Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin

Canopy and aerodynamic conductances (g(C) and g(A)) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (lambda E-T) and evaporation (lambda E-E) flux components of the terrestrial latent heat flux (lambda E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (T-R) into an integrated framework of the Penman-Monteith and Shuttleworth-Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on lambda E-T and lambda E-E over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a T-R-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between g(C), lambda E-T, and atmospheric vapor pressure deficit (D-A), without using any leaf-scale empirical parameterizations for the modeling. The T-R-based model shows minor biophysical control on lambda E-T during the wet (rainy) seasons where lambda E-T becomes predominantly radiation driven and net radiation (RN) determines 75 to 80% of the variances of lambda E-T. However, biophysical control on lambda E-T is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65% of the variances of lambda E-T, and indicates lambda E-T to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in g(A) between forests and pastures, very similar canopy-atmosphere coupling was found in these two biomes due to soil moistureinduced decrease in g(C) in the pasture. This revealed the pragmatic aspect of the T-R-driven model behavior that exhibits a high sensitivity of g(C) to per unit change in wetness as opposed to g(A) that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between lambda E-T and g(C) during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by g(A) for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of g(C) and g(A) to changes in atmospheric radiation, D-A, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land-surface-atmosphere exchange parameterizations across a range of spatial scales.