Articles | Volume 23, issue 9
https://doi.org/10.5194/acp-23-5217-2023
https://doi.org/10.5194/acp-23-5217-2023
Research article
 | 
09 May 2023
Research article |  | 09 May 2023

Mixed-phase direct numerical simulation: ice growth in cloud-top generating cells

Sisi Chen, Lulin Xue, Sarah Tessendorf, Kyoko Ikeda, Courtney Weeks, Roy Rasmussen, Melvin Kunkel, Derek Blestrud, Shaun Parkinson, Melinda Meadows, and Nick Dawson

Related authors

Glaciation of mixed-phase clouds: insights from bulk model and bin-microphysics large-eddy simulation informed by laboratory experiment
Aaron Wang, Steve Krueger, Sisi Chen, Mikhail Ovchinnikov, Will Cantrell, and Raymond A. Shaw
Atmos. Chem. Phys., 24, 10245–10260, https://doi.org/10.5194/acp-24-10245-2024,https://doi.org/10.5194/acp-24-10245-2024, 2024
Short summary
Impact of hygroscopic seeding on the initiation of precipitation formation: results of a hybrid bin microphysics parcel model
Istvan Geresdi, Lulin Xue, Sisi Chen, Youssef Wehbe, Roelof Bruintjes, Jared A. Lee, Roy M. Rasmussen, Wojciech W. Grabowski, Noemi Sarkadi, and Sarah A. Tessendorf
Atmos. Chem. Phys., 21, 16143–16159, https://doi.org/10.5194/acp-21-16143-2021,https://doi.org/10.5194/acp-21-16143-2021, 2021
Short summary
Impact of aerosols and turbulence on cloud droplet growth: an in-cloud seeding case study using a parcel–DNS (direct numerical simulation) approach
Sisi Chen, Lulin Xue, and Man-Kong Yau
Atmos. Chem. Phys., 20, 10111–10124, https://doi.org/10.5194/acp-20-10111-2020,https://doi.org/10.5194/acp-20-10111-2020, 2020
Short summary
Bridging the condensation–collision size gap: a direct numerical simulation of continuous droplet growth in turbulent clouds
Sisi Chen, Man-Kong Yau, Peter Bartello, and Lulin Xue
Atmos. Chem. Phys., 18, 7251–7262, https://doi.org/10.5194/acp-18-7251-2018,https://doi.org/10.5194/acp-18-7251-2018, 2018
Short summary

Related subject area

Subject: Clouds and Precipitation | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
Glaciation of mixed-phase clouds: insights from bulk model and bin-microphysics large-eddy simulation informed by laboratory experiment
Aaron Wang, Steve Krueger, Sisi Chen, Mikhail Ovchinnikov, Will Cantrell, and Raymond A. Shaw
Atmos. Chem. Phys., 24, 10245–10260, https://doi.org/10.5194/acp-24-10245-2024,https://doi.org/10.5194/acp-24-10245-2024, 2024
Short summary
Microphysical processes involving the vapour phase dominate in simulated low-level Arctic clouds
Theresa Kiszler, Davide Ori, and Vera Schemann
Atmos. Chem. Phys., 24, 10039–10053, https://doi.org/10.5194/acp-24-10039-2024,https://doi.org/10.5194/acp-24-10039-2024, 2024
Short summary
Understanding aerosol–cloud interactions using a single-column model for a cold-air outbreak case during the ACTIVATE campaign
Shuaiqi Tang, Hailong Wang, Xiang-Yu Li, Jingyi Chen, Armin Sorooshian, Xubin Zeng, Ewan Crosbie, Kenneth L. Thornhill, Luke D. Ziemba, and Christiane Voigt
Atmos. Chem. Phys., 24, 10073–10092, https://doi.org/10.5194/acp-24-10073-2024,https://doi.org/10.5194/acp-24-10073-2024, 2024
Short summary
On the sensitivity of aerosol–cloud interactions to changes in sea surface temperature in radiative–convective equilibrium
Suf Lorian and Guy Dagan
Atmos. Chem. Phys., 24, 9323–9338, https://doi.org/10.5194/acp-24-9323-2024,https://doi.org/10.5194/acp-24-9323-2024, 2024
Short summary
Exploring aerosol–cloud interactions in liquid-phase clouds over eastern China and its adjacent ocean using the WRF-Chem–SBM model
Jianqi Zhao, Xiaoyan Ma, Johannes Quaas, and Hailing Jia
Atmos. Chem. Phys., 24, 9101–9118, https://doi.org/10.5194/acp-24-9101-2024,https://doi.org/10.5194/acp-24-9101-2024, 2024
Short summary

Cited articles

Avramov, A. and Harrington, J. Y.: Influence of parameterized ice habit on simulated mixed phase Arctic clouds, J. Geophys. Res.-Atmos., 115, D03205, https://doi.org/10.1029/2009JD012108, 2010. 
Ayala, O., Rosa, B., Wang, L.-P., and Grabowski, W. W.: Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 1. Results from direct numerical simulation, New J. Phys., 10, 075015, https://doi.org/10.1088/1367-2630/10/7/075015, 2008. 
Barrett, A. I., Hogan, R. J., and Forbes, R. M.: Why are mixed-phase altocumulus clouds poorly predicted by large-scale models? Part 1. Physical processes, J. Geophys. Res.-Atmos., 122, 9903–9926, https://doi.org/10.1002/2016JD026321, 2017. 
Baumgardner, D, Abel, S. J., Axisa, D., Cotton, R., Crosier, J., Field, P., Gurganus, C., Heymsfield, A., Korolev, A., Kraemer, M., and Lawson, P.: Cloud Ice Properties: In Situ Measurement Challenges, Meteor. Mon., 58, 9.1–9.23, https://doi.org/10.1175/AMSMONOGRAPHS-D-16-0011.1, 2017. 
Chen, J.-P., and Lamb, D.: The Theoretical Basis for the Parameterization of Ice Crystal Habits: Growth by Vapor Deposition, J. Atmospheric Sci., 51, 1206–1222, https://doi.org/10.1175/1520-0469(1994)051<1206:TTBFTP>2.0.CO;2, 1994. 
Download
Short summary
The possible mechanism of effective ice growth in the cloud-top generating cells in winter orographic clouds is explored using a newly developed ultra-high-resolution cloud microphysics model. Simulations demonstrate that a high availability of moisture and liquid water is critical for producing large ice particles. Fluctuations in temperature and moisture down to millimeter scales due to cloud turbulence can substantially affect the growth history of the individual cloud particles.
Altmetrics
Final-revised paper
Preprint