CMIP5模式对EU、WP遥相关型的模拟评估和预估

基于国际第5次耦合模式比较计划（CMIP5）历史试验输出资料和情景模拟试验结果,评估了14个耦合模式对北半球冬季影响东亚冬季气候的遥相关型——欧亚型（EU）和西太平洋型（WP）的模拟能力以及其对局地气温、降水影响的模拟效果,并预估未来EU和WP变化。结果表明:（1）模式对EU、WP信号的整体年际变率有一定模拟技巧,对空间模态特征的模拟能较好再现遥相关的异常中心,但也存在一定的位置偏差。（2）模式和多模式集合能再现EU与东亚以及西北太平洋地区表面气温的负相关性,但对我国华北以及黄淮流域降水负相关性模拟能力较差,且低估EU与东亚地区气温、降水的关系。（3）各模式对WP与东亚—西太平洋区相关性的南负北正分布均有较好模拟能力,空间相关系数为0.5~0.9;多数模式能再现WP与降水在鄂霍次克海的正相关性,但对于我国大陆至西太平洋的负相关性模拟能力较弱,且各模式对WP和东亚地区表面气温关系的模拟优于其与降水的关系。（4）对EU、WP遥相关整体模拟能力S评分可知,CSIRO-Mk3.6.0对EU整体评估能力最强,CNRM-CM5对WP综合评估能力最好;而HadCM3整体评分较低。（5）RCP4.5情景下,EU和WP在未来略趋于负位相发展;EU与东亚气温相关范围向东南移动,与降水相关不显著;WP与气温相关范围高纬西撤、低纬东移,与降水相关显著增强。     

CMIP5模式对青藏高原中东部夏季降水双极型模拟能力的评估

青藏高原中东部夏季降水主要表现为东北和东南反位相变化的双极型特征。采用经验正交函数(empirical orthogonal function,EOF)分解方法,系统性地评估参与第五次耦合模式比较计划 (Coupled Model Intercomparison Project Phase 5,CMIP5)历史模拟试验的 47 个模式对青藏高原中东部夏季降水双极型变化特征的模拟能力。结果表明,大多数模式基本可以反映青藏高原中东部夏季降水东北部和东南部反位相的变化特征。模式间 EOF 分析结果表明在35°N 以南的东西向模拟偏差是 CMIP5 模式模拟降水空间型态的主要偏差,且大多数模式对时间系数的模拟效果差于空间型态。文中定义了一个综合评估指标 Snew 来定量描述模式对空间型态、时间系数以及方差贡献的综合模拟效果。由定量评估结果来看,MIROC-ESM、HadGEM2-CC 和 ACCESS1-0 (FIO-ESM、 HadGEM2-AO 和 MIROC-ESM-CHEM)模式对观测降水的 EOF1(EOF2)模态的综合模拟能力相对较好,而 GISS 系列模式、CESM1-CAM5 和 MPI-ESM-LR (CMCC-CESM、MPI-ESM-MR 和 GFDL- CM3)模式对观测降水的 EOF1(EOF2)模态的综合模拟效果较差。由 EOF1 和 EOF2 的综合评估结果来看,MIROC-ESM-CHEM模式对观测降水的 EOF1 和 EOF2 模态的综合模拟效果最好。     

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。     

华北地区极端降水变化特征及多模式模拟评估

利用1961—2010年华北地区68个台站逐日降水数据计算了6个极端降水指数,对华北极端降水的时空变化特征进行了分析。进一步评估了CMIP5的31个全球气候模式对华北地区极端降水的模拟效果。结果表明:1华北地区极端降水指数具有较大地区性差异,平均日降水强度、极端降水阈值等指标东南高西北低,大雨日数和连续干日东西分布差异明显。6个极端降水指标的年际变化显示华北地区强降水事件增多的同时,极端干旱程度加剧。2CMIP5模式对华北地区极端降水指数的模拟差异较大,其中对平均日降水强度和极端降水阈值空间分布模拟能力较好,有1/3模式的空间相关系数超过了0.6。同一模式对不同指数的模拟能力也存在较大的差异。3模式模拟相关系数和均方根误差有较好的一致性,根据这两个指标分别得到两组模式排序,其相关系数超过了0.4。HadGEM2-CC,HadGEM2-ES,MIROC4h,MIROC5以及CCSM4是模拟华北地区极端指数最好的5个全球模式。相比于多模式集合平均,优选模式集合能够显著降低模拟的湿偏差。     

CMIP5 模式对中国极端气温及其变化趋势的模拟评估

本文基于中国区域逐日气温资料和CMIP5 中30 个全球气候模式资料,计算了平均日最高气温（TXAV)、平均日最低气温（TNAV)、热浪指数（HWDI)、霜冻日数（FD)、和暖夜指数（TNF90）5 个极端气温指数,评估各模式对中国区域极端气温的气候平均场和趋势的模拟能力。研究结果表明,大部分模式能够较好地模拟出极端指数的气候平均场,其中对TNAV、TXAV 和FD 平均场模拟能力较强,大部分模式平均场与观测场的相关系数超过0.90,但对TNF90 和HWDI 的模拟能力相对较低,相关系数均低于0.70,且各模式的模拟能力存在较大的差异。对极端指数的趋势模拟来说,模式模拟的中国区域平均各极端气温指数的线性变化趋势与观测相同,但大多数模式模拟趋势的强度偏弱。相比于气候平均场,模式对极端气温指数趋势空间场模拟较差,除TNAV 有1/3 的模式平均场与观测场的相关系数超过0.60 外,模式模拟其余指数的相关系数均低于0.60。模拟极端气温气候平均场的能力最优的5 个模式为：IPSL-CM5A-MR、CMCC-CM、IPSL-CM5A-LR、MPI-ESM-MR 和MPI-ESM-P。趋势空间场模拟最好的5 个模式为：MPI-ESM-P、CANESM2、ACCESS1-3、BCC-CSM1-1 和NorESM1-M。模式对极端气温指数的时空模拟能力一致性较差,但基于气候平均场或趋势空间场的优选模式,相比于所有集合模式平均,模拟能力均有一定程度的改善。     

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模式中El Ni?o-EAWM关系的模拟对东亚冬季风模拟的影响

本文利用统计学的方法,评估了17个参加第五次国际耦合模式比较计划(CMIP5)的海气耦合模式对东亚冬季风(EAWM)年际变化的模拟。结果表明:多数模式对东亚冬季风的年际变化有一定的模拟能力,其中对东亚大槽年际变化的模拟最好;模式对东亚冬季主要系统的年际变化在空间上的模拟好于强度,对强度的模拟以偏弱为主;通过综合评估得到模拟能力好的模式有:bcc-csm1-1,CCSM4,HadCM3,NorESM1-M。针对模式间对冬季风年际变化模拟能力差别较大的现象,选取了4个模拟能力最好的模式和5个最差的进行讨论;通过评估El Ni?o对东亚冬季环流的影响,发现模式对El Ni?o与EAWM之间相互关系(El Ni?o-EAWM)的模拟能力是模式间对冬季风年际变化模拟偏差较大的原因之一,即对El Ni?o-EAWM模拟好的模式对东亚冬季风年际变化的模拟也好。     

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。     

不同分辨率CCSM4对东亚和中国气候模拟能力分析

本文利用通用气候系统模式CCSM4在三种水平分辨率下的工业化革命前期气候模拟试验,结合观测和再分析资料,比较了各分辨率下模式对中国温度和降水、东亚海平面气压和850 hPa风场的模拟能力,综合评价了模式分辨率对东亚和中国气候模拟的影响.结果表明,三种分辨率对中国温度均具有很好的模拟能力,除春季外,低分辨率(T31,约3.75°×3.75°)对全年温度的模拟能力均要稍好于中(f19,约1.9°×2.5°)、高(f09,约0.9°×1.25°)分辨率;各分辨率对中国降水的模拟能力远不如温度,除冬季外全年都出现的中部地区虚假降水并未因为模式分辨率提高而得到本质改善;对于东亚海平面气压场,低分辨率在冬季模拟能力相对最好,中等分辨率在夏季相对较好,而高分辨率的模拟能力均表现最差;低分辨率对850 hPa东亚冬季风和夏季风的模拟能力均要好于中、高分辨率,而两种较高分辨率的模拟能力则比较接近.总的来说,低分辨率CCSM4在东亚和中国气候模拟中表现出了较大优势,加之其计算代价小,适合进行需要较长时间积分的气候模拟研究.     

CMIP5模式对北极涛动的模拟评估

基于国际耦合模式比较计划第五阶段(CMIP5)历史试验(historical)的输出结果,评估了26个耦合模式对北极涛动(AO)的模拟能力。对各模式逐月AO指数序列的功率谱分析表明,有23个模式能够模拟出AO模态无显著变化周期的特征。这些模式也能够较好地再现冬季AO在海平面气压场上的主要分布特征,但均高估了AO模态的强度。对于伴随着冬季AO位相变化而出现的中高纬度偶极型的纬向平均纬向风异常,CMIP5中只有一些模式有较好的模拟表现,大多数模式对其中心位置和强度的模拟存在明显不足。对比之下,MPI-ESM-P对AO时空特征的模拟更接近观测结果。     

中国CMIP5模式对未来北极海冰的模拟偏差

本文对中国参加CMIP5的6个气候模式对未来北极海冰的模拟情况进行了评估。通过与1979-2005年海冰的观测值以及2050年代的多模式集合平均值对比发现,中国的气候模式对海冰范围的模拟结果与CMIP5模式的平均水平存在一定差距,具体表现为：BNU-ESM和FGOALS-s2对当前海冰范围估计很好,但对温度敏感性略偏高;FIO-ESM对当前海冰范围估计很好,但由于海冰对温度的敏感性偏低,导致其模拟的未来海冰在各种RCP情景中都融化缓慢;FGOALS-g2（BCC-CSM1-1和BCC-CSM1-1-m）对当前海冰范围的模拟存在显著偏多（显著偏少）的问题,这导致其对未来海冰融化的估计也持续偏多（偏少）。中国模式对北极海冰的模拟偏差导致它们对极区地表大气温度和湿度的模拟出现偏差,并且这些极区气象要素的偏差会进一步通过动力过程传导到对秋、冬季西风带、极涡的模拟中去。研究表明：从对海冰本身的模拟以及海冰偏差带来的气候影响这两个角度看,BNU-ESM在中国模式中水平较高,但总体上中国6个气候模式在海冰分量的模拟上仍与世界平均水平存在差距,这需要中国各模式中心的持续改进。     

Evaluation of CMIP5 Earth System Models in Reproducing Leaf Area Index and Vegetation Cover over the Tibetan Plateau

The abilities of 12 earth system models (ESMs) from the Coupled Model Intercomparison Project Phase5 (CMIP5) to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau (TP) were examined. The results show that most of the models tend to overestimate the observed leaf area index (LAI) and vegetation carbon above the ground, with the possible reasons being overestimation of photosynthesis and precipitation. The model simulations show a consistent increasing trend with observed LAI over most of the TP during the reference period of 1986-2005, while they fail to reproduce the downward trend around the headstream of the Yellow River shown in the observation due to their coarse resolutions. Three of the models: CCSM4, CESM1-BGC, and NorESM1-ME, which share the same vegetation model, show some common strengths and weaknesses in their simulations according to our analysis. The model ensemble indicates a reasonable spatial distribution but overestimated land coverage, with a significant decreasing trend (-1.48% per decade) for tree coverage and a slight increasing trend (0.58% per decade) for bare ground during the period 1950-2005. No significant sign of variation is found for grass. To quantify the relative performance of the models in representing the observed mean state, seasonal cycle, and interannual variability, a model ranking method was performed with respect to simulated LAI. INMCM4, bcc-csm-1.1m, MPI-ESM-LR, IPSL CM5A-LR, HadGEM2-ES, and CCSM4 were ranked as the best six models in reproducing vegetation dynamics among the 12 models.     

Dynamical Downscaling of the Arctic Climate with a Focus on Polar Cyclone Climatology

We present a dynamical downscaling of the Arctic climatology using a high-resolution implementation of the Polar Weather Research and Forecasting, version 3.6 (WRF3.6) model, with a focus on Arctic cyclone activity. The study period is 1979–2004 and the driving fields are data from the Hadley Centre Global Environmental Model, version 2, with an Earth System component (HadGEM2-ES) simulations. We show that the results from the Polar WRF model provide significantly improved simulations of the frequency, intensity, and size of cyclones compared with the HadGEM2-ES simulations. Polar WRF reproduces the intensity of winter cyclones found in ERA-Interim, the global atmospheric reanalysis produced by the European Centre for Medium-range Weather Forecasts (ECMWF), and suggests that the average minimum central pressure of the cyclones is about 10?hPa lower than that derived from HadGEM2-ES simulations. Although both models underestimate the frequency of summer Arctic cyclones, Polar WRF simulations suggest there are 10.5% more cyclones per month than do HadGEM2-ES results. Overall, the Polar WRF model captures more intense and smaller cyclones than are obtained in HadGEM2-ES results, in better agreement with the ERA-Interim reanalysis data. Our results also show that the improved simulations of Arctic synoptic weather systems contribute to better simulations of atmospheric surface fields. The Polar WRF model is better able to simulate both the spatial patterns and magnitudes of the ERA-Interim reanalysis data than HadGEM2-ES is; in particular, the latter overestimates the absorbed solar radiation in the Arctic basin by as much as 30?W?m^?2 and underestimates longwave radiation by about 10?W?m^?2 in summer. Our results suggest that the improved simulations of longwave and solar radiation are partly associated with a better simulation of cloud liquid water content in the Polar WRF model, which is linked to improvements in the simulation of cyclone frequency and intensity and the resulting transient eddy transports of heat and water vapour.     

气候变化情景下澜沧江流域极端洪水事件研究

以澜沧江流域为研究对象,基于ISIMIP2b协议中提供的GFDL-ESM2M、HadGEM2-ES、IPSL-CM5A-LR、MIROC5这4种全球气候模式,通过4种模式的输出数据耦合VIC模型,分析4种模式在历史时期（1961—2005年)对洪峰洪量极值(年最大洪峰流量、3 d最大洪量)、极端洪水的模拟能力,比较RCR2.6和RCP6.0两种情景下未来时期（2021—2050年)年均径流量较基准期（1971—2000年)的变化情况,并结合P-III型分布曲线预估了澜沧江流域在两种情景下未来时期极端洪水的强度变化情况。结果表明：VIC模型在该流域能够较好地模拟极端洪水;HadGEM2-ES和MIROC5两种气候模式的输出数据在澜沧江流域有较好的径流模拟适用性;在RCP2.6情景下,澜沧江流域未来时期年均径流量没有明显变化,可能会有略微的增加,而在RCP6.0情景下,未来时期年均径流量有较大可能增加;澜沧江流域未来时期极端洪水较基准期,在RCP2.6情景下无明显变化,而在RCP6.0情景下,洪峰、洪量增加的可能性较大,极端洪水频率和强度也较大可能增加。     

Evaluating the performance of CMIP3 and CMIP5 global climate models over the north-east Atlantic region

One of the main sources of uncertainty in estimating climate projections affected by global warming is the choice of the global climate model (GCM). The aim of this study is to evaluate the skill of GCMs from CMIP3 and CMIP5 databases in the north-east Atlantic Ocean region. It is well known that the seasonal and interannual variability of surface inland variables (e.g. precipitation and snow) and ocean variables (e.g. wave height and storm surge) are linked to the atmospheric circulation patterns. Thus, an automatic synoptic classification, based on weather types, has been used to assess whether GCMs are able to reproduce spatial patterns and climate variability. Three important factors have been analyzed: the skill of GCMs to reproduce the synoptic situations, the skill of GCMs to reproduce the historical inter-annual variability and the consistency of GCMs experiments during twenty-first century projections. The results of this analysis indicate that the most skilled GCMs in the study region are UKMO-HadGEM2, ECHAM5/MPI-OM and MIROC3.2(hires) for CMIP3 scenarios and ACCESS1.0, EC-EARTH, HadGEM2-CC, HadGEM2-ES and CMCC-CM for CMIP5 scenarios. These models are therefore recommended for the estimation of future regional multi-model projections of surface variables driven by the atmospheric circulation in the north-east Atlantic Ocean region.     

通用地球系统模式对亚洲夏季风降水的模拟能力评估

通过与观测/再分析资料和参加第五次耦合模式比较计划(CMIP5)的模式模拟结果进行对比,评估了通用地球系统模式(CESM,1.0.3版本)对亚洲夏季风降水的模拟能力。结果表明:CESM能够合理地模拟出亚洲夏季风降水的气候平均态,但与其他CMIP5模式模拟结果类似,对中国东南地区降水模拟偏少,而对中国西部高原地区降水模拟偏多;CESM可以再现亚洲季风区降水冬弱夏强、雨带北进南退的季节变化特征,其模拟偏差具有区域性和季节性差异;从EOF分析结果来看,CESM能够模拟出亚洲夏季风降水的时空变化特征,且能较好地抓住亚洲夏季风降水与厄尔尼诺-南方涛动(El Ni?o-Southern Oscillation,简称ENSO)的相关关系。总的说来,CESM对亚洲夏季风降水的模拟是合理的,模拟水平与4个最好的CMIP5模式相当。     

Skill assessment of three earth system models with common marine biogeochemistry

We have assessed the ability of a common ocean biogeochemical model, PISCES, to match relevant modern data fields across a range of ocean circulation fields from three distinct Earth system models: IPSL-CM4-LOOP, IPSL-CM5A-LR and CNRM-CM5.1. The first of these Earth system models has contributed to the IPCC 4th assessment report, while the latter two are contributing to the ongoing IPCC 5th assessment report. These models differ with respect to their atmospheric component, ocean subgrid-scale physics and resolution. The simulated vertical distribution of biogeochemical tracers suffer from biases in ocean circulation and a poor representation of the sinking fluxes of matter. Nevertheless, differences between upper and deep ocean model skills significantly point to changes in the underlying model representations of ocean circulation. IPSL-CM5A-LR and CNRM-CM5.1 poorly represent deep-ocean circulation compared to IPSL-CM4-LOOP degrading the vertical distribution of biogeochemical tracers. However, their representations of surface wind, wind stress, mixed-layer depth and geostrophic circulations (e.g., Antarctic Circumpolar Current) have been improved compared to IPSL-CM4-LOOP. These improvements result in a better representation of large-scale structure of biogeochemical fields in the upper ocean. In particular, a deepening of 20–40 m of the summer mixed-layer depth allows to capture the 0–0.5 μgChl L^?1 concentrations class of surface chlorophyll in the Southern Ocean. Further improvements in the representation of the ocean mixed-layer and deep-ocean ventilation are needed for the next generations of models development to better simulate marine biogeochemistry. In order to better constrain ocean dynamics, we suggest that biogeochemical or passive tracer modules should be used routinely for both model development and model intercomparisons.     

Use of variability modes to evaluate AR4 climate models over the Euro-Atlantic region

This paper analyzes the ability of the multi-model simulations from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) to simulate the main leading modes of variability over the Euro-Atlantic region in winter: the North-Atlantic Oscillation (NAO), the Scandinavian mode (SCAND), the East/Atlantic Oscillation (EA) and the East Atlantic/Western Russia mode (EA/WR). These modes of variability have been evaluated both spatially, by analyzing the intensity and location of their anomaly centres, as well as temporally, by focusing on the probability density functions and e-folding time scales. The choice of variability modes as a tool for climate model assessment can be justified by the fact that modes of variability determine local climatic conditions and their likely change may have important implications for future climate changes. It is found that all the models considered are able to simulate reasonably well these four variability modes, the SCAND being the mode which is best spatially simulated. From a temporal point of view the NAO and SCAND modes are the best simulated. UKMO-HadGEM1 and CGCM3.1(T63) are the models best at reproducing spatial characteristics, whereas CCSM3 and CGCM3.1(T63) are the best ones with regard to the temporal features. GISS-AOM is the model showing the worst performance, in terms of both spatial and temporal features. These results may bring new insight into the selection and use of specific models to simulate Euro-Atlantic climate, with some models being clearly more successful in simulating patterns of temporal and spatial variability than others.