Articles | Volume 16, issue 19
https://doi.org/10.5194/acp-16-12441-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-12441-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
05 Oct 2016
Research article |
| 05 Oct 2016
Reynolds-number dependence of turbulence enhancement on collision growth
Center for Earth Information Science and Technology, Japan Agency for Marine-Earth Science and Technology, 3173-25 Showa-machi, Kanazawa-ku, Yokohama Kanagawa 236-0001 Japan
Axel Seifert
Deutscher Wetterdienst, Offenbach, Germany
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Cited
13 citations as recorded by crossref.
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- Intricate relations among particle collision, relative motion and clustering in turbulent clouds: computational observation and theory E. Saw & X. Meng 10.5194/acp-22-3779-2022
- DNS and LES for Simulating Stratocumulus: Better Together J. Mellado et al. 10.1029/2018MS001312
- Predicting the morphology of ice particles in deep convection using the super-droplet method: development and evaluation of SCALE-SDM 0.2.5-2.2.0, -2.2.1, and -2.2.2 S. Shima et al. 10.5194/gmd-13-4107-2020
- The impact of fluctuations and correlations in droplet growth by collision–coalescence revisited – Part 2: Observational evidence of gel formation in warm clouds L. Alfonso et al. 10.5194/acp-19-14917-2019
- Broadening of Cloud Droplet Size Distributions by Condensation in Turbulence I. SAITO et al. 10.2151/jmsj.2019-049
- Comparison of Observed and Simulated Drop Size Distributions from Large-Eddy Simulations with Bin Microphysics M. Witte et al. 10.1175/MWR-D-18-0242.1
- Bridging the condensation–collision size gap: a direct numerical simulation of continuous droplet growth in turbulent clouds S. Chen et al. 10.5194/acp-18-7251-2018
- Effect of Turbulence on Collisional Growth of Cloud Droplets X. Li et al. 10.1175/JAS-D-18-0081.1
- Condensational and Collisional Growth of Cloud Droplets in a Turbulent Environment X. Li et al. 10.1175/JAS-D-19-0107.1
- Reynolds number dependence of heavy particles clustering in homogeneous isotropic turbulence X. Wang et al. 10.1103/PhysRevFluids.5.124603
- Large‐eddy simulations of drizzling shallow cumuli using a turbulence‐aware autoconversion parametrization H. Jin et al. 10.1002/qj.4395
- Turbulence effects on warm-rain formation in precipitating shallow convection revisited A. Seifert & R. Onishi 10.5194/acp-16-12127-2016
12 citations as recorded by crossref.
- Parameterization and Explicit Modeling of Cloud Microphysics: Approaches, Challenges, and Future Directions Y. Liu et al. 10.1007/s00376-022-2077-3
- Intricate relations among particle collision, relative motion and clustering in turbulent clouds: computational observation and theory E. Saw & X. Meng 10.5194/acp-22-3779-2022
- DNS and LES for Simulating Stratocumulus: Better Together J. Mellado et al. 10.1029/2018MS001312
- Predicting the morphology of ice particles in deep convection using the super-droplet method: development and evaluation of SCALE-SDM 0.2.5-2.2.0, -2.2.1, and -2.2.2 S. Shima et al. 10.5194/gmd-13-4107-2020
- The impact of fluctuations and correlations in droplet growth by collision–coalescence revisited – Part 2: Observational evidence of gel formation in warm clouds L. Alfonso et al. 10.5194/acp-19-14917-2019
- Broadening of Cloud Droplet Size Distributions by Condensation in Turbulence I. SAITO et al. 10.2151/jmsj.2019-049
- Comparison of Observed and Simulated Drop Size Distributions from Large-Eddy Simulations with Bin Microphysics M. Witte et al. 10.1175/MWR-D-18-0242.1
- Bridging the condensation–collision size gap: a direct numerical simulation of continuous droplet growth in turbulent clouds S. Chen et al. 10.5194/acp-18-7251-2018
- Effect of Turbulence on Collisional Growth of Cloud Droplets X. Li et al. 10.1175/JAS-D-18-0081.1
- Condensational and Collisional Growth of Cloud Droplets in a Turbulent Environment X. Li et al. 10.1175/JAS-D-19-0107.1
- Reynolds number dependence of heavy particles clustering in homogeneous isotropic turbulence X. Wang et al. 10.1103/PhysRevFluids.5.124603
- Large‐eddy simulations of drizzling shallow cumuli using a turbulence‐aware autoconversion parametrization H. Jin et al. 10.1002/qj.4395
1 citations as recorded by crossref.
Latest update: 23 Apr 2024
Short summary
This study includes massively parallel simulation results on droplet collisions in turbulence. The attained maximum Taylor-microscale-based Reynolds number (Re) exceeds 103, which steps into the typical range (O(103)–O(104)) of observed Re in turbulent clouds. The results clearly show that the Re dependence of turbulence enhancement on droplet collision growth is relevant for cloud microphysics modeling. This will promote the discussion on the Re dependence of turbulent collision statistics.
This study includes massively parallel simulation results on droplet collisions in turbulence....
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