The Sensitivity of Ice Cloud Optical and Microphysical Passive Satellite Retrievals to Cloud Geometrical Thickness

Most satellite-based ice cloud retrieval algorithms rely on precomputed lookup libraries for inferring the ice cloud optical thickness (tau) and effective particle size ( D_e). However, this retrieval methodology does not account for the case where cloud geometrical thickness may vary by several kilometers. In this paper, we investigate the effect of the ice cloud geometrical thickness on the retrieval of tau and D_e for algorithms using the Moderate Resolution Imaging Spectroradiometer infrared (IR) bands at 8.5 and 11 mum (or 12 mum) or solar bands at 0.65 and 1.64 mum (or 2.13 mum). We use a rigorous radiative transfer package to simulate the IR brightness temperatures and solar reflectances, assuming that the ice cloud top height is fixed at 12 or 15 km with a variation of cloud geometrical thickness from 0.5 to 5 km. The simulated brightness temperatures and reflectances are then used to investigate the errors of cloud tau and D_e inferred from the precomputed lookup tables developed with a specific geometrical thickness. It is found that the retrieval errors in tau and D_e increase with increasing tau for the IR and solar methods. In both cases, cloud tau and D_e may be underestimated and overestimated, respectively, if the effect of the cloud geometrical thickness is not taken into account. The effect of the cloud geometrical thickness on the retrieval of cloud optical and microphysical properties is much larger for the IR algorithm than for the solar-band-based algorithm. This paper demonstrates that the inclusion of the information about the cloud geometrical thickness may improve the accuracy of the retrieval of the cloud properties on the basis of the precomputed lookup libraries