对ENSO模拟和预测的研究以往大多数着眼于ENSO演变过程中温度场的变化和作用。近年来随着新的盐度观测资料（Argo和盐度卫星）出现，海洋盐度作为直接影响海洋层结状况的另一个重要物理量，其对ENSO的影响和作用也在逐步得到认识和重视。与此同时，目前大多数气候模式对海洋上层盐度的变化仍存在着明显偏差。因此，本研究将在一个已发展的大气所ENSO集合预测系统基础上（该系统基于一个中等复杂程度海气耦合模式，但缺乏盐度物理过程），进一步地发展该系统的盐度分量模型，实现热带太平洋盐度变化对ENSO演变的影响。同时发展“耦合”同化方法将盐度观测信息进一步协调地同化到系统中，改进预测系统的初始场，提高ENSO预测水平。研究的创新点在于：（1）研究发展的盐度分量模型将在中等复杂程度耦合模式中实现盐度变化对ENSO模拟和预测的影响，（2）这将是盐度新观测在ENSO预测初始化中的新应用。

Previous works on ENSO simulation and forecast mainly focused on the effects and variations of temperature during the ENSO evolution. With the appearance of new salinity observations (Argo and salinity satellite) in recent years, salinity, as another importance physical variable on affecting the oceanic verification, its effects on ENSO have been getting more and more attentions. At the same time, most present climate models still have significant biases on simulating the salinity changes in the upper ocean. Therefore, this study aims to develop a component model of salinity over the tropical Pacific for a developed ENSO ensemble prediction system at IAP, which basic model is an intermediate coupled model, but lacking of salinity process. Then the study will develop a coupled initialization (assimilation) method of new salinity observations on improving the initial condition for ENSO prediction. The innovation of the proposal is the development of the salinity component model into the intermediate coupled model will help to actualize the effects of salinity variations on ENSO simulation and prediction, and this study will be the new application of salinity observations on ENSO initialization and prediction.