Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 23, issue 21
Articles | Volume 23, issue 21
https://doi.org/10.5194/acp-23-13791-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-23-13791-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 21
Opinion
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06 Nov 2023
Opinion | Highlight paper |  | 06 Nov 2023

Opinion: A critical evaluation of the evidence for aerosol invigoration of deep convection

Adam C. Varble, Adele L. Igel, Hugh Morrison, Wojciech W. Grabowski, and Zachary J. Lebo

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This provocative opinion piece examines the theoretical, numerical, and observational evidence in support of two highly cited proposed mechanisms for invigorating deep convective clouds through higher aerosol concentrations. Both start with high concentrations of water droplets. Through cold-phase invigoration, precipitation is reduced allowing for greater release of latent heat from freezing higher up in clouds. With warm-phase invigoration, increased latent heating occurs lower down due to accelerated liquid condensation. In both cases, the article persuasively argues from a variety of standpoints that the evidence to support the importance of the effects is weak, particularly once the full complexity of clouds and their interactions with their environment is fully taken into account. Concrete suggestions are made for improving definition, observations, and modeling of the problem, but also an admonishment that attention in the field might be better directed towards more fruitful aspects of the aerosol-cloud interaction problem.
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As atmospheric particles called aerosols increase in number, the number of droplets in clouds tends to increase, which has been theorized to increase storm intensity. We critically evaluate the evidence for this theory, showing that flaws and limitations of previous studies coupled with unaddressed cloud process complexities draw it into question. We provide recommendations for future observations and modeling to overcome current uncertainties.
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