Atmos. Chem. Phys., 20, 10111–10124, 2020 https://doi.org/10.5194/acp-20-10111-2020 © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. Impact of aerosols and turbulence on cloud droplet growth: an in-cloud seeding case study using a parcel–DNS (direct numerical simulation) approach Sisi Chen1,2, Lulin Xue1,3, and Man-Kong Yau2 1National Center for Atmospheric Research, Boulder, Colorado, USA 2Department of Atmospheric and Oceanic Sciences, McGill University, Montréal, Quebec, Canada 3Hua Xin Chuang Zhi Science and Technology LLC, Beijing, China Correspondence: Sisi Chen (
[email protected]) Received: 1 October 2019 – Discussion started: 21 October 2019 Revised: 6 July 2020 – Accepted: 24 July 2020 – Published: 31 August 2020 Abstract. This paper investigates the relative importance est autoconversion rate is not co-located with the smallest of turbulence and aerosol effects on the broadening of the mean droplet radius. The finding indicates that the traditional droplet size distribution (DSD) during the early stage of Kessler-type or Sundqvist-type autoconversion parameteri- cloud and raindrop formation. A parcel–DNS (direct nu- zations, which depend on the LWC or mean radius, cannot merical simulation) hybrid approach is developed to seam- capture the drizzle formation process very well. Properties lessly simulate the evolution of cloud droplets in an ascend- related to the width or the shape of the DSD are also needed, ing cloud parcel. The results show that turbulence and cloud suggesting that the scheme of Berry and Reinhardt(1974) condensation nuclei (CCN) hygroscopicity are key to the ef- is conceptually better.