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

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/m2 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. Plain Language Summary Evaporative fraction (EF; defined as latent heat flux‐LE divided by the sum of LE and sensible heat flux‐H) can vary under different climatic and land surface conditions, but its influencing factors remain poorly understood. To this end, we explored the effects of environmental variables on annual and daily EF variations at different sites around the globe. We found that mean annual EF decreased with increasing aridity index and increased with mean annual soil water content and leaf area index. By comparison, the boosted regression tree method quantitatively showed that environmental variables exerted equally important roles in regulating daily EF, especially at humid sites. The complex interplays of daily