Variations in the eastern Indian Ocean warm pool and its relation to the dipole in the tropical Indian Ocean

Based on the monthly average SST and 850 hPa monthly average wind data,the seasonal,interannual and long-term variations in the eastern Indian Ocean warm pool(EIWP) and its relationship to the Indian Ocean Dipole(IOD),and its response to the wind over the Indian Ocean are analyzed in this study.The results show that the distribution range,boundary and area of the EIWP exhibited obviously seasonal and interannual variations associated with the ENSO cycles.Further analysis suggests that the EIWP had obvious l...     

The role of barrier layer in southeastern Arabian Sea during the development of positive Indian Ocean Dipole events

Using data from Argo and simple ocean data assimilation (SODA), the role of the barrier layer (BL) in the southeastern Arabian Sea (SEAS: 60°E–75°E, 0°–10°N) is investigated during the development of positive Indian Ocean Dipole (IOD) events from 1960 to 2008. It is found that warmer sea surface temperature (SST) in the northern Indian Ocean appears in June in the SEAS. This warm SST accompanying anomalous southeastern wind persists for six months and a thicker BL and a corresponding thinner mixed layer in the SEAS contribute to the SST warming during the IOD formation period. The excessive precipitation during this period helps to form a thicker BL and a thinner mixed layer, resulting in a higher SST in the SEAS. Warm SST in the SEAS and cold SST to the southeast of the SEAS intensify the southeasterly anomaly in the tropical Indian Ocean, which transports more moisture to the SEAS, and then induces more precipitation there. The ocean-atmosphere interaction process among wind, precipitation, BL and SST is very important for the anomalous warming in the SEAS during the development of positive IOD events.     

Characteristics of change of the SST in the tropical western Pacific and the tropical Indian Ocean and its response to the change of the Antarctic ice area

In this paper, by using ocean surface temperature data (COADS), the study is made of the characteristics of the monthly and annual changes of the SST in the tropical western Pacific and Indian Oceans, which have important influences on the climate change of the whole globe and the relation between ENSO(E1 Nino-Southern Oscillation) and the Antarctic ice area is also discussed. The result indicates that in the tropical western Pacific and the Indian Oceans the change of Sea Surface Temperture (SST) is conspicuous both monthly and armaully, and shows different change tendency between them. This result may be due to different relation in the vibration period of SST between the two Oceans. The better corresponding relationship is obvious in the annual change of SST in the tropical Indian Ocean with the occurrence El Nino and LaNlra. The change of the SST in the tropical western Pacific and the tropical Indian Oceans has a close relation to the Antarctic ice area, especially to the ice areas in the eastern-south Pole and Ross Sea, and its notable correlative relationship appears in 16 months when the SST of the tropical western Pacific and the Indian Oceans lag back the Antarctic ice area.     

Modeling the hook depth distribution of pelagic longlining in the equatorial area of Indian Ocean

A survey was conducted in the equatorial area of Indian Ocean for a better understanding of the dynamics of hook depth distribution of pelagic longline fishery.We determined the relationship between hook depth and vertical shear of current coefficiency,wind speed,hook position code,sine of wind angle,sine of angle of attack and weight of messenger weight.We identified the hook depth models by the analysis of covariance with a general linear model.The results showed that the wind effect on the hook depth can be ignored from October to November in the survey area;the surface current effect on the hook depth can be ignored;the equatorial undercurrent is the key factor for the hook depth in Indian Ocean;and there is a negative correlation between the hook depth and vertical shear of current and angle of attack.It was also found that the deeper the hook was set,the higher hook depth shoaling was.The proposed model improves the accuracy of the prediction of hook depth,which can be used to estimate the vertical distribution of pelagic fish in water column.     

Indian Ocean Dipole response to global warming: A multi-member study with CCSM4

Based on a coupled ocean-atmosphere model, the response of the Indian Ocean Dipole (IOD) mode to global warming is investigated with a six member ensemble of simulations for the period 1850–2100. The model can simulate the IOD features realistically, including the east-west dipole pattern and the phase locking in boreal autumn. The ensemble analysis suppresses internal variability and isolates the radiative forced response. In response to increasing greenhouse gases, a weakening of the Walker circulation leads to the easterly wind anomalies in the equatorial Indian Ocean and the shoaling thermocline in the eastern equatorial Indian Ocean (EEIO), and sea surface temperature and precipitation changes show an IOD-like pattern in the equatorial Indian Ocean. Although the thermocline feedback intensifies with shoaling, the interannual variability of the IOD mode surprisingly weakens under global warming. The zonal wind feedback of IOD is found to weaken as well, due to decreased precipitation in the EEIO. Therefore, the atmospheric feedback decreases much more than the oceanic feedback increases, causing the decreased IOD variance in this model.     

A heat budget study on the mechanism of SST variations in the Indian ocean dipole regions

By using a new heat budget equation that is closely related to the sea surface temperature （SST） and a dataset from an ocean general circulation model （MOM2） with 10-a integration （1987-1996）, the relative importance of various processes determining SST variations in two regions of the Indian Ocean is compared. These regions are defined by the Indian Ocean Dipole Index and will be referred to hereafter as the eastern （0^＊-10^＊S, 90^＊-110^＊E） and western regions （10^＊S- 10^＊N, 50^＊-70^＊E）, respectively. It is shown that in each region there is a falling of SST in boreal summer and a rising in most months of other seasons, but the phases are quite different. In the eastern region, maximum cooling rate occurs in July, whereas in the western region it occurs in June with much larger magnitude. Maximum heating rate occurs in November in the eastern region, but in March in the western one. The western region exhibits another peak of increasing rate of SST in October, indicating a typical half-year period. Net surface heat flux and entrainment show roughly the same phases as the time-varying term, but the former has much larger contribution in most of a year, whereas the latter is important in the boreal summer. Horizontal advection, however, shows completely different seasonal variations as compared with any other terms in the heat budget equation. In the eastern region, it has a maximum in June/November and a minimum in March/ September, manifesting a half-year period; in the western region, it reaches the maximum in August and the minimum in November. Further investigation of the horizontal advection indicates that the zonal advection has almost the opposite sign to the meridional advection. In the eastern region, the zonal advection is negative with a peak in August, whereas the meridional one is positive with two peaks in June and October. In the western region, the zonal advection is negative from March to November with two peaks in June and November, whereas the meridional one is positive with one peak in July. Different phases can be clearly seen between the two regions for each component of the horizontal advection. A detailed analysis of the data of 1994, a year identified when the Indian Ocean dipole event happened, indicates that the horizontal advection plays a dominant role in the remarkable cooling of the eastern region, in which zonal and meridional advections have the same sign of anomaly. However, in the western region in 1994 no any specialty was shown as compared with other years, for the SST anomaly is not positive in large part of this region. All these imply that the eastern and western regions may be related in a quite complex way and have many differences in dynamics. Further study is needed.     

印度洋dipole事件的年际变化与ENSO事件的联系

通过对nino3指数和DMI序列的分析,发现两种物理现象都有4 a左右的主要周期,而且印度洋偶极子事件还存在有2 a左右的振荡周期,而厄尔尼诺事件在2 a时间尺度上周期性不明显;对nino3指数和DMI进行年际时间尺度滤波,结果表明,在年际时间尺度上,两者的相关性比未滤波时有了一定的提高;对年际滤波之后的偶极子事件和ELNINO事件的相关分析可以发现,ELNINO对于印度洋偶极子事件的影响要大于IOD对于太平洋ENSO事件,显示了两者物理现象的影响不对称。     

印度洋dipole事件的年际变化与ENSO事件的联系

通过对nino3指数和DMI序列的分析，发现两种物理现象都有4a左右的主要周期，而且印度洋偶极子事件还存在有2a左右的振荡周期，而厄尔尼诺事件在2a时间尺度上周期性不明显；对nino3指数和DMI进行年际时间尺度滤波，结果表明，在年际时间尺度上，两者的相关性比未滤波时有了一定的提高；对年际滤波之后的偶极子事件和ELNINO事件的相关分析可以发现，ELNINO对于印度洋偶极子事件的影响要大于IOD对于太平洋ENSO事件，显示了两者物理现象的影响不对称。     

夏冬季热带太平洋、印度洋海表温度年际异常的年代际变化

用Nino 3指数、印度洋单极指数、偶极子指数描述热带太平洋、印度洋海表温度 (SST)的年际异常 ,季节分析表明 :冬季Nino3区与热带印度洋海表温度距平 (SSTA)相互关系表现为单极 ,且 1976年以后两者的相互关系减弱 ,其可能原因 :一是冬季是ENSO(厄尔尼诺 )事件的盛期 ;二是冬季西太平洋暖水区东移 ,造成两洋的垂直纬向环流耦合减弱。夏季两者相互关系表现为偶极 ,1976年以后两者的相互关系加强 ,其可能原因 ,一是夏季是偶极子盛期 ,ENSO事件的发展期 ;二是夏季西太平洋暖水区虽然东移 ,但暖水区位置偏北 ,且东南印度洋的上升支强度增大 ,造成两洋的纬向环流耦合更强烈     

Southern ocean SST variability and its relationship with ENSO on inter-decadal time scales

Empirical orthogonal function (EOF) analysis reveals a co-variability of Sea surface temperatures (SSTs) in the Southern Hemisphere (0°-60°S). In the South Indian and Atlantic Oceans, there is a subtropical dipole pattern slanted in the southwest- north-east direction. In the South Pacific Ocean, a meridional tripole structure emerges, whose middle pole co-varies with the dipoles in the South Indian and Atlantic Oceans and is used in this study to track subtropical Pacific variability. The South Indian and Atlantic Ocean dipoles and the subtropical Pacific variability are phase-locked in austral summer. On the inter-decadal time scales, the dipoles in the South Indian and Atlantic Oceans weaken in amplitude after 1979/1980. No such weakening is found in the subtropical South Pacific Ocean. Interestingly, despite the reduced amplitude, the correlation of the Indian Ocean and Atlantic dipoles with El Nio and Southern Oscillation (ENSO) are enhanced after 1979/1980. The same increase in correlation is found for subtropical South Pacific variability after 1979/1980. These inter-decadal modulations imply that the Southern Hemisphere participates in part of the climate shift in the late 1970s. The correlation between Southern Hemisphere SST and ENSO reduces after 2000.     

The distribution and variability of simulated chlorophyll concentration over the tropical Indian Ocean from five CMIP5 models

Performances of 5 models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating the chlorophyll concentration over the tropical Indian Ocean are evaluated. Results show that these models are able to capture the dominant spatial distribution of observed chlorophyll concentration and reproduce the maximum chlorophyll concentration over the western part of the Arabian Sea, around the tip of the Indian subcontinent, and in the southeast tropical Indian Ocean. The seasonal evolution of chlorophyll concentration over these regions is also reproduced with significant amplitude diversity among models. All of 5 models is able to simulate the interannual variability of chlorophyll concentration. The maximum interannual variation occurs at the same regions where the maximum climatological chlorophyll concentration is located. Further analysis also reveals that the Indian Ocean Dipole events have great impact on chlorophyll concentration in the tropical Indian Ocean. In the general successful simulation of chlorophyll concentration, most of the CMIP5 models present higher than normal chlorophyll concentration in the eastern equatorial Indian Ocean.     

Relationships of interannual variability between the equatorial pacific and tropical Indian Ocean in 17 CMIP5 models

Seventeen coupled general circulation models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are employed to assess the relationships of interannual variations of sea surface temperature (SST) between the tropical Pacific (TP) and tropical Indian Ocean (TIO). The eastern/central equatorial Pacific features the strongest SST interannual variability in the models except for the model CSIRO-Mk3-6-0, and the simulated maximum and minimum are produced by models GFDL-ESM2M and GISS-E2-H respectively. However, It remains a challenge for these models to simulate the correct climate mean SST with the warm pool-cold tongue structure in the equatorial Pacific. Almost all models reproduce El Niño-Southern Oscillation (ENSO), Indian Ocean Dipole mode (IOD) and Indian Ocean Basin-wide mode (IOB) together with their seasonal phase lock features being simulated; but the relationship between the ENSO and IOD is different for different models. Consistent with the observation, an Indian Ocean basin-wide warming (cooling) takes place over the tropical Indian Ocean in the spring following an El Niño (La Niña) in almost all the models. In some models (e.g., GFDL-ESM2G and MIROC5), positive ENSO and IOB events are stronger than the negative events as shown in the observation. However, this asymmetry is reversed in some other models (e.g., HadGEM2-CC and HadGEM2-ES).     

SST variations of the Kuroshio from AVHRR observation

1 INTRODUCTION The Kuroshio Current (KC), being the western boundary current in the North Pacific subtropical gyre, is the second strongest current in the world af- ter the Gulf Stream and is famous as a strong and fast flow. KC plays an important role in…     

Contrast between the climatic states of the warm pool in the Indian Ocean and in the Pacific Ocean

Based on the analysis of Levitus data, the climatic states of the warm pool in the Indian Ocean (WPIO) and in the Pacific Ocean (WPPO) are studied. it is found that WPIO has a relatively smaller area, a shallower bottom and a slightly lower seawater temperature than those of WPPO. The horizontal area at different depths, volumes, central positions, and bottom depths of both WPIO and WPPO show quite apparent signals of seasonal variation. The maximum amplitude of WPIO surface area’s seasonal variation is 58% larger over the annual mean value. WPIO’s maximum volume variation amplitude is 66% larger over the annual mean value. The maximum variation amplitudes of the surface area and volume of WPPO are 20.9% and 20.6% larger over the annual mean value respectively. WPIO and WPPO show different temporal and spatial characteristics mainly due to the different wind fields and restriction of ocean basin geometry. For instance, seasonal northern displacement of WPIO is, to some extent, constrained by the basin of the Indian Ocean, while WPPO moves relatively freely in the longitudinal direction. The influence of WPIO and WPPO over the atmospheric motion must be quite different.     

Influence of the Eastern Indian Ocean Warm Pool Variability on the Spring Precipitation in China

The relationship between the variability of the Eastern India Ocean Warm Pool （EIWP） and the spring precipitation in China is studied in the paper based on an analysis of the Simple Ocean Data Assimilation （SODA） Sea Surface Temperature （SST） data, the reanalysis data of monthly grid wind field at 925 hPa with a resolution of 2.5^＊ latitude and longitude from the National Center for Environmental Prediction/National Center for Atmospheric Research （NCEP/NCAR）, and the monthly mean rainfall data from 160 observational stations in China. The results show that there is a strong correlation between the EIWP variability and the spring precipitation in China. The area, volume and intensity indices of the EIWP are negatively correlated with the spring precipitation in southwestern China, while they are positively correlated with the spring precipitation in the rest of China, especially in the northeast. For this correlation between the EIWP variability and the spring precipitation in China, it is found that the correlative relationship is mainly connected with the variations of the moisture transport by the warm air flow, which is under the influence of the EIWP variability, into the inland of China in spring. Two causative factors may influence this transport. One is the variation of the moisture transport carried by the warm air flow from the Arabian Sea influenced by the EIWP variability. The other is the variation of the equator-crossing flow （70^＊-90^＊E） influenced by the EIWP anomaly in the previous winter which exerts its effect on the moist warm air transported from the Southern Hemisphere. The position and intensity of the Western North Pacific Subtropical High （WNPSH） variability caused by EIWP variation also influence the spring precipitation in China.     

Events of decadal thermocline variations in the South Pacific Ocean

1 INTRODUCTION It has been suggested that interior thermal anomalies that subduct into the subtropics of the North Pacific may propagate to the equatorial region of the Pacific (Russell, 1994; Deser et al., 1996; Gu and Philander, 1997; Huang and Huang an…     

Southern high latitude climate anomalies associated with the Indian Ocean dipole mode

1 INTRODUCTION In southern high latitudes, recent observations have shown a standing mode of ACW (Antarctic Circumpolar Wave) with eastward propagation across the Southern Ocean of the Antarctic in co- varying SST (sea surface temperature) and SLP (sea le…     

印度洋西北部海域鸢乌贼的触腕和腕足钓捕断裂强度

鱿鱼的腕足断裂强度是影响鱿钓脱钩率的重要因素。通过现场实测，分析了印度洋西北部海域鸢乌贼（Symplectoteuthis oualaniensis）的腕足断裂强度对手钓作业脱钩率产生的影响。结果表明，鸢乌贼的每根触腕仅能承受的拉力相当于体重的0．7倍，因此，钓捕过程中，因触腕断裂造成的脱钩率接近100％；而另外的第Ⅰ一Ⅳ腕足的断裂强度分别是其体重的2．30、2．05、2．06和1．87倍；5对腕足整体的平均脱钩率接近10％。     

印度洋西北部海域鸢乌贼的触腕和腕足钓捕断裂强度

鱿鱼的腕足断裂强度是影响鱿钓脱钩率的重要因素。通过现场实测,分析了印度洋西北部海域鸢乌贼(Symplectoteuthis oualaniensis)的腕足断裂强度对手钓作业脱钩率产生的影响。结果表明,鸢乌贼的每根触腕仅能承受的拉力相当于体重的0.7倍,因此,钓捕过程中,因触腕断裂造成的脱钩率接近100%;而另外的第I-IV腕足的断裂强度分别是其体重的2.30、2.05、2.06和1.87倍;5对腕足整体的平均脱钩率接近10%。     

多变量分位数回归构建印度洋大眼金枪鱼栖息地指数

以0～300m水层加权平均水温、50～150m水层的温差和氧差及其交互变量为影响因子,运用分位数回归法,寻找出环境变量与大眼金枪鱼(Thunnus obesus)延绳钓钓获率的最佳上界分位数回归方程,计算出栖息地指数(HSI),并应用地理信息系统(GIS)软件绘制各月HSI空间分布图。研究表明:大眼金枪鱼延绳钓钓获率(HR)依加权平均水温(x)、温差(y)、氧差(z)与的最佳上界分位数回归方程为HR0.70=-15.596+2.124x-0.003x3+0.033xyz-0.036y2z+0.107yz2-0.337z3;HSI空间分布为:16°S—10°N印度洋海域HSI高于0.7,HSI>0.8的海域随季节发生显著变化,马达加斯加外海至100°E、16°S—26°S海域常年存在一片HSI<0.4的区域,26°S—40°S海域的HSI介于0.4～0.5,40°S以南海域HSI<0.4,东非外海季节性地出现一片HSI<0.6的海域。利用多个环境变量的栖息地指数模型来预测分析大洋金枪鱼资源分布效果较好。