Insights of warm-cloud biases in Community Atmospheric Model 5 and 6 from the single-column modeling framework and  Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) observations

Wang, Yuan; Zheng, Xiaojian; Dong, Xiquan; Xi, Baike; Yung, Yuk L.

doi:https://doi.org/10.5194/acp-23-8591-2023

Articles | Volume 23, issue 15

https://doi.org/10.5194/acp-23-8591-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Marine aerosols, trace gases, and clouds over the North Atlantic...

https://doi.org/10.5194/acp-23-8591-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 15

Research article

|

04 Aug 2023

Research article |

| 04 Aug 2023

Insights of warm-cloud biases in Community Atmospheric Model 5 and 6 from the single-column modeling framework and Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) observations

Yuan Wang, Xiaojian Zheng, Xiquan Dong, Baike Xi, and Yuk L. Yung

Supplement

https://doi.org/10.5194/acp-23-8591-2023-supplement

Data sets

Aircraft and ground observation Atmospheric Radiation Measurement Data Center https://adc.arm.gov/discovery/#/results/site_code::ena

Model code and software

The Community Earth System Model NCAR https://github.com/ESCOMP/cesm

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Short summary

Marine boundary layer clouds remain poorly predicted in global climate models due to multiple entangled uncertainty sources. This study uses the in situ observations from a recent field campaign to constrain and evaluate cloud physics in a simplified version of a climate model. Progress and remaining issues in the cloud physics parameterizations are identified. We systematically evaluate the impacts of large-scale forcing, microphysical scheme, and aerosol concentrations on the cloud property.