本研究採用18年海平面高度反演的地轉流進行研究，同時以一個先進的人工智慧類神經網路演算法－GHSOM為基礎，來對海流資料進行分類分析黑潮在呂宋海峽及台灣東北海域的入侵型態，並運用衛星風場及熱通量分析其相關性。
在呂宋海峽終年均有黑潮入侵現象，但係以不入侵為主，入侵型態僅佔總體的25.8%，其中以黑潮強入侵為主，以弱入侵較少，強入侵與風速相關，弱入侵則可能與上游的黑潮傳輸量相關。在季變化部分，冬季入侵多於夏季入侵，冬季入侵型態為強入侵與弱入侵均有，但以強入侵為主，夏季入侵則幾乎均為弱入侵。黑潮入侵在年際變化方面與PDO有關，黑潮入侵通常發生於PDO 指標為正值時（72.1%）。
台灣東北海域方面，黑潮入侵與不入侵約各半，但係以占57.4 % 的入侵模式為主，其中弱入侵發生較強入侵為多，強入侵與熱通量相關，而弱入侵與風速及熱通量均相關。關於季節性變化部分，秋冬季的入侵事件明顯多於夏季，弱入侵事件在秋季較明顯，在冬季則多由強入侵占優勢，黑潮在本區入侵的年際變化方面也與在呂宋海峽相同，均與PDO有關，黑潮入侵通常發生於PDO 指標為正值時（64.5%）。

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