Relative efficiency of land surface energy balance components

Abstract

[1] The partitioning of available energy into dissipative fluxes over land surfaces is dependent on the state variable of the surface energy balance (land surface temperature) and the state variable of the surface water balance (soil moisture). The direct measurement of the turbulent fluxes is achieved with in situ instruments at tower sites. These point-scale measurements are sparsely distributed. Broader scale mapping of the turbulent fluxes is mostly dependent on land surface temperature (LST) and optical/infrared vegetation that can be sensed remotely. There are several data assimilation approaches currently in use that intake sequences of daytime LST that attain different diurnal amplitudes depending on available energy and the relative efficiency of surface energy balance to infer the magnitude of surface flux components such as latent and sensible heat flux. In this study we perform stability analysis on the evolution of LST in order to provide insights into the physical bases for why LST variations can be used to diagnose surface energy balance (SEB) components. The derived relative efficiencies of SEB components in dissipating available energy at the land surface are tested using two field experiment measurements. The results show that the theoretically derived relative efficiencies of SEB components agree well with field observations. The study provides insight into how LST sequences implicitly contain the signature of partitioning of available energy among SEB components and can be used to infer their magnitudes.

Surface Energy Balance and Buoyancy Response to Shallow Cumulus Shading

“…These results offer insight on the impact of shallow cumulus clouds when diagnosing G as an empirical fraction of Q (e.g., Kustas and Daughtry 1990;Santanello and Friedl 2003;Bateni and Entekhabi 2012). These results are also important because of the difficulties in observing soil heat flux experimentally, even for cloud-free PBLs (e.g., Small and Kurc 2003), and they confirm the difficulty to experimentally determine H, LE, and consequently EF in the presence of shallow cumuli.…”

“…However, even though the impact of cumulus convection on surface fluxes has been shown to significantly affect larger-scale circulations (Betts and Ridgway 1988) and the skill of medium-range weather forecasts (Tiedtke 1989), the coupling between shallow cumulus and the land surface deserves further analysis. Without focusing specifically on shallow cumuli, some recent investigations (e.g., Small and Kurc 2003;Gentine et al 2011a;Bateni and Entekhabi 2012) provide clues into the role of broader cloud types on the surface energy balance. A more complete approach is provided by Gentine et al (2011b), who used an analytical linear model of the soilvegetation-ABL continuum (Gentine et al 2010) to study the spectral state of this continuum response to different radiative forcing harmonics.…”

Sharpening method of satellite thermal image based on the geographical statistical model

“…30,39,45,46 Generally, the more moist the soil, the more evaporation removes heat. Therefore, soil moisture is an indispensable factor of thermal image modeling.…”

“…These environmental factors were judged on the basis of previous studies focusing on SEB. 29,30,39,40 In addition, some other explanatory variables were proxy variables, which were used to replace those environmental factors proved by previous studies as directly related to the BT, whereas their raster layers were difficult to obtain. This process could guarantee the simplicity and feasibility of this method.…”

“…Given that LST is the result of land SEB, 29,30 it is determined by land surface properties and energy balance together. This study selected various parameters in the SEB process as the explanatory variables.…”