identified.Compared to the observation,most models have late seasonal maximum snow depth(by two months),remarkably thinner snow for the seasonal minimum,an incorrect transition from the growth to decay period,and a greatly underestimated interannual variability and thinning trend of snow depth over areas with frequent occurrence of multi-year sea ice.Most models are unable to reproduce the observed snow depth gradient from the Canadian Arctic to the outer areas and the largest thinning rate in the central Arctic.Future projections suggest that snow depth in the Arctic will continue to decrease from 2015 to 2099.Under the SSP5-8.5 scenario,the Arctic will be almost snow-free during the summer and fall and the accumulation of snow starts from January.Further investigation into the possible causes of the issues for the simulated snow depth by some models based on the same family of models suggests that resolution,the inclusion of a hightop atmospheric model,and biogeochemistry processes are important factors for snow depth simulation.     

Future changes in daily snowfall events over China based on CMIP6 models

China has been frequently affected by severe snowstorms in recent years that have particularly large economic and human impacts. It is thus of great importance to increase our understanding of the underlying mechanisms of and future changes in snowfall occurrences over China. In this study, the effects of anthropogenic influences on snowfall and the associated future changes are explored using new simulations from CMIP6 (phase 6 of the Coupled Model Intercomparison Project) models. Observational evidence reveals a decrease in the annual total snowfall days and an increase in intense snowfall days over the snowfall-dominated regions in China during recent decades. Fingerprints of anthropogenic influences on these changes are detectable, especially the impacts of increased greenhouse gas emissions. During the winter seasons, low temperatures still cover the regions of northern China, and the associated precipitation days show an increase due to anthropogenic warming, which substantially benefits the occurrence of snowfall over these regions, particularly for intense snowfall events. This is also true in the future, despite rapid warming being projected. By the end of this century, approximately 23% of grids centered over northern China are projected to still experience an increase in daily intense snowfall events in winters. Additionally, the length of the snowfall season is projected to narrow by nearly 41 days compared to the current climate. Thus, in the future, regions of China, especially northern China, are likely to experience more intense snowfall days over a more concentrated period of time during the winter seasons.摘要近年来, 中国部分地区频繁遭遇极端降雪事件袭击, 造成巨大经济损失和人员伤亡. 因此, 亟需深入理解中国地区极端降雪变化的物理机制及其未来演变趋势, 为国家防灾减灾及气候变化应对措施制定提供科学依据. 本文基于CMIP6模式结果, 深入开展人类活动对中国地区降雪变化的影响及其未来演变趋势预估研究. 观测显示, 过去几十年在中国降雪频发区, 其年降雪日数呈现减少趋势但强降雪日数增加; 在这些变化中能够检测到人类活动的痕迹, 尤其是温室气体排放的影响. 对于冬季, 全球变暖背景下中国北方地区降水日数明显增加, 但北方地区仍为低温控制, 这有利于降雪尤其是强降雪事件的发生; 到了本世纪末, 中国仍有约23%的区域 (主要集中在北方地区) 其冬季强降雪日数呈现增加趋势. 此外, 中国地区降雪季长度相比当前气候减少了约41天. 因此, 在未来持续变暖背景下, 中国北方部分地区冬季将经历更多更为集中的强降雪事件.