Addressing the difficulties in quantifying droplet number response to aerosol from satellite observations

Abstract

Abstract. Aerosol–cloud interaction is the most uncertain component of the overall anthropogenic forcing of the climate, in which cloud droplet number concentration (Nd) sensitivity to aerosol (S) is a key term for the overall estimation. However, satellite-based estimates of S are especially challenging, mainly due to the difficulty in disentangling aerosol effects on Nd from possible confounders. By combining multiple satellite observations and reanalysis, this study investigates the impacts of (a) updraft, (b) precipitation, (c) retrieval errors, and (d) vertical co-location between aerosol and cloud on the assessment of S in the context of marine warm (liquid) clouds. Our analysis suggests that S increases remarkably with both cloud-base height and cloud geometric thickness (proxies for vertical velocity at cloud base), consistent with stronger aerosol–cloud interactions at larger updraft velocity for midlatitude and low-latitude clouds. In turn, introducing the confounding effect of aerosol–precipitation interaction can artificially amplify S by an estimated 21 %, highlighting the necessity of removing precipitating clouds from analyses of S. It is noted that the retrieval biases in aerosol and cloud appear to underestimate S, in which cloud fraction acts as a key modulator, making it practically difficult to balance the accuracies of aerosol–cloud retrievals at aggregate scales (e.g., 1∘×1∘ grid). Moreover, we show that using column-integrated sulfate mass concentration (SO4C) to approximate sulfate concentration at cloud base (SO4B) can result in a degradation of correlation with Nd, along with a nearly twofold enhancement of S, mostly attributed to the inability of SO4C to capture the full spatiotemporal variability of SO4B. These findings point to several potential ways forward to practically account for the major influential factors by means of satellite observations and reanalysis, aiming at optimal observational estimates of global radiative forcings due to the Twomey effect and also cloud adjustments.