Latent Heat Flux and Canopy Conductance Based on Penman–Monteith, Priestley–Taylor Equation, and Bouchet’s Complementary Hypothesis

Abstract

A novel method is presented to analytically resolve the terrestrial latent heat flux (lE) and conductances (boundary layer g B and surface g S ) using net radiation (R N ), ground heat flux (G), air temperature (T a ), and relative humidity (RH). This method consists of set of equations where the two unknown internal state variables (g B and g S ) were expressed in terms of the known core variables, combining diffusion equations, the Penman-Monteith equation, the Priestley-Taylor equation, and Bouchet's complementary hypothesis. Estimated lE is validated with the independent eddy covariance lE observations over Soil Moisture Experiment 2002 (SMEX-02); the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project (GCIP) selected sites from FLUXNET and tropics eddy flux, representing four climate zones (tropics, subtropics, temperate, and cold); and multiple biomes. The authors find a RMSE of 23.8-54.6 W m 22 for hourly lE over SMEX-02 and GCIP and 23.8-29.0 W m 22 for monthly lE over the FLUXNET and tropics. Observational and modeled evidence in the reduction in annual evaporation (E) pattern on the order of 33% from 1999 to 2006 was found in central Amazonia. Retrieved g S responded to vapor pressure deficit, measured lE, and gross photosynthesis in a theoretically robust behavior. However, the current scheme [Penman-Monteith-Bouchet-Lhomme (PMBL)] showed some overestimation of lE in limited soil moisture regimes. PMBL provides similar results when compared with another Priestley-Taylor-based lE estimation approach [Priestley-Taylor-Jet Propulsion Laboratory (PT-JPL)] but with the advantage of having the conductances analytically recovered.

Parameter sensitivity analysis and optimization for a satellite‐based evapotranspiration model across multiple sites using Moderate Resolution Imaging Spectroradiometer and flux data

“…Although the performance of the PT‐JPL model was evaluated as good compared to other remote sensing ET models in recent studies [ McCabe et al ., ; Ershadi et al ., ; Zhu et al ., ), data are insufficient to demonstrate that it provides consistently good simulations over a wide range of biomes and different temporal scales [ Vinukollu et al ., ; Mallick et al ., ; Garcia et al ., ; Michel et al ., ]. Generally, poorer performance has been shown by McCabe et al .…”

“…Similar performance has been reported by Mallick et al . [], with the mean bias revealing a consistent overestimation at a majority of sites. Our model with optimized parameters addressed this problem by reducing the value of the most sensitive parameter ( m 1 ) from an original constant value of 1.36 to an optimized value of the posterior distribution in 95% high‐probability intervals (Table and Figures and ).…”

Hysteresis loops between canopy conductance of grapevines and meteorological variables in an oasis ecosystem

“…The values of D at which g c began to decline were about 2 kPa, which were higher than 1 kPa for some forest species (Ewers et al, 2005;Herbst et al, 2007Herbst et al, , 2008. In the third period, as stomatal aperture kept decreasing until sunset, g c decreased positively to decreasing R, D and T (Mallick et al, 2013), and R was the primary factor controlling g c (r 2 > 0.58; Table 1). Noticeably, the slopes of regression equations in the first period were significantly higher than the third period (Table 1 and Fig.…”

Evaluating the complementary relationship of evapotranspiration in the alpine steppe of the Tibetan Plateau

“…Application of the CR at the catchment/basin scale is very convenient since it bypasses the collection of multiyear precipitation and runoff data to calculate ET a with the help of a water balance approach. As a result, the CR theory has been applied to quantify ET a on a wide range of spatial scales from a few kilometers [ Huntington et al ., ; Liu et al ., ; Kahler and Brutsaert , ; Mallick et al ., ] to basin‐size [ Liu et al ., ; Matin and Bourque , ; Wang et al ., ], as well as temporal scales from annual [ Hobbins et al ., ; Ramírez et al ., ], to monthly [ Szilagyi and Jozsa , ; Szilagyi et al ., ; Hobbins et al ., ; Xu and Singh , ], daily [ Han et al ., ; Jaksa et al ., ; Ozdogan and Salvucci , ], or subdaily [ Crago and Crowley , ; Han et al ., ; Parlange and Katul , ].…”