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用主振荡型（ Ｐ Ｏ Ｐ）方法分析了热带洋区月平均海表温度异常（ Ｓ Ｓ Ｔ Ａ）。结果表明，最重要的 ４ 个传播型 Ｐ Ｏ Ｐ对与 Ｅｌ Ｎｉｎｏ／ Ｌａ Ｎｉｎａ 事件关系密切，说明这类事件具有复杂的时空结构。在此基础上，给出了一个能定量地综合多个传播型 Ｐ Ｏ Ｐ对作用的 Ｐ Ｏ Ｐ中性预测方案。非独立样本和独立样本试验表明，它具有 ４ 个月的预测时效，且其预测能力在 Ｓ Ｓ Ｔ 强异常的 Ｅｌ Ｎｉｎｏ、 Ｌａ Ｎｉｎａ 事件阶段强于弱异常的非 Ｅｌ Ｎｉｎｏ／ Ｌａ Ｎｉｎａ 事件阶段。
The main monthly oscillation (P O P) method is used to analyze the monthly mean SSTA over the tropical ocean. The results show that the four most important P P P pairs are closely related to the El Nino / La Nina events, indicating that these events have complex temporal and spatial structures. On this basis, a P O P neutral prediction scheme that can quantitatively synthesize multiple propagating P O P pairs is given. Non-independent samples and independent sample tests show that it has a predicted aging time of 4 months and its prediction ability is stronger than that of the weak anomalous non-El Nino / La Nina events in El Nino and La Nina events with strong S S T anomalies.