A coupled ground heat flux–surface energy balance model of evaporation using thermal remote sensing observations

[摘要] One of the major undetermined problems in evaporation (ET) retrieval using thermal infrared remote sensing is the lack of a physically based groundheat flux ( G ) model and its integration within the surface energy balance(SEB) equation. Here, we present a novel approach based on coupling athermal inertia (TI)-based mechanistic G model with an analytical surfaceenergy balance model, Surface Temperature Initiated Closure (STIC, versionSTIC1.2). The coupled model is named STIC-TI. The model is driven bynoon–night (13:30 and 01:30 local time) land surface temperature, surface albedo, and a vegetation index from MODIS Aqua in conjunction with a clear-sky netradiation sub-model and ancillary meteorological information. SEB fluxestimates from STIC-TI were evaluated with respect to the in situ fluxes from eddy covariance measurements in diverse ecosystems of contrasting aridity in boththe Northern Hemisphere and Southern Hemisphere. Sensitivity analysis revealed substantial sensitivity of STIC-TI-derived fluxes due to the land surface temperatureuncertainty. An evaluation of noontime G ( G i ) estimates showed 12 %–21 % error across six flux tower sites, and a comparison between STIC-TI versus empirical G models also revealed the substantially better performanceof the former. While the instantaneous noontime net radiation ( R Ni ) andlatent heat flux ( LE i ) were overestimated (15 % and 25 %), sensibleheat flux ( H i ) was underestimated (22 %). Overestimation(underestimation) of LE i ( H i ) was associated with theoverestimation of net available energy ( R Ni − G i ) and use ofunclosed surface energy balance flux measurements in LE i ( H i ) validation. The mean percent deviations in G i and H i estimates were found to bestrongly correlated with satellite day–night view angle difference inparabolic and linear pattern, and a relatively weak correlation was foundbetween day–night view angle difference versus LE i deviation. Findingsfrom this parameter-sparse coupled G –ET model can make a valuable contribution to mapping and monitoring the spatiotemporal variability ofecosystem water stress and evaporation using noon–night thermal infrared observations from future Earth observation satellite missions such asTRISHNA, LSTM, and SBG.

[学科分类] 大气科学