On Radiative Transfer Model and its Relationship with Thermal Fluxes Across Space, Time, and Hydroclimates

Modeling of Radiative Transfer Equation (RTE) for passive soil moisture retrieval requires characterizing the heterogeneous land surface variables (soil and vegetation). In addition to characterizing the principal (first order) effect, the land surface variables also engage in complex nonlinear land-atmosphere interactions (higher order), which are also the critical drivers of hydrological and metrological processes. Of all the land surface variables, surface roughness and vegetation are found to highly impact soil moisture retrieval accuracy.

In this work, we propose a new model to characterize surface roughness spatio-temporally and a scaling technique for vegetation optical depth. The performance of the model is compared with the current Soil Moisture Active Passive (SMAP) parametrizations, in addition to quantifying the soil moisture error using Taylor's error propagation method.

Additionally, the nonlinear land surface interactions are also quantified over multiple landcovers, and hydroclimates. These land surface interactions are further analyzed with respect to evaporative fraction (EF), sensible heat (H), and vapor pressure deficit (VPD). Our results indicate that; the land surface interactions are observed to be higher under temperate climate than other climate classes. Also, the land surface interactions increased with EF, and decreased with H and VPD. This relationship varies according to the availability of soil moisture. The effect of VPD on land surface interactions is significant under arid climate compared to the temperate or continental climates. This work led to propose a framework to classify the environments as homogenous and heterogeneous environments. These environments are further classified as water and energy rich environments.