Articles | Volume 18, issue 22
https://doi.org/10.5194/acp-18-16537-2018
https://doi.org/10.5194/acp-18-16537-2018
Research article
 | 
22 Nov 2018
Research article |  | 22 Nov 2018

Building a cloud in the southeast Atlantic: understanding low-cloud controls based on satellite observations with machine learning

Julia Fuchs, Jan Cermak, and Hendrik Andersen

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Cited articles

Adebiyi, A. A. and Zuidema, P.: The role of the southern African easterly jet in modifying the southeast Atlantic aerosol and cloud environments, Q. J. Roy. Meteor. Soc., 142, 1574–1589, https://doi.org/10.1002/qj.2765, 2016. a, b
Adebiyi, A. A. and Zuidema, P.: Low Cloud Cover Sensitivity to Biomass-Burning Aerosols and Meteorology over the Southeast Atlantic, J. Climate, 31, 4329–4346, https://doi.org/10.1175/JCLI-D-17-0406.1, 2018. a, b, c, d, e, f
Adebiyi, A. A., Zuidema, P., and Abel, S. J.: The Convolution of Dynamics and Moisture with the Presence of Shortwave Absorbing Aerosols over the Southeast Atlantic, J. Climate, 28, 1997–2024, https://doi.org/10.1175/JCLI-D-14-00352.1, 2015. a, b
Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989. a, b
Andersen, H. and Cermak, J.: How thermodynamic environments control stratocumulus microphysics and interactions with aerosols, Environ. Res. Lett., 10, 024004, https://doi.org/10.1088/1748-9326/10/2/024004, 2015. a, b
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Short summary
This study separates the influence of aerosol on cloud properties in the southeast Atlantic region from meteorological conditions in the biomass-burning season. Machine learning is used to link 8-day-averaged satellite and reanalysis data sets. Distinct regimes of aerosol–cloud interactions are identified in the subregions of the southeast Atlantic based on the obtained sensitivities.
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