Degree of ice particle surface roughness inferred from polarimetric observations
- 1Department of Atmospheric Sciences, Texas A&M University, College Station, Texas, USA
- 2Space Science and Engineering Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
- 3Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- 4Goddard Earth Sciences Technology and Research, Universities Space Research Association, Columbia, Maryland, USA
- 5Laboratory for Atmospheric & Space Physics, University of Colorado, Boulder, CO, USA
- 6Laboratoire d'Optique Atmosphérique, Université de Lille – Sciences et Technologies, Villeneuve d'Ascq, France
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.