Daytime Multilayered Cloud Detection Using Multispectral Imager Data.

This study reports on recent progress toward the daytime detection of multilayered clouds in satellite multispectral data, specifically for the case of optically thin cirrus overlying lower-level water clouds. The technique is applied to 200 × 200 pixel arrays of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and is primarily based on the relationship between the near-infrared reflectance (at either 1.6 or 2.1 (mu)m) and the 11-(mu)m brightness temperature. Additional information used by the algorithm inclAudes the operational MODIS cloud mask and cloud thermodynamic phase as inferred from the 8.5- and 11-(mu)m brightness temperatures. The performance of the algorithm is evaluated for two MODIS case studies, and results are compared to coincident cloud physics lidar (CPL) data obtained from an aircraft platform. In both cases, the multilayered cloud detection algorithm results appear reasonable in comparison with the CPL data. The first case study, from 11 December 2002 during the Terra–Aqua Experiment (TX-2002), also examines the behavior of the algorithm when midlevel or mixed-phase cloud is present. The second case study, from 26 February 2003 during The Observing System Research and Predictability Experiment (THORPEX) campaign, sheds light on the sensitivity of the algorithm to optically thin cirrus. In this case, the algorithm does not detect cirrus with a visible (0.564(mu)m) optical thickness of less than 0.1 when it overlies a lower-level water cloud