Why climate models undercount cloud-forming particles in polluted air (Preprint)
Year: 2026
Type: preprint
Abstract: Climate models underestimate cloud condensation nuclei (CCN) measured near the surface, especially in polluted regions. Improved emissions and chemistry have not closed this gap. We test a structural cause. Climate models mix each emission at once through a grid box tens of kilometres wide. They therefore miss the weak near-surface wind that keeps fresh emissions concentrated. We used 3D-ICAM, a detailed three-dimensional aerosol model coupled to resolved winds. We ran it at 10 m resolution over 1 km tiles in Delhi, Beijing, London and Hyytiälä. We compared 3D-ICAM with a single 1 km grid box that mixes like a climate model but keeps the detailed aerosol. In stagnant winter air in Delhi and Beijing, the grid box had 40–69% less CCN at 10 m than 3D-ICAM. Yet their column means differed by 2–8%. 3D-ICAM reproduced 52–90% of observed CCN; the grid box 30–54%. Both share the same chemistry, so the gap comes from mixing. In ventilated London and the boreal forest, the models agreed. In stagnant polluted air, surface stations therefore sample a near-surface excess that a grid box cannot hold. Comparing grid boxes with these stations can mistake this mixing error for errors in emissions or chemistry. This is a preprint and has not been peer reviewed. For submission to PNAS.
Authors: MISHRA, SUNEETI, Sengupta, Gargi, Ghosh, Kunal
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W7225574949