Variability of Summer Monsoon Rainfall in India on Inter-Annual and Decadal Time Scales

Indian Summer Monsoon Rainfall(ISMR)exhibits a prominent inter-annual variability known as troposphere biennial oscillation.A season of deficient June to September monsoon rainfall in India is followed by warm sea surface temperature(SST)anomalies over the tropical Indian Ocean and cold SST anomalies over the western Pacific Ocean.These anomalies persist until the following monsoon,which yields normal or excessive rainfall.Monsoon rainfall in India has shown decadal variability in the form of 30 year epochs of alternately occurring frequent and infrequent drought monsoons since1841,when rainfall measurements began in India.Decadal oscillations of monsoon rainfall and the well known decadal oscillations in SSTs of the Atlantic and Pacific oceans have the same period of approximately 60 years and nearly the same temporal phase.In both of these variabilities,anomalies in monsoon heat source,such as deep convection,and middle latitude westerlies of the upper troposphere over south Asia have prominent roles.     

南海夏季风爆发与热带海洋海温和大气环流异常变化关系的研究

用合成和相关分析方法及SVD技术研究了南海夏季风爆发早、晚年份4～6月季风建立时期季风环流的异常及其与热带太平洋-印度洋海温的关系。结果表明,南海夏季风爆发与热带大气环流和海温变异密切相关。（1）当热带中、东太平洋—印度洋（主要在西南部）及南海海温低（高）,西太平洋—澳洲邻近海域海温高（低）时,南海夏季风爆发早（晚）。不同区域海温对季风的影响有明显的季节差异,印度洋主要为晚春至初夏（4～6月）,南海为5～6月,而热带太平洋从前冬一直持续到夏季。（2）不同的海温异常产生不同的季风环流型,南海夏季风爆发早、晚年大气环流的异常变化基本相反。南海夏季风的活动主要受印度季风环流变化的影响,与前期冬春季西太副高的强弱及位置变化密切相关。西太副高弱时,南海夏季风爆发早;反之,爆发晚。（3）热带太平洋—印度洋海温异常引起季风环流和Walker环流的异常变化可能是影响南海夏季风爆发早、晚的物理过程。     

Pacific Ocean sea-surface temperature variability and predictability of rainfall in the early and late parts of the Indian summer monsoon season

For central India and its west coast, rainfall in the early (15 May–20 June) and late (15 September–20 October) monsoon season correlates with Pacific Ocean sea-surface temperature (SST) anomalies in the preceding month (April and August, respectively) sufficiently well, that those SST anomalies can be used to predict such rainfall. The patterns of SST anomalies that correlate best include the equatorial region near the dateline, and for the early monsoon season (especially since ~1980), a band of opposite correlation stretching from near the equator at 120°E to ~25°N at the dateline. Such correlations for both early and late monsoon rainfall and for both regions approach, if not exceed, 0.5. Although correlations between All India Summer Monsoon Rainfall and typical indices for the El Ni?o-Southern Oscillation (ENSO) commonly are stronger for the period before than since 1980, these correlations with early and late monsoon seasons suggest that ENSO continues to affect the monsoon in these seasons. We exploit these patterns to assess predictability, and we find that SSTs averages in specified regions of the Pacific Ocean in April (August) offer predictors that can forecast rainfall amounts in the early (late) monsoon season period with a ~25% improvement in skill relative to climatology. The same predictors offer somewhat less skill (~20% better than climatology) for predicting the number of days in these periods with rainfall greater than 2.5?mm. These results demonstrate that although the correlation of ENSO indices with All India Rainfall has decreased during the past few decades, the connections with ENSO in the early and late parts have not declined; that for the early monsoon season, in fact, has grown stronger in recent decades.     

The crucial role of ocean�Catmosphere coupling on the Indian monsoon anomalous response during dipole events

This paper examines an issue concerning the simulation of anomalously wet Indian summer monsoons like 1994 which co-occurred with strong positive Indian Ocean Dipole (IOD) conditions in the tropical Indian Ocean. Contrary to observations it has been noticed that standalone atmospheric general circulation models (AGCM) forced with observed SST boundary condition, consistently depicted a decrease of the summer monsoon rainfall during 1994 over the Indian region. Given the ocean?Catmosphere coupling during IOD events, we have examined whether the failure of standalone AGCM simulations in capturing wet Indian monsoons like 1994 can be remedied by including a simple form of coupling that allows the monsoon circulation to dynamically interact with the IOD anomalies. With this view, we have performed a suite of simulations by coupling an AGCM to a slab-ocean model with spatially varying mixed-layer-depth (MLD) specified from observations for the 1994 IOD; as well as four other cases (1983, 1997, 2006, 2007). The specification of spatially varying MLD from observations allows us to constrain the model to observed IOD conditions. It is seen that the inclusion of coupling significantly improves the large-scale circulation response by strengthening the monsoon cross-equatorial flow; leading to precipitation enhancement over the subcontinent and rainfall decrease over south-eastern tropical Indian Ocean??in a manner broadly consistent with observations. A plausible physical mechanism is suggested to explain the monsoonal response in the coupled frame-work. These results warrant the need for improved monsoon simulations with fully coupled models to be able to better capture the observed monsoon interannual variability.     

季节预测模式对东亚夏季环流的预测能力及其对热带海洋的响应分析

东亚夏季环流变化对中国夏季降水的年际变化有重要影响,因此需要进一步理解季节预测模式对东亚夏季环流的预测能力。利用1991~2013年美国国家环境预测中心（NCEP）、中国气象局国家气候中心（NCC）和日本东京气候中心（TCC）的三个季节预测模式（CFS V2、BCC_CSM V2和MRI-CGCM）以及NCEP/NCAR再分析资料,定量评估了模式对东亚夏季风（EASM）和夏季西太平洋副热带高压（WPSH）强度的预测能力。在此基础上,分析了模式预测的EASM和WPSH对热带海温异常的响应能力,以及ENSO事件对EASM和WPSH预测的影响,阐述了预测误差产生的原因。结果表明:整体而言,三个模式对EASM和WPSH的预测技巧较高,但TCC模式对WPSH的预测技巧相对较低。三个模式预测的850 hPa风场在西北太平洋存在一个异常气旋,使得预测的EASM偏强和WPSH偏弱。同时,二者的年际变率整体比观测小。三个模式预测的EASM和WPSH对热带海洋海温异常的响应随季节演变特征与观测比较接近,但NCEP模式和TCC模式预测的EASM对前期热带太平洋和前期、同期热带印度洋的海温异常响应要强于观测,NCC模式预测的EASM对前期和同期的热带太平洋的海温异常响应明显比观测强。此外,三个模式预测的WPSH对前期和同期的热带太平洋、热带印度洋和热带大西洋的海温异常响应明显强于观测。三个模式预测的EASM和WPSH在ENSO年的平均绝对误差（MAE）整体而言要比正常年的小很多,NCEP模式和NCC模式预测的EASM和WPSH的MAE在La Ni?a年和El Ni?o年差别不大,而TCC模式预测的EASM和WPSH的MAE在El Ni?o年比在La Ni?a年大很多,表明ENSO事件是东亚夏季环流重要的可预报源。     

Impacts of Indian Ocean SST biases on the Indian Monsoon: as simulated in a global coupled model

In this study, the impact of the ocean–atmosphere coupling on the atmospheric mean state over the Indian Ocean and the Indian Summer Monsoon (ISM) is examined in the framework of the SINTEX-F2 coupled model through forced and coupled control simulations and several sensitivity coupled experiments. During boreal winter and spring, most of the Indian Ocean biases are common in forced and coupled simulations, suggesting that the errors originate from the atmospheric model, especially a dry islands bias in the Maritime Continent. During boreal summer, the air-sea coupling decreases the ISM rainfall over South India and the monsoon strength to realistic amplitude, but at the expense of important degradations of the rainfall and Sea Surface Temperature (SST) mean states in the Indian Ocean. Strong SST biases of opposite sign are observed over the western (WIO) and eastern (EIO) tropical Indian Ocean. Rainfall amounts over the ocean (land) are systematically higher (lower) in the northern hemisphere and the south equatorial Indian Ocean rainfall band is missing in the control coupled simulation. During boreal fall, positive dipole-like errors emerge in the mean state of the coupled model, with warm and wet (cold and dry) biases in the WIO (EIO), suggesting again a significant impact of the SST errors. The exact contributions and the distinct roles of these SST errors in the seasonal mean atmospheric state of the coupled model have been further assessed with two sensitivity coupled experiments, in which the SST biases are replaced by observed climatology either in the WIO (warm bias) or EIO (cold bias). The correction of the WIO warm bias leads to a global decrease of rainfall in the monsoon region, which confirms that the WIO is an important source of moisture for the ISM. On the other hand, the correction of the EIO cold bias leads to a global improvement of precipitation and circulation mean state during summer and fall. Nevertheless, all these improvements due to SST corrections seem drastically limited by the atmosphere intrinsic biases, including prominently the unimodal oceanic position of the ITCZ (Inter Tropical Convergence Zone) during summer and the enhanced westward wind stress along the equator during fall.     

Interannual variability and predictability of sea level along the Indian Coast

Summary The Indian coast stretching more than 7,500 km constitutes the major portion of the South Asian coastline in the North Indian Ocean region. The South Asian region is significantly influenced by meteorological/oceanographic phenomena like monsoons, El Ni?o/Southern Oscillation (ENSO) and tropical cyclones. Direct/indirect impacts of these phenomena, which exhibit large interannual variabilities, on sea level changes in this region are considerable. Our results show that the mean sea level along the eastern coast of India, which is highly vulnerable to the incidence of severe tropical cyclones, is considerably higher than normal during the intense cyclonic period of a year falling in the positive phase of the Southern Oscillation (La Ni?a epoch), thereby enhancing the hazardous potential of tropical cyclones. Further, in the closing phase of the La Ni?a southwest monsoon, higher sea level anomalies prevail along the Indian coast raising the flooding potential of such monsoons. Over the west coast of India significant simultaneous correlations have been found between the amount of southwest monsoon rainfall and the mean sea level during the period from June to September. Over the east coast of India at Visakhapatnam, mean sea level is predictable with a fair degree of confidence one month in advance, by using the Sea Surface Temperature (SST) and the Southern Oscillation Index (SOI) as predictors. These results will be useful in the annual preparedness programmes aimed at mitigating the impacts of natural disasters like tropical cyclones and floods in the South Asian region. Received November 9, 2001     

Predictable patterns and predictive skills of monsoon precipitation in Northern Hemisphere summer in NCEP CFSv2 reforecasts

The predictable patterns and predictive skills of monsoon precipitation in the Northern Hemisphere summer (June–July–August) are examined using reforecasts (1983–2010) from the National Center for Environmental Prediction Climate Forecast System version 2 (CFSv2). The possible connections of these predictable patterns with global sea surface temperature (SST) are investigated. The empirical orthogonal function analysis with maximized signal-to-noise ratio is used to isolate the predictable patterns of the precipitation for three regional monsoons: the Asian and Indo-Pacific monsoon (AIPM), the Africa monsoon (AFM), and the North America monsoon (NAM). Overall, the CFSv2 well predicts the monsoon precipitation patterns associated with El Niño-South Oscillation (ENSO) due to its good prediction skill for ENSO. For AIPM, two identified predictable patterns are an equatorial dipole pattern characterized by opposite variations between the equatorial western Pacific and eastern Indian Ocean, and a tropical western Pacific pattern characterized by opposite variations over the tropical northwestern Pacific and the Philippines and over the regions to its west, north, and southeast. For NAM, the predictable patterns are a tropical eastern Pacific pattern with opposite variations in the tropical eastern Pacific and in Mexico, the Guyana Plateau and the equatorial Atlantic, and a Central American pattern with opposite variations in the eastern Pacific and the North Atlantic and in the Amazon Plains. The CFSv2 can predict these patterns at least 5 months in advance. However, compared with the good skill in predicting AIPM and NAM precipitation patterns, the CFSv2 exhibits little predictive skill for AFM precipitation, probably because the variability of the tropical Atlantic SST plays a more important than ENSO in the AFM precipitation variation and the prediction skill is lower for the tropical Atlantic SST than the tropical Pacific SST.     

气候系统模式FGOALS-s1.1对热带降水年循环模态的模拟

文中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)新一代耦合气候模式Fgoals_s1.1对热带降水年循环模态的模拟能力。通过与观测表层海温(SST)强迫的大气模式SAMIL试验结果比较,分析了海气耦合过程对年循环模态模拟效果的影响。结果表明Fgoals_s1.1能合理再现热带地区降水年循环模态的基本特征。Fgoals_s1.1模拟出了年平均降水场中的主要降水中心,但模拟的赤道和南太平洋降水偏多,而北太平洋降水则偏少。Fgoals_s1.1的季风模态降水呈现与观测一致的关于赤道反对称的特征,其模拟偏差大部分来自大气分量,尤其是在赤道外。Fgoals_s1.1的主要缺陷在于它对春秋非对称模态模拟能力低于单独大气模式,这主要是由于耦合模式模拟的SST距平的年循环位相与观测相反。SST纬向梯度的位相偏差使得太平洋沃克环流和印度洋的反沃克环流在春季强于秋季,最终导致模拟的春秋非对称模态的偏差。Fgoals_s1.1模拟的季风区范围接近观测,存在的问题在于模拟的西北太平洋季风区、东亚季风区都偏小。本文结果表明,大气模式偏差仅是Fgoals_s1.1在降水年循环模态模拟上的偏差的部分来源,改进模式模拟的SST,特别是赤道地区SST季节循环,是今后Fgoals_s1.1发展过程中急需解决的问题。     

太阳活动11年周期对ENSO事件海温异常演变和东亚降水的影响

本文利用美国NCEP/NCAR再分析资料、海温、降水和反映太阳活动强弱的太阳10.7 cm射电流量资料,研究了1952～2010年太阳活动11年周期对ENSO年海温异常演变以及与之相联系的东亚降水的影响,在此基础上着重分析了ENSO发展期秋季东亚地区降水异常对太阳射电流量高(HS)/低(LS)的不同响应以及相关的物理过...     

Contrasting Regional Responses of Indian Summer Monsoon Rainfall to Exhausted Spring and Concurrently Emerging Summer El Ni?o Events

The inverse relationship between the warm phase of the El Ni?o Southern Oscillation(ENSO) and the Indian Summer Monsoon Rainfall(ISMR) is well established. Yet, some El Ni?o events that occur in the early months of the year(boreal spring) transform into a neutral phase before the start of summer, whereas others begin in the boreal summer and persist in a positive phase throughout the summer monsoon season. This study investigates the distinct influences of an exhausted spring El Ni?o(springtime)...     

南亚和东亚热带夏季风强弱不同配置及其对中国夏季降水的影响北大核心

利用NOAA向外长波辐射(OLR)、NCEP/NCAR再分析资料和CN05.1降水资料,研究了南亚和东亚热带夏季风强度年际变化关系,及其强弱不同配置对中国夏季降水的影响。结果表明:南亚和东亚热带夏季风强度变化之间存在同相和反相两种配置,定义的强度同相和反相变化指数可以很好地表征该关系。同相变化模态可能与海温异常时的强El Nino(La Nina)影响有关,其反相变化模态受El Nino(La Nina)以及印度洋海盆一致模的影响,同时西太平洋副热带高压和伊朗高压位置东西偏移和强度变化也影响着不同配置的出现。两者不同配置时,对中国夏季降水的影响不同。当变化呈同相偏强时,夏季中国东部地区降水为“中间少南北多”的雨型。当变化呈反相,东亚热带夏季风偏强南亚夏季风偏弱时,夏季中国东部地区降水为“一致偏少”雨型。     

A comparison of regional monsoon variability using monsoon indices

The present study aims to (a) examine meteorological basis for construction of regional monsoon indices and (b) explore the commonality and differences among tropical regional monsoons, especially the teleconnection and monsoon–ENSO relationship. We show that the area-averaged summer precipitation intensity is generally a meaningful precipitation index for tropical monsoons because it represents very well both the amplitude of annual cycle and the leading mode of year-to-year rainfall variability with a nearly uniform spatial pattern. The regional monsoon circulation indices can be defined in a unified way (measuring monsoon trough vorticity) for seven tropical monsoon regions, viz.: Indian, Australian, western North Pacific, North and South American, and Northern and Southern African monsoons. The structures of the tropical monsoons are commonly characterized by a pair of upper-level double anticyclones residing in the subtropics of both hemispheres; notably the winter hemispheric anticyclone has a barotropic structure and is a passive response. Two types of upper-level teleconnection patterns are identified. One is a zonal wave train emanating from the double anticyclones downstream along the westerly jets in both hemispheres, including Indian, Northern African and Australian monsoons; the other is a meridional wave train emanating from the double anticyclones polewards, such as the South American and western North Pacific monsoons. Over the past 55 years all regional summer monsoons have non-stationary relationship with ENSO except the Australian monsoon. The regional monsoon–ENSO relationship is found to have common changing points in 1970s. The relationships were enhanced for the western North Pacific, Northern African, North American and South American summer monsoons, but weakened for the Indian summer monsoon (with a recovery in late 1990s). Regardless the large regional differences, the monsoon precipitations over land areas of all tropical monsoon regions are significantly correlated with the ENSO, suggesting that ENSO drives global tropical monsoon rainfall variability. These results provide useful guidance for monitoring sub-seasonal to seasonal variations of the regional monsoons currently done at NCEP and for assessment of the climate models’ performances in representing regional and global monsoon variability.     

Factors controlling January�CApril rainfall over southern India and Sri Lanka

Most of the annual rainfall over India occurs during the Southwest (June?CSeptember) and Northeast (October?CDecember) monsoon periods. In March 2008, however, Southern peninsular India and Sri Lanka received the largest rainfall anomaly on record since 1979, with amplitude comparable to summer-monsoon interannual anomalies. This anomalous rainfall appeared to be modulated at intraseasonal timescale by the Madden Julian Oscillation, and was synchronous with a decaying La Ni?a event in the Pacific Ocean. Was this a coincidence or indicative of a teleconnection pattern? In this paper, we explore factors controlling rainfall over southern India and Sri Lanka between January and April, i.e. outside of the southwest and northeast monsoons. This period accounts for 20% of annual precipitation over Sri Lanka and 10% over the southern Indian states of Kerala and Tamil Nadu. Interannual variability is strong (about 40% of the January?CApril climatology). Intraseasonal rainfall anomalies over southern India and Sri Lanka are significantly associated with equatorial eastward propagation, characteristic of the Madden Julian Oscillation. At the interannual timescale, we find a clear connection with El Ni?o-Southern Oscillation (ENSO); with El Ni?os being associated with decreased rainfall (correlation of ?0.46 significant at the 98% level). There is also a significant link with local SST anomalies over the Indian Ocean, and in particular with the inter-hemispheric sea surface temperature (SST) gradient over the Indian Ocean (with colder SST south of the equator being conducive to more rainfall, correlation of 0.55 significant at the 99% level). La Ni?as/cold SSTs south of the equator tend to have a larger impact than El Ni?os. We discuss two possible mechanisms that could explain these statistical relationships: (1) subsidence over southern India remotely forced by Pacific SST anomalies; (2) impact of ENSO-forced regional Indian Ocean SST anomalies on convection. However, the length of the observational record does not allow distinguishing between these two mechanisms in a statistically significant manner.     

关于亚洲夏季风爆发的动力学研究的若干近期进展

资料分析显示,与850 hPa风场相比,地面风的变化能更好地表征亚洲各季风系统的特征。基于地面风的季节性反转和降水的显著变化所构建的亚洲夏季风(ASM)爆发指数和等时线图表明:亚洲热带夏季风(TASM)在5月初首先在孟加拉湾(BOB)东南部爆发后不是向西传播,而是向东经中印半岛向东推进,于5月中到达中国南海(SCS),6月初到达热带西北太平洋。印度夏季风的表面低压系统源于近赤道阿拉伯海地区,于6月初到达印度西南部喀拉拉邦,印度夏季风随之爆发。亚洲副热带夏季风(STASM)5月初在西北太平洋日本本州东南的海区发生后向西南伸展,于6月初与南海季风降水区连接,形成东北—西南向雨带,夏季风在中国东南沿海登陆,日本的“梅雨”(Baiu)开始。6月中该雨带向北到达长江流域和韩国,江淮梅雨和韩国的“梅雨”(Changma) 开始。本文还回顾了亚洲热带夏季风爆发的动力学研究的若干近期进展。春季青藏高原和南亚海陆分布的联合强迫作用使海表温度(SST)在BOB中东部形成短暂但强盛的暖池,在高层南亚高压的抽吸作用下,常伴有季风爆发涡旋(MOV)发展,使冬季连续带状的副高脊线在孟加拉湾东部断裂,导致亚洲热带季风首先在BOB爆发。BOB东/西部有东/西风型垂直切变,利于激发/抑制对流活动,并增加/减少海洋向大气的表面感热加热,从而使得亚洲夏季风爆发的向西传播在BOB西海岸遇到屏障。季风爆发逐渐向东伸展引发南海和热带西太平洋夏季风相继爆发。季风降水释放的强大潜热使南亚高压发展西伸,纬向非对称位涡强迫显著增强;在阿拉伯半岛强烈的表面感热加热所诱发的中层阿拉伯反气旋的共同作用下,位于阿拉伯海近赤道的低压系统北移发展成为季风爆发涡旋,导致印度季风爆发。由此可见,历时约一个月的亚洲热带夏季风爆发的三个阶段(孟加拉湾、南海和印度季风爆发)是发生在特定的地理环境下受特定的动力—热力学规律驱动的接续过程。     

春季热带南大西洋海表温度异常与夏季亚澳季风区降水异常的联系

利用1979—2019年Hadley中心的海表温度资料、GPCP的降水资料以及NCEP-DOE的再分析资料等,分析了北半球春季热带南大西洋海表温度异常与北半球夏季亚澳季风区降水异常的联系。研究表明,北半球春季热带南大西洋海表温度异常与随后夏季热带西太平洋到南海（澳大利亚东侧海域到热带东印度洋）地区的降水异常为显著负相关（正相关）关系。北半球春季热带南大西洋的海表温度正异常可以引起热带大西洋和热带太平洋间的异常垂直环流,其中异常上升支（下沉支）位于热带大西洋（热带中太平洋）。热带中太平洋的异常下沉气流和低层辐散气流引起热带中西太平洋低层的异常东风,后者有利于热带中东太平洋海表温度出现负异常。通过Bjerknes正反馈机制,热带中东太平洋海表温度异常从北半球春季到夏季得到发展。热带中东太平洋海表温度负异常激发的Rossby波使得北半球夏季热带西太平洋低层出现一对异常反气旋。此时,850 hPa上热带西太平洋到海洋性大陆地区为显著的异常东风,有利于热带西太平洋到南海（澳大利亚东侧海域到热带东印度洋）地区出现异常的水汽辐散（辐合）,导致该地区降水减少（增加）。     

Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction’s (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS’s hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50°E–110°E and 10°S–35°N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon Rainfall (AISMR; only the land stations of India during JJAS), the predicted mean AISMR with March, April and May initial conditions is found to be well correlated with actual AISMR and is found to provide skillful prediction. Thus, the calibrated CFS forecast could be used as a better tool for the real time prediction of AISMR.     

TROPICAL SEA SURFACE TEMPERATURE ANOMALY AND INDIAN SUMMER MONSOON*

The time series of the sea surface temperature(SST) anomaly,covering the eastern (western) equatorial Pacific,central Indian Ocean,Arabian Sea.Bay of Bengal and South China Sea(SCS),have been analyzed by using wavelet transform.Results show that there exists same interdeeadal variability of SST in the tropical Pacific and tropical Indian Ocean,and also show that the last decadal abrupt change occurred in the 1970s.On the interannual time scale,there is a similar interannual variability among the equatorial central Indian Ocean and the adjacent three sea basins(Arabian Sea.Bay of Bengal and South China Sea).but the SST interannual changes of the Indian Ocean lagged 4-5 months behind that of the equatorial central-east Pacific.Meanwhile,the interannual variability and long-range change between SST anomaly and Indian summer monsoon rainfall in recent decades have been explained and analyzed.It indicates that there existed a wet(dry) period in India when the tropical SST was lower(higher)than normal,but there was a lag of phase between them.     

1991～1994年El Niño的异常特征的诊断研究

1991～1994年热带中东太平洋海温持续4a多出现正距平。Niño3指数一直为正值。在此正距平背景下,产生了两次振荡和3次ElNiño暖期。在此期间赤道东太平洋海温在±5°纬度范围内发生了两次负距平的变化,形成了一个狭窄的温度梯度很大的“冷核”,而赤道外的中纬度海洋则持续维持两个正海温距平。这一时期海表温度资料EOF分析的结果进一步表明,第一特征向量的空间分布实际上反映了上述冷核特征。1991～1994年的ENSO事件主要是低频分量发生了较大异常,赤道低层纬向风和高层西风在前期减弱(1991-01-1992-05),后期加强(1992-06-1994-011).无论是海温还是风场的低频分量都表现出一次ENSO循环的特征。因此作者认为,虽然Niño3指数等在这4a多期间均为正值,但是大气和海洋耦合系统的低频变化部分只发生了一次完整的ENSO循环过程。1991年至1992年上半年对应于ElNiño暖位相,1992年下半年至1994年底对应于LaNina冷位相。但是这个冷位相没有能够得到充分发展,只出现两次极狭窄的冷核。冷位相的明显“夭折”,而代之以出现两次较弱的增暖,可能与季节内尺度的大气强迫与低频变化部分的相互作用有关。     

海温异常对东亚夏季风强度先兆信号的影响

利用ERA-Interim再分析资料、NOAA海温资料、CMAP格点降水资料和中国气象站降水资料,通过合成、相关和回归分析等方法研究了1979—2012年东亚夏季风强度与其先兆信号的关系,并分析了热带海温异常的可能影响。研究表明:东亚夏季风先兆指数反映了2月200 hPa纬向风距平的主要模态特征 (EOF1),前冬热带中东太平洋海温偏低 (高),2月亚洲地区西风急流位置偏北 (偏南),东亚夏季风先兆指数偏强 (弱)。前期热带海温异常对东亚夏季风强度有明显影响,前冬热带中东太平洋海温偏低 (高) 有利于东亚夏季风偏强 (弱)。2月亚洲中纬度地区纬向风异常特征在春季不能持续,先兆信号与东亚夏季风强度的联系主要源自热带海洋。