热带印度洋春季海表温度异常与南海夏季风强度变化的关系

利用50年的Reynolds月平均海表温度资料和NCEP/NCAR全球大气再分析资料,分析了热带印度洋春季海温异常对南海夏季风强度变化的影响。结果表明:1)热带印度洋春季海表温度距平(SSTA)的模态主要是全区一致型(USBM)和热带南印度洋偶极型(SIODM),USBM模态既有年际时间尺度的变化特征,又有年际以上时间尺度的变化特征,既包含有对冬季ENSO信号响应的变化特征,又有独立于ENSO的变化特征;SIODM模态主要表现为独立于ENSO的年际时间尺度变化。2)USBM模态与南海夏季风强度变化呈显著负相关关系,且二者都是对冬季ENSO信号的响应,USBM模态的年际变化不能独立于ENSO信号影响南海夏季风的强度变化。3)经(1~8年)带通滤波及去除ENSO信号的热带印度洋春季SSTA的SIODM型分布是影响南海夏季风强度变化的主要模态,表现为热带东南印度洋为负(正)、其他海区为正(负)时,南海夏季风强度增强(减弱),大气环流对热带东南印度洋SSTA热力作用的响应是造成这一关系的直接原因,SIODM型的SSTA分布与南海夏季风年际异常关系在热带印度洋长期变化趋势的暖位相期显著,在长期变化趋势的冷位相期不显著。     

热带印度洋秋季偶极子模态与南海夏季风强度变化的关系

利用多年的Reynolds月平均海表温度资料和NCEP／NCAR全球大气再分析资料，采用经验正交函数（EOF）分析和滑动相关方法，研究了热带印度洋秋季偶极子模态和南海夏季风强度变化的关系。结果表明：（1）热带印度洋秋季海表温度距平（SSTA）的主要模态是全区一致型和偶极子（IOD）型，全区一致型模态主要代表了秋季SSTA全海盆一致的年代际及其以上时间尺度的变化，IOD型模态主要反映热带印度洋秋季SSTA年际时间尺度的变化。（2）当前期秋季热带印度洋存在正（负）IOD模态时，南海的夏季风强度减弱（增强）。二者年际变化的负相关关系在长期趋势的冷位相期不显著，而在暖位相期显著。（3）当南海夏季风强度增强（减弱）时，后期秋季热带印度洋出现正（负）IOD模态。二者年际变化的正相关关系在长期趋势的冷、暖位相期显著，在冷、暖位相转换期前后不显著。     

CMIP5耦合模式对太平洋年代际振荡的模拟与预估

利用第五次耦合模式比较计划（CMIP5）40个模式的模拟资料和分类集合的方法,评估了耦合模式对20世纪太平洋年代际振荡（PDO）特征的模拟能力。结果表明,CMIP5多数模式对PDO周期有着较好的刻画能力,能模拟出PDO的年代际变化周期。模式对PDO模态空间特征的模拟能力存在较大差异,小部分模式模拟效果较差。进一步的分析表明,对PDO模态模拟较好的第1类模式,能较好地再现热带太平洋与北太平洋海表温度异常（SSTA）年代际变化间的关系,而且热带太平洋SSTA通过大气遥相关影响北太平样海表温度的过程也模拟的较成功。对PDO模态模拟差的模式,不能合理模拟出热带太平洋SSTA对北太平洋海表温度影响的遥相关过程。以上研究也证实了热带太平洋地区海表温度的年代际变率对北太平洋海表温度年代际变率的重要影响,热带太平洋SSTA对北太平洋SSTA的影响是通过大气遥相关实现的。利用CMIP5中等排放情景模拟结果,分析了第1类模式预估的北太平洋年代际变率的特征,发现21世纪北太平洋年代际变率的主要模态为一致的正异常分布且呈现明显的上升趋势,第二模态则表现为类似于20世纪典型PDO的马蹄型SSTA分布。     

热带印度洋海温与西北地区东部降水关系研究

利用西北地区东部1961 2009年99个气象测站逐月降水量资料,以及Hardley中心逐月海表面温度(SST)资料,采用最大协方差分析(MCA)、相关、回归等统计方法,考虑扣除ENSO(El Ni珘noSouthern Oscillation)影响后,分析了西北地区东部降水量和热带印度洋SST之间年际、年代际变化关系。结果表明:前期冬、春季持续异常的热带印度洋海盆模与西北地区东部5月降水异常主模态存在显著正相关关系,通常超前1~2个季节的暖(冷)海盆模对应5月西北地区东部降水偏多(少),并且这种显著关系存在年代际差异,20世纪70年代中期之前两者关系不显著,之后两者关系加强,通过了0.05显著性水平检验。热带印度洋海盆模对西北地区东部5月降水的影响可能是热带印度洋海盆模"电容器"效应的一种具体体现。     

冬季和春季印度洋海温异常年际变率模态对中国东部夏季降水的可能影响过程

印度洋热力状况是影响全球气候变化和亚洲季风变异的一个重要的因素,但以往研究更多关注热带印度洋海温的变化,对南印度洋中高纬地区海温变化关注不够,由此限制了我们对印度洋的全面认识.本文研究了年际尺度上整个印度洋海温异常主导模态的特征及其对我国东部地区夏季降水的可能影响过程,以期望为气候变异研究及预测提供理论依据.研究结果表明:全印度洋海温异常年际变率的主导模态特征是在南印度洋副热带地区海温异常呈现西南—东北反向变化的偶极子模态,西极子位于马达加斯加以东南洋面,东极子位于澳大利亚以西洋面;同时,热带印度洋海温异常与东极子一致.当西极子为正的海温异常,东极子、热带印度洋为负异常时定义为正的印度洋海温异常年际变率模态;反之,则为负的印度洋海温异常年际变率模态.从冬至春,印度洋海温异常年际变率模态具有较好的季节持续性;与我国长江中游地区夏季降水显著负相关,而与我国华南地区夏季降水显著正相关.其可能的影响过程为:对于正的冬、春季印度洋海温异常年际变率模态事件,印度洋地区异常纬向风的经向大气遥相关使得热带印度洋盛行西风异常,导致春、夏季海洋性大陆对流减弱,使夏季西太平洋副热带高压强度偏弱、位置偏东偏北,造成华南地区夏季降水增多,长江中游地区降水减少;反之亦然.同时,印度洋海温异常年际变率模态可通过改变印度洋和孟加拉湾向长江中游地区的水汽输送而影响其夏季降水.     

印度洋偶极子与热带太平洋海洋表面温度异常多时间尺度相互作用初析

本文利用交叉谱方法, 将印度洋偶极子 (简称IOD) 与ENSO的相关关系分解到不同的时间尺度上来分析, 进而通过对海气耦合过程的初步分析, 讨论了不同时间尺度上IOD与ENSO的相互作用。结果表明, IOD与ENSO在准1～2年、 准3年、 准4年等三个时间尺度上存在显著相关, 同时, IOD还存在一个独立于ENSO的模态, 主要表现在准8个月时间尺度上。从海气相互作用的角度看, 在与ENSO相关的三个特征时间尺度上, IOD年际变率主要通过引发热带印度洋纬向风异常并且东传到太平洋, 从而引起热带中东太平洋海温的年际变率。与ENSO相对独立的IOD模态则没有类似的纬向风异常东传过程。此外, 在上述四个不同时间尺度上, 产生IOD变率的印度洋海气耦合过程不尽相同, 各具特点。     

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

采用NCEP/NCAR的1979～1998年逐月平均的海表温度及1000hPa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14%和12%.     

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 %。     

10月份热带印度洋海气耦合的统计动力诊断

本文将热带印度洋10月份的大气风场和海洋上层流场看作一个整体, 对其作了动力统计诊断, 即作了复EOF分析, 考察了其年际和年代际变化, 并揭示其与印度洋偶极子 (IOD) 和ENSO的关系。结果表明: 在同一模态中, 海洋模态表现出很强的赤道俘获现象, 而大气则无此现象; 第一模态为印度洋偶极子模态; 第二模态为ENSO前期在印度洋的延伸模态。前2个模态的风场都揭示了Walker环流异常的结构; 印度洋海温的年际变化主要取决于印度洋地区的海气耦合状态, 但太平洋的ENSO循环对其也有一定影响。     

近20年来热带印度洋与热带太平洋海气系统相互作用特征的诊断研究

利用1979年1月～1998年12月的月平均海表温度(SST)、向外长波辐射(OLR)和l000hPa纬向风速等NCEP/NCAR再分析资料，对近20年来热带印度洋与太平洋海温异常(SSTA)及相关的环流特征量进行综合分析和研究，发现热带印度洋的内部耦合动力特征模态—偶极子模的强度，存在着年代间的差异，80年代偏弱，90年代偏强。热带印度洋与热带太平洋海气耦合系统之间存在着相互作用，80年代热带印度洋的SSTA主要是对太平洋ENSO的响应，90年代太平洋ENSO的异常发展在一定程度上是受印度洋偶极子模态异常活跃影响的结果。从观测资料诊断分析的角度，找出了90年代后ZC耦合模式对ENSO事件预报失败的可能原因。     

冬/夏季热带太平洋与印度洋海表温度年际异常关系的年代际变化

利用NCEP/NCAR再分析资料、全球海温海冰GISST 2.3b资料, 用EOF技术分析了热带太平洋海表温度的年际异常 (SSTA) 变化特征表明:可用Ni?o3指数表示热带太平洋SSTA, 并用该指数来讨论热带太平洋、热带印度洋SSTA间的关系。分季节分析表明:冬季Ni?o3指数与热带印度洋SSTA间的关系表现为热带印度洋整体相关系数为正的单极形态, 且1976年以后两者的关系减弱, 其原因是冬季为ENSO事件的盛期, 另外, 冬季西太平洋暖水区东移导致太平洋Walker环流上升支强盛处的东移, 造成两洋的垂直纬向环流耦合减弱。夏季两者关系表现为偶极形态 (热带西印度洋与Ni?o3指数同相变化, 热带东印度洋则相反), 但1976年以后两者的关系有所加强, 是因为夏季为偶极子盛期, 也是ENSO事件的发展期, 同时夏季西太平洋暖水区东移并未引起太平洋Walker环流上升支强盛处的明显东移, 且印度洋季风环流、太平洋Walker环流的上升支强盛处的强度增大了, 造成两洋的垂直纬向环流耦合更强烈。即1976年以后, 冬季热带两洋SSTA间的关系减弱了, 而夏季两者关系则变得更密切。     

Contrasting Indian Ocean SST variability with and without ENSO influence: A coupled atmosphere-ocean GCM study

Summary In this study, we perform experiments with a coupled atmosphere-ocean general circulation model (CGCM) to examine ENSO’s influence on the interannual sea-surface temperature (SST) variability of the tropical Indian Ocean. The control experiment includes both the Indian and Pacific Oceans in the ocean model component of the CGCM (the Indo-Pacific Run). The anomaly experiment excludes ENSO’s influence by including only the Indian Ocean while prescribing monthly-varying climatological SSTs for the Pacific Ocean (the Indian-Ocean Run). In the Indo-Pacific Run, an oscillatory mode of the Indian Ocean SST variability is identified by a multi-channel singular spectral analysis (MSSA). The oscillatory mode comprises two patterns that can be identified with the Indian Ocean Zonal Mode (IOZM) and a basin-wide warming/cooling mode respectively. In the model, the IOZM peaks about 3–5 months after ENSO reaches its maximum intensity. The basin mode peaks 8 months after the IOZM. The timing and associated SST patterns suggests that the IOZM is related to ENSO, and the basin-wide warming/cooling develops as a result of the decay of the IOZM spreading SST anomalies from western Indian Ocean to the eastern Indian Ocean. In contrast, in the Indian-Ocean Run, no oscillatory modes can be identified by the MSSA, even though the Indian Ocean SST variability is characterized by east–west SST contrast patterns similar to the IOZM. In both control and anomaly runs, IOZM-like SST variability appears to be associated with forcings from fluctuations of the Indian monsoon. Our modeling results suggest that the oscillatory feature of the IOZM is primarily forced by ENSO.     

Tropical Indian Ocean variability revealed by self-organizing maps

The tropical Indian Ocean climate variability is investigated using an artificial neural network analysis called self-organizing map (SOM) for both observational data and coupled model outputs. The SOM successfully captures the dipole sea surface temperature anomaly (SSTA) pattern associated with the Indian Ocean Dipole (IOD) and basin-wide warming/cooling associated with ENSO. The dipole SSTA pattern appears only in boreal summer and fall, whereas the basin-wide warming/cooling appears mostly in boreal winter and spring owing to the phase-locking nature of these phenomena. Their occurrence also undergoes significant decadal variation. Composite diagrams constructed for nodes in the SOM array based on the simulated SSTA reveal interesting features. For the nodes with the basin-wide warming, a strong positive SSTA in the eastern equatorial Pacific, a negative Southern Oscillation, and a negative precipitation anomaly in East Africa are found. The nodes with the positive IOD are associated with a weak positive SSTA in the central equatorial Pacific or positive SSTA in the eastern equatorial Pacific, a positive (negative) sea level pressure anomaly in the eastern (western) tropical Indian Ocean, and a positive precipitation anomaly over East Africa. The warming in the central equatorial Pacific appears to correspond to El Niño Modoki discussed recently. These results suggest usefulness of SOM in studying large-scale ocean–atmosphere coupled phenomena.     

A DIAGNOSIS OF THE INTERANNUAL VARIABILITY OF SEA SURFACE TEMPERATURE AND SURFACE WIND FIELD IN THE TROPICAL OCEANS AND ITS CORRELATIVE CHARACTERS WITH ENSO CYCLE*

Utilizing the NCEP/NCAR reanalysis monthly datasets,and based on the filter and standard deviation calculation,the interannual variability of sea surface temperature (SST) and 1000 hPa wind field for the tropical Pacific,Indian and Atlantic Oceans is investigated for the past 20 years (1979-1998).The characters of space-time evolution in SST anomalies (SSTA) for each ocean and corresponding wind anomaly field are acquired by using rotated principal component (RPC) and linear regression analysis methods.Using the method of correlation analysis.the characters of three tropical oceans correlated with ENSO are investigated.The contemporary correlation between the SSTA in the Indian Ocean and in the equatorial eastern Pacific is positive,and there is a weak negative correlation between the SSTA in the equatorial east Atlantic Ocean and in the equatorial eastern Pacific.The lead-lag correlation analysis indicates that the SSTA in the equatorial Indian Ocean lags the dominant Pacific ENSO mode by 3 months,and the SSTA in the equatorial Atlantic Ocean leads ENSO mode by 6 months.The ENSO-correlated components in tropical Indian Ocean and tropical Atlantic Ocean display much the same amount of total variance in each ocean,i.e..14% in the Indian Ocean and 12% in the Atlantic Ocean and the maximums are all above 40%.     

Future change of the Indian Ocean basin-wide and dipole modes in the CMIP5

The Indian Ocean sea surface temperature (SST) variability has been represented with the two dominant variability modes: the Indian Ocean basin-wide (IOBW) and dipole (IOD) modes. Here we investigate future changes of the two modes together with mean state and El Niño and Southern Oscillation (ENSO) relationship under the anthropogenic global warming using 20 coupled models that participated in the phase five of Coupled Model Intercomparison Project by comparing the historical run from 1950 to 2005 and the RCP 4.5 run from 2050 to 2099. The five best models are selected based on the evaluation of the 20 models’ performances in simulating the two modes and Indian Ocean basic state for the latest 56 years. They are capable of capturing the IOBW and IOD modes in their spatial distribution, seasonal cycle, major periodicity, and relationship with ENSO to some extent. The five best models project the significant changes in the Indian Ocean mean state and variability including the two dominant modes in the latter part of twenty-first century under the anthropogenic warming scenario. First, the annual mean climatological SST displays an IOD-like pattern change over the Indian Ocean with enhanced warming in the northwestern Indian Ocean and relatively weaker warming off the Sumatra–Java coast. It is also noted that the monthly SST variance is increased over the eastern and southwestern Indian Ocean. Second, the IOBW variability on a quasi-biennial time scale will be enhanced due to the strengthening of the ENSO–IOBW mode relationship although the total variance of the IOBW mode will be significantly reduced particularly during late summer and fall. The enhanced air-sea coupling over the Indian-western Pacific climate in response to El Nino activity in the future projection makes favorable condition for a positive IOD while it tends to derive relatively cold temperature over the eastern Indian Ocean. This positive IOD-like ENSO response weakens the relationship between the eastern Indian Ocean and El Nino while strengthens the relationship with western Indian Ocean. Third, the IOD mode, intrinsic coupled mode of the Indian Ocean may not be changed appreciably under the anthropogenic global warming.     

An objective analysis of the observed spatial structure of the tropical Indian Ocean SST variability

The observed interannual Indian Ocean sea surface temperature (SST) variability from 1950 to 2008 is analyzed in respect to the spatial structure of the variability. The analysis is based on an objective comparison of the leading empirical orthogonal function modes against the stochastic null hypothesis of spatial red noise (isotropic diffusion). Starting from this red noise assumption, the analysis searches for those structures that are most distinct from the red noise hypothesis. This objective approach will put previously well and less known modes of variability into the context of the multivariate SST variability. The Indian Ocean SST variability is marked by relatively weak SST variability, which is strongly dominated by a basin wide monopole pattern that is caused by different processes. The leading modes of variability are the El Nino Southern Oscillation (ENSO) variability and the warming trend, which both project onto the basin wide monopole structure. Other more characteristic spatial patterns of internal variability are much less dominant in the tropical Indian Ocean, which is quite different from all other ocean basin, where characteristic teleconnection patterns exist. The remaining, ENSO independent, detrended variability is dominated by multi-pole patterns from the southern Indian Ocean reaching into the tropical Indian Ocean, which are probably primarily caused by extra-tropical atmospheric forcings. The large scale tropical Indian Ocean internal variability itself has no dominant structure. The currently often used dipole mode index (DMI) does not appear to present a dominant teleconnection pattern of the Indian Ocean internal SST variability. In the context of the objective analysis presented here, the DMI partly reflects the ENSO variability and is also a representation of the multi-dimensional, chaotic spatial red noise (isotropic diffusion) process. As such the DMI cannot be interpreted as a coherent teleconnection between the two poles.     

Indian Ocean Dipole-related Predictability Barriers Induced by Initial Errors in the Tropical Indian Ocean in a CGCM

利用GFDL CM2p1模式, 本文探讨了初始海温误差对印度洋偶极子(IOD)事件可预报性的影响. 当热带印度洋存在初始海温误差时, IOD预报发生了冬季预报障碍(WPB)现象和夏季预报障碍(SPB)现象. WPB发生与否与正IOD事件发展位相冬季的厄尔尼诺-南方涛动(ENSO)有关. 即当冬季存在ENSO时, IOD预测不发生WPB现象, 反之亦然. 相比之下, SPB发生与否和ENSO没有必然联系. 此外, 进一步探讨了最容易导致SPB现象的初始海温误差的主要模态, 指出该模态在热带印度洋上表现为东-西偶极子型, 这和前人研究中最容易导致WPB现象的初始海温误差模态相似. 当在热带印度洋上叠加这些初始海温误差后, 热带太平洋上出现了海表温度异常和风场异常, 进而通过大气桥和印尼贯穿流的作用影响热带印度洋, 使之在夏季出现了东-西偶极子型的海表温度异常, 该异常在Bjerknes作用下快速发展, 加强, 最终导致SPB现象的发生.     

热带印度洋偶极子模态的不对称性及其成因的数值研究

热带印度洋偶极子 (Indian Ocean Dipole) 是印度洋海域内海洋和大气环流年际变化的主要特征模态之一, 在热带海气耦合系统中起到非常重要的作用。同热带太平洋的ENSO现象类似, 热带印度洋偶极子也呈现出显著的不对称性。本文利用中国科学院大气物理研究所发展的全球海洋环流模式, 在观测风应力距平的强迫下, 评估了模式对热带印度洋季节变化、 热带印度洋偶极子 (IOD) 模态及其不对称性的模拟能力, 并且通过数值试验分析了IOD模态不对称性特征及其对气候平均态的影响。对照观测资料, 模式较好地再现了热带印度洋SST在季风驱动下的季节变化特征。在年际时间尺度上, 模式不仅能够再现IOD指数的变化趋势, 而且可以成功模拟出IOD模态的空间分布特征, 即表层和次表层海温在西印度洋表现为正异常, 在东印度洋表现为负异常。可见, 对于热带印度洋而言, IOD模态主要是对风应力异常的响应。热带印度洋海温与Niño3.4指数的相关性分析表明, 模式能够模拟出超前热带太平洋ENSO现象2～4个月时海温的偶极子型分布, 但是不能模拟出滞后ENSO现象2个月左右的全海盆增暖模态, 可能是因为模式试验中没有考虑热通量年际异常的强迫。同时, 模式模拟的IOD模态具有同观测结果相类似的不对称性, 进一步的敏感性试验表明风应力的不对称性对偶极子指数的不对称性贡献较小, 次表层及以下海温的不对称性可能主要受到海洋内部非线性动力过程的影响。通过数值试验, 本文还发现热带印度洋海温的不对称性对气候平均态会有影响, 而这种不对称性长期积累后, 会导致上层热带印度洋温度层结趋于稳定状态。