Addressing the difficulties in quantifying the Twomey effect for marine warm clouds from multi-sensor satellite observations and reanalysis

Abstract

Abstract. Aerosol–cloud interaction is the most uncertain component of the overall anthropogenic forcing of the climate, in which the Twomey effect plays a fundamental role. Satellite-based estimates of the Twomey effect are especially challenging, mainly due to the difficulty in disentangling aerosol effects on cloud droplet number concentration (Nd) from possible confounders. By combining multiple satellite observations and reanalysis, this study investigates the impacts of a) updraft, b) precipitation, c) retrieval errors, as well as (d) vertical co-location between aerosol and cloud, on the assessment of Nd-toaerosol sensitivity (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. 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 on the Twomey effect. 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 spatio-temporal variability of SO4B. These findings point to several potential ways forward to account for the major influential factors practically by means of satellite observations and reanalysis, aiming at an optimal observational estimate of global radiative forcing due to the Twomey effect.

Machine-Learning Based Analysis of Liquid Water Path Adjustments to Aerosol Perturbations in Marine Boundary Layer Clouds Using Satellite Observations

“…The magnitude and sign of the radiative forcing due to these aerosol-cloud interactions remain among the largest uncertainties in projections of future climate [6][7][8]. While there is a large body of research on the Twomey effect from the last decades, e.g., [5,[9][10][11][12][13][14][15][16][17], this is much less the case for LWP adjustments, where disagreement between observations and models is large and even the sign of the aerosol effect on LWP is unclear [18]. As LWP is the main controlling factor of liquid-cloud albedo [18], it is therefore important to better understand the effect of aerosols on LWP to ultimately improve climate model predictions.…”

Comment on acp-2022-295

“…Cloud responses in these regions are consistent with the expectations. Droplet number concentrations decrease, although by a rate that is a factor of 2 (compared to MODIS AOD) to 4 (compared to MISR AODFM) less than for aerosol optical depth, highlighting that there is not a 1:1 relationship of droplet number and aerosol measured as AOD (e.g., Quaas et al, 2020;Jia et al, 2022). There is only a small LWP response that is inconsistent in sign between regions with increasing and decreasing aerosol emissions.…”

Uncertainty in aerosol-cloud radiative forcing is driven by clean conditions

“…Recent observational estimates have thus focussed on better estimates of this term. Theoretical considerations (Twomey, 1959), supported by observational studies (Gryspeerdt and Stier, 2012;Jia et al, 2021Jia et al, , 2022, suggest it is a strong function of cloud updraught, entrainment, and hence cloud type.…”