Articles | Volume 22, issue 2
https://doi.org/10.5194/acp-22-1159-2022
https://doi.org/10.5194/acp-22-1159-2022
Research article
 | 
24 Jan 2022
Research article |  | 24 Jan 2022

Subgrid-scale horizontal and vertical variation of cloud water in stratocumulus clouds: a case study based on LES and comparisons with in situ observations

Justin A. Covert, David B. Mechem, and Zhibo Zhang

Related authors

Influence of cloud retrieval errors due to three-dimensional radiative effects on calculations of broadband shortwave cloud radiative effect
Adeleke S. Ademakinwa, Zahid H. Tushar, Jianyu Zheng, Chenxi Wang, Sanjay Purushotham, Jianwu Wang, Kerry G. Meyer, Tamas Várnai, and Zhibo Zhang
Atmos. Chem. Phys., 24, 3093–3114, https://doi.org/10.5194/acp-24-3093-2024,https://doi.org/10.5194/acp-24-3093-2024, 2024
Short summary
How well do Earth system models reproduce the observed aerosol response to rapid emission reductions? A COVID-19 case study
Ruth A. R. Digby, Nathan P. Gillett, Adam H. Monahan, Knut von Salzen, Antonis Gkikas, Qianqian Song, and Zhibo Zhang
Atmos. Chem. Phys., 24, 2077–2097, https://doi.org/10.5194/acp-24-2077-2024,https://doi.org/10.5194/acp-24-2077-2024, 2024
Short summary
Thermal infrared dust optical depth and coarse-mode effective diameter over oceans retrieved from collocated MODIS and CALIOP observations
Jianyu Zheng, Zhibo Zhang, Hongbin Yu, Anne Garnier, Qianqian Song, Chenxi Wang, Claudia Di Biagio, Jasper F. Kok, Yevgeny Derimian, and Claire Ryder
Atmos. Chem. Phys., 23, 8271–8304, https://doi.org/10.5194/acp-23-8271-2023,https://doi.org/10.5194/acp-23-8271-2023, 2023
Short summary
Where does the dust deposited over the Sierra Nevada snow come from?
Huilin Huang, Yun Qian, Ye Liu, Cenlin He, Jianyu Zheng, Zhibo Zhang, and Antonis Gkikas
Atmos. Chem. Phys., 22, 15469–15488, https://doi.org/10.5194/acp-22-15469-2022,https://doi.org/10.5194/acp-22-15469-2022, 2022
Short summary
Size-resolved dust direct radiative effect efficiency derived from satellite observations
Qianqian Song, Zhibo Zhang, Hongbin Yu, Jasper F. Kok, Claudia Di Biagio, Samuel Albani, Jianyu Zheng, and Jiachen Ding
Atmos. Chem. Phys., 22, 13115–13135, https://doi.org/10.5194/acp-22-13115-2022,https://doi.org/10.5194/acp-22-13115-2022, 2022
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)
Cloud water adjustments to aerosol perturbations are buffered by solar heating in non-precipitating marine stratocumuli
Jianhao Zhang, Yao-Sheng Chen, Takanobu Yamaguchi, and Graham Feingold
Atmos. Chem. Phys., 24, 10425–10440, https://doi.org/10.5194/acp-24-10425-2024,https://doi.org/10.5194/acp-24-10425-2024, 2024
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
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

Cited articles

Ahlgrimm, M. and Forbes, R. M.: Regime dependence of cloud condensate variability observed at the Atmospheric Radiation Measurement Sites, Q. J. Roy. Meteorol. Soc., 142, 1605–1617, https://doi.org/10.1002/qj.2783, 2016. a
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, 1989. a
ARM: Ka ARM Zenith Radar (KAZR2CFRGE), Atmospheric Radiation Measurement (ARM) user facility, edited by: Lindenmaier, I., Bharadwaj, N., Johnson, K., Nelson, D., Isom, B., Hardin, J., Matthews, A., Wendler, T., and Castro, V., ARM Data Center, https://doi.org/10.5439/1608607, 2019. a
Atmospheric Radiation Measurement: ACE-ENA field campaign data, available at: https://adc.arm.gov/discovery/#/results/s::ENA, last access: 11 January 2022. 
Download
Short summary
Stratocumulus play an important role in Earth's radiative balance. The simulation of these cloud systems in climate models is difficult due to the scale at which cloud microphysical processes occur compared with model grid sizes. In this study, we use large-eddy simulation to analyze subgrid-scale variability of cloud water and its implications on a cloud water to drizzle model enhancement factor E. We find current values of E may be too large and that E should be vertically dependent in models.
Altmetrics
Final-revised paper
Preprint