Deriving polarization properties of desert-reflected solar spectra with PARASOL data
Abstract. One of the major objectives of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) is to conduct highly accurate spectral observations to provide an on-orbit inter-calibration standard for relevant Earth-observing sensors with various channels. To calibrate an Earth-observing sensor's measurements with the highly accurate data from the CLARREO, errors in the measurements caused by the sensor's sensitivity to the polarization state of light must be corrected. For correction of the measurement errors due to the light's polarization, both the instrument's dependence on the incident polarization state and the on-orbit knowledge of the polarization state of light as a function of observed scene type, viewing geometry, and solar wavelength are required. In this study, an algorithm for deriving the spectral polarization state of solar light from the desert is reported. The desert/bare land surface is assumed to be composed of two types of areas: fine sand grains with diffuse reflection (Lambertian non-polarizer) and quartz-rich sand particles with facets of various orientations (specular-reflection polarizer). The Adding–Doubling Radiative Transfer Model (ADRTM) is applied to integrate the atmospheric absorption and scattering in the system. Empirical models are adopted in obtaining the diffuse spectral reflectance of sands and the optical depth of the dust aerosols over the desert. The ratio of non-polarizer area to polarizer area and the angular distribution of the facet orientations are determined by fitting the modeled polarization states of light to the measurements at three polarized channels (490, 670, and 865 nm) by the Polarization and Anisotropy of Reflectances for Atmospheric Science instrument coupled with Observations from a Lidar (PARASOL). Based on this physical model of the surface, the desert-reflected solar light's polarization state at any wavelength in the whole solar spectra can be calculated with the ADRTM.