Discrimination of Mineral Aerosols From Clouds With Passive Multi-channel Space-borne Sensors.

Reliable discrimination of aerosols from clouds is critical for retrieving both aerosol and cloud properties as well as other atmospheric characteristics. Using MODIS data for the period 2000-2004, this study examines several techniques that were proposed for discriminating mineral dust from clouds. A number of representative cases of dust plumes mixed with clouds over oceans were analyzed. Selected cases represent the main dust sources located in East and South Asia, Middle East, Northern Africa, and Australia. For each case, we examine the performance of the commonly used 3x3 1km pixel standard deviation approach and compare it against other improved methods that account for the scale of the variable used in the variability analysis. We also tested the techniques based on brightness temperature differences. Our study demonstrates various limitations of existing methods and stresses the need for improved techniques. A new technique that uses ratios of VIS and NIR channels is being tested on a regional basis. The results will be presented and implications for the discrimination of dust from clouds with passive sensors planned for the NPOESS mission will be discussed.