@article{Im:2026:10.1029/2025av001872,
author = {Im, U and Samset, BH and Nenes, A and Thomas, JL and Kokkola, H and Dubovik, O and Amiridis, V and Arola, A and Bellouin, N and Benedetti, A and Bilde, M and Blichner, S and Decesari, S and Ekman, AML and GarcíaPando, CP and Gross, S and Gryspeerdt, E and Hasekamp, O and Kahn, RA and Laakso, A and Lohmann, U and Marelle, L and Massling, AH and Myhre, CL and Pöhlker, M and Quaas, J and Raatikainen, T and Riipinen, I and Schmale, J and Seifert, P and Skov, H and Smith, C and Sporre, MK and Stier, P and Storelvmo, T and Tsigaridis, K and van, Diedenhoven B and Virtanen, A and Wandinger, U and Wilcox, LJ and Zieger, P},
doi = {10.1029/2025av001872},
journal = {AGU Advances},
title = {Aerosolcloud interactions: overcoming a barrier to projecting nearterm climate evolution and risk},
url = {http://dx.doi.org/10.1029/2025av001872},
volume = {7},
year = {2026}
}

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TY  - JOUR
AB  - 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.
AU  - Im,U
AU  - Samset,BH
AU  - Nenes,A
AU  - Thomas,JL
AU  - Kokkola,H
AU  - Dubovik,O
AU  - Amiridis,V
AU  - Arola,A
AU  - Bellouin,N
AU  - Benedetti,A
AU  - Bilde,M
AU  - Blichner,S
AU  - Decesari,S
AU  - Ekman,AML
AU  - GarcíaPando,CP
AU  - Gross,S
AU  - Gryspeerdt,E
AU  - Hasekamp,O
AU  - Kahn,RA
AU  - Laakso,A
AU  - Lohmann,U
AU  - Marelle,L
AU  - Massling,AH
AU  - Myhre,CL
AU  - Pöhlker,M
AU  - Quaas,J
AU  - Raatikainen,T
AU  - Riipinen,I
AU  - Schmale,J
AU  - Seifert,P
AU  - Skov,H
AU  - Smith,C
AU  - Sporre,MK
AU  - Stier,P
AU  - Storelvmo,T
AU  - Tsigaridis,K
AU  - van,Diedenhoven B
AU  - Virtanen,A
AU  - Wandinger,U
AU  - Wilcox,LJ
AU  - Zieger,P
DO  - 10.1029/2025av001872
PY  - 2026///
SN  - 2576-604X
TI  - Aerosolcloud interactions: overcoming a barrier to projecting nearterm climate evolution and risk
T2  - AGU Advances
UR  - http://dx.doi.org/10.1029/2025av001872
UR  - https://doi.org/10.1029/2025av001872
VL  - 7
ER  - 

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