Investigation of a Nonlinear Complementary Relationship Model for Monthly Evapotranspiration Estimation at Global Flux Sites.

Proper parameterization of the parameter (αe) that governs the wet environment evaporation is critical for the regional estimation of evapotranspiration (ET) using the generalized complementary relationship (GCR) model. Here, we proposed a global parameterization for the GCR model. We found that the GCR model is sensitive to the parameter αe, which varies spatially with the climate aridity index (AI, the ratio between the apparent potential ET and the precipitation) across 60 sites that span a large variety of climate types worldwide. We found that αe and the AI are generally more strongly correlated in drier climates (AI > 2) where water supply instead of energy supply is the limiting factor for actual ET. The strong correlation between αe and AI can be partly explained by 1) the usage of the air temperature measurements in the nonpotential conditions instead of potential conditions, and 2) the insensitivity of the actual ET to the apparent potential ET in the drier climate. Temporally, the parameter αe exhibits seasonal courses at monthly scales and decreases with increasing of vapor pressure deficit (VPD) in a hysteresis loop. Incorporation of the seasonal course and hysteresis significantly improved the model performances at most of the sites. The global parameterization we established can help the GCR model to be a more useful tool for regional and global ET estimations. [ABSTRACT FROM AUTHOR]