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1.
A simple method for initializing intermediate coupled models (ICMs) using only sea surface temperature (SST) anomaly data is comprehensively tested in two sets of hindcasts with a new ICM. In the initialization scheme, both the magnitude of the nudging parameter and the duration of the assimilation are considered, and initial conditions for both atmosphere and ocean are generated by running the coupled model with SST anomalies nudged to the observations. A comparison with the observations indicates that the scheme can generate realistic thermal fields and surface dynamic fields in the equatorial Pacific through hindcast experiments. An ideal experiment is performed to get the optimal nudging parameters which include the nudging intensity and nudging time length. Twelve-month-long hindcast experiments are performed with the model over the period 1984–2003 and the period 1997–2003. Compared with the original prediction results, the model prediction skills are significantly improved by the nudging method especially beyond a 6-month lead time during the two different periods. Potential problems and further improvements are discussed regarding the new coupled assimilation system.  相似文献   

2.
基于海气耦合环流模式的ENSO预测   总被引：5，自引：0，他引：5  
Predictions of ENSO are described by using a coupled atmosphere-ocean general circulation model. The initial conditions are created by forcing the coupled system using SST anomalies in the tropical Pacific at the background of the coupled model climatology. A series of 24-month hindcasts for the period from November 1981 to December 1997 are carried out to validate the performance of the coupled system. Correlations of SST anomalies in the Nino3 region exceed 0.54 up to 15 months in advance and the rms errors are less than 0.9℃. The system is more skillful in predicting SST anomalies in the 1980s and less in the 1990s. The model skills are also seasonal-dependent, which are lower for the predictions starting from late autumn to winter and higher for those from spring to autumn in a year-time forecast length. The prediction, beginning from March, persists 8 months long with the correlation skill exceeding 0.6, which is important in predictions of summer rainfall in China. The predictions are succesful in many aspects for the 1997-2000 ENSO events.  相似文献   

3.
The sea surface temperature(SST) in the Indian Ocean affects the regional climate over the Asian continent mostly through a modulation of the monsoon system.It is still difficult to provide an a priori indication of the seasonal variability over the Indian Ocean.It is widely recognized that the warm and cold events of SST over the tropical Indian Ocean are strongly linked to those of the equatorial eastern Pacific.In this study,a statistical prediction model has been developed to predict the monthly SST over the tropical Indian Ocean.This model is a linear regression model based on the lag relationship between the SST over the tropical Indian Ocean and the Ni o3.4(5°S-5°N,170°W-120°W) SST Index.The predictor(i.e.,Ni o3.4 SST Index) has been operationally predicted by a large size ensemble El Ni o and the Southern Oscillation(ENSO) forecast system with coupled data assimilation(Leefs_CDA),which achieves a high predictive skill of up to a 24-month lead time for the equatorial eastern Pacific SST.As a result,the prediction skill of the present statistical model over the tropical Indian Ocean is better than that of persistence prediction for January 1982 through December 2009.  相似文献   

4.
A simple air–sea coupled model,the atmospheric general circulation model(AGCM) of the National Centers for Environmental Prediction coupled to a mixed-layer slab ocean model,is employed to investigate the impact of air–sea coupling on the signals of the Atlantic Multidecadal Oscillation(AMO). A regional coupling strategy is applied,in which coupling is switched off in the extratropical North Atlantic Ocean but switched on in the open oceans elsewhere. The coupled model is forced with warm-phase AMO SST anomalies,and the modeled responses are compared with those from parallel uncoupled AGCM experiments with the same SST forcing. The results suggest that the regionally coupled responses not only resemble the AGCM simulation,but also have a stronger intensity. In comparison,the coupled responses bear greater similarity to the observational composite anomaly. Thus,air–sea coupling enhances the responses of the East Asian winter climate to the AMO. To determine the mechanism responsible for the coupling amplification,an additional set of AGCM experiments,forced with the AMO-induced tropical SST anomalies,is conducted. The SST anomalies are extracted from the simulated AMO-induced SST response in the regionally coupled model. The results suggest that the SST anomalies contribute to the coupling amplification. Thus,tropical air–sea coupling feedback tends to enhance the responses of the East Asian winter climate to the AMO.  相似文献   

5.
Twenty-one-year hindcasts of sea surface temperature (SST) anomalies in the tropical Pacific were performed to validate the influence of ocean subsurface entrainment on SST prediction.A new hybrid coupled model was used that considered the entrainment of subsurface temperature anomalies into the sea surface.The results showed that predictions were improved significantly in the new coupled model.The predictive correlation skill increased by about 0.2 at a lead time of 9 months,and the root-mean-square (RMS) errors were decreased by nearly 0.2°C in general.A detailed analysis of the 1997-98 El Nio hindcast showed that the new model was able to predict the onset,peak (both time and amplitude),and decay of the 1997-98 strong El Nio event up to a lead time of one year,factors that are not represented well by many other forecast systems.This implies,in terms of prediction,that subsurface anomalies and their impact on the SST are one of the controlling factors in ENSO cycles.Improving the presentation of such effects in models would increase the forecast skill.  相似文献   

6.
This study presents the spatial and temporal structures of the decadal variability of the Pacific from an extended control run of a coupled global climate model (GCM).The GCM used was version-g2.0 of the Flexible Global Ocean Atmosphere Land System (FGOALS-g2.0) developed at LASG/IAP.The GCM FGOALS-g2.0 re-produces similar spatial-temporal structures of sea surface temperature (SST) as observed in the Pacific decadal os-cillation (PDO) with a significant period of approximately 14 years.Correspondingly,the PDO signals were closely related to the decadal change both in the upper-ocean temperature anomalies and in the atmospheric circulation.The present results suggest that warm SST anomalies along the equator relax the trade winds,causing the SSTs to warm even more in the eastern equatorial Pacific,which is a positive feedback.Meanwhile,warm SST anomalies along the equator force characteristic off-equa-torial wind stress curl anomalies,inducing much more poleward transport of heat,which is a negative feedback.The upper-ocean meridional heat transport,which is asso-ciated with the PDO phase transition,links the equatorial to the off-equatorial Pacific Ocean,acting as a major mechanism responsible for the tropical Pacific decadal variations.Therefore,the positive and negative feedbacks working together eventually result in the decadal oscilla-tion in the Pacific.  相似文献   

7.
A new hybrid coupled model(HCM) is presented in this study, which consists of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model. The ocean component is the intermediate ocean model(IOM)of the intermediate coupled model(ICM) used at the Institute of Oceanology, Chinese Academy of Sciences(IOCAS). The atmospheric component is ECHAM5, the fifth version of the Max Planck Institute for Meteorology atmospheric general circulation model. The HCM integrates its atmospheric and oceanic components by using an anomaly coupling strategy. A100-year simulation has been made with the HCM and its simulation skills are evaluated, including the interannual variability of SST over the tropical Pacific and the ENSO-related responses of the global atmosphere. The model shows irregular occurrence of ENSO events with a spectral range between two and five years. The amplitude and lifetime of ENSO events and the annual phase-locking of SST anomalies are also reproduced realistically. Despite the slightly stronger variance of SST anomalies over the central Pacific than observed in the HCM, the patterns of atmospheric anomalies related to ENSO,such as sea level pressure, temperature and precipitation, are in broad agreement with observations. Therefore, this model can not only simulate the ENSO variability, but also reproduce the global atmospheric variability associated with ENSO, thereby providing a useful modeling tool for ENSO studies. Further model applications of ENSO modulations by ocean–atmosphere processes, and of ENSO-related climate prediction, are also discussed.  相似文献   

8.
The tropical storm day(TSD)is a combined measure of genesis and lifespan.It reflects tropical cyclone(TC)overall activity,yet its variability has rarely been studied,especially globally.Here we show that the global total TSDs exhibit pronounced interannual(3-6 years)and decadal(10 years)variations over the past five-to-six decades without a significant trend.The leading modes of the interannual and decadal variability of global TSD feature similar patterns in the western Pacific and Atlantic,but different patterns in the Eastern Pacific and the Southern Indian Ocean.The interannual and decadal leading modes are primarily linked to El Ni?o-Southern Oscillation(ENSO)and Pacific Decadal Oscillation(PDO),respectively.The TSDs-ENSO relationship has been steady during the entire 55-year period,but the TSDs-PDO relationship has experienced a breakdown in the 1980 s.We find that the decadal variation of TSD in the Pacific is associated with the PDO sea surface temperature(SST)anomalies in the tropical eastern Pacific(PDO-E),while that in the Atlantic and the Indian Ocean is associated with the PDO SST anomalies in the western Pacific(PDO-W).However,the PDO-E and PDO-W SST anomalies are poorly coupled in the 1980 s,and this"destructive PDO"pattern results in a breakdown of the TSDs-PDO relationship.The results here have an important implication for seasonal to decadal predictions of global TSD.  相似文献   

9.
The Argo(Array for Real-time Geostrophic Oceanography) data from 1998 to 2003 were used in the Beijing Climate Center-Global Ocean Data Assimilation System(BCC-GODAS). The results show that the utilization of Argo global ocean data in BCC-GODAS brings about remarkable improvements in assimilation effects. The assimilated sea surface temperature(SST) of BCC-GODAS can well represent the climatological states of observational data. Comparison experiments based on a global coupled atmosphere-ocean general circulation model(AOCGM) were conducted for exploring the roles of ocean data assimilation system with or without Argo data in improving the climate predictability of rainfall in boreal summer. Firstly, the global ocean data assimilation system BCC-GODAS was used to obtain ocean assimilation data under the conditions with or without Argo data. Then, the global coupled atmosphere-ocean general circulation model(AOCGM) was utilized to do hindcast experiments with the two sets of the assimilation data as initial oceanic fields. The simulated results demonstrate that the seasonal predictability of rainfall in boreal summer, particularly in China, increases greatly when initial oceanic conditions with Argo data are utilized. The distribution of summer rainfall in China hindcast by the AOGCM under the condition when Argo data are used is more in accordance with observation than that when no Agro data are used. The area of positive correlation between hindcast and observation enlarges and the hindcast skill of rainfall over China in summer improves significantly when Argo data are used.  相似文献   

10.
Through observational analyses,an inter-hemispheric teleconnection is identified between the subtropical region of the South China Sea to the western Pacific near the Philippines(WP)and the region to the east of Australia(AE).The teleconnection is significantly correlated with sea surface temperature anomalies(SSTAs)in key sea areas(including the Indian Ocean,the South China Sea,and the area to the east of Australia).Based on the IAP T42L9 model,numerical experiments are performed to explore a possible mechanism for the formation of the teleconnection.The results show that the positive SST anomalies in the key sea areas may jointly contribute to the occurrence and maintenance of the positive geopotential height anomalies over both the WP and AE and be a critical factor in the teleconnection formation.The large-scale SST anomaly in the Indian Ocean,involving the tropics and subtropics of both hemispheres,may lead to concurrent atmospheric responses over both the WP and AE,while the effect of the local SST anomaly to the east of Australia seems to reinforce and maintain the positive height anomaly over the AE.  相似文献   

11.
一个全球耦合模式的ENSO后报试验   总被引：1，自引：1，他引：0  
A group of seasonal hindcast experiments are conducted using a coupled model known as the Flexible Global Ocean-Atmosphere-Land System Model-gamil1.11 (FGOALS-g1.11) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG). Two steps are included in our El Niño-Southern Oscillation (ENSO) hindcast experiments. The first step is to integrate the coupled GCM with the Sea Surface Temperature (SST) strongly nudged towards the observation from 1971 to 2006. The second step is to remove the SST nudging term. We carried out a one-year hindcast by adopting the initial values from SST nudging experiments from the first step on January 1st, April 1st, July 1st, and October 1st from 1982 to 2005. In the SST nudging experiment, the model can reproduce the observed equatorial thermocline anomalies and zonal wind stress anomalies in the Pacific, which demonstrates that the SST nudging approach can provide realistic atmospheric and oceanic initial conditions for seasonal prediction experiments. The model also demonstrates a high Anomaly Correlation Coefficient (ACC) score for SST in most of the tropical Pacific, Atlantic Ocean, and some Indian Ocean regions with a 3-month lead. Compared with the persistence ACC score, this model shows much higher ACC scores for the Nino3.4 index for a 9-month lead.  相似文献   

12.
中国业务动力季节预报的进展   总被引：26，自引：9，他引：26  
利用动力模式开展季节到年际的短期气候预测 ,是目前国际上气候预测的发展方向。自 1996年以来 ,经过 8a多的研制和发展 ,国家气候中心已建立起第 1代动力气候模式预测业务系统 ,其中包括 1个全球大气 海洋耦合模式 (CGCM )、1个高分辨率东亚区域气候模式 (RegCM_NCC)和 5个简化的ENSO预测模式 (SAOMS) ,可用于季节—年际时间尺度的全球气候预测 ;全球海气耦合模式与区域气候模式嵌套 ,可以提供高分辨率的东亚区域气候模式制做季节预测。CGCM对 1982～ 2 0 0 0年夏季的历史回报试验表明 ,该模式对热带太平洋海表面温度和东亚区域的季节预测具有较好的预测能力。RegCM NCC的 5a模拟基本上能再现东亚地区主要雨带的季节进展。利用嵌套的区域气候模式RegCM NCC对 1991～ 2 0 0 0年的夏季回报表明 ,在预报主要季节雨带方面有一定技巧。 2 0 0 1～ 2 0 0 3年 ,CGCM和RegCM NCC的实时季节预报与观测相比基本合理。特别是 ,模式成功地预报了 2 0 0 3年梅雨季节长江和黄河之间比常年偏多的降水。SAOMS模式系统的回报试验表明 ,该系统对热带太平洋海表面温度距平有一定的预报能力 ,模式超前 6～ 12个月的回报与观测的相关系数明显高于持续预报。 1997～ 2 0 0 3年 ,SAOMS多模式集合实时预报与观测的相关系数达到  相似文献   

13.
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   

14.
Sea surface temperature (SST) variations include negative feedbacks from the atmosphere, whereas SST anomalies are specified in stand-alone atmospheric general circulation simulations. Is the SST forced response the same as the coupled response? In this study, the importance of air–sea coupling in the Indian and Pacific Oceans for tropical atmospheric variability is investigated through numerical experiments with a coupled atmosphere-ocean general circulation model. The local and remote impacts of the Indian and Pacific Ocean coupling are obtained by comparing a coupled simulation with an experiment in which the SST forcing from the coupled simulation is specified in either the Indian or the Pacific Ocean. It is found that the Indian Ocean coupling is critical for atmospheric variability over the Pacific Ocean. Without the Indian Ocean coupling, the rainfall and SST variations are completely different throughout most of the Pacific Ocean basin. Without the Pacific Ocean coupling, part of the rainfall and SST variations in the Indian Ocean are reproduced in the forced run. In regions of large mean rainfall where the atmospheric negative feedback is strong, such as the North Indian Ocean and the western North Pacific in boreal summer, the atmospheric variability is significantly enhanced when air–sea coupling is replaced by specified SST forcing. This enhancement is due to the lack of the negative feedback in the forced SST simulation. In these regions, erroneous atmospheric anomalies could be induced by specified SST anomalies derived from the coupled model. The ENSO variability is reduced by about 20% when the Indian Ocean air–sea coupling is replaced by specified SST forcing. This change is attributed to the interfering roles of the Indian Ocean SST and Indian monsoon in western and central equatorial Pacific surface wind variations.  相似文献   

15.
We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.  相似文献   

16.
The 2009 drought in India was one of the major droughts that the country faced in the last 100?years. This study describes the anomalous features of 2009 summer monsoon and examines real-time seasonal predictions made using six general circulation models (GCMs). El Ni?o conditions evolved in the Pacific Ocean, and sea surface temperatures (SSTs) over the Indian Ocean were warmer than normal during monsoon 2009. The observed circulation patterns indicate a weaker monsoon in that year over India with weaker than normal convection over the Bay of Bengal and Indian landmass. Skill of the GCMs during hindcast period shows that neither these models simulate the observed interannual variability nor their multi-model ensemble (MME) significantly improves the skill of monsoon rainfall predictions. Except for one model used in this study, the real-time predictions with longer lead (2- and 1-month lead) made for the 2009 monsoon season did not provide any indication of a highly anomalous monsoon. However, with less lead time (zero lead), most of the models as well as the MME had provided predictions of below normal rainfall for that monsoon season. This study indicates that the models could not predict the 2009 drought over India due to the use of less warm SST anomalies over the Pacific in the longer lead runs. Hence, it is proposed that the uncertainties in SST predictions (the lower boundary condition) have to be represented in the model predictions of summer monsoon rainfall over India.  相似文献   

17.
印度洋对ENSO事件的响应:观测与模拟   总被引：11，自引：3，他引：8  
观测事实显示,在El Ni(n～)o期间,伴随着赤道中东太平洋表层海温(SST)的升高,热带印度洋SST出现正距平.作者利用海气耦合模式模拟了印度洋对ENSO事件的上述响应,并进而讨论了其物理机制.所用模式为法国国家科研中心Pierre-Simon-Laplace 全球环境科学联合实验室(IPSL)发展的全球海气耦合模式.该模式成功地控制了气候漂移,能够合理再现印度洋的基本气候态.观测中与ENSO相关的热带印度洋SST变化,表现为全海盆一致的正距平,并且这种变化要滞后赤道中东太平洋SST变化大约一个季度,意味着它主要是对东太平洋SST强迫的一种遥响应,模式结果也支持这一机制,尽管模式中的南方涛动现象被夸大了,使得模拟的与ENSO相关联的SST正距平的位置南移,阿拉伯海和孟加拉湾被负距平(而不是正距平)所控制.研究表明,东太平洋主要通过大气桥影响潜热释放来影响印度洋SST变化.赤道东太平洋El Ni(n～)o事件的发展,导致印度洋上空风场异常自东而西传播;伴随着风场的变化,潜热发生相应变化,并最终导致SST异常的发生.非洲东海岸受索马里急流控制的海域,其SST的变化不能简单地利用热通量的变化来解释.证据显示,印度洋的增暖是ENSO事件发生的结果而不是其前期信号.  相似文献   

18.
The impact of realistic atmospheric initialisation on the seasonal prediction of tropical Pacific sea surface temperatures is explored with the Predictive Ocean–Atmosphere Model for Australia (POAMA) dynamical seasonal forecast system. Previous versions of POAMA used data from an Atmospheric Model Intercomparison Project (AMIP)-style simulation to initialise the atmosphere for the hindcast simulations. The initial conditions for the hindcasts did not, therefore, capture the true intra-seasonal atmospheric state. The most recent version of POAMA has a new Atmosphere and Land Initialisation scheme (ALI), which captures the observed intra-seasonal atmospheric state. We present the ALI scheme and then compare the forecast skill of two hindcast datasets, one with AMIP-type initialisation and one with realistic initial conditions from ALI, focussing on the prediction of El Niño. For eastern Pacific (Niño3) sea surface temperature anomalies (SSTAs), both experiments beat persistence and have useful SSTA prediction skill (anomaly correlations above 0.6) at all lead times (forecasts are 9 months duration). However, the experiment with realistic atmospheric initial conditions from ALI is an improvement over the AMIP-type initialisation experiment out to about 6 months lead time. The improvements in skill are related to improved initial atmospheric anomalies rather than an improved initial mean state (the forecast drift is worse in the ALI hindcast dataset). Since we are dealing with a coupled system, initial atmospheric errors (or differences between experiments) are amplified though coupled processes which can then lead to long lasting errors (or differences).  相似文献   

19.
Using the Flexible Global Ocean--Atmosphere--Land System model (FGOALS) version g1.11, a group of seasonal hindcasting experiments were carried out. In order to investigate the potential predictability of sea surface temperature (SST), singular value decomposition (SVD) analyses were applied to extract dominant coupled modes between observed and predicated SST from the hindcasting experiments in this study. The fields discussed are sea surface temperature anomalies over the tropical Pacific basin (20oS--20oN, 120oE--80oW), respectively starting in four seasons from 1982 to 2005. On the basis of SVD analysis, the simulated pattern was replaced with the corresponding observed pattern to reconstruct SST anomaly fields to improve the ability of the simulation. The predictive skill, anomaly correlation coefficients (ACC), after systematic error correction using the first five modes was regarded as potential predictability. Results showed that: 1) the statistical postprocessing approach was effective for systematic error correction; 2) model error sources mainly arose from mode 2 extracted from the SVD analysis---that is, during the transition phase of ENSO, the model encountered the spring predictability barrier; and 3) potential predictability (upper limits of predictability) could be high over most of the tropical Pacific basin, including the tropical western Pacific and an extra 10-degrees region of the mid and eastern Pacific.  相似文献   

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