The interannual variability of the sea surface temperature （SST） in the South China Sea （SCS） is investigated according to its relationship with E1 Nifio/La Nifia （EN/LN） using monthly products from ICOADS. The SCS SST bears two peaks associated with EN/LN and shows the asymmetric features. Coinciding with the mature phase of EN/LN, the first SST warming/cooling peaks in December（0）-February（1） （DJF（1）） and centers in the southern part. The major difference is in the amplitude associated with the strength of EN/LN. However, the SCS SST anomaly shows distinct difference after the mature phase of EN/LN. The EN SST warm- ing develops a mid-summer peak in June-August（1） （JJA（1）） and persists up to September-October（l）, with the same amplitude of the first warming peak. Whereas the LN SST cooling peaks in May（l）, it decays slowly until the end of the year, with amplitude much weaker. Comparing with SST and atmospheric circulations, the weak response and early termination of the second cooling is due to the failure of the cyclonic wind anomalies to develop in the northwest Pacific during JJA（1）.
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-northeast 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 E1 Nino 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 tropical Indian Ocean （TIO） displays a uniform basin-wide warming or cooling in sea surface temperature （SST） during the decay year of E1 Nifio-Southern Oscillation （ENSO） events. This warming or cooling is called the tropical Indian Ocean Basin Mode （IOBM）. Recent studies showed that the IOBM dominates the interannual variability of the TIO SST and has impacts on the tropical climate from the TIO to the western Pacific. Analyses on a 148-year-long monthly coral δ28O record from the Seychelles Islands demonstrate that the Seychelles coral δ18O not only is associated with the local SST but also indicates the interannul variability of the basin-wide SST in the TIO. Moreover, the Seychelles coral δ180 shows a dominant period of 3-7 years that well represents the variability of the IOBM, which in return is modulated by the inter-decadal climate variability The correlation between the Seychelles coral dlSO and the SST reveals that the coral δ18O lags the SST in the eastern equato- rial Pacific by five months and reaches its peak in the spring following the mature phase of ENSO. The spatial pattern of the first EOF mode indicates that the Seychelles Islands are located at the crucial place of the IOBM. Thus, the Seychelles coral δ80 could be used as a proxy of the IOBM to investigate the ENSO teleconnection on the TIO in terms of long-time climate variability.
Isopycnal analyses were performed on the Global Ocean Data Assimilation System （GODAS） to determine the oceanic processes leading to so-called second-year cooling of the La Nina event.In 2010-12,a horseshoe-like pattern was seen,connecting negative temperature anomalies off and on the Equator,with a dominant influence from the South Pacific.During the 2010 La Nina event,warm waters piled up at subsurface depths in the western tropical Pacific.Beginning in early 2011,these warm subsurface anomalies propagated along the Equator toward the eastern basin,acting to reverse the sign of sea surface temperature （SST） anomalies （SSTAs） there and initiate a warm SSTA.However,throughout early 2011,pronounced negative anomalies persisted off the Equator in the subsurface depths of the South Pacific.As isopycnal surfaces outcropped in the central equatorial Pacific,negative anomalies from the subsurface spread upward along with mean circulation pathways,naturally initializing a cold SSTA.In the summer,a cold SSTA reappeared in the central basin,which subsequently strengthened due to the off-equatorial effects mostly in the South Pacific.These SSTAs acted to initiate local coupled air-sea interactions,generating atmospheric-oceanic anomalies that developed and evolved with the second-year cooling in the fall of 2011.However,the cooling tendency in mid-2012 did not develop into another La Nina event,since the cold anomalies in the South Pacific were not strong enough.An analysis of the 2007-09 La Nina event revealed similar processes to the 2010-12 La Nina event.
The relationship between ENSO and Indian Ocean Dipole was discussed by using the data set of sea temperature from Scripps Institute of Oceanography, the air temperature at 1000hPa from the NCEP reanalysis data and the Nino3 index from the Climate Prediction Center （CPC） of U.S.A. during the period from 1955 to 2001. The results show that there exists a Dipole on the maximum temperature anomalous level （MTAL） in the Indian Ocean, which close relates to ENSO in the Pacific Ocean. During El Nino periods there are good relationships between ENSO and Indian Ocean Dipole which maximum correlation occurring when ENSO leads by one month, but in La Nina periods the relationship is not so good. The distribution of Dipole in Indian Ocean is from northeast to southwest, which one （west） pole in 65°E - 75°E, 6°S - 10°S and the other in 85°E - 95°E, 2°N - 6°N, which is different from that defined by Saij. The correlation coefficients of Nino3 index with temperature anomalies in the west/east poles on the MTAL are over 0.4 - 0.15, respectively. It is a main sea temperature system in the tropical Indian Ocean. However, in the surface layer from sea surface to the depth of 20 m - 30 m there is no such a dipole with opposite sea temperature anomalies in the NE and SW of tropical Indian Ocean. The SSTA in the NE might be influenced by the sensible exchange process because the evolution of sea and 1 000 hPa air temperature anomaly time series of the NE of tropical Indian Ocean is quite similar except those during 1962 - 1963 and 1986. The periods of Indian Ocean Dipole are shorter than that of ENSO, and about 1 to 6-year.
Based on the merged satellite altimeter data and in-situ observations, as well as a diagnosis of linear baroclinic Rossby wave solutions, this study analyzed the rapidly rise of sea level/sea surface height （SSH） in the tropical Pacific and Indian Oceans during recent two decades. Results show that the sea level rise signals in the tropical west Pacific and the southeast Indian Ocean are closely linked to each other through the pathways of oceanic waveguide within the Indonesian Seas in the form of thermocline adjustment. The sea level changes in the southeast Indian Ocean are strongly influenced by the low-frequency westward-propagating waves originated in the tropical Pacific, whereas those in the southwest Indian Ocean respond mainly to the local wind forcing. Analyses of the lead-lag correlation further reveal the different origins of interannual and interdecadal variabilities in the tropical Pacific. The interannual wave signals are dominated by the wind variability along the equatorial Pa- cific, which is associated with the El Nifio-Southern Oscillation; whereas the interdecadal signals are driven mainly by the wind curl off the equatorial Pacific, which is closely related to the Pacific Decadal Oscillation.
