The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Deep Blue Retrievals of Asian Aerosol Properties During ACE-Asia
Open accessAbstract
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
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Cited by
The Collection 6 MODIS aerosol products over land and ocean
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Self-citationThe CALIPSO Automated Aerosol Classification and Lidar Ratio Selection Algorithm
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Remote Sensing of Particulate Pollution from Space: Have We Reached the Promised Land?
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Metadata
- Authors
- Hsu, N. C., Tsay, S.-C., King, M. D., & Herman, J. R.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2006-11
- Volume
- 44
- Issue
- 11
- Pages
- 3180-3195
- ISSN
- 0196-2892 (ISSN-L)
- OpenAlex
- W2102834380
- Cited by
- 719
- References
- 18
- FWCI
- 11.26
- Type
- journal article
- Language
- en
- Open access
- green
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