Atmos. Chem. Phys. Discuss., 11, 12519-12560, 2011
www.atmos-chem-phys-discuss.net/11/12519/2011/
doi:10.5194/acpd-11-12519-2011
© Author(s) 2011. This work is distributed
under the Creative Commons Attribution 3.0 License.
Review Status
This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
A multi-angle aerosol optical depth retrieval algorithm for geostationary satellite data over the United States
H. Zhang1, A. Lyapustin2, Y. Wang2, S. Kondragunta3, I. Laszlo3, P. Ciren4, and R. M. Hoff1,2
1Joint Center for Earth Systems Technology (JCET), University of Maryland Baltimore County, Suite 320, 5523 Research Park Drive, Baltimore, MD 21228, USA
2Goddard Earth Sciences and Technology Center (GEST), University of Maryland Baltimore County, Suite 320, 5523 Research Park Drive, Baltimore, MD 21228, USA
3NOAA/NESDIS/STAR, 5825 University Research Ct, College Park, MD 20740, USA
4PSGS/Dell, 5825 University Research Ct, College Park, MD 20740, USA

Abstract. Aerosol optical depth (AOD) retrieval from geostationary satellites has high temporal resolution compared to the polar orbiting satellites and thus enables us to monitor aerosol motion. However, current Geostationary Operational Environmental Satellites (GOES) have only one visible channel for retrieving aerosol and hence the retrieval accuracy is lower than those from the multichannel polar-orbiting satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS). The operational GOES AOD retrieval algorithm (GOES Aerosol/Smoke Product, GASP) uses 28-day composite images from the visible channel to derive surface reflectance, which can produce large uncertainties. In this work, we develop a new AOD retrieval algorithm for the GOES imager by applying a modified multi-angle Implementation of Atmospheric Correction (MAIAC) algorithm. The algorithm assumes the surface Bidirectional Reflectance Distribution Function (BRDF) at channel 1 of GOES is proportional to seasonal average BRDF in the 2.1 μm channel from MODIS. The ratios between them are derived through time series analysis of the GOES visible channel images. The results of the AOD and surface reflectance retrievals are evaluated through comparison against those from Aerosol Robotic Network (AERONET), GASP, and MODIS. The AOD retrievals from the new algorithm demonstrate good agreement with AERONET retrievals at several sites across the US. They are comparable to the GASP retrievals in the eastern-central sites and are more accurate than GASP retrievals in the western sites. In the western US where surface reflectance is high, the new algorithm also produces larger AOD retrieval coverage than both GASP and MODIS.

Citation: Zhang, H., Lyapustin, A., Wang, Y., Kondragunta, S., Laszlo, I., Ciren, P., and Hoff, R. M.: A multi-angle aerosol optical depth retrieval algorithm for geostationary satellite data over the United States, Atmos. Chem. Phys. Discuss., 11, 12519-12560, doi:10.5194/acpd-11-12519-2011, 2011.
 
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