Articles | Volume 22, issue 8
https://doi.org/10.5194/acp-22-5459-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-5459-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Apr 2022
Research article |
| 25 Apr 2022
| 25 Apr 2022
Influences of an entrainment–mixing parameterization on numerical simulations of cumulus and stratocumulus clouds
Xiaoqi Xu
Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
Nanjing Joint Institute for Atmospheric Sciences, Nanjing, China
Key Laboratory of Transportation Meteorology, CMA, Nanjing, China
Chunsong Lu
CORRESPONDING AUTHOR
Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
Environmental and Climate Sciences Department, Brookhaven National
Laboratory, Upton, USA
Shi Luo
Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
College of Aviation Meteorology, Civil Aviation Flight University of China, Guanghan, China
Environmental and Climate Sciences Department, Brookhaven National
Laboratory, Upton, USA
Satoshi Endo
Environmental and Climate Sciences Department, Brookhaven National
Laboratory, Upton, USA
Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
Yuan Wang
Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing, China
Viewed
Total article views: 2,310 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 15 Nov 2021)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,703 | 540 | 67 | 2,310 | 41 | 48 |
- HTML: 1,703
- PDF: 540
- XML: 67
- Total: 2,310
- BibTeX: 41
- EndNote: 48
Total article views: 1,665 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 25 Apr 2022)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,292 | 333 | 40 | 1,665 | 36 | 38 |
- HTML: 1,292
- PDF: 333
- XML: 40
- Total: 1,665
- BibTeX: 36
- EndNote: 38
Total article views: 645 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 15 Nov 2021)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 411 | 207 | 27 | 645 | 5 | 10 |
- HTML: 411
- PDF: 207
- XML: 27
- Total: 645
- BibTeX: 5
- EndNote: 10
Viewed (geographical distribution)
Total article views: 2,310 (including HTML, PDF, and XML)
Thereof 2,310 with geography defined
and 0 with unknown origin.
Total article views: 1,665 (including HTML, PDF, and XML)
Thereof 1,665 with geography defined
and 0 with unknown origin.
Total article views: 645 (including HTML, PDF, and XML)
Thereof 645 with geography defined
and 0 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
17 citations as recorded by crossref.
- Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1 C. Yin et al. 10.5194/gmd-17-5167-2024
- Aerosol–cloud interaction in the atmospheric chemistry model GRAPES_Meso5.1/CUACE and its impacts on mesoscale numerical weather prediction under haze pollution conditions in Jing–Jin–Ji in China W. Zhang et al. 10.5194/acp-22-15207-2022
- Between Broadening and Narrowing: How Mixing Affects the Width of the Droplet Size Distribution J. Lim & F. Hoffmann 10.1029/2022JD037900
- Modeling study of the effects of entrainment-mixing on fog simulation in the chemistry–weather coupling model GRAPES_Meso5.1/CUACE CW Y. Zhao et al. 10.1039/D4EA00003J
- Effect of Single and Double Moment Microphysics Schemes and Change in Cloud Condensation Nuclei, Latent Heating Rate Structure Associated with Severe Convective System over Korean Peninsula A. Madhulatha et al. 10.3390/atmos14111680
- Competition Between Radiative and Seeding Effects of Overlying Clouds on Underlying Marine Stratocumulus B. Jian et al. 10.1029/2022GL100729
- Improvement of cloud microphysical parameterization and its advantages in simulating precipitation along the Sichuan-Xizang Railway X. Xu et al. 10.1007/s11430-023-1247-2
- 云微物理参数化的改进及其对川藏铁路沿线降水的模拟优势 晓. 徐 et al. 10.1360/SSTe-2023-0178
- Establishment of an analytical model for remote sensing of typical stratocumulus cloud profiles under various precipitation and entrainment conditions H. Shang et al. 10.5194/acp-23-2729-2023
- The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation L. Zhu et al. 10.1007/s00376-023-2357-6
- The Effects of Shallow Cumulus Cloud Shape on Interactions Among Clouds and Mixing With Near‐Cloud Environments J. Chen et al. 10.1029/2023GL106334
- The impact of aerosol-cloud interaction on mesoscale numerical weather prediction when low-cloud and haze coexist in winter over major polluted regions of China W. Zhang et al. 10.1016/j.atmosenv.2023.120270
- Parameterization and Explicit Modeling of Cloud Microphysics: Approaches, Challenges, and Future Directions Y. Liu et al. 10.1007/s00376-022-2077-3
- Using Machine Learning to Predict Cloud Turbulent Entrainment‐Mixing Processes S. Gao et al. 10.1029/2024MS004225
- Parameterization of Entrainment Rate for Cumulus Clouds with WRF Simulation X. Guo et al. 10.3390/atmos14081285
- Relationships between Cloud Droplet Spectral Relative Dispersion and Entrainment Rate and Their Impacting Factors S. Luo et al. 10.1007/s00376-022-1419-5
- Assessment of the corrected CCN activation parameterizations in simulating shallow cumulus using large-eddy simulations Y. Wang et al. 10.1016/j.atmosres.2024.107881
17 citations as recorded by crossref.
- Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1 C. Yin et al. 10.5194/gmd-17-5167-2024
- Aerosol–cloud interaction in the atmospheric chemistry model GRAPES_Meso5.1/CUACE and its impacts on mesoscale numerical weather prediction under haze pollution conditions in Jing–Jin–Ji in China W. Zhang et al. 10.5194/acp-22-15207-2022
- Between Broadening and Narrowing: How Mixing Affects the Width of the Droplet Size Distribution J. Lim & F. Hoffmann 10.1029/2022JD037900
- Modeling study of the effects of entrainment-mixing on fog simulation in the chemistry–weather coupling model GRAPES_Meso5.1/CUACE CW Y. Zhao et al. 10.1039/D4EA00003J
- Effect of Single and Double Moment Microphysics Schemes and Change in Cloud Condensation Nuclei, Latent Heating Rate Structure Associated with Severe Convective System over Korean Peninsula A. Madhulatha et al. 10.3390/atmos14111680
- Competition Between Radiative and Seeding Effects of Overlying Clouds on Underlying Marine Stratocumulus B. Jian et al. 10.1029/2022GL100729
- Improvement of cloud microphysical parameterization and its advantages in simulating precipitation along the Sichuan-Xizang Railway X. Xu et al. 10.1007/s11430-023-1247-2
- 云微物理参数化的改进及其对川藏铁路沿线降水的模拟优势 晓. 徐 et al. 10.1360/SSTe-2023-0178
- Establishment of an analytical model for remote sensing of typical stratocumulus cloud profiles under various precipitation and entrainment conditions H. Shang et al. 10.5194/acp-23-2729-2023
- The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation L. Zhu et al. 10.1007/s00376-023-2357-6
- The Effects of Shallow Cumulus Cloud Shape on Interactions Among Clouds and Mixing With Near‐Cloud Environments J. Chen et al. 10.1029/2023GL106334
- The impact of aerosol-cloud interaction on mesoscale numerical weather prediction when low-cloud and haze coexist in winter over major polluted regions of China W. Zhang et al. 10.1016/j.atmosenv.2023.120270
- Parameterization and Explicit Modeling of Cloud Microphysics: Approaches, Challenges, and Future Directions Y. Liu et al. 10.1007/s00376-022-2077-3
- Using Machine Learning to Predict Cloud Turbulent Entrainment‐Mixing Processes S. Gao et al. 10.1029/2024MS004225
- Parameterization of Entrainment Rate for Cumulus Clouds with WRF Simulation X. Guo et al. 10.3390/atmos14081285
- Relationships between Cloud Droplet Spectral Relative Dispersion and Entrainment Rate and Their Impacting Factors S. Luo et al. 10.1007/s00376-022-1419-5
- Assessment of the corrected CCN activation parameterizations in simulating shallow cumulus using large-eddy simulations Y. Wang et al. 10.1016/j.atmosres.2024.107881
Latest update: 22 Feb 2025
Short summary
A new entrainment–mixing parameterization which can be directly implemented in microphysics schemes without requiring the relative humidity of the entrained air is proposed based on the explicit mixing parcel model. The parameterization is implemented in the two-moment microphysics scheme and exhibits different effects on different types of clouds and even on different stages of stratocumulus clouds, which are affected by turbulent dissipation rate and aerosol concentration.
A new entrainment–mixing parameterization which can be directly implemented in microphysics...
Altmetrics
Final-revised paper
Preprint