Relative performance of CMIP5 and CMIP6 models in simulating rainfall in Peninsular Malaysia

Theoretical and Applied Climatology - This study evaluated the skills of global climate models (GCMs) of the fifth and sixth Coupled Model Intercomparison Project (CMIP5 and CMIP6) in simulating...     

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.     

Parallel comparison of the northern winter stratospheric circulation in reanalysis and in CMIP5 models

A parallel comparison is made of the circulation climatology and the leading oscillation mode of the northern winter stratosphere among six reanalysis products and 24 CMIP5(Coupled Model Intercomparison Project Phase 5) models. The results reveal that the NCEP/NCAR, NECP/DOE, ERA40, ERA-Interim and JRA25 reanalyses are quite consistent in describing the climatology and annual cycle of the stratospheric circulation. The 20 CR reanalysis, however, exhibits a remarkable"cold pole" bias accompanied by a much stronger stratospheric polar jet, similar as in some CMIP5 models. Compared to the1–2 month seasonal drift in most coupled general circulation models(GCMs), the seasonal cycle of the stratospheric zonal wind in most earth system models(ESMs) agrees very well with reanalysis. Similar to the climatology, the amplitude of Polar Vortex Oscillation(PVO) events also varies among CMIP5 models. The PVO amplitude in most GCMs is relatively weaker than in reanalysis, while that in most of the ESMs is more realistic. In relation to the "cold pole" bias and the weaker oscillation in some CMIP5 GCMs, the frequency of PVO events is significantly underestimated by CMIP5 GCMs; while in most ESMs, it is comparable to that in reanalysis. The PVO events in reanalysis(except in 20CR) mainly occur from mid-winter to early spring(January–March); but in some of the CMIP5 models, a 1–2 month delay exists, especially in most of the CMIP5 GCMs. The long-term trend of the PVO time series does not correspond to long-term changes in the frequency of PVO events in most of the CMIP5 models.     

Evaluation of CMIP5 dynamic sea surface height multi-model simulations against satellite observations

We evaluate the representation of dynamic sea surface height (SSH) fields of 33 global coupled models (GCMs) contributed to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We use observations from satellite altimetry and basic performance metrics to quantify the ability of the GCMs to replicate observed SSH of the time-mean, seasonal cycle, and inter-annual variability patterns. The time-mean SSH representation has markedly improved from CMIP3 to CMIP5, both in terms of overall reduction in root-mean square differences, and in terms of reduced GCM ensemble spread. Biases of the time-mean SSH field in the Indian and Pacific Ocean equatorial regions are consistent with biases in the zonal surface wind stress fields identified with independent measurements. In the Southern Ocean, the latitude of the maximum meridional gradient of the zonal mean SSH CMIP5 models is shifted equatorward, consistent with the GCMs’ spatial biases in the maximum of the zonal mean westerly surface wind stress fields. However, while the Southern Ocean SSH gradients correlate well with the maximum Antarctic circumpolar current transports, there is no significant correlation with the maximum zonal mean wind stress amplitudes, consistent with recent findings that the eddy parameterisations in GCMs dominate over wind stress amplitudes in this region. There is considerable spread across the CMIP5 ensemble for the seasonal and interannual SSH variability patterns. Because of the short observational period, the interannual variability patterns depend on the time-period over which they are derived, while no such dependency is found for the time-mean patterns. The model performance metrics for SSH presented here provide insight into GCM shortcoming due to inadequate model physics or processes. While the diagnostics of CMIP5 GCM performance relative to observations reveal that some models are clearly better than others, model performance is sensitive to the spatio-temporal scales chosen.     

Improved atmospheric circulation over Europe by the new generation of CMIP6 earth system models

Global Climate Models (GCMs) generally exhibit significant biases in the representation of large-scale atmospheric circulation. Even after a sensible bias adjustment these errors remain and are inherited to some extent by the derived downscaling products, impairing the credibility of future regional projections. In this study we perform a process-based evaluation of state-of-the-art GCMs from CMIP5 and CMIP6, with a focus on the simulation of the synoptic climatological patterns having a most prominent effect on the European climate. To this aim, we use the Lamb Weather Type Classification (LWT, Lamb British isles weather types and a register of the daily sequence 736 of circulation patterns 1861-1971. METEOROL OFF, GEOPHYS MEM; 737 GB; DA 1972; NO 116; PP 1-85; BIBL 2P1/2, 1972), a subjective classification of circulation weather types constructed upon historical simulations of daily mean sea level pressure. Observational uncertainty has been taken into account by considering four different reanalysis products of varying characteristics. Our evaluation unveils an overall improvement of salient atmospheric circulation features consistent across observational references, although this is uneven across models and large frequency biases still remain for the main LWTs. Some CMIP6 models attain similar or even worse results than their CMIP5 counterparts, although in most cases consistent improvements have been found, demonstrating the ability of the new models to better capture key synoptic conditions. In light of the large differences found across models, we advocate for a careful selection of driving GCMs in downscaling experiments with a special focus on large-scale atmospheric circulation aspects.

     

Current and future atmospheric circulation at 500 hPa over Greenland simulated by the CMIP3 and CMIP5 global models

The Greenland ice sheet is projected to be strongly affected by global warming. These projections are either issued from downscaling methods (such as Regional Climate Models) or they come directly from General Circulation Models (GCMs). In this context, it is necessary to evaluate the accuracy of the daily atmospheric circulation simulated by the GCMs, since it is used as forcing for downscaling methods. Thus, we use an automatic circulation type classification based on two indices (Euclidean distance and Spearman rank correlation using the daily 500 hPa geopotential height) to evaluate the ability of the GCMs from both CMIP3 and CMIP5 databases to simulate the main circulation types over Greenland during summer. For each circulation type, the GCMs are compared to three reanalysis datasets on the basis of their frequency and persistence differences. For the current climate (1961–1990), we show that most of the GCMs do not reproduce the expected frequency and the persistence of the circulation types and that they simulate poorly the observed daily variability of the general circulation. Only a few GCMs can be used as reliable forcings for downscaling methods over Greenland. Finally, when applying the same approach to the future projections of the GCMs, no significant change in the atmospheric circulation over Greenland is detected, besides a generalised increase of the geopotential height due to a uniform warming of the atmosphere.     

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...     

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.     

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...     

CMIP3与CMIP5模式对中国西北干旱区气温和降水的模拟能力比较

通过对15组CMIP3和CMIP5两代模式集合平均对中国西北干旱区气温和降水的模拟能力比较,发现CMIP5模式对气温和降水的模拟更接近观测值。CMIP5模式模拟年、春季、夏季、秋季平均气温的相关系数比CMIP3模式分别提升了0.15、0.13、0.24和0.02,冬季下降了0.07。CMIP5模式对西北干旱区的平均气温变化趋势的模拟效果比CMIP3有所提高,对年、春季、夏季、秋季、冬季趋势的模拟偏差比CMIP3分别减少了0.03℃/10a、0.10℃/10a、0.01℃/10a、0.06℃/10a、0.14℃/10a。对西北干旱区平均气温年、季的模拟偏差分布上,CMIP5模式的偏差均比CMIP3低1~2℃。但是天山区年、季节平均气温的模拟与整体模拟偏低情况相反,CMIP3和CMIP5分别偏高3~6℃和1~4℃,对夏季的模拟偏高最严重,分别达到6℃和4℃。CMIP5模式整体对西北干旱区降水量的模拟结果与观测值的平均相关系数与CMIP3相差不大,均不超过0.1,而且偏差仍然较大。CMIP5模式对西北干旱区的降水量的变化趋势模拟效果比CMIP3有所降低,对年、春季、夏季、秋季、冬季趋势的模拟偏差比CMIP3增加了0.67 mm/10a、0.23 mm/10a、0.51 mm/10a、0.11 mm/10a、0.14 mm/10a。CMIP5模式对年、春季、夏季、秋季和冬季的降水量模拟的均方根误差相比CMIP3分别减少77.6 mm、25.5 mm、25.0 mm、18.8 mm和13.9 mm。在空间上,CMIP5模式对年、季节降水模拟仍然偏高,但是比CMIP3有明显缓解;CMIP3和CMIP5模式对夏季天山区年降水量和夏季降水量的模拟也与大部分区域偏高的趋势明显相反,两代模式对夏季天山区的降水模拟均偏低50 mm左右。     

Interannual variability of the sea surface salinity and its related freshwater flux in the tropical Pacific: A comparison of CMIP5 and CMIP6

This paper assesses the interannual variabilities of simulated sea surface salinity (SSS) and freshwater flux (FWF) in the tropical Pacific from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). The authors focus on comparing the simulated SSS and FWF responses to El Niño–Southern Oscillation (ENSO) from two generations of models developed by the same group. The results show that CMIP5 and CMIP6 models can perform well in simulating the spatial distributions of the SSS and FWF responses associated with ENSO, as well as their relationship. It is found that most CMIP6 models have improved in simulating the geographical distribution of the SSS and FWF interannual variability in the tropical Pacific compared to CMIP5 models. In particular, CMIP6 models have corrected the underestimation of the spatial relationship of the FWF and SSS variability with ENSO in the central-western Pacific. In addition, CMIP6 models outperform CMIP5 models in simulating the FWF interannual variability (spatial distribution and intensity) in the tropical Pacific. However, as a whole, CMIP6 models do not show improved skill scores for SSS interannual variability, which is due to their overestimation of the intensity in some models. Large uncertainties exist in simulating the interannual variability of SSS among CMIP5 and CMIP6 models and some improvements with respect to physical processes are needed.摘要通过比较CMIP5和CMIP6来自同一个单位两代模式模拟, 表明CMIP5和CMIP6均能较好地模拟出热带太平洋的海表盐度 (SSS) 和淡水通量 (FWF) 对ENSO响应的分布及其响应间的关系. 与CMIP5模式相比, 大部份CMIP6模式模拟的SSS和FWF年际变化分布均呈现改进, 特别是纠正了较低的中西太平洋SSS和FWF变化的空间关系. 但是, 整体上, CMIP6模式模拟的SSS年际变化技巧没有提高, 与SSS年际变率的强度被高估有关. CMIP5和CMIP6模式模拟SSS的年际变化还存在较大的不确定性, 在物理方面需要改进.     

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.

     

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/m²和3.3 W/m²。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。     

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.     

ENSO representation in climate models: from CMIP3 to CMIP5

We analyse the ability of CMIP3 and CMIP5 coupled ocean–atmosphere general circulation models (CGCMs) to simulate the tropical Pacific mean state and El Niño-Southern Oscillation (ENSO). The CMIP5 multi-model ensemble displays an encouraging 30 % reduction of the pervasive cold bias in the western Pacific, but no quantum leap in ENSO performance compared to CMIP3. CMIP3 and CMIP5 can thus be considered as one large ensemble (CMIP3 + CMIP5) for multi-model ENSO analysis. The too large diversity in CMIP3 ENSO amplitude is however reduced by a factor of two in CMIP5 and the ENSO life cycle (location of surface temperature anomalies, seasonal phase locking) is modestly improved. Other fundamental ENSO characteristics such as central Pacific precipitation anomalies however remain poorly represented. The sea surface temperature (SST)-latent heat flux feedback is slightly improved in the CMIP5 ensemble but the wind-SST feedback is still underestimated by 20–50 % and the shortwave-SST feedbacks remain underestimated by a factor of two. The improvement in ENSO amplitudes might therefore result from error compensations. The ability of CMIP models to simulate the SST-shortwave feedback, a major source of erroneous ENSO in CGCMs, is further detailed. In observations, this feedback is strongly nonlinear because the real atmosphere switches from subsident (positive feedback) to convective (negative feedback) regimes under the effect of seasonal and interannual variations. Only one-third of CMIP3 + CMIP5 models reproduce this regime shift, with the other models remaining locked in one of the two regimes. The modelled shortwave feedback nonlinearity increases with ENSO amplitude and the amplitude of this feedback in the spring strongly relates with the models ability to simulate ENSO phase locking. In a final stage, a subset of metrics is proposed in order to synthesize the ability of each CMIP3 and CMIP5 models to simulate ENSO main characteristics and key atmospheric feedbacks.     

Evaluating historical simulations of CMIP5 GCMs for key climatic variables in Zhejiang Province,China

Assessing the regional impact of climate change on agriculture, hydrology, and forests is vital for sustainable management. Trustworthy projections of climate change are needed to support these assessments. In this paper, 18 global climate models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to simulate regional climate change in Zhejiang Province, Southeast China. Simple graphical approaches and three indices are used to evaluate the performance of six key climatic variables during simulations from 1971 to 2000. These variables include maximum and minimum air temperature, precipitation, wind speed, solar radiation, and relative humidity. These variables are of great importance to researchers and decision makers in climate change impact studies and developing adaptation strategies. This study found that most GCMs failed to reproduce the observed spatial patterns, due to insufficient resolution. However, the seasonal variations of the six variables are simulated well by most GCMs. Maximum and minimum air temperatures are simulated well on monthly, seasonal, and yearly scales. Solar radiation is reasonably simulated on monthly, seasonal, and yearly scales. Compared to air temperature and solar radiation, it was found that precipitation, wind speed, and relative humidity can only be simulated well at seasonal and yearly scales. Wind speed was the variable with the poorest simulation results across all GCMs.     

Evaluation of spring persistent rainfall over East Asia in CMIP3/CMIP5 AGCM simulations

The progress made fi＇om Phase 3 to Phase 5 of the Coupled Model Intercomparison Project （CMIP3 to CMIP5） in simulating spring persistent rainfall （SPR） over East Asia was examined from the outputs of nine atmospheric general circulation models （AGCMs）. The majority of the models overestimated the precipitation over the SPR domain, with the mean latitude of the SPR belt shifting to the north. The overestimation was about 1mm d-1 in the CMIP3 ensemble, and the northward displacement was about 3°, while in the CMIP5 ensemble the overestimation was suppressed to 0.7 mm d-i and the northward shift decreased to 2.5°. The SPR features a northeast-southwest extended rain belt with a slope of 0.4°N/°E. The CMIP5 ensemble yielded a smaller slope （0.2°N/°E）, whereas the CMIP3 ensemble featured an unre- alistic zonally-distributed slope. The CMIP5 models also showed better skill in simulating the interannual variability of SPR. Previous studies have suggested that the zonal land-sea thermal contrast and sensible heat flux over the southeastern Tibetan Plateau are important for the existence of SPR. These two ther- mal factors were captured well in the CMIP5 ensemble, but underestimated in the CMIP3 ensemble. The variability of zonal land-sea thermal contrast is positively correlated with the rainfall amount over the main SPR center, but it was found that an overestimated thermal contrast between East Asia and South China Sea is a common problem in most of the CMIP3 and CMIP5 models. Simulation of the meridional thermal contrast is therefore important for the future improvement of current AGCMs.     

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。     

Identification of the principal patterns of summer moisture transport in South America and their representation by WCRP/CMIP3 global climate models

The goal of this study is to assess the ability of a set of global climate models (GCMs) to represent the main regional spatial patterns of austral summer moisture transport in South America in order to evaluate if one of the possible causes of GCMs misestimating summer precipitation in this region could be associated with an erroneous representation of these patterns. For this purpose, NCEP/NCAR reanalysis and 20 GCMs from the WCRP/CMIP3 multi-model dataset for the period 1960–1999 were considered. Extreme cases of moisture transport patterns were selected to assess their association with rainfall anomalies. Results obtained indicate that only some aspects of water vapor transport and convergence in South America as well as the associated precipitation anomalies can be reproduced adequately by GCMs. Finally, a case study is presented showing that one of the moisture transport patterns identified was observed during December 2008–February 2009.