Deep Blue Retrievals of Asian Aerosol Properties During ACE-Asia

By N. C. Hsu, Si-Chee Tsay, Michael D. King, Jay R. Herman. IEEE Transactions on Geoscience and Remote Sensing, 2006

691 citations recorded by the source corpus.

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, the newly developed satellite aerosol algorithm called "Deep Blue" was employed to characterize the properties of aerosols over source regions using radiance measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Based upon the Aringngstroumlm exponent derived from the Deep Blue algorithm, it was demonstrated that this new algorithm is able to distinguish dust plumes from fine-mode pollution particles even in complex aerosol environments such as the one over Beijing. Furthermore, these results were validated by comparing them with 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%-30% of those measured by sunphotometers. The 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. This paper 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

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/b66b7b280017af68130fcbbd3fc83a91cfbb764e

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Citations in the corpus

Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product (2018, background): “Remote Sens.) cloud retrieval code; and aerosol property retrievals from Remer et al. (2008), Levy et al. (2013), and Hsu et al. (2004, 2006).”
The CALIPSO Automated Aerosol Classification and Lidar Ratio Selection Algorithm (2009, background): “Arctic haze has a low depolarization ratio ; 2% (Ishii et al. 1999), and it is modeled as polluted continental in this algorithm.”