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In situ observations indicate the existence of significant and highly variable microphysical vertical structures in marine boundary layer (MBL) clouds due to the combined effects of condensational growth, entrainment mixing, collision-coalescence, and sedimentation.

An understanding of this vertical structure (e.g., liquid water content and cloud effective particle radius) is important for a variety of reasons. First, cloud vertical structure reflects the interaction and competition of cloud processes in shaping the macro- and microphysical properties of MBL clouds. Second, an understanding of cloud vertical structure is crucial for assessing the uncertainties caused by the homogeneous cloud assumption in cloud remote sensing. In addition, it is also an essential step toward possible MODIS-based retrieval cloud droplet number concentration (CDNC) and drizzle, two key parameters for studying aerosol indirect effects.

Despite its importance, the vertical structures of MBL clouds on a global scale remains largely unexplored. Although space-borne active sensors, such as CALIOP and CloudSat, are designed to resolve cloud vertical structure, some challenging issues and inherent limitations hinder their application to MBL clouds. The MODIS instruments on both Terra and Aqua have three shortwave infrared (SWIR) bands centered at about 1.6, 2.1 and 3.7 μm. These SWIR bands have different cloud penetration depths, and therefore carry information about different layers in a cloud. Previous studies have shown that the combination of these MODIS bands can be used for studying cloud vertical structure. However, several factors, such as 3-D radiative effects, algorithm issues and instrument radiometric accuracy complicate the information contained in these bands. Motivated by the need for improved knowledge of MBL cloud vertical structure and the recognized need to understand potential biases in MODIS retrievals, we propose a comprehensive modeling investigation. We intend to first evaluate the cloud vertical structure information content in MODIS-like observations from simulated MBL large-eddy simulation (LES) cloud fields and 3-D radiative transfer models. Based on results from these simulations, we will explore the capabilities, as well as limitations, of MODIS observations for studying temporal and spatial variations in the vertical structure of MBL clouds. Our specific goals are as follows:

1. Integrate LES model, 3-D radiative transfer model and a MODIS retrieval simulator into an analysis tool for analyzing MODIS-like MBL cloud property retrievals;
2. Achieve a better understanding of the information content in MODIS observations on the vertical structure of MBL clouds by applying MODIS-like retrievals to LES cloud simulations;
3. Explore the theoretical basis for potential future MODIS cloud algorithms, including cloud adiabatic index, cloud droplet number concentration (CDNC) and drizzle flags for MBL clouds;
4. Improve our understanding of the uncertainties in current MODIS operational cloud products;
5. Study vertical cloud structure as revealed by MODIS and other A-train sensors over key MBL cloud regimes.