Articles | Volume 9, issue 6
Atmos. Meas. Tech., 9, 2463–2482, 2016
Atmos. Meas. Tech., 9, 2463–2482, 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 et al.

Related authors

The identification and tracking of volcanic ash using the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI)
A. R. Naeger and S. A. Christopher
Atmos. Meas. Tech., 7, 581–597,,, 2014

Related subject area

Subject: Aerosols | Technique: Remote Sensing | Topic: Instruments and Platforms
Rethinking the correction for absorbing aerosols in the OMI- and TROPOMI-like surface UV algorithms
Antti Arola, William Wandji Nyamsi, Antti Lipponen, Stelios Kazadzis, Nickolay A. Krotkov, and Johanna Tamminen
Atmos. Meas. Tech., 14, 4947–4957,,, 2021
Short summary
Mie–Raman–fluorescence lidar observations of aerosols during pollen season in the north of France
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Marie Choël, Nicolas Visez, and Mikhail Korenskiy
Atmos. Meas. Tech., 14, 4773–4786,,, 2021
Short summary
Satellite imagery and products of the 16–17 February 2020 Saharan Air Layer dust event over the eastern Atlantic: impacts of water vapor on dust detection and morphology
Lewis Grasso, Daniel Bikos, Jorel Torres, John F. Dostalek, Ting-Chi Wu, John Forsythe, Heather Q. Cronk, Curtis J. Seaman, Steven D. Miller, Emily Berndt, Harry G. Weinman, and Kennard B. Kasper
Atmos. Meas. Tech., 14, 1615–1634,,, 2021
Short summary
Combined use of Mie–Raman and fluorescence lidar observations for improving aerosol characterization: feasibility experiment
Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Mikhail Korenskiy, Olivier Pujol, Oleg Dubovik, and Anton Lopatin
Atmos. Meas. Tech., 13, 6691–6701,,, 2020
Short summary
Solar radiometer sensing of multi-year aerosol features over a tropical urban station: direct-Sun and inversion products
Katta Vijayakumar, Panuganti C. S. Devara, Sunil M. Sonbawne, David M. Giles, Brent N. Holben, Sarangam Vijaya Bhaskara Rao, and Chalicheemalapalli K. Jayasankar
Atmos. Meas. Tech., 13, 5569–5593,,, 2020
Short summary

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,, 2005.
ARL: HYSPLIT Trajectory Model, available at: http://ready., last access: March 2016.
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.