Articles | Volume 17, issue 7
https://doi.org/10.5194/amt-17-1913-2024
https://doi.org/10.5194/amt-17-1913-2024
Research article
 | 
04 Apr 2024
Research article |  | 04 Apr 2024

Parameterizing spectral surface reflectance relationships for the Dark Target aerosol algorithm applied to a geostationary imager

Mijin Kim, Robert C. Levy, Lorraine A. Remer, Shana Mattoo, and Pawan Gupta

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Cited articles

Al-Saadi, J., Szykman, J., Pierce, R. B., Kittaka, C., Neil, D., Chu, D. A., Remer, L., Gumley, L., Prins, E., Weinstock, L., MacDonald, C., Wayland, R., Dimmick, F., and Fishman, J.: Improving National Air Quality Forecasts with Satellite Aerosol Observations, B. Am. Meteorol. Soc., 86, 1249–1262, https://doi.org/10.1175/BAMS-86-9-1249, 2005. 
Baldridge, A. M., Hook, S. J., Grove, C. I., and Rivera, G.: The ASTER spectral library version 2.0, Remote Sens. Environ., 113, 711–715, https://doi.org/10.1016/j.rse.2008.11.007, 2009. 
Belward, A. S., Estes, J. E., and Kline, K. D.: The IGBP-DIS global 1-km land-cover data set DISCover: A project overview, Photogramm. Eng. Rem. S., 65, 1013–1020, 1999. 
Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhang, X. Y.: Clouds and Aerosols, in: Climate Change 2013 – The Physical Science Basis, Cambridge University Press, https://doi.org/10.1017/CBO9781107415324.016, 2014. 
Ceamanos, X., Moparthy, S., Carrer, D., and Seidel, F. C.: Assessing the Potential of Geostationary Satellites for Aerosol Remote Sensing Based on Critical Surface Albedo, Remote Sens.-Basel, 11, 2958, https://doi.org/10.3390/rs11242958, 2019. 
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Short summary
The study focused on evaluating and modifying the surface reflectance parameterization (SRP) of the Dark Target (DT) algorithm for geostationary observation. When using the DT SRP with the ABIs sensor on GOES-R, artificial diurnal signatures were present in AOD retrieval. To overcome this issue, a new SRP was developed, incorporating solar zenith angle and land cover type. The revised SRP resulted in improved AOD retrieval, demonstrating reduced bias around local noon.