氣候數據可以提供有價值的信息來了解我們的環境。 探索和識別不同氣候事件之間的關係是氣候分析的一項重要任務。 特別是在研究古代氣候數據時，這是許多氣象學家非常感興趣的話題。 認識古代氣候事件的關係並弄清楚它們之間的關係可以幫助氣象學家重建歷史氣候，甚至預測未來的氣候。 在本研究中，我們基於REACHES（重建東亞氣候歷史編碼系列）數據集設計了一個交互式可視化系統。 為了幫助專家探索明清兩代跨越600年的關聯事件，並找出他們可能感興趣的事件的關係。我們使用關聯規則學習來計算不同氣候事件之間的關係，並找出其中意想不到的關係具體的時間和空間。

Climate data can provide valuable information to understand our environment. Exploring and identifying the relation between different climate events is a crucial task in climate analysis. Particularly when studying ancient climate data, which is a topic of great interest to many meteorologists. Realizing ancient climate events’ relation and figuring out their relation can help meteorologists to reconstruct the historical climate, and even predict the future’s climate. In this study, we design an interactive visualization system base on the REACHES (Reconstructed East Asian Climate Historical Encoded Series) dataset. To help experts explore the relation events over the Ming and Qing dynasties spanning 600 years, and find out which event’s relation they may be interested in. We used association rule learning to calculate the relation between different climate events, and find out an unexpected relation in specific time and space.

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