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1.
本文评估了中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室（LASG/IAP）研发的全球气候系统模式（FGOALS）的4个版本（FGOALS-g2、s2、g3、f3-L）对赤道太平洋地区的海温、降水气候态和季节循环的模拟能力。本文从海气耦合机制和热量收支的角度对耦合模式结果和相应的大气模式比较计划试验（AMIP）进行了对比分析,探讨了造成这一地区海温和降水模拟偏差的原因。结果显示,上一代模式g2和s2的海表温度均方根误差大于2°C,新一代模式g3和f3-L模拟的均方根误差降低50%,为1°C左右。因为新版本中赤道太平洋地区的净短波辐射平均态误差的减小,海洋上层热量动力输送过程的改善和净短波辐射与海温回归关系改进,赤道太平洋地区海温的平均态,南北温度和降水的不对称性都更加接近观测。f3-L比g3在上述方面改进更多,海温也更加合理。但是新一代版本模拟的降水均没有显著改进,赤道北侧ITCZ的降水偏大4 mm d?1。对流降水带来的凝结潜热释放加强了南北非绝热加热梯度,越赤道南风偏差抵消了一部分因为短波辐射偏大带来的海温偏暖,这说明海温平均态的改善是模拟误差相互抵消的结果。在季节循环的模拟方面也存在类似的现象,f3-L和g3中的海温年循环有所改进但较观测振幅仍旧偏弱。这是因为f3-L和g3模拟的经向风和潜热的年循环振幅比前版本要偏强,误差加大的同时也更大地抵消短波辐射的年循环偏差。g2和s2模拟的海温在赤道东太平洋则存在一个虚假半年循环分量,这主要是由潜热通量半年循环偏差所引起的。 相似文献
2.
Warm sea-surface temperature (SST) biases in the southeastern tropical Atlantic (SETA), which is defined by a region from 5°E to the west coast of southern Africa and from 10°S to 30°S, are a common problem in many current and previous generation climate models. The Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble provides a useful framework to tackle the complex issues concerning causes of the SST bias. In this study, we tested a number of previously proposed mechanisms responsible for the SETA SST bias and found the following results. First, the multi-model ensemble mean shows a positive shortwave radiation bias of ~20 W m?2, consistent with models’ deficiency in simulating low-level clouds. This shortwave radiation error, however, is overwhelmed by larger errors in the simulated surface turbulent heat and longwave radiation fluxes, resulting in excessive heat loss from the ocean. The result holds for atmosphere-only model simulations from the same multi-model ensemble, where the effect of SST biases on surface heat fluxes is removed, and is not sensitive to whether the analysis region is chosen to coincide with the maximum warm SST bias along the coast or with the main SETA stratocumulus deck away from the coast. This combined with the fact that there is no statistically significant relationship between simulated SST biases and surface heat flux biases among CMIP5 models suggests that the shortwave radiation bias caused by poorly simulated low-level clouds is not the leading cause of the warm SST bias. Second, the majority of CMIP5 models underestimate upwelling strength along the Benguela coast, which is linked to the unrealistically weak alongshore wind stress simulated by the models. However, a correlation analysis between the model simulated vertical velocities and SST biases does not reveal a statistically significant relationship between the two, suggesting that the deficient coastal upwelling in the models is not simply related to the warm SST bias via vertical heat advection. Third, SETA SST biases in CMIP5 models are correlated with surface and subsurface ocean temperature biases in the equatorial region, suggesting that the equatorial temperature bias remotely contributes to the SETA SST bias. Finally, we found that all CMIP5 models simulate a southward displaced Angola–Benguela front (ABF), which in many models is more than 10° south of its observed location. Furthermore, SETA SST biases are most significantly correlated with ABF latitude, which suggests that the inability of CMIP5 models to accurately simulate the ABF is a leading cause of the SETA SST bias. This is supported by simulations with the oceanic component of one of the CMIP5 models, which is forced with observationally derived surface fluxes. The results show that even with the observationally derived surface atmospheric forcing, the ocean model generates a significant warm SST bias near the ABF, underlining the important role of ocean dynamics in SETA SST bias problem. Further model simulations were conducted to address the impact of the SETA SST biases. The results indicate a significant remote influence of the SETA SST bias on global model simulations of tropical climate, underscoring the importance and urgency to reduce the SETA SST bias in global climate models. 相似文献
3.
Over the mid-latitude North Pacific, there is a close relationship between interannual variations of the sea surface temperature (SST) and surface shortwave radiation during boreal summer. The present study evaluates this relationship in coupled model simulations, forced model simulations, and retrospective forecasts. It is found that the simulation of this relationship in climate models is closely related to the model biases in the meridional gradients of mean SST and surface shortwave radiation. A southward shift in the region of large mean meridional gradients leads to a similar southward shift in the region of large correlation between the SST and shortwave radiation variations. The relationship is enhanced (weakened) when the mean meridional gradients are stronger (weaker) compared to observations. The shortwave radiation?CSST correlation is weak in individual forced simulations because of the interference of internally generated shortwave radiation variations. The shortwave radiation?CSST correlation increases significantly in the ensemble mean due to reduction of internally generated variability. The long-lead Climate Forecast System (CFS) forecasts have a better simulation of the shortwave radiation?CSST correlation compared to the short-lead forecasts. Estimation based on the CFS ensemble forecasts indicates that the high-frequency atmospheric variations contribute importantly to the SST variability over the mid-latitude North Pacific during boreal summer. 相似文献
4.
Sensitivity of tropical climate to low-level clouds in the NCEP climate forecast system 总被引：1，自引：1，他引：0
Zeng-Zhen Hu Bohua Huang Yu-Tai Hou Wanqiu Wang Fanglin Yang Cristiana Stan Edwin K. Schneider 《Climate Dynamics》2011,36(9-10):1795-1811
In this work, we examine the sensitivity of tropical mean climate and seasonal cycle to low clouds and cloud liquid water path (CLWP) by prescribing them in the NCEP climate forecast system (CFS). It is found that the change of low cloud cover alone has a minor influence on the amount of net shortwave radiation reaching the surface and on the warm biases in the southeastern Atlantic. In experiments where CLWP is prescribed using observations, the mean climate in the tropics is improved significantly, implying that shortwave radiation absorption by CLWP is mainly responsible for reducing the excessive surface net shortwave radiation over the southern oceans in the CFS. Corresponding to large CLWP values in the southeastern oceans, the model generates large low cloud amounts. That results in a reduction of net shortwave radiation at the ocean surface and the warm biases in the sea surface temperature in the southeastern oceans. Meanwhile, the cold tongue and associated surface wind stress in the eastern oceans become stronger and more realistic. As a consequence of the overall improvement of the tropical mean climate, the seasonal cycle in the tropical Atlantic is also improved. Based on the results from these sensitivity experiments, we propose a model bias correction approach, in which CLWP is prescribed only in the southeastern Atlantic by using observed annual mean climatology of CLWP. It is shown that the warm biases in the southeastern Atlantic are largely eliminated, and the seasonal cycle in the tropical Atlantic Ocean is significantly improved. Prescribing CLWP in the CFS is then an effective interim technique to reduce model biases and to improve the simulation of seasonal cycle in the tropics. 相似文献
5.
An evaluation of the surface radiation budget over North America for a suite of regional climate models against surface station observations 总被引：2，自引：2，他引：0
Marko Markovic Colin G. Jones Paul A. Vaillancourt Dominique Paquin Katja Winger Danahé Paquin-Ricard 《Climate Dynamics》2008,31(7-8):779-794
Components of the surface radiation budget (SRB) [incoming shortwave radiation (ISR) and downwelling longwave radiation (DLR)] and cloud cover are assessed for three regional climate models (RCM) forced by analysed boundary conditions, over North America. We present a comparison of the mean seasonal and diurnal cycles of surface radiation between the three RCMs, and surface observations. This aids in identifying in what type of sky situation simulated surface radiation budget errors arise. We present results for total-sky conditions as well as overcast and clear-sky conditions separately. Through the analysis of normalised frequency distributions we show the impact of varying cloud cover on the simulated and observed surface radiation budget, from which we derive observed and model estimates of surface cloud radiative forcing. Surface observations are from the NOAA SURFRAD network. For all models DLR all-sky biases are significantly influenced by cloud-free radiation, cloud emissivity and cloud cover errors. Simulated cloud-free DLR exhibits a systematic negative bias during cold, dry conditions, probably due to a combination of omission of trace gas contributions to the DLR and a poor treatment of the water vapor continuum at low water vapor concentrations. Overall, models overestimate ISR all-sky in summer, which is primarily linked to an underestimate of cloud cover. Cloud-free ISR is relatively well simulated by all RCMs. We show that cloud cover and cloud-free ISR biases can often compensate to result in an accurate total-sky ISR, emphasizing the need to evaluate the individual components making up the total simulated SRB. 相似文献
6.
Evaluation of CMIP5 Climate Models in Simulating 1979–2005 Oceanic Latent Heat Flux over the Pacific
The climatological mean state,seasonal variation and long-term upward trend of 1979–2005 latent heat flux(LHF) in historical runs of 14 coupled general circulation models from CMIP5(Coupled Model Intercomparison Project Phase 5) are evaluated against OAFlux(Objectively Analyzed air–sea Fluxes) data. Inter-model diversity of these models in simulating the annual mean climatological LHF is discussed. Results show that the models can capture the climatological LHF fairly well,but the amplitudes are generally overestimated. Model-simulated seasonal variations of LHF match well with observations with overestimated amplitudes. The possible origins of these biases are wind speed biases in the CMIP5 models. Inter-model diversity analysis shows that the overall stronger or weaker LHF over the tropical and subtropical Pacific region,and the meridional variability of LHF,are the two most notable diversities of the CMIP5 models. Regression analysis indicates that the inter-model diversity may come from the diversity of simulated SST and near-surface atmospheric specific humidity.Comparing the observed long-term upward trend,the trends of LHF and wind speed are largely underestimated,while trends of SST and air specific humidity are grossly overestimated,which may be the origins of the model biases in reproducing the trend of LHF. 相似文献
7.
南海夏季风爆发前后海-气界面热交换特征 总被引：20，自引：1，他引：20
文中利用 2 0 0 0与 2 0 0 2年二次南海海 气通量观测资料和同期西沙站资料 ,研究了南海夏季风爆发前后海洋表面热收支变化特征。研究表明 :南海夏季风爆发前后 ,影响海面热收支变化的主要分量是净短波辐射通量和潜热通量 ,在季风爆发前后不同阶段 ,二个分量的变化有不同表现形式 ,但不论二者如何变化 ,季风爆发与活跃期 ,海面热收入减小或为净支出 ;季风爆发前及中断期间 ,海面热收入逐渐增加 ;由于大的热惯性 ,海温变化落后于海面热收支的变化 ,海温的这种滞后效应通过影响潜热通量调节海面热收支的变化 ,又反过来影响自身的变化 ,形成短期振荡过程 ,这种振荡过程与季风的活跃、中断过程相对应。 相似文献
8.
利用卫星和再分析数据,评估了区域气候模式Reg CM4对中国东部地区辐射收支的基本模拟能力,重点关注地表净短波(SNS)、地表净长波(SNL)、大气顶净短波(TNS)、大气顶净长波(TNL)4个辐射分量。结果表明:1)短波辐射的误差值在夏季较大,而长波辐射的误差值在冬季较大。但各辐射分量模拟误差的空间分布在冬、夏季都有较好的一致性。2)对于地表辐射通量,SNS表现为正偏差(向下净短波偏多),在各分量中误差最大,区域平均误差值近50 W/m2;SNL表现为负偏差(向上净长波偏多);对于大气顶辐射通量,TNS和TNL分别表现为"北负南正"的误差分布和整体正偏差。3)利用空间相关和散点线性回归方法对4个辐射分量的模拟误差进行归因分析,发现在云量、地表反照率、地表温度三个直接影响因子中,云量模拟误差的贡献最大,中国东部地区云量模拟显著偏少。 相似文献
9.
Using a non-linear statistical analysis called “self-organizing maps”, the interannual sea surface temperature (SST) variations
in the southern Indian Ocean are investigated. The SST anomalies during austral summer from 1951 to 2006 are classified into
nine types with differences in the position of positive and negative SST anomaly poles. To investigate the evolution of these
SST anomaly poles, heat budget analysis of mixed-layer using outputs from an ocean general circulation model is conducted.
The warming of the mixed-layer by the climatological shortwave radiation is enhanced (suppressed) as a result of negative
(positive) mixed-layer thickness anomaly over the positive (negative) SST anomaly pole. This contribution from shortwave radiation
is most dominant in the growth of SST anomalies. In contrast to the results reported so far, the contribution from latent
heat flux anomaly is not so important. The discrepancy in the analysis is explained by the modulation in the contribution
from the climatological heat flux by the interannual mixed-layer depth anomaly that was neglected in the past studies. 相似文献
10.
Satellite observations reveal a much stronger intraseasonal sea surface temperature (SST) variability in the southern Indian Ocean along 5-10oS in boreal winter than in boreal summer. The cause of this seasonal dependence is studied using a 2?-layer ocean model forced by ERA-40 reanalysis products during 1987-2001. The simulated winter-summer asymmetry of the SST variability is consistent with the observed. A mixed-layer heat budget is analyzed. Mean surface westerlies along the ITCZ (5-10oS) in December-January-February (DJF) leads to an increased (decreased) evaporation in the westerly (easterly) phase of the intraseasonal oscillation (ISO), during which convection is also enhanced (suppressed). Thus the anomalous shortwave radiation, latent heat flux and entrainment effects are all in phase and produce strong SST signals. During June-July-August (JJA), mean easterlies prevail south of the equator. Anomalies of the shortwave radiation tend to be out of phase to those of the latent heat flux and ocean entrainment. This mutual cancellation leads to a weak SST response in boreal summer. The resultant SST tendency is further diminished by a deeper mixed layer in JJA compared to that in DJF. The strong intraseasonal SST response in boreal winter may exert a delayed feedback to the subsequent opposite phase of ISO, implying a two-way air-sea interaction scenario on the intraseasonal timescale.
Citation: Li, T., F. Tam, X. Fu, et al., 2008: Causes of the intraseasonal SST variability in the tropical Indian ocean, Atmos. Oceanic Sci. Lett., 1, 18-23 相似文献
11.
本文通过与观测和再分析资料的对比,评估了LASG/IAP发展的气候系统模式FGOALS的两个版本FGOALS-g2和FGOALS-s2对南亚夏季风的气候态和年际变率的模拟能力,并使用水汽收支方程诊断,研究了造成降水模拟偏差的原因。结果表明,两个模式夏季气候态降水均在陆地季风槽内偏少,印度半岛附近海域偏多,在降水年循环中表现为夏季北侧辐合带北推范围不足。FGOALS-g2中赤道印度洋"东西型"海温偏差导致模拟的东赤道印度洋海上辐合带偏弱,而FGOALS-s2中印度洋"南北型"海温偏差导致模拟的海上辐合带偏向西南。水汽收支分析表明,两个模式中气候态夏季风降水的模拟偏差主要来自于整层积分的水汽通量,尤其是垂直动力平流项的模拟偏差。一方面,夏季阿拉伯海和孟加拉湾的海温偏冷而赤道西印度洋海温偏暖,造成向印度半岛的水汽输送偏少;另一方面,对流层温度偏冷,冷中心位于印度半岛北部对流层上层,同时季风槽内总云量偏少,云长波辐射效应偏弱,对流层经向温度梯度偏弱以及大气湿静力稳定度偏强引起的下沉异常造成陆地季风槽内降水偏少。在年际变率上,观测中南亚夏季风环流和降水指数与Ni?o3.4指数存在负相关关系,但FGOALS两个版本模式均存在较大偏差。两个模式中与ENSO暖事件相关的沃克环流异常下沉支和对应的负降水异常西移至赤道以南的热带中西印度洋,沿赤道非对称的加热异常令两个模式中越赤道环流季风增强,导致印度半岛南部产生正降水异常。ENSO相关的沃克环流异常下沉支及其对应的负降水异常偏西与两个模式对热带南印度洋气候态降水的模拟偏差有关。研究结果表明,若要提高FGOALS两个版本模式对南亚夏季风气候态模拟技巧,需减小耦合模式对印度洋海温、对流层温度及云的模拟偏差;若要提高南亚夏季风和ENSO相关性模拟技巧需要提高模式对热带印度洋气候态降水以及与ENSO相关的环流异常的模拟能力。 相似文献
12.
为了定量评估北京气候中心(BCC)发展的BCC_CSM对当代全球海表温度和混合层深度的模拟能力,以WOA09(World Ocean Atlas 2009)观测资料作为检验模式的气候态实况场,提取包括BCC_CSM在内的CMIP5中的17个海气耦合模式的模拟结果,评估BCC_CSM模拟的全球海表温度和混合层深度的气候平均态并分析造成偏差的可能原因。结果表明:BCC_CSM模拟的海表温度在北半球中高纬的误差较大,而在其余纬度的模拟性能较佳。偏差的产生主要归因于海洋环流偏差。BCC_CSM模拟的最深混合层在北半球中高纬和南半球高纬地区的误差较大,同时这些区域也是多模式模拟差异最大的区域;其模拟的最浅混合层在南半球中高纬的偏差较大。冬季大西洋经向翻转环流的模拟在北大西洋下沉的位置偏南导致北半球高纬地区海表温度偏冷。由此认为包括BCC_CSM在内的许多海气耦合模式需重点改进对南、北半球深对流海域物理过程的描述,以提高气候预测的可信度。 相似文献
13.
The temperature biases of 28 CMIP5 AGCMs are evaluated over the Tibetan Plateau(TP) for the period 1979–2005. The results demonstrate that the majority of CMIP5 models underestimate annual and seasonal mean surface 2-m air temperatures(T_(as)) over the TP. In addition, the ensemble of the 28 AGCMs and half of the individual models underestimate annual mean skin temperatures(T_s) over the TP. The cold biases are larger in T_(as) than in T_s, and are larger over the western TP. By decomposing the T_s bias using the surface energy budget equation, we investigate the contributions to the cold surface temperature bias on the TP from various factors, including the surface albedo-induced bias, surface cloud radiative forcing, clear-sky shortwave radiation, clear-sky downward longwave radiation, surface sensible heat flux, latent heat flux,and heat storage. The results show a suite of physically interlinked processes contributing to the cold surface temperature bias.Strong negative surface albedo-induced bias associated with excessive snow cover and the surface heat fluxes are highly anticorrelated, and the cancelling out of these two terms leads to a relatively weak contribution to the cold bias. Smaller surface turbulent fluxes lead to colder lower-tropospheric temperature and lower water vapor content, which in turn cause negative clear-sky downward longwave radiation and cold bias. The results suggest that improvements in the parameterization of the area of snow cover, as well as the boundary layer, and hence surface turbulent fluxes, may help to reduce the cold bias over the TP in the models. 相似文献
14.
The Southern Ocean is covered by a large amount of clouds with high cloud albedo. However, as reported by previous climate model intercomparison projects, underestimated cloudiness and overestimated absorption of solar radiation (ASR) over the Southern Ocean lead to substantial biases in climate sensitivity. The present study revisits this long-standing issue and explores the uncertainty sources in the latest CMIP6 models. We employ 10-year satellite observations to evaluate cloud radiative effect (CRE) and cloud physical properties in five CMIP6 models that provide comprehensive output of cloud, radiation, and aerosol. The simulated longwave, shortwave, and net CRE at the top of atmosphere in CMIP6 are comparable with the CERES satellite observations. Total cloud fraction (CF) is also reasonably simulated in CMIP6, but the comparison of liquid cloud fraction (LCF) reveals marked biases in spatial pattern and seasonal variations. The discrepancies between the CMIP6 models and the MODIS satellite observations become even larger in other cloud macro- and micro-physical properties, including liquid water path (LWP), cloud optical depth (COD), and cloud effective radius, as well as aerosol optical depth (AOD). However, the large underestimation of both LWP and cloud effective radius (regional means ~20% and 11%, respectively) results in relatively smaller bias in COD, and the impacts of the biases in COD and LCF also cancel out with each other, leaving CRE and ASR reasonably predicted in CMIP6. An error estimation framework is employed, and the different signs of the sensitivity errors and biases from CF and LWP corroborate the notions that there are compensating errors in the modeled shortwave CRE. Further correlation analyses of the geospatial patterns reveal that CF is the most relevant factor in determining CRE in observations, while the modeled CRE is too sensitive to LWP and COD. The relationships between cloud effective radius, LWP, and COD are also analyzed to explore the possible uncertainty sources in different models. Our study calls for more rigorous calibration of detailed cloud physical properties for future climate model development and climate projection. 相似文献
15.
海-陆-气全球耦合模式能量收支的误差 总被引：4，自引：0，他引：4
通过分析GOALS模式两个版本GOALS 1.1和GOALS 2的能量收支 ,并与观测对比 ,结果表明 :模式模拟的地表净短波辐射通量在高纬地区偏低 ,而净长波辐射通量又偏高 ,导致极地表面温度偏低 ,感热通量在高纬地区为很高的负值。而在陆地上感热加热作用显著偏强 ,使地表有较大的向上净能量给大气 ,引起陆地上有些暖中心也偏强 ,这也解释了模式模拟地表面空气温度场的误差原因。海洋上潜热通量偏低 ,特别是在副热带洋面上偏少更明显。陆地上的欧亚和北美大陆大部分地区潜热通量仍偏低。这也是模式降水在大部分地区偏少的重要原因。两模式大气顶OLR偏低的模拟主要是在中低纬度 ,大气顶净短波辐射通量的模拟在中低纬度虽然与NCEP结果接近 ,但与地球辐射收支试验ERBE资料比较仍偏小较多 ,说明改进中低纬度云 辐射参数化方案对改进全球能量收支的模拟有重要意义。GOALS 2模式中诊断云方案模拟的云量除赤道地区外普遍偏小 ,尤以中纬度为甚 ,造成那里能量收支出现大的误差 ,这表明了更好的云参数化方案的引入是今后模式发展的重要任务之一 相似文献
16.
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. 相似文献
17.
June-Yi Lee Bin Wang I.-S. Kang J. Shukla A. Kumar J.-S. Kug J. K. E. Schemm J.-J. Luo T. Yamagata X. Fu O. Alves B. Stern T. Rosati C.-K. Park 《Climate Dynamics》2010,35(2-3):267-283
Given observed initial conditions, how well do coupled atmosphere–ocean models predict precipitation climatology with 1-month lead forecast? And how do the models’ biases in climatology in turn affect prediction of seasonal anomalies? We address these questions based on analysis of 1-month lead retrospective predictions for 21 years of 1981–2001 made by 13 state-of-the-art coupled climate models and their multi-model ensemble (MME). The evaluation of the precipitation climatology is based on a newly designed metrics that consists of the annual mean, the solstitial mode and equinoctial asymmetric mode of the annual cycle, and the rainy season characteristics. We find that the 1-month lead seasonal prediction made by the 13-model ensemble has skills that are much higher than those in individual model ensemble predictions and approached to those in the ERA-40 and NCEP-2 reanalysis in terms of both the precipitation climatology and seasonal anomalies. We also demonstrate that the skill for individual coupled models in predicting seasonal precipitation anomalies is positively correlated with its performances on prediction of the annual mean and annual cycle of precipitation. In addition, the seasonal prediction skill for the tropical SST anomalies, which are the major predictability source of monsoon precipitation in the current coupled models, is closely link to the models’ ability in simulating the SST mean state. Correction of the inherent bias in the mean state is critical for improving the long-lead seasonal prediction. Most individual coupled models reproduce realistically the long-term annual mean precipitation and the first annual cycle (solstitial mode), but they have difficulty in capturing the second annual (equinoctial asymmetric) mode faithfully, especially over the Indian Ocean (IO) and Western North Pacific (WNP) where the seasonal cycle in SST has significant biases. The coupled models replicate the monsoon rain domains very well except in the East Asian subtropical monsoon and the tropical WNP summer monsoon regions. The models also capture the gross features of the seasonal march of the rainy season including onset and withdraw of the Asian–Australian monsoon system over four major sub-domains, but striking deficiencies in the coupled model predictions are observed over the South China Sea and WNP region, where considerable biases exist in both the amplitude and phase of the annual cycle and the summer precipitation amount and its interannual variability are underestimated. 相似文献
18.
基于耦合器框架，中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室大气环流谱模式 （SAMIL）最近成功地实现了与海洋、海冰等气候分量模式的耦合，形成了“非通量调整”的海－陆－气－冰直接耦合的气候模式系统（FGOALS-s）。在耦合系统中，由于海温、海冰等的分布由预报模式驱动，大气与海洋、海冰之间引入了相互作用过程，这样大气环流的模拟特征与耦合前会有不同。为分析耦合系统的性能，作者对耦合前后的模拟结果进行了分析比较，重点是大气模拟特征的差异。结果表明，耦合前、后大气环流的基本特征相似，都能成功地模拟出主要的环流系统分布及季节变化，但是由于海温和海冰的模拟存在系统性的偏差，使得耦合后的大气环流受到明显影响。例如耦合后热带海温偏冷，南大洋、北太平洋和北大西洋等中纬度地区的海温偏高，导致海温等值线向高纬海域的伸展较弱，海温经向梯度减小。耦合后海冰在北极区域范围偏大，在南极周边地区则偏小。海温、海冰分布模拟的偏差影响到中、高纬低层大气的温度。热带海温偏低，使得赤道地区降水偏弱，凝结潜热减少，热带对流层中高层温度比耦合前要低，大气温度的经向梯度减小。经向温度梯度的改变，直接影响到对平均经圈环流及西风急流强度的模拟。尽管耦合系统中海温、海冰的模拟存在偏差，但在亚洲季风区，耦合后季风环流及降水等的分布都比耦合前单独大气模式的结果合理，表明通过海[CD*2]气相互作用可减少耦合前季风区的模拟误差，改善季风模拟效果。比较发现，海温、海冰模拟的偏差，除与海洋模式中经向热输送偏弱、海冰模式中海冰处理等有关外，也与大气模式中总云量模拟偏低有关。大气模式本身的误差，特别是云、辐射过程带来的误差，对耦合结果具有极为重要的影响。完全耦合后，这些误差通过与海洋、海冰的反馈作用而放大。因此，对于FGOALS-s而言，要提高耦合系统的整体性能，除改进各气候分量模式的模拟性能外，需要重点改进大气模式中的云、辐射过程。 相似文献
19.
南亚夏季风的变化决定着印度半岛的旱涝状况,气候系统模式则是研究南亚夏季风变化规律的重要工具。本文基于观测和JRA55再分析资料,系统评估了FGOALS-g3模式模拟的南亚夏季风气候态和年际变率,并重点关注FGOALS-g3与FGOALS-g2以及是否考虑海气相互作用的模拟差异。结果表明,由于局地海温模拟的变化,相比于FGOALS-g2,FGOALS-g3模拟的南亚夏季风在气候态热带印度洋信风和El Ni?o期间沃克环流下沉支上有明显改进。同时,由于对流层系统性冷偏差持续存在并且中心位于副热带300 hPa附近,造成气候态上经向温度梯度减弱,使季风环流减弱,导致FGOALS-g3中陆地季风槽的水汽辐散偏差和降水干偏差仍然存在;在年际变率上,FGOALS-g3模拟的El Ni?o期间赤道西太平洋海温冷异常偏弱,印度洋偶极子偏强,导致印度半岛下沉运动减弱,FGOALS-g3中ENSO—印度降水负相关关系也依然偏弱。研究表明,耦合过程导致的气候态海温偏差通过改变环流和水汽输送,有效补偿了大气模式中印度半岛中部和中南半岛的降水湿偏差;在年际变率上,耦合模式由于考虑了海温—降水—云短波辐射的负反馈过程,能够减小大气模式模拟偏差的强度,但印太暖池区海温模拟偏差导致沃克环流下沉支偏西,使得印度半岛的降水响应出现更大的湿偏差。 相似文献