清华大学CIESM模式及其参与CMIP6的方案

世界气候研究计划（WCRP）组织实施第六次国际耦合模式比较计划（CMIP6),清华大学联合国内多家单位,通过多年的模式研发,完成联合地球系统模式（CIESM),除了CMIP6的气候诊断、评估和描述试验（DECK）和历史气候模拟试验（Historical),模式拟参与6个CMIP6子计划。通过介绍该模式的基本情况及其参与的试验子计划,为今后模式试验数据使用者提供参考。     

FIO-ESM v2.0模式及其参与CMIP6的方案

目前,世界气候研究计划（WCRP）组织的国际耦合模式比较计划（CMIP）已经进入到第六阶段（CMIP6),CMIP6试验的开展也已成为国内外地球系统模式工作组的首要工作之一。自然资源部第一海洋研究所地球系统模式FIO-ESM是以耦合自主开发的海浪模式为特色的地球系统模式。在参与CMIP5的FIO-ESM v1.0的基础上,通过升级分量模式、改进海气通量相关物理过程和提高分辨率等,FIO-ESM v2.0现已完成研发,正在开展CMIP6科学计划的相关试验。文中围绕FIO-ESM v2.0的特色和计划参与CMIP6的情况,介绍了FIO-ESM v2.0的模式框架、包含的特色物理过程以及拟参加的CMIP6科学计划情况,以方便气候研究领域的科学家了解和使用。     

BCC模式及其开展的CMIP6试验介绍

世界气候研究计划（WCRP）正在组织实施第六次国际耦合模式比较计划（CMIP6),国家气候中心作为参与单位之一,通过近几年的模式研发,推出3个最新模式版本参与该计划,包括含有气溶胶化学模块的地球系统模式BCC-ESM1.0、中等分辨率气候模式BCC-CSM2-MR和高分辨率气候模式BCC-CSM2-HR。除了CMIP6中的气候诊断、评估和描述试验（DECK）和历史气候模拟试验（Historical),这3个模式共将参与CMIP6中的10个模式比较子计划。文中主要介绍这3个模式的基本情况以及所开展的CMIP试验,并对BCC-CSM2-MR模式的Historical试验结果进行简要评估,为试验数据使用者提供参考。     

NUIST-ESM模式及其参与CMIP6的方案

近几年来,南京信息工程大学（NUIST）地球系统模拟中心致力于地球系统模式研发。最新发展的第三版本南京信息工程大学地球系统模式（NUIST-ESM v3）在原有的基础上改进了边界层方案与对流参数化方案,调整了模式中云物理过程,改进了耦合物理过程和海冰反照率等过程。此版本作为参加第六次国际耦合模式比较计划（CMIP6）的模式之一,注册了气候诊断、评估和描述试验（DECK）和历史气候模拟试验（Historical）以及ScenarioMIP、DAMIP、GMMIP、DCPP、PMIP、VolMIP和GeoMIP等7个比较子计划试验。目前DECK和Historical试验都已经完成,正将数据提交到ESGF数据发布平台。CMIP6模式比较子计划也将陆续完成并将发布数据,以供国内外学者下载使用。     

FGOALS-g模式及其参与CMIP6的方案

为参加第六次国际耦合模式比较计划（CMIP6）和进一步提高模式的模拟能力,大气科学和地球流体力学数值模拟国家重点实验室（LASG）模式团队发展了新一代的格点大气版本的FGOALS-g耦合模式。新版本模式在大气分辨率、海洋网格,以及各分量模式的物理过程等方面都有一定的改进,并正在参与CMIP6最核心的试验以及多个CMIP6模式比较子计划试验。给定CMIP6外强迫,模式在工业革命前参照试验（piControl）和大气模式比较计划（AMIP）试验中模拟的初步结果都比较合理。     

CMIP6的设计

正目前第六阶段耦合模式比较计划(Coupled Model Intercomparison Project Phase 6,简称CMIP6)正在紧张有序地进行中,这次参加对比的气候模式都是地球系统模式,其所有模式的全部计算结果将提供给各国科学家在研究全球和区域气候变化科学、影响和对策中使用。为便于大家了解和在未来的应用,这里简述CMIP6的设计~([1])。1 CMIP6设计考虑的科学焦点(1)科学背景。核心是生物地球化学强迫和反     

CAMS-CSM模式及其参与CMIP6的方案

世界气候研究计划(WCRP)组织开展的耦合模式比较计划已实施到第六阶段（CMIP6),中国气象科学研究院发展的气候系统模式CAMS-CSM是注册参加CMIP6的模式之一。除CMIP6要求的气候诊断、评估和描述试验（DECK）以及历史气候模拟试验（Historical）外,CAMS-CSM还计划参加情景模式比较计划（ScenarioMIP)、云反馈模式比较计划（CFMIP)、全球季风模式比较计划（GMMIP）和高分辨率模式比较计划（HighResMIP)这4个模式比较子计划（MIPs)。文中通过介绍CAMS-CSM的基本情况和模拟性能,以及计划参加的CMIP6试验及MIPs,为模式试验数据使用者提供参考。     

CMIP6海洋模式比较计划（OMIP）概况与评述

海洋模式比较计划（OMIP）是第六次国际耦合模式比较计划（CMIP6）中的一个支撑子计划。OMIP致力于CMIP6中模式系统偏差来源及其影响这样一个重要科学问题。同时,OMIP也将在区域海平面变化和近期气候（未来10~30 a）或者年代际气候预测的相关科学问题上有重要贡献,这些问题被世界气候研究计划（WCRP）列为气候科学领域巨大挑战的科学问题。OMIP采用统一的大气外强迫数据集和通量计算方案,进行全球海洋-海冰耦合试验、示踪物试验以及生物地球化学循环试验。同时,OMIP提供了一套针对海洋变量的详细的诊断框架,这个框架既可以评估和改进模式模拟,也可以用于理解海洋-海冰过程在整个气候系统中的作用。     

CMIP6二氧化碳移除模式比较计划（CDRMIP）概况与评述

地球工程是指通过人工方法在大规模尺度上干预气候系统,使地球气候降温的一种手段。CO₂移除是地球工程的主要途径之一。文中概述了CO₂移除地球工程的科学背景、各种CO₂移除方法的利弊、大尺度应用CO₂移除方法可能产生的气候效应和风险,以及CO₂移除方案在未来气候情景研究中的现状。在第六次国际耦合模式比较计划（CMIP6）框架下开展的CO₂移除模式比较计划（CDRMIP),为深入研究CO₂移除地球工程减缓气候变化的效能和气候系统对其的响应提供了统一试验方案和平台。CDRMIP的开展,对地球工程和气候变化研究具有重要的促进作用。     

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。      

Understanding the sources of Caribbean precipitation biases in CMIP3 and CMIP5 simulations

We assess the ability of Global Climate Models participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) to simulate observed annual precipitation cycles over the Caribbean. Compared to weather station records and gridded observations, we find that both CMIP3 and CMIP5 models can be grouped into three categories: (1) models that correctly simulate a bimodal distribution with two rainfall maxima in May–June and September–October, punctuated by a mid-summer drought (MSD) in July–August; (2) models that reproduce the MSD and the second precipitation maxima only; and (3) models that simulate only one precipitation maxima, beginning in early summer. These categories appear related to model simulation of the North Atlantic Subtropical High (NASH) and sea surface temperature (SST) in the Caribbean Sea and Gulf of Mexico. Specifically, models in category 2 tend to anticipate the westward expansion of the NASH into the Caribbean in early summer. Early onset of NASH results in strong moisture divergence and MSD-like conditions at the time of the May–June observed precipitation maxima. Models in category 3 tend to have cooler SST across the region, particularly over the central Caribbean and the Gulf of Mexico, as well as a weaker Caribbean low-level jet accompanying a weaker NASH. In these models, observed June-like patterns of moisture convergence in the central Caribbean and the Central America and divergence in the east Caribbean and the Gulf of Mexico persist through September. This analysis suggests systematic biases in model structure may be responsible for biases in observed precipitation variability over the Caribbean and more confidence may be placed in the precipitation simulated by the GCMs that are able to correctly simulate seasonal cycles of SST and NASH.     

ENSO phase-locking to the boreal winter in CMIP3 and CMIP5 models

In this study, the El Nino-Southern Oscillation (ENSO) phase-locking to the boreal winter in CMIP3 and CMIP5 models is examined. It is found that the models that are poor at simulating the winter ENSO peak tend to simulate colder seasonal-mean sea-surface temperature (SST) during the boreal summer and associated shallower thermocline depth over the eastern Pacific. These models tend to amplify zonal advection and thermocline depth feedback during boreal summer. In addition, the colder eastern Pacific SST in the model can reduce the summertime mean local convective activity, which tends to weaken the atmospheric response to the ENSO SST forcing. It is also revealed that these models have more serious climatological biases over the tropical Pacific, implying that a realistic simulation of the climatological fields may help to simulate winter ENSO peak better. The models that are poor at simulating ENSO peak in winter also show excessive anomalous SST warming over the western Pacific during boreal winter of the El Nino events, which leads to strong local convective anomalies. This prevents the southward shift of El Nino-related westerly during boreal winter season. Therefore, equatorial westerly is prevailed over the western Pacific to further development of ENSO-related SST during boreal winter. This bias in the SST anomaly is partly due to the climatological dry biases over the central Pacific, which confines ENSO-related precipitation and westerly responses over the western Pacific.     

Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models

There is a long-standing debate on how the El Niño/Southern Oscillation (ENSO) amplitude may change during the twenty-first century in response to global warming. Here we identify the sources of uncertainty in the ENSO amplitude projections in models participating in the Coupled Model Intercomparison Phase 5 (CMIP5) and Phase 6 (CMIP6), and quantify scenario uncertainty, model uncertainty and uncertainty due to internal variability. The model projections exhibit a large spread, ranging from increasing standard deviation of up to 0.6 °C to diminishing standard deviation of up to − 0.4 °C by the end of the twenty-first century. The ensemble-mean ENSO amplitude change is close to zero. Internal variability is the main contributor to the uncertainty during the first three decades; model uncertainty dominates thereafter, while scenario uncertainty is relatively small throughout the twenty-first century. The total uncertainty increases from CMIP5 to CMIP6: while model uncertainty is reduced, scenario uncertainty is considerably increased. The models with “realistic” ENSO dynamics have been analyzed separately and categorized into models with too small, moderate and too large ENSO amplitude in comparison to instrumental observations. The smallest uncertainties are observed in the sub-ensemble exhibiting realistic ENSO dynamics and moderate ENSO amplitude. However, the global warming signal in ENSO-amplitude change is undetectable in all sub-ensembles. The zonal wind-SST feedback is identified as an important factor determining ENSO amplitude change: global warming signal in ENSO amplitude and zonal wind-SST feedback strength are highly correlated across the CMIP5 and CMIP6 models.

     

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.     

Evaluation of the performance of CMIP5 and CMIP6 models in simulating the South Pacific Quadrupole-ENSO relationship

先前的观测研究表明,南太平洋四极子海温模态(SPQ)可以有效地作为ENSO的前兆信号.本文利用20个CMIP6模式及其对应的20个先前的CMIP5模式的工业化前气候模拟试验数据,评估和比较了CMIP6以及CMIP5模式对SPQ与ENSO的关系的模拟能力.结果表明,大多数CMIP5和CMIP6模式可以合理地模拟SPQ的基本特征.与早期的CMIP5模式相比,CMIP6模式能够更加真实地模拟SPQ与ENSO之间的关系.进一步分析表明,CMIP6模式模拟SPQ与ENSO关系的能力提高,是因为CMIP6模式能够更好地模拟出在副热带/热带太平洋上与SPQ相关的表面海气热力耦合过程,以及在赤道太平洋上与SPQ相关的次表层海温的异常相应.     

Reproducibility of precipitation distribution over the tropical oceans in CMIP5 multi-climate models compared to CMIP3

Reproducibility of precipitation distribution over the tropical oceans for the recent dataset of the Coupled Model Intercomparison Project phase 5 (CMIP5) is investigated and compared to CMIP3. The Taylor skill score for the reproducibility of the CMIP5 multi-model ensemble mean (0.64) is slightly higher than that of CMIP3 (0.60), but the difference is not statistically significant. Still, there is some evidences that the double intertropical convergence zone (ITCZ) bias is mitigated from CMIP3 to CMIP5, whereas the cold tongue bias remains similar. An inter-model empirical orthogonal function analysis shows that these two biases are closely related to the dominant inter-model discrepancies of precipitation patterns. The two biases are attributed to two factors, respectively. In the CMIP5 models with the prominent double ITCZ, the deep convection is not sensitive enough to environmental air humidity at the lower-mid troposphere, as is in CMIP3. Thus, the deep convection is not suppressed even over the dry subsidence region of the southeastern Pacific, forming the double ITCZ bias. Conversely, models with the severe cold tongue bias have lower ocean model resolution with too strong equatorial trades. Therefore, proper representation of the sensitivity of deep convection to humidity and higher resolution of the ocean models with better equatorial trades are important for reducing the double ITCZ and the cold tongue biases.