Articles | Volume 23, issue 20
https://doi.org/10.5194/acp-23-13523-2023
https://doi.org/10.5194/acp-23-13523-2023
Research article
 | 
27 Oct 2023
Research article |  | 27 Oct 2023

Evaluation of liquid cloud albedo susceptibility in E3SM using coupled eastern North Atlantic surface and satellite retrievals

Adam C. Varble, Po-Lun Ma, Matthew W. Christensen, Johannes Mülmenstädt, Shuaiqi Tang, and Jerome Fast

Related authors

General circulation models simulate negative liquid water path–droplet number correlations, but anthropogenic aerosols still increase simulated liquid water path
Johannes Mülmenstädt, Edward Gryspeerdt, Sudhakar Dipu, Johannes Quaas, Andrew S. Ackerman, Ann M. Fridlind, Florian Tornow, Susanne E. Bauer, Andrew Gettelman, Yi Ming, Youtong Zheng, Po-Lun Ma, Hailong Wang, Kai Zhang, Matthew W. Christensen, Adam C. Varble, L. Ruby Leung, Xiaohong Liu, David Neubauer, Daniel G. Partridge, Philip Stier, and Toshihiko Takemura
Atmos. Chem. Phys., 24, 7331–7345, https://doi.org/10.5194/acp-24-7331-2024,https://doi.org/10.5194/acp-24-7331-2024, 2024
Short summary
Atmospheric Radiation Measurement (ARM) airborne field campaign data products between 2013 and 2018
Fan Mei, Jennifer M. Comstock, Mikhail S. Pekour, Jerome D. Fast, Beat Schmid, Krista L. Gaustad, Shuaiqi Tang, Damao Zhang, John E. Shilling, Jason Tomlinson, Adam C. Varble, Jian Wang, L. Ruby Leung, Lawrence Kleinman, Scot Martin, Sebastien C. Biraud, Brian D. Ermold, and Kenneth W. Burk
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-97,https://doi.org/10.5194/essd-2024-97, 2024
Preprint under review for ESSD
Short summary
Aerosol-induced closure of marine cloud cells: enhanced effects in the presence of precipitation
Matthew W. Christensen, Peng Wu, Adam C. Varble, Heng Xiao, and Jerome D. Fast
Atmos. Chem. Phys., 24, 6455–6476, https://doi.org/10.5194/acp-24-6455-2024,https://doi.org/10.5194/acp-24-6455-2024, 2024
Short summary
Large Spatiotemporal Variability in Aerosol Properties over Central Argentina during the CACTI Field Campaign
Jerome D. Fast, Adam C. Varble, Fan Mei, Mikhail Pekour, Jason Tomlinson, Alla Zelenyuk, Art J. Sedlacek III, Maria Zawadowicz, and Louisa K. Emmons
EGUsphere, https://doi.org/10.5194/egusphere-2024-1349,https://doi.org/10.5194/egusphere-2024-1349, 2024
Short summary
Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol–cloud interactions
Charlotte M. Beall, Po-Lun Ma, Matthew W. Christensen, Johannes Mülmenstädt, Adam Varble, Kentaroh Suzuki, and Takuro Michibata
Atmos. Chem. Phys., 24, 5287–5302, https://doi.org/10.5194/acp-24-5287-2024,https://doi.org/10.5194/acp-24-5287-2024, 2024
Short summary

Related subject area

Subject: Radiation | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
A sensitivity study on radiative effects due to the parameterization of dust optical properties in models
Ilias Fountoulakis, Alexandra Tsekeri, Stelios Kazadzis, Vassilis Amiridis, Angelos Nersesian, Maria Tsichla, Emmanouil Proestakis, Antonis Gkikas, Kyriakoula Papachristopoulou, Vasileios Barlakas, Claudia Emde, and Bernhard Mayer
Atmos. Chem. Phys., 24, 4915–4948, https://doi.org/10.5194/acp-24-4915-2024,https://doi.org/10.5194/acp-24-4915-2024, 2024
Short summary
Uncertainties in cloud-radiative heating within an idealized extratropical cyclone
Behrooz Keshtgar, Aiko Voigt, Bernhard Mayer, and Corinna Hoose
Atmos. Chem. Phys., 24, 4751–4769, https://doi.org/10.5194/acp-24-4751-2024,https://doi.org/10.5194/acp-24-4751-2024, 2024
Short summary
Evaluation of downward and upward solar irradiances simulated by the Integrated Forecasting System of ECMWF using airborne observations above Arctic low-level clouds
Hanno Müller, André Ehrlich, Evelyn Jäkel, Johannes Röttenbacher, Benjamin Kirbus, Michael Schäfer, Robin J. Hogan, and Manfred Wendisch
Atmos. Chem. Phys., 24, 4157–4175, https://doi.org/10.5194/acp-24-4157-2024,https://doi.org/10.5194/acp-24-4157-2024, 2024
Short summary
Decadal trends in observed surface solar radiation and their causes in Brazil in the first two decades of the 21st century
Lucas Ferreira Correa, Doris Folini, Boriana Chtirkova, and Martin Wild
EGUsphere, https://doi.org/10.5194/egusphere-2024-509,https://doi.org/10.5194/egusphere-2024-509, 2024
Short summary
A colorful look at climate sensitivity
Bjorn Stevens and Lukas Kluft
Atmos. Chem. Phys., 23, 14673–14689, https://doi.org/10.5194/acp-23-14673-2023,https://doi.org/10.5194/acp-23-14673-2023, 2023
Short summary

Cited articles

Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation: 2. Multiple aerosol types, J. Geophys. Res., 105, 6837–6844, https://doi.org/10.1029/1999JD901161, 2000. 
Ackerman, A. S., Kirkpatrick, M. P., Stevens, D. E., and Toon, O. B.: The impact of humidity above stratiform clouds on indirect aerosol climate forcing, Nature, 432, 1014–1017, https://doi.org/10.1038/nature03174, 2004. 
Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989. 
ARM – Atmospheric Radiation Measurement user facility: Interpolated Sonde (INTERPOLATEDSONDE), 2016-01-01 to 2020-12-31, Eastern North Atlantic (ENA) Graciosa Island, Azores, Portugal (C1), compiled by: Jensen, M., Giangrande, S., Fairless, T., and Zhou, A., ARM Data Center [data set], https://doi.org/10.5439/1095316, 2013a.  
ARM – Atmospheric Radiation Measurement user facility: Minnis Cloud Products Using Visst Algorithm (VISSTGRIDM10MINNIS), 2016-01-01 to 2018-02-20, Eastern North Atlantic (ENA) External Data (satellites and others) (X1), ARM Data Center [data set], https://adc.arm.gov/discovery/#/results/datastream::enavisstgridm10minnisX1.c1 (last access: 12 August 2021), 2013b. 
Download
Short summary
We evaluate how clouds change in response to changing atmospheric particle (aerosol) concentrations in a climate model and find that the model-predicted cloud brightness increases too much as aerosols increase because the cloud drop number increases too much. Excessive drizzle in the model mutes this difference. Many differences between observational and model estimates are explained by varying assumptions of how much liquid has been lost in clouds, which impacts the estimated cloud drop number.
Altmetrics
Final-revised paper
Preprint