Articles | Volume 9, issue 7
https://doi.org/10.5194/amt-9-3293-2016
https://doi.org/10.5194/amt-9-3293-2016
Research article
 | 
26 Jul 2016
Research article |  | 26 Jul 2016

A surface reflectance scheme for retrieving aerosol optical depth over urban surfaces in MODIS Dark Target retrieval algorithm

Pawan Gupta, Robert C. Levy, Shana Mattoo, Lorraine A. Remer, and Leigh A. Munchak

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Cited articles

Cooper, M., Martin, R. V., van Donkelaar, A., Lamsal, L., Brauer, M., and Brook, J.: A satellite-based multi-pollutant index of global air quality, Env. Sci. and Tech., 46, 8523–8524, 2012.
de Almeida Castanho, A. D., Prinn, R., Martins, V., Herold, M., Ichoku, C., and Molina, L. T.: Analysis of Visible/SWIR surface reflectance ratios for aerosol retrievals from satellite in Mexico City urban area, Atmos. Chem. Phys., 7, 5467–5477, https://doi.org/10.5194/acp-7-5467-2007, 2007.
de Almeida Castanho, A. D., Vanderlei Martins, J., and Artaxo, P.: MODIS Aerosol Optical Depth Retrievals with high spatial resolution over an Urban Area using the Critical Reflectance, J. Geophys. Res., 113, D02201, https://doi.org/10.1029/2007JD008751, 2008.
Eck, T. F., Holben, B. N., Reid, J. S., Dubovik, O., Smirnov, A., O'Neill, N. T., et al.: Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols, J. Geophys. Res.-Atmos., 104, 31333–31349, 1999.
Escribano, J., Gallardo, L., Rondanelli, R., and Choi, Y.-S.: Satellite retrievals of aerosol optical 10 depth over a subtropical urban area: the role of stratification and surface reflectance, Aerosol Air Qual. Res., 14, 596–U568, https://doi.org/10.4209/aaqr.2013.03.0082, 2014.
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Short summary
A new surface scheme inside MODIS dark target aerosol retrieval algorithm has been developed to improve the accuracy of aerosol optical depth data over cities. The new scheme integrates the MODIS land surface reflectance and land cover type information into the surface parameterization for urban areas, much of the issues associated with the standard algorithm have been mitigated for our test region. The improved aerosols data sets will be useful for air quality applications over cities.