Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

Abstract

Abstract. Cloud droplet size distributions (CDSDs), which are related to cloud albedo and rain formation, are usually broader in warm clouds than predicted from adiabatic parcel calculations. We investigate a mechanism for the CDSD broadening using a moving-size-grid cloud parcel model that considers the condensational growth of cloud droplets formed on polydisperse, submicrometer aerosols in an adiabatic cloud parcel that undergoes vertical oscillations, such as those due to cloud circulations or turbulence. Results show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation, which is consistent with early work. The relative roles of the solute effect, curvature effect, deactivation and reactivation on CDSD broadening are investigated. Deactivation of smaller cloud droplets, which is due to the combination of curvature and solute effects in the downdraft region, enhances the growth of larger cloud droplets and thus contributes particles to the larger size end of the CDSD. Droplet reactivation, which occurs in the updraft region, contributes particles to the smaller size end of the CDSD. In addition, we find that growth of the largest cloud droplets strongly depends on the residence time of cloud droplet in the cloud rather than the magnitude of local variability in the supersaturation fluctuation. This is because the environmental saturation ratio is strongly buffered by numerous smaller cloud droplets. Two necessary conditions for this CDSD broadening, which generally occur in the atmosphere, are as follows: (1) droplets form on aerosols of different sizes, and (2) the cloud parcel experiences upwards and downwards motions. Therefore we expect that this mechanism for CDSD broadening is possible in real clouds. Our results also suggest it is important to consider both curvature and solute effects before and after cloud droplet activation in a cloud model. The importance of this mechanism compared with other mechanisms on cloud properties should be investigated through in situ measurements and 3-D dynamic models.

A new approach to estimate supersaturation fluctuations in stratocumulus cloud using ground-based remote-sensing measurements

“…Although efforts have been made to improve the retrieval quality for decades, these retrieved variables still have large uncertainties that could impact the estimated supersaturation. The retrieved LWC and w can be affected by the existence of large drizzle or raindrops which are frequently observed in marine stratocumulus clouds (Yang et al, 2018b). Minimizing the influence of drizzle on the retrieved LWC and w would be helpful for the estimation of supersaturation in drizzling stratocumulus clouds using our method.…”

Droplet size distributions in turbulent clouds: experimental evaluation of theoretical distributions

“…; Arabas and Shima, ; Jensen and Nugent, ; Yang et al . ). During polluted cloud conditions, the average supersaturation is expected to be nearly zero, but the presence of turbulent flow condition allows the supersaturation to fluctuate above and below the mean value.…”

“…; Yang et al . ), turbulent fluctuations (Cooper, ; Paoli and Shariff, ; Sardina et al . ; Chandrakar et al .…”

Impact of hygroscopic CCN and turbulence on cloud droplet growth: A parcel-DNS approach

“…All aerosols are given the same hygroscopicity parameter of κ = 0.47. The parcel model applies the Lagrangian 115 bin method (i.e., moving-size-grid method, see discussion in Yang et al, 2018) to calculate the evolution of the DSD. In this way, the numerical dispersion caused by the Eulerian bins (Morrison et al, 2018;Grabowski et al, 2019) can be avoided.…”