Multi-Layer Cloud Detection from the MODIS-OMI-PARASOL Fused Dataset

Ice cloud optical thickness and effective diameter values retrieved from satellite measurements at visible/near-infrared wavelengths are highly sensitive to the single-scattering properties of predefined ice particles. To validate the single-scattering properties, knowledge of overall ice particle shape and the degree of surface roughness is necessary, but inferring particle shape and roughness from satellite measurements is challenging because it requires careful selection of cloud pixels.

Our focus in this presentation is the screening of optically thin multi-layer clouds. Such clouds frequently occur in the tropics, where boundary layer water clouds are overlaid with optically thin cirrus clouds. Three A-Train sensors, the Moderate Resolution Imaging Spectroradiometer (MODIS), the Ozone Mapping Instrument (OMI), and the Polarization and Directionality of the Earth’s Reflectance (POLDER), provide independent cloud top pressure estimates based on different measurement principles. Initially, the MODIS cloud top pressure and cloud phase flag are used to filter out possible water clouds. Then, the consistency of estimates from O₂-O₂ absorption (OMI), rotational Raman Scattering (OMI), and Oxygen A-band absorption (POLDER) are utilized to identify multi-layer and inhomogeneous clouds.

In this presentation, we discuss the feasibility of screening thin multi-layer clouds by combining the MODIS, OMI, and PARASOL cloud top pressure retrievals. The results are compared to the CALIOP vertical cloud profiles and transparency flags.