A Review of Ice Cloud Optical Property Models for Passive Satellite Remote Sensing Academic Article uri icon

abstract

  • The current wealth of spaceborne passive and active measurements from ultraviolet to the infrared wavelengths provides an unprecedented opportunity to construct ice cloud bulk optical property models that lead to consistent ice cloud property retrievals across multiple sensors and platforms. To infer the microphysical and radiative properties of ice clouds from these satellite measurements, the general approach is to assume an ice cloud optical property model that implicitly assumes the habit (shape) and size distributions of the ice particles in these clouds. The assumption is that this ice optical property model will be adequate for global retrievals. In this review paper, we first summarize the key optical properties of individual particles and then the bulk radiative properties of their ensemble, followed by a review of the ice cloud models developed for application to satellite remote sensing. We illustrate that the random orientation condition assumed for ice particles is arguably justified for passive remote sensing applications based on radiometric measurements. The focus of the present discussion is on the ice models used by the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Clouds and Earths Radiant Energy System (CERES) science teams. In addition, we briefly review the ice cloud models adopted by the Polarization and Directionality of the Earths Reflectance (POLDER) and the Himawari-8 Advanced Himawari Imager (AHI) for ice cloud retrievals. We find that both the MODIS Collection 6 ice model and the CERES two-habit model result in spectrally consistent retrievals.

published proceedings

  • ATMOSPHERE

altmetric score

  • 1.75

author list (cited authors)

  • Yang, P., Hioki, S., Saito, M., Kuo, C., Baum, B. A., & Liou, K.

citation count

  • 26

complete list of authors

  • Yang, Ping||Hioki, Souichiro||Saito, Masanori||Kuo, Chia-Pang||Baum, Bryan A||Liou, Kuo-Nan

publication date

  • December 2018

publisher