Assessing Global Warming Induced Changes in Summer Rainfall Variability over Eastern China Using the Latest Hadley Centre Climate Model HadGEM3-GC2
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Summer precipitation anomalies over eastern China are characterized spatially by meridionally banded structures fluctuating on interannual and interdecadal timescales, leading to regional droughts and floods. In addition to long-term trends, how these patterns may change under global warming has important implications for agricultural planning and water resources over this densely populated area. Using the latest Hadley Centre climate model, HadGEM3-GC2, this paper investigates the potential response of summer precipitation patterns over this region, by comparing the leading modes between a 4×CO2 simulation and the model’s pre-industrial control simulation. Empirical Orthogonal Function (EOF) analyses show that the first two leading modes account for about 20% of summer rainfall variability. EOF1 is a monopole mode associated with the developing phase of ENSO events and EOF2 is a dipole mode associated with the decaying phase of ENSO. Under 4×CO2 forcing, the dipole mode with a south–north orientation becomes dominant because of a strengthened influence from excessive warming of the Indian Ocean. On interdecadal time scales, the first EOF looks very different from the control simulation, showing a dipole mode of east–west contrast with enhanced influence from high latitudes.
Key wordsrainfall variability global warming ENSO HadGEM3-GC2
在年际和年代际尺度上, 中国东部的夏季降水异常通常表现为明显的经向型特征, 对区域性旱涝产生影响. 在气候变化影响下, 除了长期趋势外, 降水变率尤其是空间分布特征的变化对该地区的农业生产、水资源调度等具有重要意义. 通过对比分析英国气象局Hadley中心最新气候模式HadGEM3-GC2的骤增4倍CO2及工业革命前控制试验, 本文研究了增暖背景下该地区夏季降水模态的可能变化. 基于EOF分析的结果表明, 在该模式的控制实验中, 前两个降水模态占总降水变率的20%. EOF1是一个单极型, 与ENSO事件的发展位相相关;而EOF2为偶极型, 与ENSO事件的衰减位相相关. 骤增4倍CO2强迫下, 年际尺度上, 偶极型变为了主导模态, 这主要是由于印度洋的作用增强所致. 而年代际尺度上, 降水模态受到更多来自高纬度的影响, 增暖下主导模态与控制实验差距较大, 表现出更强的东-西向分布特征.
关键词降水变率 全球增暖 ENSO HadGEM3-GC2
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We thank two anonymous reviewers for their constructive comments and suggestions. This study was jointly sponsored by the National Key R&D Program of China (Grant No. 2016YFA0600404), the National Natural Science Foundation of China (Grant Nos. 41530532 and 41605057), the China Special Fund for Meteorological Research in the Public Interest (Grant No. GYHY201506001-1), the Jiangsu Collaborative Innovation Center for Climate Change, and the UK–China Research&Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund.
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