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...     

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.

     

Analysis of the Slab Ocean El Nino atmospheric feedbacks in observed and simulated ENSO dynamics

In a recent study it was illustrated that the El Nino Southern Oscillation (ENSO) mode can exist in the absence of any ocean dynamics. This oscillating mode exists just due to the interaction between atmospheric heat fluxes and ocean heat capacity. The primary purpose of this study is to further explore these atmospheric Slab Ocean ENSO dynamics and therefore the role of positive atmospheric feedbacks in model simulations and observations. The positive solar radiation feedback to sea surface temperature (SST), due to reduced cloud cover for anomalous warm SSTs, is the main positive feedback in the Slab Ocean El Nino dynamics. The strength of this positive cloud feedback is strongly related to the strength of the equatorial cold tongue. The combination of positive latent and sensible heat fluxes to the west and negative ones to the east of positive anomalies leads to the westward propagation of the SST anomalies, which allows for oscillating behavior with a preferred period of 6–7 years. Several indications are found that parts of these dynamics are indeed observed and simulated in other atmospheric or coupled general circulation models (AGCMs or CGCMs). The CMIP3 AGCM-slab ensemble of 13 different AGCM simulations shows unstable ocean–atmosphere interactions along the equatorial Pacific related to stronger cold tongues. In observations and in the CMIP3 and CMIP5 CGCM model ensemble the strength and sign of the cloud feedback is a function of the strength of the cold tongue. In summary, this indicates that the Slab Ocean El Nino dynamics are indeed a characteristic of the equatorial Pacific climate that is only dominant or significantly contributing to the ENSO dynamics if the SST cold tongue is sufficiently strong. In the observations this is only the case during strong La Nina conditions. The presence of the Slab Ocean ENSO atmospheric feedbacks in observations and CGCM model simulations implies that the family of physical ENSO modes does have another member, which is entirely driven by atmospheric processes and does not need to have the same spatial pattern nor the same time scales as the main ENSO dynamics.     

CMIP5模式对AMO与PDO模拟评估及未来预估

利用1880-2009年海表温度(Sea Surface Temperature,SST)观测资料以及耦合模式比较计划第五阶段(Coupled Model Intercomparison Project phase 5,CMIP5)中4种情景(piControl、historical、RCP2.6、RCP4.5)下的模...     

A study of biases in simulation of the Indian Ocean basin mode and its capacitor effect in CMIP3/CMIP5 models

Based on 15 Coupled Model Intercomparison Project (CMIP) phase 3 (CMIP3) and 32 CMIP phase 5 (CMIP5) models, a detailed diagnosis was carried out to understand what compose the biases in simulation of the Indian Ocean basin mode (IOBM) and its capacitor effect. Cloud-radiation-SST (CRS) feedback and wind-evaporation-SST (WES) feedback are the two major atmospheric processes for SST changes. Most CMIP models simulate a stronger CRS feedback and a weaker WES feedback. During boreal fall of the El Niño/Southern Oscillation developing year and the following spring, there are weak biases of suppressed rainfall anomalies over the Maritime Continent and anomalous anticyclone over South Indian Ocean. Most CMIP models simulate reasonable short wave radiation (SWR) and weaker latent heat flux (LHF) anomalies. This leads to a weak bias of atmospheric processes. During winter, however, the rainfall anomalies are stronger due to west bias, and the anomalous anticyclone is comparable to observations. As such, most models simulate stronger SWR and reasonable LHF anomalies, leading to a strong bias of atmospheric processes. The thermocline feedback is stronger in most models. Though there is a deep bias of climatology thermocline, most models capture reasonable sea surface height-induced SST anomalies. Therefore, the effect of oceanic processes offset the weak bias of atmospheric processes in spring, and the tropical Indian Ocean warming persists into summer. However, anomalous northwest Pacific (NWP) anticyclone is weaker due to weak and west bias of the capacitor effect. The unrealistic western Pacific SST anomalies in models favor the westward extension of Rossby wave from the Pacific, weakening the effect of Kelvin wave from the Indian Ocean. Moreover, the western Pacific warming forces the NWP anticyclone move farther north than observations, suggesting a major forcing from the Pacific. Compared to CMIP3, CMIP5 models simulate the feedbacks more realistically and display less diversity. Thus, the overall performance of CMIP5 models is better than that of CMIP3 models.     

Indian Ocean variability in the CMIP5 multi-model ensemble: the zonal dipole mode

The performance of 21 Coupled Model Intercomparison Project Phase 5 (CMIP5) models in the simulation of the Indian Ocean Dipole (IOD) mode is evaluated. Compared to CMIP3, CMIP5 models exhibit a similar spread in IOD intensity. A detailed diagnosis was carried out to understand whether CMIP5 models have shown improvement in their representation of the important dynamical and thermodynamical feedbacks in the tropical Indian Ocean. These include the Bjerknes dynamic air-sea feedback, which includes the equatorial zonal wind response to sea surface temperature (SST) anomaly, the thermocline response to equatorial zonal wind forcing, the ocean subsurface temperature response to the thermocline variations, and the thermodynamic air-sea coupling that includes the wind-evaporation-SST and cloud-radiation-SST feedback. Compared to CMIP3, the CMIP5 ensemble produces a more realistic positive wind-evaporation-SST feedback during the IOD developing phase, while the simulation of Bjerknes dynamic feedback is more unrealistic especially with regard to the wind response to SST forcing and the thermocline response to surface wind forcing. The overall CMIP5 performance in the IOD simulation does not show remarkable improvements compared to CMIP3. It is further noted that the El Niño-Southern Oscillation (ENSO) and IOD amplitudes are closely related, if a model generates a strong ENSO, it is likely that this model also simulates a strong IOD.     

SST and ENSO variability and change simulated in historical experiments of CMIP5 models

This work documents the diversity in Coupled Model Inter-comparison Project Phase 5 (CMIP5) models in simulating different aspects of sea surface temperature (SST) variability, particularly those associated with the El Niño–Southern Oscillation (ENSO), as well as the impact of low-frequency variations on the ENSO variability and its global teleconnection. The historical simulations (1870–2005) include 10 models with ensemble member ranging from 3 to 10 that are forced with observed atmospheric composition changes reflecting both natural and anthropogenic forcings. It is shown that the majority of the CMIP5 models capture the relative large SST anomaly variance in the tropical central and eastern Pacific, as well as in North Pacific and North Atlantic. The frequency of ENSO is not well captured by almost all models, particularly for the period of 5–6 years. The low-frequency variations in SST caused by external forcings affect the SST variability and also modify the global teleconnection of ENSO. The models reproduce the global averaged SST low-frequency variations, particularly since 1970s. However, majority of the models are unable to correctly simulate the spatial pattern of the observed SST trends. These results suggest that it is still a challenge to reproduce the features of global historical SST variations with the state-of-the-art coupled general circulation model.     

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.     

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。     

The Indo-Australian monsoon and its relationship to ENSO and IOD in reanalysis data and the CMIP3/CMIP5 simulations

A large spread exists in both Indian and Australian average monsoon rainfall and in their interannual variations diagnosed from various observational and reanalysis products. While the multi model mean monsoon rainfall from 59 models taking part in the Coupled Model Intercomparison Project (CMIP3 and CMIP5) fall within the observational uncertainty, considerable model spread exists. Rainfall seasonality is consistent across observations and reanalyses, but most CMIP models produce either a too peaked or a too flat seasonal cycle, with CMIP5 models generally performing better than CMIP3. Considering all North-Australia rainfall, most models reproduce the observed Australian monsoon-El Niño Southern Oscillation (ENSO) teleconnection, with the strength of the relationship dependent on the strength of the simulated ENSO. However, over the Maritime Continent, the simulated monsoon-ENSO connection is generally weaker than observed, depending on the ability of each model to realistically reproduce the ENSO signature in the Warm Pool region. A large part of this bias comes from the contribution of Papua, where moisture convergence seems to be particularly affected by this SST bias. The Indian summer monsoon-ENSO relationship is affected by overly persistent ENSO events in many CMIP models. Despite significant wind anomalies in the Indian Ocean related to Indian Ocean Dipole (IOD) events, the monsoon-IOD relationship remains relatively weak both in the observations and in the CMIP models. Based on model fidelity in reproducing realistic monsoon characteristics and ENSO teleconnections, we objectively select 12 “best” models to analyze projections in the rcp8.5 scenario. Eleven of these models are from the CMIP5 ensemble. In India and Australia, most of these models produce 5–20 % more monsoon rainfall over the second half of the twentieth century than during the late nineteenth century. By contrast, there is no clear model consensus over the Maritime Continent.     

CMIP5多模式对阿留申低压气候特征的模拟检验与预估

利用观测的海温资料和海平面气压资料,检验了CMIP5(Coupled Model Intercomparison Project 5,CMIP5)多模式对阿留申低压(Aleutian Low,AL)特征指数的时空分布和变化的模拟能力;从AL周期及变化趋势等方面,分析了CMIP5模式预估的未来AL的变化特征。结果表明,CMIP5模式及其集合平均能够很好地模拟AL的环流结构,对AL的气候态有着较强的模拟能力,尤其是模式对于东太平洋海表温度的模拟能力直接影响其对于AL的模拟效果。模式的集合平均对变率强度的模拟偏强,且对于变率的模拟效果逊于对气候态的模拟。22个模式中的16个模式能模拟出AL强度指数的年代际变化周期,对年代际周期有着较好的刻画能力。Historical试验下对于AL的变化趋势存在着较大的不确定性,而相对于两种不同排放情景,随着排放的增加,AL更加偏北,强度增强,年际、年代际周期变得更加显著。在两种排放情景下模式的集合平均以及多数模式模拟出AL有着向北和增强的趋势。     

Uncertainty in land surface temperature simulation over China by CMIP3/CMIP5 models

In this paper, China-based observations are used to evaluate the performance of 24 CMIP3 (phase 3 of the Coupled Model Intercomparison Project) and 10 CMIP5 models in simulating land surface temperature (LST). It is found that all models can generally reproduce the climatology patterns of LST averaged during the period from 1960 to 1999. Further analyses of the regional features of LST show that the discrepancies between the observations and the simulations are smaller in Southwest and East China. Moreover, these models overestimate the temperatures in almost all areas, particularly in July. Although many models have large biases relative to the observations, the spread of the model results is large (i.e., >22 °C in Northwest and Northeast China). For the interannual variations, neither the individual models nor the multi-model mean has a remarkable positive correlation to the observations in the selected subregions. However, most models can capture geographic features during trend evaluations. A multi-model ensemble is believed to be an effective way to limit uncertainties, but the results suggest that its efficiency is restricted to simulating the LST trend. Examination of the surface energy budget indicated that the modeled discrepancies of net shortwave radiation and surface sensible heat flux may be responsible for the LST results, especially in July. It is concluded that the ability of current models in simulating LST over China is still a significant challenge. The spread of the models is large in simulating the climatology, interannual variation, and trend of LSTs. In general, the magnitudes of the spread may be as large as the magnitudes of the observations. Additionally, it is found that multi-model ensembles do not simulate LST with any more skill. Therefore, more work must focus on the limitations of the models' uncertainties in land surface research.     

CMIP5模式对中国年平均气温模拟及其与CMIP3模式的比较

利用CRUT3v和CN05两套观测资料,评估25个CMIP5模式对1906-2005年中国年平均气温变化的模拟能力,并与CMIP3模式对比。结果表明：1906-2005年中国平均温升速率为0.84℃/100a,CMIP5多模式集合平均模拟的增温率为0.77℃/100a。模式对20世纪后期温升模拟好于前期,仅有两个模式能模拟中国20世纪40年代异常增暖。模式对气温气候态空间分布模拟较好,但在中国西部地区存在最大模拟冷偏差和不确定性。1961-1999年,中国北方增暖大于南方。多模式集合平均可以较好地模拟气温变化线性趋势的空间分布,但对南北气温变化趋势的差异模拟过小。总体说来,在中国平均气温变化趋势、气温气候态空间分布和气温变化趋势空间分布三方面,CMIP5模式都较CMIP3模式有所提高。     

The Atlantic Multidecadal Oscillation in twentieth century climate simulations: uneven progress from CMIP3 to CMIP5

Decadal variability in the climate system from the Atlantic Multidecadal Oscillation (AMO) is one of the major sources of variability at this temporal scale that climate models must properly incorporate because of its climate impact. The current analysis of historical simulations of the twentieth century climate from models participating in the CMIP3 and CMIP5 projects assesses how these models portray the observed spatiotemporal features of the sea surface temperature (SST) and precipitation anomalies associated with the AMO. A short sample of the models is analyzed in detail by using all ensembles available of the models CCSM3, GFDL-CM2.1, UKMO-HadCM3, and ECHAM5/MPI-OM from the CMIP3 project, and the models CCSM4, GFDL-CM3, UKMO-HadGEM2-ES, and MPI-ESM-LR from the CMIP5 project. The structure and evolution of the SST anomalies of the AMO have not progressed consistently from the CMIP3 to the CMIP5 models. While the characteristic period of the AMO (smoothed with a binomial filter applied fifty times) is underestimated by the three of the models, the e-folding time of the autocorrelations shows that all models underestimate the 44-year value from observations by almost 50 %. Variability of the AMO in the 10–20/70–80 year ranges is overestimated/underestimated in the models and the variability in the 10–20 year range increases in three of the models from the CMIP3 to the CMIP5 versions. Spatial variability and correlation of the AMO regressed precipitation and SST anomalies in summer and fall indicate that models are not up to the task of simulating the AMO impact on the hydroclimate over the neighboring continents. This is in spite of the fact that the spatial variability and correlations in the SST anomalies improve from CMIP3 to CMIP5 versions in two of the models. However, a multi-model mean from a sample of 14 models whose first ensemble was analyzed indicated there were no improvements in the structure of the SST anomalies of the AMO or associated regional precipitation anomalies in summer and fall from CMIP3 to CMIP5 projects.     

CMIP6全球气候模式对中国冬季寒潮频次模拟能力的评估北大核心CSCD

基于1961~2013年观测资料和第六次国际耦合模式比较计划(CMIP6)中32个气候模式的最低气温数据,评估了各模式及多模式集合平均方法对中国冬季寒潮频次的模拟能力,并筛选了中国不同区域的最优模式,为中国未来寒潮频次预估和气候模式改进提供理论支撑。结果表明,CMIP6全球气候模式可以很好地再现出中国冬季寒潮频次由北向南逐级递减的空间特征,EC-Earth3-Veg对中国寒潮频次模拟能力最好;绝大多数模式可以模拟出中国冬季寒潮频次下降的趋势,但对趋势变化幅度的模拟能力则相对有限。多模式等权重集合平均和多模式中位数集合平均较单一模式分别对中国北方地区和南方地区冬季寒潮频次空间格局的模拟效果改进显著,但是对趋势值的模拟普遍偏低。     

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.     

Zonal structure and variability of the Western Pacific dynamic warm pool edge in CMIP5

The equatorial edge of the Western Pacific Warm Pool is operationally identified by one isotherm ranging between 28° and 29 °C, chosen to align with the interannual variability of strong zonal salinity gradients and the convergence of zonal ocean currents. The simulation of this edge is examined in 19 models from the World Climate Research Program Coupled Model Intercomparison Project Phase 5 (CMIP5), over the historical period from 1950 to 2000. The dynamic warm pool edge (DWPE), where the zonal currents converge, is difficult to determine from limited observations and biased models. A new analysis technique is introduced where a proxy for DWPE is determined by the isotherm that most closely correlates with the movements of the strong salinity gradient. It can therefore be a different isotherm in each model. The DWPE is simulated much closer to observations than if a direct temperature-only comparison is made. Aspects of the DWPE remain difficult for coupled models to simulate including the mean longitude, the interannual excursions, and the zonal convergence of ocean currents. Some models have only very weak salinity gradients trapped to the western side of the basin making it difficult to even identify a DWPE. The model’s DWPE are generally 1–2 °C cooler than observed. In line with theory, the magnitude of the zonal migrations of the DWPE are strongly related to the amplitudes of the Nino3.4 SST index. Nevertheless, a better simulation of the mean location of the DWPE does not necessarily improve the amplitude of a model’s ENSO. It is also found that in a few models (CSIROMk3.6, inmcm and inmcm4-esm) the warm pool displacements result from a net heating or cooling rather than a zonal advection of warm water. The simulation of the DWPE has implications for ENSO dynamics when considering ENSO paradigms such as the delayed action oscillator mechanism, the Advective-Reflective oscillator, and the zonal-advective feedback. These are also discussed in the context of the CMIP5 simulations.     

On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates

This study diagnoses the climate sensitivity, radiative forcing and climate feedback estimates from eleven general circulation models participating in the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5), and analyzes inter-model differences. This is done by taking into account the fact that the climate response to increased carbon dioxide (CO₂) is not necessarily only mediated by surface temperature changes, but can also result from fast land warming and tropospheric adjustments to the CO₂ radiative forcing. By considering tropospheric adjustments to CO₂ as part of the forcing rather than as feedbacks, and by using the radiative kernels approach, we decompose climate sensitivity estimates in terms of feedbacks and adjustments associated with water vapor, temperature lapse rate, surface albedo and clouds. Cloud adjustment to CO₂ is, with one exception, generally positive, and is associated with a reduced strength of the cloud feedback; the multi-model mean cloud feedback is about 33 % weaker. Non-cloud adjustments associated with temperature, water vapor and albedo seem, however, to be better understood as responses to land surface warming. Separating out the tropospheric adjustments does not significantly affect the spread in climate sensitivity estimates, which primarily results from differing climate feedbacks. About 70 % of the spread stems from the cloud feedback, which remains the major source of inter-model spread in climate sensitivity, with a large contribution from the tropics. Differences in tropical cloud feedbacks between low-sensitivity and high-sensitivity models occur over a large range of dynamical regimes, but primarily arise from the regimes associated with a predominance of shallow cumulus and stratocumulus clouds. The combined water vapor plus lapse rate feedback also contributes to the spread of climate sensitivity estimates, with inter-model differences arising primarily from the relative humidity responses throughout the troposphere. Finally, this study points to a substantial role of nonlinearities in the calculation of adjustments and feedbacks for the interpretation of inter-model spread in climate sensitivity estimates. We show that in climate model simulations with large forcing (e.g., 4 × CO₂), nonlinearities cannot be assumed minor nor neglected. Having said that, most results presented here are consistent with a number of previous feedback studies, despite the very different nature of the methodologies and all the uncertainties associated with them.     

CMIP3及CMIP5模式对冬季和春季北极涛动变率模拟的比较

结合NCEP再分析资料,评估了28个参加第五次耦合模式比较计划（CMIP5）的耦合模式对1950-2000年冬、春季北极涛动（AO）变率的模拟能力,并与CMIP3模式模拟结果进行了对比。结果表明,尽管CMIP5模式没能模拟出冬、春季AO指数前30年处于显著的负位相期而后20年处于显著的正位相期的特征,但是基本能够模拟出冬、春季AO指数1950-2000年显著的增强趋势以及振荡周期,多模式集合改进了模拟效果。同样,CMIP3模式没能模拟出冬、春季AO指数前30年处于显著的负位相而后20年处于显著的正位相的特征,而且1950-2000年冬、春季AO指数的增强趋势在CMIP3模式模拟结果中也没有表现出来,多模式集合没有改进模式模拟效果。不仅如此,CMIP3模式对AO指数的长期变化周期模拟不好,只是模拟出了冬季周期为2～3 a的振荡,没有模拟出春季AO指数的4～5 a振荡周期。尽管CMIP5模式对冬、春季AO指数的模拟能力还不够理想,没有完全模拟出AO指数的变化特征,但是相对于CMIP3模式,无论是对AO指数变化趋势的模拟还是对其变化周期的模拟,CMIP5模式都有所提高。     

Annual cycle and interannual variability in the tropical pacific as simulated by three versions of FGOALS

The seasonal cycle and interannual variability in the tropical oceans simulated by three versions of the Flexible Ocean-Atmosphere-Land System (FGOALS) model (FGOALS-g1.0, FGOALS-g2 and FGOALSs2), which have participated in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5), are presented in this paper. The seasonal cycle of SST in the tropical Pacific is realistically reproduced by FGOALS-g2 and FGOALSs2, while it is poorly simulated in FGOALS-g1.0. Three feedback mechanisms responsible for the SST annual cycle in the eastern Pacific are evaluated. The ocean-atmosphere dynamic feedback, which is successfully reproduced by both FGOALS-g2 and FGOALS-s2, plays a key role in determining the SST annual cycle, while the overestimated stratus cloud-SST feedback amplifies the annual cycle in FGOALS-s2. Because of the serious warm bias existing in FGOALS-g1.0, the ocean-atmosphere dynamic feedback is greatly underestimated in FGOALS-g1.0, in which the SST annual cycle is mainly driven by surface solar radiation. FGOALS-g1.0 simulates much stronger ENSO events than observed, whereas FGOALS-g2 and FGOALSs2 successfully simulate the observed ENSO amplitude and period and positive asymmetry, but with less strength. Further ENSO feedback analyses suggest that surface solar radiation feedback is principally responsible for the overestimated ENSO amplitude in FGOALS-g1.0. Both FGOALS-g1.0 and FGOALS-s2 can simulate two different types of El Ni-no events — with maximum SST anomalies in the eastern Pacific (EP) or in the central Pacific (CP) — but FGOALS-g2 is only able to simulate EP El Ni-no, because the negative cloud shortwave forcing feedback by FGOALS-g2 is much stronger than observed in the central Pacific.