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

Assessing glaciogenic seeding impacts in Australia’s Snowy Mountains: an ensemble modeling approach
Sisi Chen, Lulin Xue, Sarah A. Tessendorf, Thomas Chubb, Andrew Peace, Suzanne Kenyon, Johanna Speirs, Jamie Wolff, and Bill Petzke
EGUsphere, https://doi.org/10.5194/egusphere-2025-1434,https://doi.org/10.5194/egusphere-2025-1434, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
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)
Constraining aerosol–cloud adjustments by uniting surface observations with a perturbed parameter ensemble
August Mikkelsen, Daniel T. McCoy, Trude Eidhammer, Andrew Gettelman, Ci Song, Hamish Gordon, and Isabel L. McCoy
Atmos. Chem. Phys., 25, 4547–4570, https://doi.org/10.5194/acp-25-4547-2025,https://doi.org/10.5194/acp-25-4547-2025, 2025
Short summary
Investigating ice formation pathways using a novel two-moment multi-class cloud microphysics scheme
Tim Lüttmer, Peter Spichtinger, and Axel Seifert
Atmos. Chem. Phys., 25, 4505–4529, https://doi.org/10.5194/acp-25-4505-2025,https://doi.org/10.5194/acp-25-4505-2025, 2025
Short summary
Microphysics regimes due to haze–cloud interactions: cloud oscillation and cloud collapse
Fan Yang, Hamed Fahandezh Sadi, Raymond A. Shaw, Fabian Hoffmann, Pei Hou, Aaron Wang, and Mikhail Ovchinnikov
Atmos. Chem. Phys., 25, 3785–3806, https://doi.org/10.5194/acp-25-3785-2025,https://doi.org/10.5194/acp-25-3785-2025, 2025
Short summary
Impact of secondary ice production on thunderstorm electrification under different aerosol conditions
Shiye Huang, Jing Yang, Jiaojiao Li, Qian Chen, Qilin Zhang, and Fengxia Guo
Atmos. Chem. Phys., 25, 1831–1850, https://doi.org/10.5194/acp-25-1831-2025,https://doi.org/10.5194/acp-25-1831-2025, 2025
Short summary
Model analysis of biases in the satellite-diagnosed aerosol effect on the cloud liquid water path
Harri Kokkola, Juha Tonttila, Silvia M. Calderón, Sami Romakkaniemi, Antti Lipponen, Aapo Peräkorpi, Tero Mielonen, Edward Gryspeerdt, Timo Henrik Virtanen, Pekka Kolmonen, and Antti Arola
Atmos. Chem. Phys., 25, 1533–1543, https://doi.org/10.5194/acp-25-1533-2025,https://doi.org/10.5194/acp-25-1533-2025, 2025
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.
Share
Altmetrics
Final-revised paper
Preprint