Degree of ice particle surface roughness inferred from polarimetric observations Academic Article uri icon


  • 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.

published proceedings


altmetric score

  • 2.75

author list (cited authors)

  • Hioki, S., Yang, P., Baum, B. A., Platnick, S., Meyer, K. G., King, M. D., & Riedi, J.

citation count

  • 17

complete list of authors

  • Hioki, Souichiro||Yang, Ping||Baum, Bryan A||Platnick, Steven||Meyer, Kerry G||King, Michael D||Riedi, Jerome

publication date

  • June 2016