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

Related authors

Algorithm for continual monitoring of fog life cycles based on geostationary satellite imagery as a basis for solar energy forecasting
Babak Jahani, Steffen Karalus, Julia Fuchs, Tobias Zech, Marina Zara, and Jan Cermak
EGUsphere, https://doi.org/10.5194/egusphere-2023-2885,https://doi.org/10.5194/egusphere-2023-2885, 2024
Short summary
High-resolution satellite-based cloud detection for the analysis of land surface effects on boundary layer clouds
Julia Fuchs, Hendrik Andersen, Jan Cermak, Eva Pauli, and Rob Roebeling
Atmos. Meas. Tech., 15, 4257–4270, https://doi.org/10.5194/amt-15-4257-2022,https://doi.org/10.5194/amt-15-4257-2022, 2022
Short summary
Meteorology-driven variability of air pollution (PM1) revealed with explainable machine learning
Roland Stirnberg, Jan Cermak, Simone Kotthaus, Martial Haeffelin, Hendrik Andersen, Julia Fuchs, Miae Kim, Jean-Eudes Petit, and Olivier Favez
Atmos. Chem. Phys., 21, 3919–3948, https://doi.org/10.5194/acp-21-3919-2021,https://doi.org/10.5194/acp-21-3919-2021, 2021
Short summary
Synoptic-scale controls of fog and low-cloud variability in the Namib Desert
Hendrik Andersen, Jan Cermak, Julia Fuchs, Peter Knippertz, Marco Gaetani, Julian Quinting, Sebastian Sippel, and Roland Vogt
Atmos. Chem. Phys., 20, 3415–3438, https://doi.org/10.5194/acp-20-3415-2020,https://doi.org/10.5194/acp-20-3415-2020, 2020
Short summary
Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks
Hendrik Andersen, Jan Cermak, Julia Fuchs, Reto Knutti, and Ulrike Lohmann
Atmos. Chem. Phys., 17, 9535–9546, https://doi.org/10.5194/acp-17-9535-2017,https://doi.org/10.5194/acp-17-9535-2017, 2017
Short summary

Related subject area

Subject: Clouds and Precipitation | Research Activity: Remote Sensing | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Air mass history linked to the development of Arctic mixed-phase clouds
Rebecca J. Murray-Watson and Edward Gryspeerdt
Atmos. Chem. Phys., 24, 11115–11132, https://doi.org/10.5194/acp-24-11115-2024,https://doi.org/10.5194/acp-24-11115-2024, 2024
Short summary
Distinct structure, radiative effects, and precipitation characteristics of deep convection systems in the Tibetan Plateau compared to the tropical Indian Ocean
Yuxin Zhao, Jiming Li, Deyu Wen, Yarong Li, Yuan Wang, and Jianping Huang
Atmos. Chem. Phys., 24, 9435–9457, https://doi.org/10.5194/acp-24-9435-2024,https://doi.org/10.5194/acp-24-9435-2024, 2024
Short summary
The correlation between Arctic sea ice, cloud phase and radiation using A-Train satellites
Grégory V. Cesana, Olivia Pierpaoli, Matteo Ottaviani, Linh Vu, Zhonghai Jin, and Israel Silber
Atmos. Chem. Phys., 24, 7899–7909, https://doi.org/10.5194/acp-24-7899-2024,https://doi.org/10.5194/acp-24-7899-2024, 2024
Short summary
Technical note: Retrieval of the supercooled liquid fraction in mixed-phase clouds from Himawari-8 observations
Ziming Wang, Husi Letu, Huazhe Shang, and Luca Bugliaro
Atmos. Chem. Phys., 24, 7559–7574, https://doi.org/10.5194/acp-24-7559-2024,https://doi.org/10.5194/acp-24-7559-2024, 2024
Short summary
Characterisation of low-base and mid-base clouds and their thermodynamic phase over the Southern Ocean and Arctic marine regions
Barbara Dietel, Odran Sourdeval, and Corinna Hoose
Atmos. Chem. Phys., 24, 7359–7383, https://doi.org/10.5194/acp-24-7359-2024,https://doi.org/10.5194/acp-24-7359-2024, 2024
Short summary

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
Download
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.
Altmetrics
Final-revised paper
Preprint