Articles | Volume 9, issue 6
https://doi.org/10.5194/amt-9-2463-2016
https://doi.org/10.5194/amt-9-2463-2016
Research article
 | 
03 Jun 2016
Research article |  | 03 Jun 2016

Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth composites

Aaron R. Naeger, Pawan Gupta, Bradley T. Zavodsky, and Kevin M. McGrath

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Cited articles

Ackerman, S., Strabala, K., Menzel, P., Frey, R., Moeller, C., Gumley, L., Baum, B., Seemann, S. W., and Zhang, H.: Discriminating clear-sky from cloud with MODIS: Algorithm theoretical basis document (MOD35), version 5.0, NASA Goddard Space Flight Cent., Greenbelt, MD, USA, 2006.
Ackerman, S. A.: Remote sensing aerosols using satellite infrared observations, J. Geophys. Res., 102, 17069–17079, 1997.
Ackerman, S. A., Holz, R. E., Frey, R., Eloranta, E. W., Maddux, B. C., and McGill, M.: Cloud detection with MODIS. Part II: validation, J. Atmos. Ocean. Tech., 25, 1073–1086, 2008.
Al-Saadi, J., Szykman, J., Pierce, B. R., 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, 1249–1261, https://doi.org/10.1175/BAMS-86-9-1249, 2005.
ARL: HYSPLIT Trajectory Model, available at: http://ready. arl.noaa.gov/HYSPLIT.php, last access: March 2016.
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Short summary
In this study, we merge aerosol information from multiple satellite sensors on board low-earth orbiting (LEO) and geostationary (GEO) platforms in order to provide a more comprehensive understanding of the spatial distribution of aerosols compared to when only using single sensors as is commonly done. Our results show that merging aerosol information from LEO and GEO platforms can be very useful, which paves the way for applications to the more advanced next-generation of satellites.