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Aerosol-Cloud Interactions : Overcoming a Barrier to Projecting Near-Term Climate Evolution and Risk

Im, Ulas ; Samset, Bjørn H. ; Nenes, Athanasios ; Thomas, Jennie L. ; Kokkola, Harri ; Dubovik, Oleg ; Amiridis, Vassilis ; Arola, Antti ; Bellouin, Nicolas and Benedetti, Angela , et al. (2026) In AGU Advances 7(1).
Abstract

Aerosol-cloud interactions (ACI) are a major source of uncertainty in climate science, critically affecting our ability to project near-term climate evolution and assess societal risks. These interactions influence effective radiative forcing, cloud dynamics, and precipitation patterns, yet remain insufficiently constrained due to limitations in observations, modeling, and process understanding. This uncertainty hampers robust policy advice across multiple domains—from estimating remaining carbon budgets and climate sensitivity, to anticipating regional extreme events and evaluating climate interventions such as solar radiation modification. In many cases, the influence of ACI is either underappreciated or excluded from decision-making... (More)

Aerosol-cloud interactions (ACI) are a major source of uncertainty in climate science, critically affecting our ability to project near-term climate evolution and assess societal risks. These interactions influence effective radiative forcing, cloud dynamics, and precipitation patterns, yet remain insufficiently constrained due to limitations in observations, modeling, and process understanding. This uncertainty hampers robust policy advice across multiple domains—from estimating remaining carbon budgets and climate sensitivity, to anticipating regional extreme events and evaluating climate interventions such as solar radiation modification. In many cases, the influence of ACI is either underappreciated or excluded from decision-making frameworks due to its complexity and lack of quantification. This perspective outlines a path forward to overcome these barriers by leveraging emerging opportunities in satellite remote sensing, ground-based and airborne observations, high-resolution climate modeling, and machine learning. We identify key areas where rapid progress is feasible, including improved retrievals of cloud microphysical properties, better representation of natural aerosols in a warming world, and enhanced integration of observational and modeling communities. Even as anthropogenic aerosol and its impacts on clouds is reducing owing to emissions controls, addressing ACI uncertainties remains essential for refining climate projections, supporting effective mitigation and adaptation strategies, and delivering actionable science to policymakers in a rapidly changing climate system.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Aerosol-cloud interactions, climate change impacts, extreme events, radiative forcing, roadmap
in
AGU Advances
volume
7
issue
1
article number
e2025AV001872
publisher
John Wiley & Sons Inc.
external identifiers
  • scopus:105029759131
ISSN
2576-604X
DOI
10.1029/2025AV001872
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2026. The Author(s).
id
f33680ec-c297-4d9b-9b16-1948e6daed43
date added to LUP
2026-02-26 14:10:28
date last changed
2026-03-12 15:34:19
@article{f33680ec-c297-4d9b-9b16-1948e6daed43,
  abstract     = {{<p>Aerosol-cloud interactions (ACI) are a major source of uncertainty in climate science, critically affecting our ability to project near-term climate evolution and assess societal risks. These interactions influence effective radiative forcing, cloud dynamics, and precipitation patterns, yet remain insufficiently constrained due to limitations in observations, modeling, and process understanding. This uncertainty hampers robust policy advice across multiple domains—from estimating remaining carbon budgets and climate sensitivity, to anticipating regional extreme events and evaluating climate interventions such as solar radiation modification. In many cases, the influence of ACI is either underappreciated or excluded from decision-making frameworks due to its complexity and lack of quantification. This perspective outlines a path forward to overcome these barriers by leveraging emerging opportunities in satellite remote sensing, ground-based and airborne observations, high-resolution climate modeling, and machine learning. We identify key areas where rapid progress is feasible, including improved retrievals of cloud microphysical properties, better representation of natural aerosols in a warming world, and enhanced integration of observational and modeling communities. Even as anthropogenic aerosol and its impacts on clouds is reducing owing to emissions controls, addressing ACI uncertainties remains essential for refining climate projections, supporting effective mitigation and adaptation strategies, and delivering actionable science to policymakers in a rapidly changing climate system.</p>}},
  author       = {{Im, Ulas and Samset, Bjørn H. and Nenes, Athanasios and Thomas, Jennie L. and Kokkola, Harri and Dubovik, Oleg and Amiridis, Vassilis and Arola, Antti and Bellouin, Nicolas and Benedetti, Angela and Bilde, Merete and Blichner, Sara and Decesari, Stefano and Ekman, Annica M.L. and García-Pando, Carlos Pérez and Gross, Silke and Gryspeerdt, Edward and Hasekamp, Otto and Kahn, Ralph A. and Laakso, Anton and Lohmann, Ulrike and Marelle, Louis and Massling, Andreas H. and Myhre, Cathrine Lund and Pöhlker, Mira and Quaas, Johannes and Raatikainen, Tomi and Riipinen, Ilona and Schmale, Julia and Seifert, Patric and Skov, Henrik and Smith, Chris and Sporre, Moa K. and Stier, Philip and Storelvmo, Trude and Tsigaridis, Kostas and van Diedenhoven, Bastiaan and Virtanen, Annele and Wandinger, Ulla and Wilcox, Laura J. and Zieger, Paul}},
  issn         = {{2576-604X}},
  keywords     = {{Aerosol-cloud interactions; climate change impacts; extreme events; radiative forcing; roadmap}},
  language     = {{eng}},
  month        = {{02}},
  number       = {{1}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{AGU Advances}},
  title        = {{Aerosol-Cloud Interactions : Overcoming a Barrier to Projecting Near-Term Climate Evolution and Risk}},
  url          = {{http://dx.doi.org/10.1029/2025AV001872}},
  doi          = {{10.1029/2025AV001872}},
  volume       = {{7}},
  year         = {{2026}},
}