During the ACE-Asia field campaign, unprecedented amounts of aerosol property data in East Asia during springtime were collected from an array of aircraft, shipboard, and surface instruments. However, most of the observations were obtained in areas downwind of the source regions. In this paper, we employ the newly developed satellite aerosol algorithm called ìDeep Blueî to characterize the properties of aerosols over source regions using radiance measurements from SeaWiFS and MODIS. Based upon the Angstrom exponent derived from the Deep Blue algorithm, we demonstrate that this new algorithm is able to distinguish the dust plumes from fine-mode pollution particles, even in complex aerosol environments such as the one over Beijing. Furthermore, we validate these results by comparing them to the observations from AERONET sites in China and Mongolia during spring 2001. These comparisons show that the values of satellite retrieved aerosol optical thickness from Deep Blue are generally within 20 % to 30% of those measured by sunphotometers.

Our analyses also indicate that the roles of mineral dust and anthropogenic particles are comparable in contributing to the overall aerosol distributions during spring in northern China, while fine mode particles are dominant over southern China. The spring season in East Asia consists of one of the most complex environments in terms of frequent cloudiness and wide ranges of aerosol loadings and types. We will discuss how the factors contributing to this complexity influence the resulting aerosol monthly averages from various satellite sensors and, thus, the synergy among satellite aerosol products.