Articles | Volume 26, issue 13
https://doi.org/10.5194/acp-26-9337-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-9337-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
02 Jul 2026
Research article |
| 02 Jul 2026
| 02 Jul 2026
The remarkable inefficiency of stratocumulus
Benjamin Hernandez
CORRESPONDING AUTHOR
Geoscience and Remote Sensing, Delft University of Technology, Delft, the Netherlands
Martin S. Singh
School of Earth, Atmosphere, and Environment, Monash University, Melbourne, Australia
Takanobu Yamaguchi
Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USA
Chemical Sciences Laboratory, NOAA, Boulder, Colorado, USA
Graham Feingold
Chemical Sciences Laboratory, NOAA, Boulder, Colorado, USA
Franziska Glassmeier
Geoscience and Remote Sensing, Delft University of Technology, Delft, the Netherlands
Max Planck Institute for Meteorology, Hamburg, Germany
Related authors
No articles found.
Netta Yeheskel, Matthew W. Christensen, Fabian Hoffmann, Graham Feingold, and Guy Dagan
Atmos. Chem. Phys., 26, 8765–8781, https://doi.org/10.5194/acp-26-8765-2026, https://doi.org/10.5194/acp-26-8765-2026, 2026
Short summary
Short summary
Aerosols influence cloud formation, structure, and radiative effects. As air masses move from the subtropics to the tropics, clouds transition from shallow to deeper systems. Using five years of satellite observations and numerical simulations, we find a robust aerosol impact on this Lagrangian cloud evolution: higher aerosol levels produce thicker, more reflective clouds, enhancing cooling and modifying energy and moisture transport toward the tropics.
Rebecca Gjini, Matthias Morzfeld, Franziska Glassmeier, and Graham Feingold
EGUsphere, https://doi.org/10.5194/egusphere-2026-2871, https://doi.org/10.5194/egusphere-2026-2871, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
We connect two very different types of precipitating stratocumulus cloud models. The first model is a high-resolution simulation that can realistically represent clouds. The second model is a simple, 1D equation that interprets clouds as prey and rain as the predator of clouds. We evaluate the extent to which a simplified cloud model can represent selected aspects of a realistic cloud simulation under different meteorological conditions, highlighting both successes and limitations.
Tom Goren, Goutam Choudhury, and Graham Feingold
Atmos. Chem. Phys., 26, 7193–7206, https://doi.org/10.5194/acp-26-7193-2026, https://doi.org/10.5194/acp-26-7193-2026, 2026
Short summary
Short summary
We introduce a new way to describe marine low cloud morphologies as a continuous range rather than discrete types. Using this approach, we show that cloud brightness responses to changes in droplet concentrations vary strongly across cloud morphologies, but the overall effect is small. This suggests that marine cloud brightening may rely more on increasing cloud cover than on making existing clouds brighter.
Jianhao Zhang, David Painemal, Tom Dror, Jung-Sub Lim, Armin Sorooshian, and Graham Feingold
Atmos. Chem. Phys., 26, 6015–6034, https://doi.org/10.5194/acp-26-6015-2026, https://doi.org/10.5194/acp-26-6015-2026, 2026
Short summary
Short summary
Clouds transitioning from overcast to broken fields play an important role in regulating the amount of sunlight reaching Earth’s surface. Using satellite imagery and a novel space-time exchange approach, we examine these transitions during marine cold-air outbreaks. Our analysis reveals characteristic signatures (or fingerprints) of liquid- and ice-phase processes, demonstrating how space-borne observations can provide new physical insight into cloud evolution.
Prasanth Prabhakaran, Timothy A. Myers, Fabian Hoffmann, and Graham Feingold
Atmos. Chem. Phys., 26, 5151–5167, https://doi.org/10.5194/acp-26-5151-2026, https://doi.org/10.5194/acp-26-5151-2026, 2026
Short summary
Short summary
We explore how climate change and aerosol affect the evolution of marine low-clouds. Using high-resolution simulations, we find that warming has a stronger impact on these clouds, but aerosol becomes more important after the clouds form precipitation. Our results suggest that attempts to brighten these clouds using aerosol may become less effective in a warmer future due to the decrease in cloud cover.
Muhamad Reyhan Respati, Martin S. Singh, and Christian Jakob
EGUsphere, https://doi.org/10.5194/egusphere-2026-1981, https://doi.org/10.5194/egusphere-2026-1981, 2026
Short summary
Short summary
Unlike in the extratropics, there is no standard way to classify tropical weather systems. We introduce a new classification based on how fast a system moves and the relative importance of moisture and buoyancy in its driving mechanisms. We find that systems for which moisture is a key driver contribute up to 75 % of extreme rainfall in certain areas. This new model provides a much-needed "roadmap" for scientists to understand how tropical dynamics and rainfall are connected across the globe.
Lucinda A. Palmer and Martin S. Singh
Weather Clim. Dynam., 6, 1565–1582, https://doi.org/10.5194/wcd-6-1565-2025, https://doi.org/10.5194/wcd-6-1565-2025, 2025
Short summary
Short summary
This study investigates the relationship between stability and humidity in the tropical troposphere in global climate models. We develop a method for quantifying the relationship and find varying relationships that are similar or even opposite to observations. We theorise that measures of intense thunderstorms and humid heatwaves are influenced by the stability-humidity relationship. Models that have a relationship like observations project greater increases in these measures under warming.
Isabel L. McCoy, Sunil Baidar, Paquita Zuidema, Jan Kazil, W. Alan Brewer, Wayne M. Angevine, and Graham Feingold
Atmos. Chem. Phys., 25, 16233–16261, https://doi.org/10.5194/acp-25-16233-2025, https://doi.org/10.5194/acp-25-16233-2025, 2025
Short summary
Short summary
We use ship observations to investigate the dynamics of small clouds over the tropical oceans. When these cumulus clouds cluster together, they more efficiently move moisture into the cloud layer due to strengthened updrafts. This encourages further clustering, increases local cloud development success, and may help sustain clouds against diurnal variations in their environment. These results have implications for cumulus feedback on the climate, a significant uncertainty in future projections.
Graham Feingold, Franziska Glassmeier, Jianhao Zhang, and Fabian Hoffmann
Atmos. Chem. Phys., 25, 10869–10885, https://doi.org/10.5194/acp-25-10869-2025, https://doi.org/10.5194/acp-25-10869-2025, 2025
Short summary
Short summary
Scientists usually use snapshots of atmospheric data to glean understanding of time-evolving atmospheric processes. We examine how much can be learned about processes from snapshots using examples from cloud and atmospheric physics. We couch the analysis in terms of the theory of ergodic systems, space-time-exchange, and the Deborah number – concepts that are commonly applied in other branches of physics. We discuss the reasons for the varying degrees of success.
Fabian Hoffmann, Yao-Sheng Chen, and Graham Feingold
Atmos. Chem. Phys., 25, 8657–8670, https://doi.org/10.5194/acp-25-8657-2025, https://doi.org/10.5194/acp-25-8657-2025, 2025
Short summary
Short summary
Clouds reflect a substantial portion of the incoming solar radiation back into space. This capacity is determined by the number of cloud droplets, which in turn is influenced by the number of aerosol particles, forming the basis for aerosol–cloud–climate interactions. In this study, we use a simple entrainment parameterization to understand the effect of aerosol on cloud water in weakly and non-precipitating stratocumulus.
Yao-Sheng Chen, Prasanth Prabhakaran, Fabian Hoffmann, Jan Kazil, Takanobu Yamaguchi, and Graham Feingold
Atmos. Chem. Phys., 25, 6141–6159, https://doi.org/10.5194/acp-25-6141-2025, https://doi.org/10.5194/acp-25-6141-2025, 2025
Short summary
Short summary
Injecting sea salt aerosols into marine stratiform clouds can distribute the cloud water over more droplets in smaller sizes. This process is expected to make the clouds brighter, allowing them to reflect more sunlight back to space. However, it may also cause the clouds to lose water over time, reducing their ability to reflect sunlight. We use a computer model to show that the loss of cloud water occurs relatively quickly and does not completely offset the initial brightening.
Pouriya Alinaghi, Fredrik Jansson, Daniel A. Blázquez, and Franziska Glassmeier
Atmos. Chem. Phys., 25, 6121–6139, https://doi.org/10.5194/acp-25-6121-2025, https://doi.org/10.5194/acp-25-6121-2025, 2025
Short summary
Short summary
Shallow clouds in the trades are a major source of uncertainty in climate projections. These clouds organize into striking mesoscale patterns that are exactly what climate models lack. This study explores the origin of such patterns and investigates how variations in microscale properties control them. The importance of microscale effects is compared to that of large-scale forcing on the mesoscale organization of trade-cumulus fields.
Fabian Hoffmann, Franziska Glassmeier, and Graham Feingold
Atmos. Chem. Phys., 24, 13403–13412, https://doi.org/10.5194/acp-24-13403-2024, https://doi.org/10.5194/acp-24-13403-2024, 2024
Short summary
Short summary
Clouds constitute a major cooling influence on Earth's climate system by reflecting a large fraction of the incident solar radiation back to space. This ability is controlled by the number of cloud droplets, which is governed by the number of aerosol particles in the atmosphere, laying the foundation for so-called aerosol–cloud–climate interactions. In this study, a simple model to understand the effect of aerosol on cloud water is developed and applied.
Yao-Sheng Chen, Jianhao Zhang, Fabian Hoffmann, Takanobu Yamaguchi, Franziska Glassmeier, Xiaoli Zhou, and Graham Feingold
Atmos. Chem. Phys., 24, 12661–12685, https://doi.org/10.5194/acp-24-12661-2024, https://doi.org/10.5194/acp-24-12661-2024, 2024
Short summary
Short summary
Marine stratocumulus cloud is a type of shallow cloud that covers the vast areas of Earth's surface. It plays an important role in Earth's energy balance by reflecting solar radiation back to space. We used numerical models to simulate a large number of marine stratocumuli with different characteristics. We found that how the clouds develop throughout the day is affected by the level of humidity in the air above the clouds and how closely the clouds connect to the ocean surface.
Jianhao Zhang, Yao-Sheng Chen, Takanobu Yamaguchi, and Graham Feingold
Atmos. Chem. Phys., 24, 10425–10440, https://doi.org/10.5194/acp-24-10425-2024, https://doi.org/10.5194/acp-24-10425-2024, 2024
Short summary
Short summary
Quantifying cloud response to aerosol perturbations presents a major challenge in understanding the human impact on climate. Using a large number of process-resolving simulations of marine stratocumulus, we show that solar heating drives a negative feedback mechanism that buffers the persistent negative trend in cloud water adjustment after sunrise. This finding has implications for the dependence of the cloud cooling effect on the timing of deliberate aerosol perturbations.
Prasanth Prabhakaran, Fabian Hoffmann, and Graham Feingold
Atmos. Chem. Phys., 24, 1919–1937, https://doi.org/10.5194/acp-24-1919-2024, https://doi.org/10.5194/acp-24-1919-2024, 2024
Short summary
Short summary
In this study, we explore the impact of deliberate aerosol perturbation in the northeast Pacific region using large-eddy simulations. Our results show that cloud reflectivity is sensitive to the aerosol sprayer arrangement in the pristine system, whereas in the polluted system it is largely proportional to the total number of aerosol particles injected. These insights would aid in assessing the efficiency of various aerosol injection strategies for climate intervention applications.
Hong Chen, K. Sebastian Schmidt, Steven T. Massie, Vikas Nataraja, Matthew S. Norgren, Jake J. Gristey, Graham Feingold, Robert E. Holz, and Hironobu Iwabuchi
Atmos. Meas. Tech., 16, 1971–2000, https://doi.org/10.5194/amt-16-1971-2023, https://doi.org/10.5194/amt-16-1971-2023, 2023
Short summary
Short summary
We introduce the Education and Research 3D Radiative Transfer Toolbox (EaR3T) and propose a radiance self-consistency approach for quantifying and mitigating 3D bias in legacy airborne and spaceborne imagery retrievals due to spatially inhomogeneous clouds and surfaces.
Jianhao Zhang and Graham Feingold
Atmos. Chem. Phys., 23, 1073–1090, https://doi.org/10.5194/acp-23-1073-2023, https://doi.org/10.5194/acp-23-1073-2023, 2023
Short summary
Short summary
Using observations from space, we show maps of potential brightness changes in marine warm clouds in response to increases in cloud droplet concentrations. The environmental and aerosol conditions in which these clouds reside covary differently in each ocean basin, leading to distinct evolutions of cloud brightness changes. This work stresses the central importance of the covariability between meteorology and aerosol for scaling up the radiative response of cloud brightness changes.
Michael S. Diamond, Pablo E. Saide, Paquita Zuidema, Andrew S. Ackerman, Sarah J. Doherty, Ann M. Fridlind, Hamish Gordon, Calvin Howes, Jan Kazil, Takanobu Yamaguchi, Jianhao Zhang, Graham Feingold, and Robert Wood
Atmos. Chem. Phys., 22, 12113–12151, https://doi.org/10.5194/acp-22-12113-2022, https://doi.org/10.5194/acp-22-12113-2022, 2022
Short summary
Short summary
Smoke from southern Africa blankets the southeast Atlantic from June-October, overlying a major transition region between overcast and scattered clouds. The smoke affects Earth's radiation budget by absorbing sunlight and changing cloud properties. We investigate these effects in regional climate and large eddy simulation models based on international field campaigns. We find that large-scale circulation changes more strongly affect cloud transitions than smoke microphysical effects in our case.
Vikas Nataraja, Sebastian Schmidt, Hong Chen, Takanobu Yamaguchi, Jan Kazil, Graham Feingold, Kevin Wolf, and Hironobu Iwabuchi
Atmos. Meas. Tech., 15, 5181–5205, https://doi.org/10.5194/amt-15-5181-2022, https://doi.org/10.5194/amt-15-5181-2022, 2022
Short summary
Short summary
A convolutional neural network (CNN) is introduced to retrieve cloud optical thickness (COT) from passive cloud imagery. The CNN, trained on large eddy simulations from the Sulu Sea, learns from spatial information at multiple scales to reduce cloud inhomogeneity effects. By considering the spatial context of a pixel, the CNN outperforms the traditional independent pixel approximation (IPA) across several cloud morphology metrics.
Edward Gryspeerdt, Franziska Glassmeier, Graham Feingold, Fabian Hoffmann, and Rebecca J. Murray-Watson
Atmos. Chem. Phys., 22, 11727–11738, https://doi.org/10.5194/acp-22-11727-2022, https://doi.org/10.5194/acp-22-11727-2022, 2022
Short summary
Short summary
The response of clouds to changes in aerosol remains a large uncertainty in our understanding of the climate. Studies typically look at aerosol and cloud processes in snapshot images, measuring all properties at the same time. Here we use multiple images to characterise how cloud temporal development responds to aerosol. We find a reduction in liquid water path with increasing aerosol, party due to feedbacks. This suggests the aerosol impact on cloud water may be weaker than in previous studies.
Graham Feingold, Tom Goren, and Takanobu Yamaguchi
Atmos. Chem. Phys., 22, 3303–3319, https://doi.org/10.5194/acp-22-3303-2022, https://doi.org/10.5194/acp-22-3303-2022, 2022
Short summary
Short summary
The evaluation of radiative forcing associated with aerosol–cloud interactions remains a significant source of uncertainty in future climate projections. Using high-resolution numerical model output, we mimic typical satellite retrieval methodologies to show that data aggregation can introduce significant error (hundreds of percent) in the cloud albedo susceptibility metric. Spatial aggregation errors tend to be countered by temporal aggregation errors.
Jianhao Zhang, Xiaoli Zhou, Tom Goren, and Graham Feingold
Atmos. Chem. Phys., 22, 861–880, https://doi.org/10.5194/acp-22-861-2022, https://doi.org/10.5194/acp-22-861-2022, 2022
Short summary
Short summary
Oceanic liquid-form clouds are effective sunlight reflectors. Their brightness is highly sensitive to changes in the amount of aerosol particles in the atmosphere and the state of the atmosphere they reside in. This study quantifies this sensitivity using long-term satellite observations and finds an overall cloud brightening (a cooling effect) potential and an essential role of the covarying meteorological conditions in governing this sensitivity for northeastern Pacific stratocumulus.
Matthew W. Christensen, Andrew Gettelman, Jan Cermak, Guy Dagan, Michael Diamond, Alyson Douglas, Graham Feingold, Franziska Glassmeier, Tom Goren, Daniel P. Grosvenor, Edward Gryspeerdt, Ralph Kahn, Zhanqing Li, Po-Lun Ma, Florent Malavelle, Isabel L. McCoy, Daniel T. McCoy, Greg McFarquhar, Johannes Mülmenstädt, Sandip Pal, Anna Possner, Adam Povey, Johannes Quaas, Daniel Rosenfeld, Anja Schmidt, Roland Schrödner, Armin Sorooshian, Philip Stier, Velle Toll, Duncan Watson-Parris, Robert Wood, Mingxi Yang, and Tianle Yuan
Atmos. Chem. Phys., 22, 641–674, https://doi.org/10.5194/acp-22-641-2022, https://doi.org/10.5194/acp-22-641-2022, 2022
Short summary
Short summary
Trace gases and aerosols (tiny airborne particles) are released from a variety of point sources around the globe. Examples include volcanoes, industrial chimneys, forest fires, and ship stacks. These sources provide opportunistic experiments with which to quantify the role of aerosols in modifying cloud properties. We review the current state of understanding on the influence of aerosol on climate built from the wide range of natural and anthropogenic laboratories investigated in recent decades.
Bjorn Stevens, Sandrine Bony, David Farrell, Felix Ament, Alan Blyth, Christopher Fairall, Johannes Karstensen, Patricia K. Quinn, Sabrina Speich, Claudia Acquistapace, Franziska Aemisegger, Anna Lea Albright, Hugo Bellenger, Eberhard Bodenschatz, Kathy-Ann Caesar, Rebecca Chewitt-Lucas, Gijs de Boer, Julien Delanoë, Leif Denby, Florian Ewald, Benjamin Fildier, Marvin Forde, Geet George, Silke Gross, Martin Hagen, Andrea Hausold, Karen J. Heywood, Lutz Hirsch, Marek Jacob, Friedhelm Jansen, Stefan Kinne, Daniel Klocke, Tobias Kölling, Heike Konow, Marie Lothon, Wiebke Mohr, Ann Kristin Naumann, Louise Nuijens, Léa Olivier, Robert Pincus, Mira Pöhlker, Gilles Reverdin, Gregory Roberts, Sabrina Schnitt, Hauke Schulz, A. Pier Siebesma, Claudia Christine Stephan, Peter Sullivan, Ludovic Touzé-Peiffer, Jessica Vial, Raphaela Vogel, Paquita Zuidema, Nicola Alexander, Lyndon Alves, Sophian Arixi, Hamish Asmath, Gholamhossein Bagheri, Katharina Baier, Adriana Bailey, Dariusz Baranowski, Alexandre Baron, Sébastien Barrau, Paul A. Barrett, Frédéric Batier, Andreas Behrendt, Arne Bendinger, Florent Beucher, Sebastien Bigorre, Edmund Blades, Peter Blossey, Olivier Bock, Steven Böing, Pierre Bosser, Denis Bourras, Pascale Bouruet-Aubertot, Keith Bower, Pierre Branellec, Hubert Branger, Michal Brennek, Alan Brewer, Pierre-Etienne Brilouet, Björn Brügmann, Stefan A. Buehler, Elmo Burke, Ralph Burton, Radiance Calmer, Jean-Christophe Canonici, Xavier Carton, Gregory Cato Jr., Jude Andre Charles, Patrick Chazette, Yanxu Chen, Michal T. Chilinski, Thomas Choularton, Patrick Chuang, Shamal Clarke, Hugh Coe, Céline Cornet, Pierre Coutris, Fleur Couvreux, Susanne Crewell, Timothy Cronin, Zhiqiang Cui, Yannis Cuypers, Alton Daley, Gillian M. Damerell, Thibaut Dauhut, Hartwig Deneke, Jean-Philippe Desbios, Steffen Dörner, Sebastian Donner, Vincent Douet, Kyla Drushka, Marina Dütsch, André Ehrlich, Kerry Emanuel, Alexandros Emmanouilidis, Jean-Claude Etienne, Sheryl Etienne-Leblanc, Ghislain Faure, Graham Feingold, Luca Ferrero, Andreas Fix, Cyrille Flamant, Piotr Jacek Flatau, Gregory R. Foltz, Linda Forster, Iulian Furtuna, Alan Gadian, Joseph Galewsky, Martin Gallagher, Peter Gallimore, Cassandra Gaston, Chelle Gentemann, Nicolas Geyskens, Andreas Giez, John Gollop, Isabelle Gouirand, Christophe Gourbeyre, Dörte de Graaf, Geiske E. de Groot, Robert Grosz, Johannes Güttler, Manuel Gutleben, Kashawn Hall, George Harris, Kevin C. Helfer, Dean Henze, Calvert Herbert, Bruna Holanda, Antonio Ibanez-Landeta, Janet Intrieri, Suneil Iyer, Fabrice Julien, Heike Kalesse, Jan Kazil, Alexander Kellman, Abiel T. Kidane, Ulrike Kirchner, Marcus Klingebiel, Mareike Körner, Leslie Ann Kremper, Jan Kretzschmar, Ovid Krüger, Wojciech Kumala, Armin Kurz, Pierre L'Hégaret, Matthieu Labaste, Tom Lachlan-Cope, Arlene Laing, Peter Landschützer, Theresa Lang, Diego Lange, Ingo Lange, Clément Laplace, Gauke Lavik, Rémi Laxenaire, Caroline Le Bihan, Mason Leandro, Nathalie Lefevre, Marius Lena, Donald Lenschow, Qiang Li, Gary Lloyd, Sebastian Los, Niccolò Losi, Oscar Lovell, Christopher Luneau, Przemyslaw Makuch, Szymon Malinowski, Gaston Manta, Eleni Marinou, Nicholas Marsden, Sebastien Masson, Nicolas Maury, Bernhard Mayer, Margarette Mayers-Als, Christophe Mazel, Wayne McGeary, James C. McWilliams, Mario Mech, Melina Mehlmann, Agostino Niyonkuru Meroni, Theresa Mieslinger, Andreas Minikin, Peter Minnett, Gregor Möller, Yanmichel Morfa Avalos, Caroline Muller, Ionela Musat, Anna Napoli, Almuth Neuberger, Christophe Noisel, David Noone, Freja Nordsiek, Jakub L. Nowak, Lothar Oswald, Douglas J. Parker, Carolyn Peck, Renaud Person, Miriam Philippi, Albert Plueddemann, Christopher Pöhlker, Veronika Pörtge, Ulrich Pöschl, Lawrence Pologne, Michał Posyniak, Marc Prange, Estefanía Quiñones Meléndez, Jule Radtke, Karim Ramage, Jens Reimann, Lionel Renault, Klaus Reus, Ashford Reyes, Joachim Ribbe, Maximilian Ringel, Markus Ritschel, Cesar B. Rocha, Nicolas Rochetin, Johannes Röttenbacher, Callum Rollo, Haley Royer, Pauline Sadoulet, Leo Saffin, Sanola Sandiford, Irina Sandu, Michael Schäfer, Vera Schemann, Imke Schirmacher, Oliver Schlenczek, Jerome Schmidt, Marcel Schröder, Alfons Schwarzenboeck, Andrea Sealy, Christoph J. Senff, Ilya Serikov, Samkeyat Shohan, Elizabeth Siddle, Alexander Smirnov, Florian Späth, Branden Spooner, M. Katharina Stolla, Wojciech Szkółka, Simon P. de Szoeke, Stéphane Tarot, Eleni Tetoni, Elizabeth Thompson, Jim Thomson, Lorenzo Tomassini, Julien Totems, Alma Anna Ubele, Leonie Villiger, Jan von Arx, Thomas Wagner, Andi Walther, Ben Webber, Manfred Wendisch, Shanice Whitehall, Anton Wiltshire, Allison A. Wing, Martin Wirth, Jonathan Wiskandt, Kevin Wolf, Ludwig Worbes, Ethan Wright, Volker Wulfmeyer, Shanea Young, Chidong Zhang, Dongxiao Zhang, Florian Ziemen, Tobias Zinner, and Martin Zöger
Earth Syst. Sci. Data, 13, 4067–4119, https://doi.org/10.5194/essd-13-4067-2021, https://doi.org/10.5194/essd-13-4067-2021, 2021
Short summary
Short summary
The EUREC4A field campaign, designed to test hypothesized mechanisms by which clouds respond to warming and benchmark next-generation Earth-system models, is presented. EUREC4A comprised roughly 5 weeks of measurements in the downstream winter trades of the North Atlantic – eastward and southeastward of Barbados. It was the first campaign that attempted to characterize the full range of processes and scales influencing trade wind clouds.
Robert Pincus, Chris W. Fairall, Adriana Bailey, Haonan Chen, Patrick Y. Chuang, Gijs de Boer, Graham Feingold, Dean Henze, Quinn T. Kalen, Jan Kazil, Mason Leandro, Ashley Lundry, Ken Moran, Dana A. Naeher, David Noone, Akshar J. Patel, Sergio Pezoa, Ivan PopStefanija, Elizabeth J. Thompson, James Warnecke, and Paquita Zuidema
Earth Syst. Sci. Data, 13, 3281–3296, https://doi.org/10.5194/essd-13-3281-2021, https://doi.org/10.5194/essd-13-3281-2021, 2021
Short summary
Short summary
This paper describes observations taken from a research aircraft during a field experiment in the western Atlantic Ocean during January and February 2020. The plane made 11 flights, most 8-9 h long, and measured the properties of the atmosphere and ocean with a combination of direct measurements, sensors falling from the plane to profile the atmosphere and ocean, and remote sensing measurements of clouds and the ocean surface.
Cited articles
Alinaghi, P., Janssens, M., and Jansson, F.: Warming from cold pools: a pathway for mesoscale organization to alter Earth's radiation budget, P. Natl. Acad. Sci. USA USA, 122, e2513699122, https://doi.org/10.1073/pnas.2513699122, 2025. a
Baker, M. B. and Charlson, R. J.: Bistability of CCN concentrations and thermodynamics in the cloud-topped boundary layer, Nature, 345, 142–145, https://doi.org/10.1038/345142a0, 1990. a
Bony, S. and Dufresne, J.-L.: Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models, Geophys. Res. Lett., 32, L20806, https://doi.org/10.1029/2005GL023851, 2005. a
Bretherton, C. S., Blossey, P. N., and Khairoutdinov, M.: An Energy-balance analysis of deep convective self-aggregation above uniform SST, J. Atmos. Sci., 62, 4273–4292, https://doi.org/10.1175/JAS3614.1, 2005. a
Bretherton, C. S., Uchida, J., and Blossey, P. N.: Slow manifolds and multiple equilibria in stratocumulus-capped boundary layers, J. Adv. Model. Earth Sy., 2, 14, https://doi.org/10.3894/JAMES.2010.2.14, 2010. a, b
Ceppi, P., Myers, T. A., Nowack, P., Wall, C. J., and Zelinka, M. D.: Implications of a pervasive climate model bias for low-cloud feedback, Geophys. Res. Lett., 51, e2024GL110525, https://doi.org/10.1029/2024GL110525, 2024. a
Chen, Y.-S., Prabhakaran, P., Hoffmann, F., Kazil, J., Yamaguchi, T., and Feingold, G.: Magnitude and timescale of liquid water path adjustments to cloud droplet number concentration perturbations for nocturnal non-precipitating marine stratocumulus, Atmos. Chem. Phys., 25, 6141–6159, https://doi.org/10.5194/acp-25-6141-2025, 2025. a
de Groot, S. R. and Mazur, P.: Non-Equilibrium Thermodynamics, Courier Corporation, ISBN 9780486153506, 2013. a
Eastman, R., Wood, R., and Bretherton, C. S.: Time scales of clouds and cloud-controlling variables in subtropical stratocumulus from a Lagrangian perspective, J. Atmos. Sci., 73, 3079–3091, https://doi.org/10.1175/JAS-D-16-0050.1, 2016. a
Emanuel, K., Wing, A. A., and Vincent, E. M.: Radiative-convective instability, J. Adv. Model. Earth Sy., 6, 75–90, https://doi.org/10.1002/2013MS000270, 2014. a
Endres, R. G.: Entropy production selects nonequilibrium states in multistable systems, Sci. Rep., 7, 14437, https://doi.org/10.1038/s41598-017-14485-8, 2017. a
Fang, J., Pauluis, O., and Zhang, F.: Isentropic Analysis on the intensification of hurricane Edouard (2014), J. Atmos. Sci., 74, 4177–4197, https://doi.org/10.1175/JAS-D-17-0092.1, 2017. a
Feingold, G., Koren, I., Yamaguchi, T., and Kazil, J.: On the reversibility of transitions between closed and open cellular convection, Atmos. Chem. Phys., 15, 7351–7367, https://doi.org/10.5194/acp-15-7351-2015, 2015. a
Fiévet, R., Meyer, B., and Haerter, J. O.: On the sensitivity of convective cold pools to mesh resolution, J. Adv. Model. Earth Sy., 15, e2022MS003382, https://doi.org/10.1029/2022MS003382, 2023. a
Gaspard, P.: The Statistical Mechanics of Irreversible Phenomena, Cambridge University Press, Cambridge, https://doi.org/10.1017/9781108563055, 2022. a
Gassmann, A. and Herzog, H.-J.: How is local material entropy production represented in a numerical model?, Q. J. Roy. Meteor. Soc., 141, 854–869, https://doi.org/10.1002/qj.2404, 2015. a
Gibbins, G. and Haigh, J. D.: Entropy production rates of the climate, J. Atmos. Sci., 77, 3551–3566, https://doi.org/10.1175/JAS-D-19-0294.1, 2020. a
Glassmeier, F. and Feingold, G.: Network approach to patterns in stratocumulus clouds, P. Natl. Acad. Sci. USA, 114, 10578–10583, https://doi.org/10.1073/pnas.1706495114, 2017. a, b
Glassmeier, F., Hoffmann, F., Johnson, J. S., Yamaguchi, T., Carslaw, K. S., and Feingold, G.: An emulator approach to stratocumulus susceptibility, Atmos. Chem. Phys., 19, 10191–10203, https://doi.org/10.5194/acp-19-10191-2019, 2019. a, b, c, d
Glassmeier, F., Hoffmann, F., Johnson, J. S., Yamaguchi, T., Carslaw, K. S., and Feingold, G.: Aerosol-cloud-climate cooling overestimated by ship-track data, Science, 371, 485–489, https://doi.org/10.1126/science.abd3980, 2021. a, b, c
Goody, R.: Sources and sinks of climate entropy, Q. J. Roy. Meteor. Soc., 126, 1953–1970, https://doi.org/10.1002/qj.49712656619, 2000. a
Hahn, C. and Warren, S.: A Gridded Climatology of Clouds over Land (1971–1996) and Ocean (1954–2008) from Surface Observations Worldwide (NDP–026E), Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory [data set], https://doi.org/10.3334/CDIAC/CLI.NDP026E, 2007. a
Hauf, T. and Höller, H.: Entropy and potential temperature, J. Atmos. Sci., 44, 2887–2901, https://doi.org/10.1175/1520-0469(1987)044<2887:EAPT>2.0.CO;2, 1987. a
Hernandez, B.: HernandezBen/Code_Data_Entropy_ACP: Entropy_Production_ACP (Entropy_production_stratocumulus_ACP), Zenodo, https://doi.org/10.5281/zenodo.18662163, 2026. a
Hernandez, B. and Glassmeier, F.: Aerosol memory in stratocumulus clouds leads to noise-induced patterns and non-ergodic sampling, arXiv [preprint], https://doi.org/10.48550/arXiv.2605.04002, 2026. a
Hirt, M., Craig, G. C., Schäfer, S. A. K., Savre, J., and Heinze, R.: Cold-pool-driven convective initiation: using causal graph analysis to determine what convection-permitting models are missing, Q. J. Roy. Meteor. Soc., 146, 2205–2227, https://doi.org/10.1002/qj.3788, 2020. a
Hoffmann, F. and Feingold, G.: Entrainment and mixing in stratocumulus: effects of a new explicit subgrid-scale scheme for large-eddy simulations with particle-based microphysics, J. Atmos. Sci., 76, 1955–1973, https://doi.org/10.1175/JAS-D-18-0318.1, 2019. a
Hoffmann, F., Glassmeier, F., Yamaguchi, T., and Feingold, G.: Liquid water path steady states in stratocumulus: insights from process-level emulation and mixed-layer theory, J. Atmos. Sci., 77, 2203–2215, https://doi.org/10.1175/JAS-D-19-0241.1, 2020. a
Hoffmann, F., Glassmeier, F., and Feingold, G.: The impact of aerosol on cloud water: a heuristic perspective, Atmos. Chem. Phys., 24, 13403–13412, https://doi.org/10.5194/acp-24-13403-2024, 2024. a
Hoffmann, F., Chen, Y.-S., and Feingold, G.: On the processes determining the slope of cloud water adjustments in weakly and non-precipitating stratocumulus, Atmos. Chem. Phys., 25, 8657–8670, https://doi.org/10.5194/acp-25-8657-2025, 2025. a
Igel, M. R. and Igel, A. L.: The energetics and magnitude of hydrometeor friction in clouds, J. Atmos. Sci., 75, 1343–1350, https://doi.org/10.1175/JAS-D-17-0285.1, 2018. a
Kalmus, P., Lebsock, M., and Teixeira, J.: Observational boundary layer energy and water budgets of the stratocumulus-to-cumulus transition, J. Climate, 27, 9155–9170, https://doi.org/10.1175/JCLI-D-14-00242.1, 2014. a
Kato, S. and Rose, F. G.: Global and regional entropy production by radiation estimated from satellite observations, J. Climate, 33, 2985–3000, https://doi.org/10.1175/JCLI-D-19-0596.1, 2020. a
Kazil, J., Yamaguchi, T., and Feingold, G.: Mesoscale organization, entrainment, and the properties of a closed-cell stratocumulus cloud, J. Adv. Model. Earth Sy., 9, 2214–2229, https://doi.org/10.1002/2017MS001072, 2017. a
Khairoutdinov, M. F. and Randall, D. A.: Cloud resolving modeling of the ARM Summer 1997 IOP: model formulation, results, uncertainties, and sensitivities, J. Atmos. Sci., 60, 607–625, https://doi.org/10.1175/1520-0469(2003)060<0607:CRMOTA>2.0.CO;2, 2003. a, b
Kleidon, A.: Beyond Gaia: thermodynamics of life and earth system functioning, Climatic Change, 66, 271–319, https://doi.org/10.1023/B:CLIM.0000044616.34867.ec, 2004. a
Koren, I. and Feingold, G.: Aerosol–cloud–precipitation system as a predator-prey problem, P. Natl. Acad. Sci. USA, 108, 12227–12232, https://doi.org/10.1073/pnas.1101777108, 2011. a
Koren, I. and Feingold, G.: Adaptive behavior of marine cellular clouds, Sci. Rep., 3, 2507, https://doi.org/10.1038/srep02507, 2013. a
Laliberté, F., Zika, J., Mudryk, L., Kushner, P. J., Kjellsson, J., and Döös, K.: Constrained work output of the moist atmospheric heat engine in a warming climate, Science, 347, 540–543, https://doi.org/10.1126/science.1257103, 2015. a
Lilly, D. K.: Models of cloud-topped mixed layers under a strong inversion, Q. J. Roy. Meteor. Soc., 94, 292–309, https://doi.org/10.1002/qj.49709440106, 1968. a
Lucarini, V.: Thermodynamic efficiency and entropy production in the climate system, Phys. Rev. E, 80, 021118, https://doi.org/10.1103/PhysRevE.80.021118, 2009. a
Lucarini, V., Fraedrich, K., and Lunkeit, F.: Thermodynamic analysis of snowball Earth hysteresis experiment: efficiency, entropy production and irreversibility, Q. J. Roy. Meteor. Soc., 136, 2–11, https://doi.org/10.1002/qj.543, 2010. a
Morris, M. D. and Mitchell, T. J.: Exploratory designs for computational experiments, J. Stat. Plann. Inference, 43, 381–402, https://doi.org/10.1016/0378-3758(94)00035-T, 1995. a
Myers, T. A., Scott, R. C., Zelinka, M. D., Klein, S. A., Norris, J. R., and Caldwell, P. M.: Observational constraints on low cloud feedback reduce uncertainty of climate sensitivity, Nat. Clim. Change, 11, 501–507, https://doi.org/10.1038/s41558-021-01039-0, 2021. a
Onsager, L.: Reciprocal relations in irreversible processes. II., Phys. Rev., 38, 2265–2279, https://doi.org/10.1103/PhysRev.38.2265, 1931. a
Ozawa, H. and Shimokawa, S.: Thermodynamics of a tropical cyclone: generation and dissipation of mechanical energy in a self-driven convection system, Tellus A, 67, 24216, https://doi.org/10.3402/tellusa.v67.24216, 2015. a
Ozawa, H., Ohmura, A., Lorenz, R. D., and Pujol, T.: The second law of thermodynamics and the global climate system: a review of the maximum entropy production principle, Rev. Geophys., 41, 1018, https://doi.org/10.1029/2002RG000113, 2003. a
Paltridge, G. W.: Global dynamics and climate – a system of minimum entropy exchange, Q. J. Roy. Meteor. Soc., 101, 475–484, https://doi.org/10.1002/qj.49710142906, 1975. a, b
Pauluis, O.: Water vapor and mechanical work: a comparison of carnot and steam cycles, J. Atmos. Sci., 68, 91–102, https://doi.org/10.1175/2010JAS3530.1, 2011. a
Pauluis, O. M.: The mean air flow as Lagrangian dynamics approximation and its application to moist convection, J. Atmos. Sci., 73, 4407–4425, https://doi.org/10.1175/JAS-D-15-0284.1, 2016. a
Pauluis, O. M. and Zhang, F.: Reconstruction of thermodynamic cycles in a high-resolution simulation of a hurricane, J. Atmos. Sci., 74, 3367–3381, https://doi.org/10.1175/JAS-D-16-0353.1, 2017. a
Pauluis, O., Balaji, V., and Held, I. M.: Frictional Dissipation in a Precipitating Atmosphere, J. Atmos. Sci., 57, 989–994, https://doi.org/10.1175/1520-0469(2000)057<0989:FDIAPA>2.0.CO;2, 2000. a
Possner, A., Eastman, R., Bender, F., and Glassmeier, F.: Deconvolution of boundary layer depth and aerosol constraints on cloud water path in subtropical stratocumulus decks, Atmos. Chem. Phys., 20, 3609–3621, https://doi.org/10.5194/acp-20-3609-2020, 2020. a
Rennó, N. O. and Ingersoll, A. P.: Natural convection as a heat engine: a theory for CAPE, J. Atmos. Sci., 53, 572–585, https://doi.org/10.1175/1520-0469(1996)053<0572:NCAAHE>2.0.CO;2, 1996. a
Romps, D. M.: The dry-entropy budget of a moist atmosphere, J. Atmos. Sci., 65, 3779–3799, https://doi.org/10.1175/2008JAS2679.1, 2008. a, b
Régibeau-Rockett, L., Pauluis, O. M., and O'Neill, M. E.: Investigating the relationship between sea surface temperature and the mechanical efficiency of tropical cyclones, J. Climate, 37, 439–456, https://doi.org/10.1175/JCLI-D-22-0877.1, 2023. a
Savic-Jovcic, V. and Stevens, B.: The structure and mesoscale organization of precipitating stratocumulus, J. Atmos. Sci., 65, 1587–1605, https://doi.org/10.1175/2007JAS2456.1, 2008. a
Schubert, W. H., Wakefield, J. S., Steiner, E. J., and Cox, S. K.: Marine stratocumulus convection. Part II: Horizontally inhomogeneous solutions, J. Atmos. Sci., 36, 1308–1324, https://doi.org/10.1175/1520-0469(1979)036<1308:MSCPIH>2.0.CO;2, 1979. a, b
Stephens, G. L. and Greenwald, T. J.: The Earth's radiation budget and its relation to atmospheric hydrology: 2. Observations of cloud effects, J. Geophys. Res.-Atmos., 96, 15325–15340, https://doi.org/10.1029/91JD00972, 1991. a
Stephens, G. L. and O'Brien, D. M.: Entropy and climate. I: ERBE observations of the entropy production of the earth, Q. J. Roy. Meteor. Soc., 119, 121–152, https://doi.org/10.1002/qj.49711950906, 1993. a
Stevens, B., Moeng, C.-H., Ackerman, A. S., Bretherton, C. S., Chlond, A., de Roode, S., Edwards, J., Golaz, J.-C., Jiang, H., Khairoutdinov, M., Kirkpatrick, M. P., Lewellen, D. C., Lock, A., Müller, F., Stevens, D. E., Whelan, E., and Zhu, P.: Evaluation of large-eddy simulations via observations of nocturnal marine stratocumulus, Mon. Weather Rev., 133, 1443–1462, https://doi.org/10.1175/MWR2930.1, 2005. a, b
Stevens, D. E. and Bretherton, C. S.: Effects of resolution on the simulation of stratocumulus entrainment, Q. J. Roy. Meteor. Soc., 125, 425–439, https://doi.org/10.1002/qj.49712555403, 1999. a
Volk, T. and Pauluis, O.: It is not the entropy you produce, rather, how you produce it, Phil. Trans. R. Soc. Lond. B, 365, 1317–1322, https://doi.org/10.1098/rstb.2010.0019, 2010. a
Wang, H. and Feingold, G.: Modeling mesoscale cellular structures and drizzle in marine stratocumulus. Part I: Impact of drizzle on the formation and evolution of open cells, J. Atmos. Sci., 66, 3237–3256, https://doi.org/10.1175/2009JAS3022.1, 2009. a, b, c
Wood, R.: Stratocumulus clouds, Mon. Weather Rev., 140, 2373–2423, https://doi.org/10.1175/MWR-D-11-00121.1, 2012. a, b, c, d
Xue, H., Feingold, G., and Stevens, B.: Aerosol effects on clouds, precipitation, and the organization of shallow cumulus convection, J. Atmos. Sci., 65, 392–406, https://doi.org/10.1175/2007JAS2428.1, 2008. a
Short summary
Using detailed numerical simulations, we quantify how stratocumulus cloud decks dissipate energy and produce entropy. We find that entropy production is dominated by irreversible moist processes and is much smaller than in deeper convective clouds. As a result, stratocumulus are remarkably inefficient at converting available energy into atmospheric motions.
Using detailed numerical simulations, we quantify how stratocumulus cloud decks dissipate energy...
Altmetrics
Final-revised paper
Preprint