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Disentangling the Impacts of Environmental Factors on Evaporative Fraction Across Climate Regimes

环境科学 分数(化学) 气候变化 蒸发冷却器 气候学 大气科学 自然资源经济学 环境资源管理 地理 气象学 经济 生态学 化学 地质学 生物 有机化学
作者
Qiong Han,Tiejun Wang,Zhe Kong,Yibin Dai,Lichun Wang
出处
期刊:Journal Of Geophysical Research: Atmospheres [Wiley]
卷期号:129 (19)
标识
DOI:10.1029/2024jd041515
摘要

Abstract Evaporative fraction (EF) is a useful measure for quantifying land surface energy partitioning processes and determining evaporative regimes; however, its influencing factors remain highly uncertain. Here, global data sets were compiled to disentangle the effects of environmental variables on EF variations along climate and land surface gradients. We found that (a) at annual timescales, ecosystem‐level EF could be expressed as a power law function of aridity index. The relationships of mean annual soil water content (SWC) and leaf area index (LAI) with mean annual EF resembled the traditional evaporative regime theory; (b) at daily timescales, the boosted regression tree method quantitatively revealed that the impacts of environmental variables (including meteorological variables) on EF showed equal importance, especially at humid sites, primarily due to the different response direction and magnitude of latent heat (LE) and sensible heat (H) fluxes to environmental changes. Particularly, the contrasting responses of LE (positive) and H (negative) to SWC, LAI, and relative humidity enhanced the positive effects of those influencing variables on EF; whereas, the correlations between EF and energy‐related factors (i.e., net radiation‐Rn and air temperature‐Ta) deteriorated as both LE and H showed positive response patterns to those variables; (c) meteorological factors were also found to have nonlinear effects on daily EF, further modified by climatic conditions. Rn near 150 W/m 2 and Ta near 15°C appeared to be important energy‐partitioning thresholds at drier and humid sites, respectively. Moreover, changing interactions among environmental variables with climates were demonstrated to be important for better explaining EF variations.
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