中國過去七百年高解析度乾旱圖集：結合歷史文獻與調整式標準化降水指數之研究

Abstract

乾旱事件對人類社會的影響日益嚴重，對糧食生產和社會安全構成重大威脅，已成為限制社會經濟系統可持續發展的主要因素之一。為了在乾旱發生前實施有效的緩解措施，需要通過評估歷史乾旱的頻率和強度來設定預警標準。中國擁有豐富的歷史文獻資料，為歷史氣候學研究提供了豐富的分析資源。然而，以往的研究多集中於分析乾旱的空間分布與密度，缺乏一個完整且詳細的資料庫。因此，本研究旨在結合歷史文獻資料與現代儀器觀測數據，建構中國地區自14世紀以來的乾旱時空目錄，進一步探討長時段乾旱事件之強度、頻率與空間變異模式。研究資料包括東亞歷史氣候資料庫（REACHES）與現代氣候觀測資料（CRU），並採用標準化降水指數（SPI）計算乾旱程度。為確保乾濕異常指標在不同時期與資料型態間具有可比性，本研究統一應用SPI5（年）指標，並進行標準化處理與資料串接。接續運用主成分分析法（EOF）辨識主導中國地區乾旱的空間變異模式，進一步結合極端乾旱事件篩選條件，分析其在主模態上的貢獻組合與時間特徵。

The impact of drought on human society is becoming increasingly severe, posing significant threats to food production and social security, and has become one of the major factors limiting the sustainable development of socio-economic systems. To implement effective mitigation measures before the occurrence of droughts, it is necessary to establish early warning standards by assessing the frequency and intensity of historical droughts. China has abundant historical documents that provide rich resources for historical climate research. However, previous studies have mostly focused on analyzing the spatial distribution and density of droughts, lacking a systematic research based on a comprehensive database. Therefore, this study aims to integrate historical documentary records with modern instrumental data to construct an annually resolved drought atlas in China dating back to the 14th century. The high-resolution drought data can be used to analyze the intensity and frequency of the drought variations, and to investigate the dominant spatial patterns in the variabilities. The data sources include the Reconstructed East Asian Climate Historical Encoded Series (REACHES) and the CRU TS observational dataset. The Standardized Precipitation Index (SPI) is adopted—specifically SPI5(yearly)—to evaluate long-term moisture anomalies across periods. To ensure comparability between datasets, standardized processing and temporal merging were performed. Empirical Orthogonal Function (EOF) analysis was then applied to extract dominant spatial drought modes, followed by the application of extreme event selection criteria to attribute spatial and temporal patterns of major drought events.