Articles | Volume 14, issue 2
Atmos. Meas. Tech., 14, 1615–1634, 2021
https://doi.org/10.5194/amt-14-1615-2021
Atmos. Meas. Tech., 14, 1615–1634, 2021
https://doi.org/10.5194/amt-14-1615-2021

Research article 01 Mar 2021

Research article | 01 Mar 2021

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 et al.

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Cited articles

Ackerman, S. A.: Using the radiative temperature difference at 3.7 and 11 µm to tract dust outbreaks, Remote Sens. Environ., 27, 129–133, https://doi.org/10.1016/0034-4257(89)90012-6, 1989. 
Ackerman, S. A.: Remote sensing aerosols using satellite infrared observations, J. Geophys. Res.-Atmos., 102, 17069–17079, https://doi.org/10.1029/96jd03066, 1997. 
Adams, A. M., Prospero, J. M., and Zhang, C.: CALIPSO-Derived three-dimensional structure of aerosol over the atlantic basin and adjacent continents, J. Climate, 25, 6862–6879, https://doi.org/10.1175/JCLI-D-11-00672.1, 2012. 
Ahmadov, R., Grell, G., James, E., Csiszar, I., Tsidulko, M., Pierce, B., McKeen, S., Benjamin, S., Alexander, C., Pereira, G., Freitas, S., and Goldberg, M.: Using VIIRS Fire Radiative Power data to simulate biomass burning emissions, plume rise and smoke transport in a real-time air quality modeling system, in: Int. Geosci. Remote Se., Fort Worth, TX, 23–28 July 2017, 2806–2808, 2017. 
Ashpole, I. and Washington, R.: An automated dust detection using SEVIRI: A multiyear climatology of summertime dustiness in the central and western Sahara, J. Geophys. Res., 117, D08202, https://doi.org/10.1029/2011JD016845, 2012. 
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This study uses geostationary imagery to detect dust. This research was done to demonstrate the ability of dust detection over ocean surfaces in a dry atmosphere.