Constraining Satellite Estimates of Aerosol–Cloud Interactions via the Droplet–Aerosol Trends Discrepancy

Aerosol–cloud interactions (ACI), which substantially offset anthropogenic greenhouse warming, remain a major source of uncertainty in current climate assessments. Satellite-based estimates of ACI radiative forcing (RFaci) serve as a key benchmark for climate predictions and for evaluating improvements in climate models. However, these estimates remain poorly constrained. A critical limitation is that satellite assessments typically rely on column-integral aerosol proxies (e.g., AOD, AODf, AI, etc.), which may not accurately represent cloud-base cloud condensation nuclei (CCN)—the particles that actually form cloud droplets. This limitation has given rise to a puzzling phenomenon: over the Southern Hemisphere, cloud droplet concentrations have declined despite increases in column-integral aerosol proxies. While some previous studies have noted this droplet–aerosol trends discrepancy, they often relied on limited datasets and single aerosol proxies, without providing systematic validation, causal analysis, or quantification of its implications for RFaci. This gap has been a significant obstacle to reducing uncertainties in ACI forcing.

To address this challenge, we first combined multi-source observations to provide robust, quantitative evidence of the droplet–aerosol trends discrepancy across the Southern Hemisphere from 2003 to 2020. We then used a source–sink framework to explore the underlying physical mechanisms, finding that the discrepancy arises from elevated cloud bases systematically reducing CCN availability, while enhanced precipitation accelerates droplet removal. By explicitly accounting for these processes, this study provides a physically grounded estimate of aerosol–cloud radiative forcing, constraining RFaci to −1.37 W m⁻². Previous global assessments relying on column-integral variables are therefore biased by –35% to +26%, with discrepancies reaching +42% over the Southern Hemisphere.

This work reconciles a long-standing discrepancy between observed droplet and column-integral aerosol trends, highlighting the critical importance of considering cloud-base CCN in future ACI radiative forcing estimations. It provides a physically grounded constraint on aerosol forcing based on cloud-base CCN, supporting more precise estimates of climate sensitivity and guiding model development.