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
EGUsphere, https://doi.org/10.5194/egusphere-2024-1140,https://doi.org/10.5194/egusphere-2024-1140, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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)
Above-cloud concentrations of cloud condensation nuclei help to sustain some Arctic low-level clouds
Lucas J. Sterzinger and Adele L. Igel
Atmos. Chem. Phys., 24, 3529–3540, https://doi.org/10.5194/acp-24-3529-2024,https://doi.org/10.5194/acp-24-3529-2024, 2024
Short summary
Contrail formation on ambient aerosol particles for aircraft with hydrogen combustion: a box model trajectory study
Andreas Bier, Simon Unterstrasser, Josef Zink, Dennis Hillenbrand, Tina Jurkat-Witschas, and Annemarie Lottermoser
Atmos. Chem. Phys., 24, 2319–2344, https://doi.org/10.5194/acp-24-2319-2024,https://doi.org/10.5194/acp-24-2319-2024, 2024
Short summary
Effects of intermittent aerosol forcing on the stratocumulus-to-cumulus transition
Prasanth Prabhakaran, Fabian Hoffmann, and Graham Feingold
Atmos. Chem. Phys., 24, 1919–1937, https://doi.org/10.5194/acp-24-1919-2024,https://doi.org/10.5194/acp-24-1919-2024, 2024
Short summary
Cloud properties and their projected changes in CMIP models with low to high climate sensitivity
Lisa Bock and Axel Lauer
Atmos. Chem. Phys., 24, 1587–1605, https://doi.org/10.5194/acp-24-1587-2024,https://doi.org/10.5194/acp-24-1587-2024, 2024
Short summary
Water isotopic characterisation of the cloud–circulation coupling in the North Atlantic trades – Part 2: The imprint of the atmospheric circulation at different scales
Leonie Villiger and Franziska Aemisegger
Atmos. Chem. Phys., 24, 957–976, https://doi.org/10.5194/acp-24-957-2024,https://doi.org/10.5194/acp-24-957-2024, 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