The sea surface temperature （SST） in the In- dian Ocean affects the regional climate over the Asian continent mostly through a modulation of the monsoon system. It is still difficult to provide an a priori indication of the seasonal variability over the Indian Ocean. It is widely recognized that the warm and cold events of SST over the tropical Indian Ocean are strongly linked to those of the equatorial eastern Pacific. In this study, a statistical prediction model has been developed to predict the monthly SST over the tropical Indian Ocean. This model is a linear regression model based on the lag relationship between the SST over the tropical Indian Ocean and the Nino3.4 （5°S-5°N, 170°W-120°W） SST Index. The pre- dictor （i.e., Nino3.4 SST Index） has been operationally predicted by a large size ensemble E1 Nifio and the Southern Oscillation （ENSO） forecast system with cou- pled data assimilation （Leefs_CDA）, which achieves a high predictive skill of up to a 24-month lead time for the equatorial eastern Pacific SST. As a result, the prediction skill of the present statistical model over the tropical In- dian Ocean is better than that of persistence prediction for January 1982 through December 2009.
ABSTRACT In this paper, interannual variations in the barrier layer thickness （BLT） are analyzed using Argo three-dimensional temperature and salinity data, with a locus on the effects of interannually varying salinity on the evolution of the El Nifio Southern Oscillation （ENSO）. The interannually varying BLT exhibits a zonal seesaw pattern across the equatorial Pacific during ENSO cycles. This phenomenon has been attributed to two different physical processes. During E1 Nifio （La Nifia）, the barrier layer （BL） is anomalously thin （thick） west of about 160°E, and thick （thin） to the east. In the western equatorial Pacific （the western part： 130°-160°E）, interannual variations of the BLT indicate a lead of one year relative to those of the ENSO onset. The interannual variations of the BLT can be largely attributed to the interannual temperature variability, through its dominant effect on the isothermal layer depth （ILD）. However, in the central equatorial Pacific （the eastern part： 160~E- 170~W）, interannual variations of the BL almost synchronously vary with ENSO, with a lead of about two months relative to those of the local SST. In this region, the interannual variations of the BL are significantly affected by the interannually varying salinity, mainly through its modulation effect on the mixed layer depth （MLD）. As evaluated by a onedimensional boundary layer ocean model, the BL around the dateline induced by interannual salinity anomalies can significantly affect the temperature fields in the upper ocean, indicating a positive feedback that acts to enhance ENSO.
The accurate simulation of the equatorial sea surlhce temperature （SST） variability is crucial for a proper representation or prediction of the El Nino-Southern Os- cillation （ENSO）. This paper describes the tropical variability simulated by the Max Planck Institute （MPI） forr meteorology coupled atmosphere-ocean general circulation model （CGCM）. A control simulation with pre-industrial greenhouse gases is analyzed, and the simulation of key oceanic features, such as SST, is compared with observa- tions. Results from the 400-yr control simulation show that the model＇s ENSO variability is quite realistic in terms of structure, strength, and period. Also, two related features （the annual cycle of SST and the-phase locking of ENSO events）, which are significant in determining the model＇s performance of realistic ENSO prediction, are further validated to be well reproduced by the MPI cli mate model, which is an atmospheric model ECHAM5 （which fuses the EC tbr European Center and HAM for Hamburg） coupled to an MPI ocean model （MPI-OM）, ECHAMS/MPI-OM.
El Nio events in the central equatorial Pacific (CP) are gaining increased attention,due to their increasing intensity within the global warming context.Various physical processes have been identified in the climate system that can be responsible for the modulation of El Nio,especially the effects of interannual salinity variability.In this work,a comprehensive data analysis is performed to illustrate the effects of interannual salinity variability using surface and subsurface salinity fields from the Met Office ENSEMBLES (EN3) quality controlled ocean dataset.It is demonstrated that during the developing phase of an El Nio event,a negative sea surface salinity (SSS) anomaly in the western-central basin acts to freshen the mixed layer (ML),decrease oceanic density in the upper ocean,and stabilize the upper layers.These related oceanic processes tend to reduce the vertical mixing and entrainment of subsurface water at the base of the ML,which further enhances the warm sea surface temperature (SST) anomalies associated with the El Nio event.However,the effects of interannually variable salinity are much more significant during the CP-El Nio than during the eastern Pacific (EP) El Nio,indicating that the salinity effect might be an important contributor to the development of CP-El Nio events.
ZHENG Fei 1,WAN Li-Ying 2,and WANG Hui 3 1 International Center for Climate and Environment Science (ICCES),Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China 2 Key Laboratory of Research on Marine Hazards Forecasting,National Marine Environmental Forecasting Center,Beijing 100081,China 3 National Meteorological Center,Beijing 100081,China
Collaboration of interannual variabilities and the climate mean state determines the type of E1 Nifio. Recent studies highlight the impact of a La Nifia-like mean state change, which acts to suppress the convection and low-level convergence over the central Pacific, on the predominance of central Pacific （CP） E1 Nifio in the most recent decade. However, how interannual variabilities affect the climate mean state has been less thoroughly investigated. Using a linear shallow-water model, the ef- fect of decadal changes of air-sea interaction on the two types of El Nifio and the climate mean state over the tropical Pacific is examined. It is demonstrated that the predominance of the eastem Pacific （EP） and CP E1 Nino is dominated mainly by relationships between anomalous wind stresses and sea surface temperature （SST）. Furthermore, changes between air-sea interactions from 1980-98 to 1999-2011 prompted the generation of the La Ninalike pattern, which is similar to the background change in the most recent decade.
Based on Global Ocean Data Assimilation System （GODAS） and NCEP reanalysis data, atmospheric and oceanic pro- cesses possibly responsible for the onset of the 2011/12 La Nifia event, which followed the 2010/11 La Nifia even--referred to as a ＂double dip＂ La Nifia--are investigated. The key mechanisms involved in activating the 2011/12 La Nifia are illus- trated by these datasets. Results show that neutral conditions were already evident in the equatorial eastern Pacific during the decaying phase of the 2010/11 La Nifia. However, isothermal analyses show obviously cold water still persisting at the surface and at subsurface depths in off-equatorial regions throughout early 2011, being most pronounced in the tropical South Pacific. The negative SST anomalies in the tropical South Pacific acted to strengthen a southern wind across the equator. The subsurface cold water in the tropical South Pacific then spread northward and broke into the equatorial region at the thermo- cline depth. This incursion process of off-equatorial subsurface cold water successfully interrupted the eastern propagation of warm water along the equator, which had previously accumulated at subsurface depths in the warm pool during the 2010/11 La Nifia event. Furthermore, the incursion process strengthened as a result of the off-equatorial effects, mostly in the tropical South Pacific. The negative SST anomalies then reappeared in the central basin in summer 2011, and acted to trigger local coupled air-sea interactions to produce atmospheric-oceanic anomalies that developed and evolved with the second cooling in the fall of 2011.
Weather and climate in East China are closely related to the variability of the western Pacific subtropical high(WPSH), which is an important part of the Asian monsoon system. The WPSH prediction in spring and summer is a critical component of rainfall forecasting during the summer flood season in China. Although many attempts have been made to predict WPSH variability, its predictability remains limited in practice due to the complexity of the WPSH evolution. Many studies have indicated that the sea surface temperature(SST) over the tropical Indian Ocean has a significant effect on WPSH variability. In this paper, a statistical model is developed to forecast the monthly variation in the WPSH during the spring and summer seasons on the basis of its relationship with SST over the tropical Indian Ocean. The forecasted SST over the tropical Indian Ocean is the predictor in this model, which differs significantly from other WPSH prediction methods. A 26-year independent hindcast experiment from 1983 to 2008 is conducted and validated in which the WPSH prediction driven by the combined forecasted SST is compared with that driven by the persisted SST. Results indicate that the skill score of the WPSH prediction driven by the combined forecasted SST is substantial.
