资源环境科技发展态势分析平台

Sea surface temperature anomalies (SSTAs), including their spatial patterns and temporal evolution, are an important source of potential predictability for climate anomalies, especially on seasonal to interannual timescales. In this study, the spatial patterns and temporal evolution of tropical SSTAs are identified by applying an extended empirical orthogonal function (EEOF) analysis of observed data from autumn to the following spring. The positive phase of first EEOF mode (EEOF1) displays an El Nino-Southern Oscillation (ENSO) phase-locking evolution pattern in the tropical Pacific, with accompanying warming in the Indian and Atlantic oceans. EEOF2 is characterized by the development of ENSO in the eastern tropical Pacific and a phase transition in the Indian Ocean and the tropical North Atlantic. The most noticeable feature of EEOF3 is the development of the central Pacific ENSO. The first three EEOF modes account for 44.7% of the total variance of tropical SSTAs over the course of the three seasons. EEOF1 is closely related to the tropical atmospheric circulation, especially over the western Pacific region, reflecting the strengthening effect of the three tropical oceans on the anomalous anticyclone over the tropical Northwest Pacific during the decaying phases of El Nino. EEOF2 significantly impacts the circulation anomalies over the Indian Ocean and western Pacific. A linear regression model is established using the time series of first four EEOF modes to forecast the June to August 500 hPa geopotential height anomalies. The forecasts show higher skill than a similar linear regression model using seasonal mean regional SST anomaly indices. The results reveal that EEOF modes could be used as a good indicator in the monitoring of tropical SSTA evolution patterns.