Evaluating soil evaporation parameterizations at near-instantaneous scales using surface dryness indices

Abstract

a b s t r a c tSoil evaporation is an important component in the water and energy cycles on land, especially for areas that are moderately or densely covered by bare soil. Soil evaporation parameterizations that scale down potential evaporation with the soil surface temperature (T s ) and/or the air humidity are regionally applicable because of the advantage of omitting pixel-scale near-surface soil moisture. In this paper, we provide an intercomparison study among these parameterizations. Potential evaporation indices are estimated from the Priestley-Taylor method, the Penman method, and the mass transfer method (with or without T s ). The surface dryness indices that indicate the water availability of the soil surface are based on T s and/or the air humidity. We establish and evaluate ten such soil evaporation parameterizations through combinations of different types of potential evaporation indices and surface dryness indices at near-instantaneous scales (30 min). The results show that incorporating the soil temperature in the surface dryness index instead of the potential evaporation index can improve soil evaporation estimations. Poorer but still reasonable estimations are achieved when only the air humidity-based surface dryness index is used. In addition, the energy balance factor is crucial in the surface dryness indices. Our study indicates that the potential evaporation indices that are based on the Penman equation are generally more useful and robust than those that are based on the Priestley-Taylor approach or the mass transfer method. However, when the surface dryness index is only based on air humidity data, the PriestleyTaylor potential evaporation index performs as well as the index that is estimated from the Penman equation. In contrast, a soil evaporation parameterization that estimates the potential evaporation through the mass transfer method (with T s ) and the surface dryness index from the soil moisture content did not perform as well as the above ten parameterizations.

Heat Storage Effect on Evaporation Estimates of China's Largest Freshwater Lake

“…The PT equation has also served as a core part of many of the evapotranspiration models (Gan et al, 2019; Gan & Gao, 2015; Gao et al, 2016; Garcia et al, 2013; Liu, Hiyama, et al, 2012). Before the work of Priestley and Taylor (1972), Penman (1948) had derived an equation that describes the joint control of energy supply and heat transport on the evaporation of water bodies, as shown in Equation .…”

Biophysical constraints on evapotranspiration partitioning for a conductance-based two source energy balance model

“…In G c -TSEB, the latent heat flux of the soil layer is calculated based on the complementary concept, expressed as the product of potential evaporation ( , W/m 2 ) and relative 𝐿𝐸 𝑠_𝑃𝑀 evaporative fraction ( ) (Gan et al, 2019;Gao et al, 2016), instead of mass transfer and soil 𝑓 𝑝 moisture (Kustas et al, 1998).…”

“…Kustas et al (2003), Li et al (2006) and Li et al (2019c) suggested the parameterizations for vegetation and soil in flux estimations are worth of attention. Considering the inaccessibility of global soil moisture at fine temporal-spatial resolution (Ahlmer et al, 2018) and the decoupling between the water content in the upper and deeper soil layers (Capehart and Carlson, 1997;Carranza et al, 2018), Gan et al (2019) revised the G c -TSEB to derive soil evaporation relying on the complementary concept and surface dryness index (SDI) (Gao et al, 2016), instead of the original TSEB scheme requiring soil moisture content as model input (Kustas et al, 1998). The difference in the result of model simulations for the combination of the new biophysical constraints and the two soil evaporation schemes can tell us something about vegetation functions and model capabilities of ET estimation and partitioning.…”

Seasonal and Diurnal Variations in the Priestley–Taylor Coefficient for a Large Ephemeral Lake

“…The Priestley-Taylor equation [18] has been widely used as a stand-alone model [45] or as a core part in many ET models [46][47][48][49][50]. The remarkable changes in the water level of Poyang Lake provide a unique opportunity for comparatively studying the variations in α and their controlling factors over water-covered and non-water-covered surfaces.…”