Multi-resolution retrieval of fractional cloudiness for CERES using MODIS data

Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Cloud optical depths and particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiances from both clear and cloudy areas within the imager pixel. Few methods have been developed to account for these effects despite the obvious biasing that results from their analysis. One means for reducing the biases is to explicitly estimate the fraction of cloud cover within an imager pixel using collocated pixels at a higher resolution. The MODerate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites has an array of channels measuring spectral intensity at multiple wavelengths at a nominal resolution of 1 km. The visible (VIS, 0.64 µm) channel also has a 250-m resolution, making it ideal for better discrimination of cloud cover within a 1-km field of view. Currently, cloud properties are being derived from multispectral 1-km MODIS data for the Clouds and the Earth's Radiant Energy Experiment (CERES). To improve the retrieval of CERES cloud properties in partly cloudy conditions, a technique is developed to estimate cloud fraction and cloud properties in 1-km pixels using multi-resolution MODIS VIS data along with the 1-km 3.8, 10.8, and 12.0-µm channels. The method is first examined using data taken over ocean and over the southern Great Plains. Validity of the results is performed visually and by comparison against surface measurements. Application limitations and improvements in retrieval accuracy are discussed.