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Degree of ice particle surface roughness inferred from polarimetric observations

Abstract : The degree of surface roughness of ice particles within thick, cold ice clouds is inferred from multi-directional, multi-spectral satellite polarimetric observations over oceans, assuming a column-aggregate particle habit. An improved roughness inference scheme is employed that provides a more noise-resilient roughness estimate than the conventional best-fit approach. The improvements include the introduction of a quantitative roughness parameter based on empirical orthogonal function analysis and proper treatment of polarization due to atmospheric scattering above clouds. A global 1-month data sample supports the use of a severely roughened ice habit to simulate the polarized reflectivity associated with ice clouds over ocean. The density distribution of the roughness parameter inferred from the global 1-month data sample and further analyses of a few case studies demonstrate the significant variability of ice cloud single-scattering properties. However, the present theoretical results do not agree with observations in the tropics. In the extratropics, the roughness parameter is inferred but 74 % of the sample is out of the expected parameter range. Potential improvements are discussed to enhance the depiction of the natural variability on a global scale.
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https://hal-insu.archives-ouvertes.fr/insu-03686208
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Submitted on : Friday, June 3, 2022 - 8:52:13 AM
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Souichiro Hioki, Ping yang, Bryan A. Baum, Steven Platnick, Kerry G. Meyer, et al.. Degree of ice particle surface roughness inferred from polarimetric observations. Atmospheric Chemistry and Physics, European Geosciences Union, 2016, 16, pp.7545-7558. ⟨10.5194/acp-16-7545-2016⟩. ⟨insu-03686208⟩

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