TOPEX/Poseidon高度计资料在全球海洋环流模式中的同化及分析

利用一个新的四维变分海洋资料同化系统LICOM-3DVM对TOPEX／Poseidon高度计资料进行了同化。该同化系统是在LASG／IAP气候海洋模式LICOM1．0的基础上建立起来的,所用的同化方法为三维变分映射资料同化方法3DVM。高度计观测资料是采取间接的方式进行同化,即先建立起二维海面高度距平场与三维温度场的统计关系,并由此通过观测的海面高度距平信息反演出“观测”的三维温度场,然后利用LICOM-3DVM四维变分同化系统将此反演的温度场同化到海洋模式中。作者设计了两组试验并对结果进行了比较分析,积分时间从1993年1月至2001年12月共9年时间。结果表明,由于上混合层相关系数较小,因此同化后海温没有改进;而在温跃层以及更深层次,同化后的海温均有很大程度的改善。从对赤道太平洋地区海温的气候态、季节变化和年际变化以及Nino3区的Nino指数的模拟情况来看,由于同化时将海面高度异常和海温异常之间的相关参数取为常数,没有考虑其季节和年际变化,因此,同化后对于赤道太平洋的年际变化没有改善。对于黑潮地区,由于模式的分辨率较低,同化之前没有很好地模拟出温度锋面,温度和盐度梯度都偏小,流速也偏弱;而同化后使得温度锋面和盐度梯度与WOA01更加吻合,流速增强。     

Numerical experiments for Typhoon Dan incorporating AMSU-A retrieved data with 3DVM

Two sets of assimilation experiments on a landfalling typhoon—Typhoon Dan(1999)over the western North Pacific were designed to compare the performances of two kinds of variational data assimilation schemes that are the 3-Dimensional Variational data assimilation of Mapped observation(3DVM)and the 4-dimensional variational data assimilation(4DVar).Results show that:(1)both the 3DVM and 4DVar successfully improved the simulations of typhoon intensity and track incorporating the satellite AMSU-A retrieved temperature and wind data into the initial conditions,and the 3DVM more significantly due to the flow-dependent of background error covariance matrix and observation error covariance matrix like 3-dimensional variational data assimilation(3DVar)circle;(2)inclusions of extra model integration iterations at each observation time in the 3DVM make it more consistent with prediction model;(3)the 3DVM is much more time-saving due to the exclusion of the adjoint technique in it.     

A global ocean reanalysis product in the China Ocean Reanalysis (CORA) project

The first version of a global ocean reanalysis over multiple decades (1979–2008) has been completed by the National Marine Data and Information Service within the China Ocean Reanalysis (CORA) project. The global ocean model employed is based upon the ocean general circulation model of the Massachusetts Institute of Technology. A sequential data assimilation scheme within the framework of 3D variational (3DVar) analysis, called multi-grid 3DVar, is implemented in 3D space for retrieving multiple-scale observational information. Assimilated oceanic observations include sea level anomalies (SLAs) from multi-altimeters, sea surface temperatures (SSTs) from remote sensing satellites, and in-situ temperature/salinity profiles. Evaluation showed that compared to the model simulation, the annual mean heat content of the global reanalysis is significantly approaching that of World Ocean Atlas 2009 (WOA09) data. The quality of the global temperature climatology was found to be comparable with the product of Simple Ocean Data Assimilation (SODA), and the major ENSO events were reconstructed. The global and Atlantic meridional overturning circulations showed some similarity as SODA, although significant differences were found to exist. The analysis of temperature and salinity in the current version has relatively larger errors at high latitudes and improvements are ongoing in an updated version. CORA was found to provide a simulation of the subsurface current in the equatorial Pacific with a correlation coefficient beyond about 0.6 compared with the Tropical Atmosphere Ocean (TAO) mooring data. The mean difference of SLAs between altimetry data and CORA was less than 0.1 m in most years.     

Initialization and simulation of a landfalling typhoon using a variational bogus mapped data assimilation (BMDA)

Summary Recently, a new data assimilation method called “3-dimensional variational data assimilation of mapped observation (3DVM)” has been developed by the authors. We have shown that the new method is very efficient and inexpensive compared with its counterpart 4-dimensional variational data assimilation (4DVar). The new method has been implemented into the Penn State/NCAR mesoscale model MM5V1 (MM5_3DVM). In this study, we apply the new method to the bogus data assimilation (BDA) available in the original MM5 with the 4DVar. By the new approach, a specified sea-level pressure (SLP) field (bogus data) is incorporated into MM5 through the 3DVM (for convenient, we call it variational bogus mapped data assimilation – BMDA) instead of the original 4DVar data assimilation. To demonstrate the effectiveness of the new 3DVM method, initialization and simulation of a landfalling typhoon – typhoon Dan (1999) over the western North Pacific with the new method are compared with that with its counterpart 4DVar in MM5. Results show that the initial structure and the simulated intensity and track are improved more significantly using 3DVM than 4DVar. Sensitivity experiments also show that the simulated typhoon track and intensity are more sensitive to the size of the assimilation window in the 4DVar than that in the 3DVM. Meanwhile, 3DVM takes much less computing cost than its counterpart 4DVar for a given time window.     

A New Approach to Data Assimilation

A significant attempt to design a timesaving and efficient four-dimensional variational data assimilation (4DVar) has been made in this paper, and a new approach to data assimilation, which is noted as 'three-dimensional variational data assimilation of mapped observation (3DVM)' is proposed, based on the new concept of mapped observation and the new idea of backward 4DVar. Like the available 4DVar, 3DVM produces an optimal initial condition (IC) that is consistent with the prediction model due to the inclusion of model constraints and best fits the observations in the assimilation window through the model solution trajectory. Different from the 4DVar, the IC derived from 3DVM is located at the end of the assimilation window rather than at the beginning conventionally. This change greatly reduces the computing cost for the new approach, which is almost the same as that of the three-dimensional variational data assimilation (3DVar). Especially, such a change is able to improve assimilation accuracy because it does not need the tangential linear and adjoint approximations to calculate the gradient of cost function. Therefore, in numerical test, the new approach produces better IC than 4DVar does for 72-h simulation of TY9914 (Dan), by assimilating the three-dimensional fields of temperature and wind retrieved from the Advanced Microwave Sounding Unit-A (AMSU-A) observations. Meanwhile, it takes only 1/7 of the computing cost that the 4DVar requires for the same initialization with the same retrieved data.     

一种新的资料同化方法

为寻求一种快速有效的四维变分资料同化(英文缩写4DVar)作了有意义的尝试,提出了映射观测的新概念和反向四维变分资料同化的新思路,并以此为基础建立了三维变分映射资料同化(英文缩写为3DVM:3-DimensionalVariational data assimilation of Mapped observation)。该方法与传统的四维变分资料同化一样,不仅考虑了模式的动力和物理约束,使得同化后的初值与模式协调,而且通过模式方程对同化窗口中不同时刻的观测资料作了最佳拟合。与传统四维变分同化方法不同的是,由3DVM得到的初值不在同化窗口的始端,而在窗口的末端。正是所求初值时刻的改变,使得该方法的计算代价大大减少,几乎与三维变分资料同化(英文缩写3DVar)相当,这实际上是用3DVar的代价实现了4DVar的功能。同时,由于3DVM不再需要切线性和伴随近似来计算代价函数的梯度也提高了同化的精度。对具体的台风个例(Dan)用AMSU-A反演的温度场进行变分同化模拟试验,发现3DVM能比传统4DVar产生更好的初值,而且所花计算时间只需4DVar的1/7。     

Evaluation of the tropical variability from the Beijing Climate Center’s real-time operational global Ocean Data Assimilation System

The second-generation Global Ocean Data Assimilation System of the Beijing Climate Center(BCC_GODAS2.0) has been run daily in a pre-operational mode.It spans the period 1990 to the present day.The goal of this paper is to introduce the main components and to evaluate BCC_GODAS2.0 for the user community.BCC_GODAS2.0 consists of an observational data preprocess,ocean data quality control system,a three-dimensional variational(3DVAR) data assimilation,and global ocean circulation model[Modular Ocean Model 4(MOM4)].MOM4 is driven by six-hourly fluxes from the National Centers for Environmental Prediction.Satellite altimetry data,SST,and in-situ temperature and salinity data are assimilated in real time.The monthly results from the BCC_GODAS2.0 reanalysis are compared and assessed with observations for 1990-2011.The climatology of the mixed layer depth of BCC-GODAS2.0 is generally in agreement with that of World Ocean Atlas 2001.The modeled sea level variations in the tropical Pacific are consistent with observations from satellite altimetry on interannual to decadal time scales.Performances in predicting variations in the SST using BCC_GODAS2.0 are evaluated.The standard deviation of the SST in BCC-GODAS2.0 agrees well with observations in the tropical Pacific.BCC-GODAS2.0 is able to capture the main features of E1 Nino Modoki I and Modoki Ⅱ,which have different impacts on rainfall in southern China.In addition,the relationships between the Indian Ocean and the two types of E1 Nino Modoki are also reproduced.     

海洋环流对全球增暖趋势的调制：基于FGOALS-s2的数值模拟研究

在工业革命以来全球长期增暖趋势背景下,全球平均表面气温还同时表现出年代际变化特征,二者叠加在一起使得全球平均气温在某些年份增暖相对停滞(如1999～2008年)或者增暖相对较快(如1980～1998年).利用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)发展的耦合气候模式FGOALS-s2历史气候和典型路径浓度(RCPs)模拟试验结果研究了可能造成全球增暖的年代际停滞及加速现象的原因,特别是海洋环流对全球变暖趋势的调制作用.该模式模拟的全球平均气温与观测类似,即在长期增暖趋势之上,还叠加了显著的年代际变化.对全球平均能量收支分析表明,模拟的气温年代际变化与大气顶净辐射通量无关,意味着年代际表面气温变化可能与能量在气候系统内部的重新分配有关.通过对全球增暖加速和停滞时期大气和海洋环流变化的合成分析及回归分析,发现全球表面气温与大部分海区海表温度(SST)均表现出几乎一致的变化特征.在增暖停滞时期,SST降低,更多热量进入海洋次表层和深层,使其温度增加;而在增暖加速时期,更多热量停留在表层,使得大部分海区SST显著增加,次表层海水和深海相对冷却.进一步分析表明,热带太平洋表层和次表层海温年代际变化主要是由于副热带—热带经圈环流(STC)的年代际变化所致,然后热带太平洋海温异常可以通过风应力和热通量强迫作用引起印度洋、大西洋海温的年代际变化.在此过程中,海洋环流变化起到了重要作用,例如印度尼西亚贯穿流(ITF)年代际异常对南印度洋次表层海温变化起到关键作用,而大西洋经圈翻转环流(AMOC)则能直接影响到北大西洋深层海温变化.     

Impact of improved assimilation of temperature and salinity for coupled model seasonal forecasts

We assess the impact of improved ocean initial conditions for predicting El Niño-Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) using the Bureau of Meteorology’s Predictive Ocean Atmosphere Model for Australia (POAMA) coupled seasonal prediction model for the period 1982–2006. The new ocean initial conditions are provided by an ensemble-based analysis system that assimilates subsurface temperatures and salinity and which is a clear improvement over the previous optimal interpolation system which used static error covariances and was univariate (temperature only). Hindcasts using the new ocean initial conditions have better skill at predicting sea surface temperature (SST) variations associated with ENSO than do the hindcasts initialized with the old ocean analyses. The improvement derives from better prediction of subsurface temperatures and the largest improvements come during ENSO–IOD neutral years. We show that improved prediction of the Niño3.4 SST index derives from improved initial depiction of the thermocline and halocline in the equatorial Pacific but as lead time increases the improved depiction of the initial salinity field in the western Pacific become more important. Improved ocean initial conditions do not translate into improved skill for predicting the IOD but we do see an improvement in the prediction of subsurface temperatures in the Indian Ocean (IO). This result reflects that the coupling between subsurface and surface temperature variations is weaker in the IO than in the Pacific, but coupled model errors may also be limiting predictive skill in the IO.     

CLIMATIC FEATURES OF SEA TEMPERATURE OF WARM POOL AND RELATIONSHIP WITH SST OF ITS ADJACENT REGIONS*

In this paper,climatic features of sea temperature of western Pacific warm pool and the relationship with sea surface temperature (SST) of its adjacent regions are analyzed based on the observed sea temperature on vertical cross section along 137°E in western Pacific,the monthly mean SST of Xisha Station in South China Sea and the global monthly mean SST with resolution of 1°×1° (U.K./GISST2.2).The results indicate that (1) in a sense of correlation.SST of western Pacific warm pool can represent its sea subsurface temperature from surface to 200 m-depth level in winter,and it can only represent sea temperature from surface to 70 m depth in summer.The sea subsurface temperature anomaly of warm pool may be more suitable for representing thermal regime of western Pacific warm pool.The sea subsurface temperature of warm pool has a characteristic of quasi-biennial oscillation.(2)Warm pool and Kuroshio current are subject to different ocean current systems (3)Furthermore,the relationship between SST of Xisha Station and SST of warm pool has a characteristic of negative correlation in winter and positive correlation in summer,and a better lag negative correlation of SST of Xisha Station with sea subsurface temperature of warm pool exists.(4)Additionally,oscillation structure of sea temperature like "a seesaw" exists in between warm pool and Regions Nino3 and Nino4.January (June) maximum (minimum) sea subsurface temperature anomaly of warm pool may serve as a strong signal that indicates maturity phase (development phase) of La Nina (El Nino) event,it also acts as a strong signal which reveals variations of SST of Regions Nino3 and Nino4.     

The retrospective prediction of El Niño-southern oscillation from 1881 to 2000 by a hybrid coupled model: (I) Sea surface temperature assimilation with ensemble Kalman filter

In this study, we assimilated sea surface temperature (SST) data of the past 120 years into an oceanic general circulation model (OGCM) for El Niño-southern oscillation (ENSO) retrospective predictions using ensemble Kalman filter (EnKF). It was found that the ensemble covariance matrix in EnKF can act as a time-variant transfer operator to project the SST corrections onto the subsurface temperatures effectively when initial perturbations of ensemble were constructed using vertically coherent random fields. As such the increments of subsurface temperatures can be obtained via the transfer operator during assimilation cycles. The results show that the SST assimilation improves the model simulation skills significantly, not only for the SST anomalies over the whole assimilated domain, but also for the subsurface temperature anomalies of the upper 100 m over the tropical Pacific off the equator. Along the equator, the improvement of the assimilation is confined within the mixing layer because strong upwelling motions there prevent the downward transfer of SST information. The retrospective prediction skills of ENSO over the past 120 years from 1881 to 2000 were significantly improved by the SST assimilation at all leads of 1–12 months, especially for the 3–6 months leads, compared with those initialized by the control run without assimilation. The skilful predictions by the assimilation allow us to further study ENSO predictability using this coupled model.     

利用ARGO资料改进海洋资料同化和海洋模式中的物理过程

国际ARGO计划的实施每年将可提供多达 10万个剖面 (0～ 2 0 0 0m水深 )的海水温度和盐度资料 ,这些资料的获取无疑将会大大促进海洋和大气科学的发展 ,使人们加深对海洋过程的了解 ,揭示海 气相互作用的机理 ,为长期天气预报和短期气候预测提供模式初始场 ,提高长期天气预报和短期气候预测的能力。如何利用这些资料开展研究工作以及在实际业务中应用这些资料是目前大气和海洋科学界的一个前沿课题。本研究将ARGO浮标资料引入了国家气候中心的NCC GODAS同化系统 ,结果分析表明 ,同化ARGO资料后所得到的海温场在三大洋中不仅在温度数值的大小 ,而且在分布形式方面都与观测场具有较好的一致性 ,可以很好地反映出观测到的冬季和夏季海温的分布形式以及海温的季节变化特征和异常特征。本研究还应用最新的ARGO海洋观测资料 ,通过建立新的热带西太平洋次表层海温参数化方案 ,改进了Zebiak Cane(1987)海洋模式 (ZC模式 ) ,克服了ZC模式几乎没有模拟赤道西太平洋表层和次表层海温变化能力的缺陷。在ZC模式中引用新的次表层海温参数化方案后 ,在赤道西太平洋不仅次表层海温的模拟得到了改善 ,对海面温度异常的模拟也有了较大的改进 ,不仅模拟出了赤道西太平洋表层和次表层海温异常的年际变化特征 ,也模拟出了与观     

An ocean data assimilation system in the Indian Ocean and west Pacific Ocean

The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian and West Pacific oceans is an endeavor motivated by this goal. In this study, we describe the system in detail. Moreover, the reanalysis in the joint area of Asia, the Indian Ocean, and the western Pacific Ocean(hereafter AIPOcean) constructed using multi-year model integration with data assimilation is used to test the performance of this system. The ocean model is an eddy-resolving,hybrid coordinate ocean model. Various types of observations including in-situ temperature and salinity profiles(mechanical bathythermograph, expendable bathythermograph, Array for Real-time Geostrophic Oceanography, Tropical Atmosphere Ocean Array, conductivity–temperature–depth, station data), remotely-sensed sea surface temperature, and altimetry sea level anomalies, are assimilated into the reanalysis via the ensemble optimal interpolation method. An ensemble of model states sampled from a long-term integration is allowed to change with season, rather than remaining stationary. The estimated background error covariance matrix may reasonably reflect the seasonality and anisotropy. We evaluate the performance of AIPOcean during the period 1993–2006 by comparisons with independent observations, and some reanalysis products. We show that AIPOcean reduces the errors of subsurface temperature and salinity, and reproduces mesoscale eddies. In contrast to ECCO and SODA products, AIPOcean captures the interannual variability and linear trend of sea level anomalies very well. AIPOcean also shows a good consistency with tide gauges.     

A Regional Ocean Reanalysis System for Coastal Waters of China and Adjacent Seas

A regional ocean reanalysis system for the coastal waters of China and adjacent seas has been developed by the National Marine Data and Information Service(NMDIS).It produces a dataset package called CORA (China ocean reanalysis).The regional ocean model used is based on the Princeton Ocean Model with a generalized coordinate system(POMgcs).The model is parallelized by NMDIS with the addition of the wave breaking and tidal mixing processes into model parameterizations.Data assimilation is a sequential three-dimensional variational(3D-Var) scheme implemented within a multigrid framework.Observations include satellite remote sensing sea surface temperature(SST),altimetry sea level anomaly(SLA),and temperature/salinity profiles.The reanalysis fields of sea surface height,temperature,salinity,and currents begin with January 1986 and are currently updated every year. Error statistics and error distributions of temperature,salinity and currents are presented as a primary evaluation of the reanalysis fields using sea level data from tidal gauges,temperature profiles,as well as the trajectories of Argo floats.Some case studies offer the opportunity to verify the evolution of certain local circulations.These evaluations show that the reanalysis data produced provide a good representation of the ocean processes and phenomena in the coastal waters of China and adjacent seas.     

GOALS模式对热带太平洋ENSO年际变化特征的模拟评估

文中重点分析了中国科学院大气物理研究所LASG最新发展的全球大气环流谱模式(R42L9)与一全球海洋环流模式(T63L30)耦合形成的全球海洋-大气-陆面气候系统模式(GOALS/LASG)新版本已积分30 a的模拟结果,通过与多种观测资料的对比分析,讨论了赤道太平洋海表温度(SST)的年际变化及其纬向传播、赤道东太平洋SST异常与其他洋面SST变化之间的遥相关关系、赤道太平洋浅表层海温的年际变化特征等研究内容.结果表明,COALS模式模拟出了赤道太平洋SST异常出现不规则的年际变化特点;赤道东太平洋SST异常的向西传播过程;赤道太平洋混合层海温变化由西向东、由深层向浅层的传播过程;同时也模拟出了赤道东太平洋SST变化与赤道西太平洋以及与西南太平洋海温之间的反相关关系,与南印度洋和副热带大西洋SST之间的正遥相关关系等实际观测现象.但COALS模式也存在明显的不足,如对赤道东、中太平洋SST异常的年际变化幅度明显偏小,没能模拟出赤道东太平洋的SST变化比赤道中太平洋强的特点;赤道太平洋SST从东向西的传播速度明显比实际观测慢得多,但混合层海温极值变化由西向东的传播速度明显比实际情况快得多;没能模拟出赤道东太平洋SST变化同西北太平洋SST的负相关和北印度洋海温变化的正相关现象,因此也影响了对南亚、东南亚降水年际变化的模拟能力.     

Evaluation and Preprocess of Chinese Fengyun-3A Sea Surface Temperature Experimental Product for Data Assimilation

Validated satellite-derived sea surface temperatures (SSTs) are widely used for climate monitoring and ocean data assimilation systems. In this study, the Fengyun-3A (FY-3A) SST experimental product is evaluated using Advanced Very High Resolution Radiometer (AVHRR)-merged and in situ SSTs. A comparison of AVHRR-merged SSTs reveals a negative bias of more than 2K in FY-3A SSTs in most of the tropical Pacific and low-latitude Indian and Atlantic Oceans. The error variance of FY-3A SSTs is estimated using three-way error analysis. FY-3A SSTs show regional error variance in global oceans with a maximum error variance of 2.2 K in the Pacific Ocean. In addition, a significant seasonal variation of error variance is present in FY-3A SSTs, which indicates that the quality of FY-3A SST could be improved by adjusting the parameters in the SST retrieval algorithm and by applying regional and seasonal algorithms, particularly in key areas such as the tropical Pacific Ocean. An objective analysis method is used to merge FY-3A SSTs with the drifter buoy data. The errors of FY-3A SSTs are decreased to-0.45K comparing with SST observations from GTSPP.     

冬季北太平洋海表热通量异常和海气相互作用——基于一个全球海气耦合模式长期积分的诊断分析

利用一个全球海气耦合模式长期积分所给出的资料,分析了冬季北太平洋海表湍流热通量（潜热和感热）异常及其对海表温度（SST）异常的影响,并比较了海表热通量诸分量和海洋内部的动力学过程对SST变化的相对重要性。结果表明,冬季热带外海洋上的湍流热通量是影响SST的主要因子,但在北太平洋中部海水的平流作用也不可忽视。冬季热带外海洋向大气释放的潜热和感热通量与SST倾向（而不是SST本身）之间存在着显著的相关,这同Cayan和Reynolds等利用COADS资料和NCEP资料同化模式分析的结果是一致的。模式诊断的结果支持这样一种看法：和热带海洋不同,冬季热带外海洋上的海气相互作用主要地表现为大气对海洋的强迫作用,而不是相反。模式给出的SST倾向的第一个EOF分量及其与海平面气压场的相关特征同Wallace等从观测资料分析所得到的结果是一致的;进一步的分析表明：在冬季北太平洋的大部分区域（特别是西太平洋）,大尺度大气环流异常在很大程度上决定着SST的异常,而这种决定作用正是通过它对湍流热通量的强烈影响来实现的。     

热带海表温度和低层风场的年际变率及与ENSO循环的相关特征研究

采用 NCEP/NCAR的 1 979～ 1 998年逐月平均的海表温度及 1 0 0 0 h Pa风场资料 ,进行滤波和均方差计算 ,得到了热带太平洋、印度洋、大西洋海表温度 (SST)和风场的年际变化特征。用旋转主分量 (RPC)方法和投影法对热带三大洋海表温度距平 (SSTA)进行分析 ,得到了各大洋 SSTA演变的主要时空特征和相应的距平风场特征 ;并用相关分析研究热带三大洋与ENSO相关的特征 ,得到三大洋间的同期相关关系为 :印度洋 SSTA与赤道东太平洋 SSTA成正相关 ,而赤道东大西洋 SSTA与赤道东太平洋 SSTA成弱的负相关 ;赤道印度洋在落后于赤道东太平洋 3个月左右时正相关达到最大 ,赤道大西洋在超前于赤道东太平洋 6个月左右时负相关达到最大 ;热带印度洋和大西洋与 ENSO相关的分量对各自大洋海表温度年际变化的方差贡献数值相近 ,最大在 40 %以上 ,平均解释方差分别为 1 4%和 1 2 %。     

超强与普通厄尔尼诺海-气特征差异及对西太平洋副热带高压的不同影响

利用NCEP/NCAR再分析资料、GODAS海洋资料、哈得来中心海表温度（SST）以及中国国家气候中心（NCC）环流指数数据,依据美国气候预测中心的厄尔尼诺事件标准筛选出1980-2016年的超强与普通厄尔尼诺事件,对比了两类事件的不同生命阶段内海表及次表层温度特征的差异,并探讨了其对西太平洋副热带高压（西太副高）的不同影响。结果表明,对超强厄尔尼诺事件而言,海表温度正距平发展早且迅速,其大值中心偏东,纬向梯度强,但对普通厄尔尼诺事件而言,海表温度正距平中心偏西,纬向梯度小。厄尔尼诺事件的发展源于次表层海温距平（SOTA）随开尔文波东传并沿温跃层上升到达海表,其波动前部区域异常垂直海流对次表层海温距平的变化起重要作用;当海气激烈耦合时,可在温跃层激发出更强的海洋波动,使得次表层变暖更明显,激发出强的厄尔尼诺事件。海温异常强迫出的大气异常环流的强度与强迫源的强度关系密切。两类厄尔尼诺均能通过异常的沃克环流引起大气Gill型响应,使得西太副高偏强、西伸,且当超强厄尔尼诺发生时,异常沃克环流更强,海洋性大陆区域上空的异常强辐散导致Gill型响应而产生的反气旋更强,对西太副高的影响更甚。印度洋海表温度对厄尔尼诺的滞后变暖所带来的影响在上述亚太大气环流的持续异常中起重要作用。这些结果有利于加深对不同类型厄尔尼诺事件及影响西太副高机理的认识。      

The Application of ARGO Data to the Global Ocean Data Assimilation Operational System of NCC

1. Introduction It is well-known that the state of ocean plays very important role in the climate change. But there is a paucity of the ocean observation data. The data distri- bution in the space, time and different components is very inhomogeneous, even in some areas, there are no any observation data. Hence, it brings some diffcul- ties to the scientists to study many problems relevant to ocean. This situation has been being changed since ARGO (Array for Real-time Geostrophic Oceanogra-…