Abstract
Due to the difficulty in accurately interpreting surface emissivity spectra, problems remain in the application of passive microwave satellite observations over land surfaces. This study develops a parameterized soil surface emissivity model to quantify the microwave emissivity accurately and rapidly for Gaussian-correlated rough surfaces. We first analyze the sensitivity of surface emissivity to parameters using the advanced integral equation model (AIEM) simulated data. On the basis of the analysis and previous empirical models, two function factors that consider the polarization dependence of surface reflectivity are developed in the parameterized soil surface emissivity model. These factors also comprehensively account for the effects of surface roughness, soil moisture, and incident angle. A comparison with the AIEM simulated data indicates that the absolute error of effective reflectivity estimated by the parameterized soil surface emissivity model is small with a magnitude of 10−2. Validation through experimental measurements suggests that a good agreement could be obtained. The parameterized soil surface emissivity model is applied to simulate satellite measurements of the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). Compared with the commonly-used microwave land emissivity model developed by Weng et al. (2001), the simulation results using the parameterized soil surface emissivity model yield a lower root-mean-square error (RMSE) and the overall errors are reduced, particularly for horizontal polarization. The newly-developed parameterized soil surface emissivity model should be useful in improving our understanding and modeling the measurements of passive microwave radiometers.
Highlights
Satellite-based passive microwave remote sensing has been shown to be increasingly valuable in understanding the land-to-atmosphere fluxes of energy and water
The model aims to improve the accuracy of land microwave emissivity over a wide range of surface conditions, frequencies, and incident angles
This model introduces a factor as a function of surface roughness, soil moisture, and incident angle based on the form of the Weng model and the advanced integral equation model (AIEM) simulated data
Summary
Satellite-based passive microwave remote sensing has been shown to be increasingly valuable in understanding the land-to-atmosphere fluxes of energy and water. With the development of remote sensing and data assimilation techniques, satellite measurements from microwave sounding can provide atmospheric temperature and moisture profiles under most weather conditions, over oceans, which has made significant contributions to improving the skill of numerical weather prediction (NWP) [1]. Due to the uncertainty in estimating microwave emissivity, problems remain in using passive microwave satellite data over land [1,2,3,4,5]. Microwave emission signals from soil surfaces depend on their reflective and scattering properties. For a perfectly smooth (specular) soil surface, the reflectivity can be described by Fresnel equations
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