Event‐Specific Meteorological Drivers Shape Diverse Water‐Use Efficiency Trajectories Under Drought Propagation

环境科学 植被(病理学) 大气科学 气候学 比例(比率) 空气温度 联轴节(管道) 气象学 可预测性 初级生产 时间尺度 焊剂(冶金) 气候变化 不确定性传播 大气模式 过程(计算) 地球系统科学 大气动力学 热的
作者
F. Li,QINCHUAN XIN,Julia K. Green,Chuixiang Yi,Armen R. Kemanian,Steven A. Kannenberg,Paul C. Stoy,Yuting Yang,Huimin Lei,Yujiu Xiong,Zheng Fu
出处
期刊:Global Change Biology [Wiley]
卷期号:32 (1): e70690-e70690
标识
DOI:10.1111/gcb.70690
摘要

ABSTRACT Drought propagation from meteorological to soil drought marks a critical phase in regulating vegetation water–carbon dynamics, yet the response trajectories of water‐use efficiency (WUE) during these events remain poorly understood. Here, combining global flux tower observations with simulations from Earth System Models (ESMs), we quantified the spatiotemporal patterns of drought propagation characteristics, identified WUE response trajectories for characteristic‐specific droughts, and investigated their dominant drivers. We found that 58% of soil droughts follow meteorological droughts. Most sites experience drought propagation events with increasing intensity, faster propagation, and shorter intervals. Among all identifiable trajectories, nonmonotonic patterns account for approximately 60%. WUE response trajectories generally follow continuous and nonmonotonic patterns, dominated by a rise‐then‐fall pattern. This pattern reflects a process in which vegetation functions regulated by stomatal behavior are initially stressed and then partially recover. Intra‐site variability is extremely pronounced, mainly driven by event‐specific thermal factors such as air temperature and net radiation. ESMs reproduce broad site‐level prevalence of nonmonotonic patterns, but show discrepancies in the relative importance of drivers due to the coupling of different land surface models. These findings challenge the notion of fixed vegetation functional responses and highlight the dynamic variability of response trajectories in relation to event‐specific characteristics, and provide concrete diagnostics to guide model improvements.
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