Abstract
Topsoil structures and inhomogeneous distribution of moisture in the soil volume will induce dielectric discontinuities from air to bulk soil, which in turn may induce multiple and volume scattering and affect the microwave surface emission. In situ ELBARA-III L-band radiometer observations of brightness temperature T B p ( p =H or V polarization) at the Maqu site on the Eastern Tibetan Plateau are exploited to understand the effect of surface roughness on coherent and incoherent emission processes. Assisted with in situ soil moisture (SM) and temperature profile measurements, this study develops an air-to-soil transition (ATS) model that incorporates the dielectric roughness (i.e., resulted from fine-scale topsoil structures and the soil volume) characterized by SM and geometric roughness effects, and demonstrates the necessity of the ATS model for modelling L-band T B p . The Wilheit (1978) coherent and Lv et al. (2014) incoherent models are compared for determining the dielectric constant of bulk soil in the ATS zone and for calculating soil effective temperature T eff . The Tor Vergata discrete scattering model (TVG) integrated with the advanced integral equation model (AIEM) is used as the baseline model configuration for simulating L-band T B p . Whereafter, the ATS model is integrated with the foregoing model for assessing its performance. Results show the ATS-based models reduce the underestimation of T B p (≈20-50 K) by the baseline simulations. Being dynamic in nature, the proposed dielectric roughness parameterization in the ATS model significantly improves the ability in interpreting T B p dynamics, which is important for improving SM retrieval at the global scale.
Highlights
IntroductionSoil moisture (hereafter soil moisture (SM)) is of significant importance for weather and climate predictions by controlling the partition of heat and water fluxes on the land-atmosphere interface [1,2,3]
Soil moisture is of significant importance for weather and climate predictions by controlling the partition of heat and water fluxes on the land-atmosphere interface [1,2,3]
The proposed dielectric roughness parameterization in the model significantly improves the ability in interpreting dynamics, which is important for improving soil moisture (SM) retrieval at the global scale
Summary
Soil moisture (hereafter SM) is of significant importance for weather and climate predictions by controlling the partition of heat and water fluxes on the land-atmosphere interface [1,2,3]. Independent L-band brightness temperature observations and radiative transfer models (e.g., the Community Microwave Emission Model [7]), if integrated with land surface models in a data assimilation framework, can be used for estimating soil physical properties [8,9,10,11,12], which are crucially important for understanding SM dynamics [13, 14]. The efforts related to microwave remote sensing of the land surface may be traced back to the work of Peake [15], which demonstrates the complementary relationship between emission and scattering and shows such with data from Straiton [16]. This may be called the scatteringemission radiative transfer approach. The more recent works are those of Fung [17] and Chen [18] on an advanced integral
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