Ice cloud particle roughness inferred from satellite polarimetric observations

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Monday, 5 January 2015
Souichiro Hioki, Texas A&M University, College Station, TX; and P. Yang and B. Baum
Manuscript (1.1 MB)

Handout (226.8 kB)

Recent studies suggest that including surface roughness in the single-scattering calculations for complex ice particles leads to improved agreement both in the reflectivities and in the inferred optical thickness values between intensity-only (such as from MODIS) and polarized reflectivity measurements. The numerical treatment of surface roughness in this case is a surrogate for a variety for imperfections in an ice particle including bubbles, internal fractures, and impurities. In this presentation, the questions we address are (1) how to choose an optimal degree of roughness for the single-scattering properties and (2) what is the impact of this choice when analyzing global satellite data? In this study, we focus on the degree of surface roughness inferred from satellite polarimetry observations in visible and near-infrared wavelengths. The polarized reflectivity is sensitive to the microphysical properties of particles, such as habit and roughness. To simulate the cloud layer reflectivity, we employ a newly-developed non-linear inversion program that retrieves cloud reflectivity and cloud top pressure simultaneously. The inversion scheme is applied to measurements from the three polarimetric channels on the PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) sensor. The measured ice cloud reflectivities are compared with those calculated from an adding-doubling radiative transfer model that employs multiple bulk scattering property models that are based on the same habits but having different roughness values. An effective roughness parameter is defined to quantify the overall roughness of the bulk scattering properties. In this presentation, we will demonstrate the extent to which the effective roughness can be constrained by the polarimetric measurements. The goal is to work towards more consistent retrievals of ice cloud optical thickness between sensors employing solar, infrared, and polarimetric measurements.