亞洲季風區內之季內振盪（ISO）變化與亞洲夏季季風之肇始、活躍以及停歇有密切關係。南海季內振盪活動與台灣西部地區豪（大）雨具高度相關性，因此若能了解及預報南海地區30～60天對流振盪之移行與結構，則有助於台灣西部地區之豪（大）雨預報。本研究之目的即在利用各種多重模式系集迴歸分析，以有效提升亞洲季風區內30～60天季內振盪活動之預報能力。
本研究採用的模式資料出自大氣模式比對計畫(Atmospheric Model Intercomparison Project,AMIP)，分別為DNM、ECHAM、JMA、NCAR、NTU以及PNNL模式。觀測資料則為CDC（Climate Diagnostic Center）所分析之每日外逸長波輻射場（Outgoing Longwave Radiation，OLR）。資料濾波採取基底函數具有正交函數特性之小波轉換（Wavelet Transform）。模式的評量方式則透過均方誤差（RMSE）、空間相關係數（Pattern Correlation Coefficent）以及誤差變異量評鑑（Error Variance Skill Score）等三種統計方法呈現。分析結果發現，除DNM模式外其餘模式均能有效掌握亞洲季風區內30～60天季內振盪氣候變化情形（空間相關係數均在0.4以上），但對於30～60天季內振盪各年變化預報則無法超越模擬氣候變化時之水準。多重模式超系集迴歸預報（Multimodel Superensemble Forecast），在訓練時期（training period）之表現均優於任何單一模式或多重模式系集預報，但在預報時期（forecast period）則不然。本研究將多重模式系集平均(ensemble mean)應用於迴歸改進之單一模式，在預報時期，其模擬亞洲季風區內30～60天季內振盪之各年變化為最佳，然其預報結果僅略優於氣候預報。

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