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
There has been a growing concern that most climate models predict precipitation that is too frequent, likely due to lack of reliable subgrid variability and vertical variations in microphysical processes in low-level warm clouds. In this study, the warm-cloud physics parameterizations in the singe-c...
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ftdoajarticles:oai:doaj.org/article:94195f21d0434c04ae581df46d2a183c 2023-08-27T04:10:51+02:00 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 Y. Wang X. Zheng X. Dong B. Xi Y. L. Yung 2023-08-01T00:00:00Z https://doi.org/10.5194/acp-23-8591-2023 https://doaj.org/article/94195f21d0434c04ae581df46d2a183c EN eng Copernicus Publications https://acp.copernicus.org/articles/23/8591/2023/acp-23-8591-2023.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 doi:10.5194/acp-23-8591-2023 1680-7316 1680-7324 https://doaj.org/article/94195f21d0434c04ae581df46d2a183c Atmospheric Chemistry and Physics, Vol 23, Pp 8591-8605 (2023) Physics QC1-999 Chemistry QD1-999 article 2023 ftdoajarticles https://doi.org/10.5194/acp-23-8591-2023 2023-08-06T00:35:13Z There has been a growing concern that most climate models predict precipitation that is too frequent, likely due to lack of reliable subgrid variability and vertical variations in microphysical processes in low-level warm clouds. In this study, the warm-cloud physics parameterizations in the singe-column configurations of NCAR Community Atmospheric Model version 6 and 5 (SCAM6 and SCAM5, respectively) are evaluated using ground-based and airborne observations from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign near the Azores islands during 2017–2018. The 8-month single-column model (SCM) simulations show that both SCAM6 and SCAM5 can generally reproduce marine boundary layer cloud structure, major macrophysical properties, and their transition. The improvement in warm-cloud properties from the Community Atmospheric Model 5 and 6 (CAM5 to CAM6) physics can be found through comparison with the observations. Meanwhile, both physical schemes underestimate cloud liquid water content, cloud droplet size, and rain liquid water content but overestimate surface rainfall. Modeled cloud condensation nuclei (CCN) concentrations are comparable with aircraft-observed ones in the summer but are overestimated by a factor of 2 in winter, largely due to the biases in the long-range transport of anthropogenic aerosols like sulfate. We also test the newly recalibrated autoconversion and accretion parameterizations that account for vertical variations in droplet size. Compared to the observations, more significant improvement is found in SCAM5 than in SCAM6. This result is likely explained by the introduction of subgrid variations in cloud properties in CAM6 cloud microphysics, which further suppresses the scheme's sensitivity to individual warm-rain microphysical parameters. The predicted cloud susceptibilities to CCN perturbations in CAM6 are within a reasonable range, indicating significant progress since CAM5 which ... Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Atmospheric Chemistry and Physics 23 15 8591 8605 |
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Directory of Open Access Journals: DOAJ Articles |
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topic |
Physics QC1-999 Chemistry QD1-999 |
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Physics QC1-999 Chemistry QD1-999 Y. Wang X. Zheng X. Dong B. Xi Y. L. Yung 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 |
topic_facet |
Physics QC1-999 Chemistry QD1-999 |
description |
There has been a growing concern that most climate models predict precipitation that is too frequent, likely due to lack of reliable subgrid variability and vertical variations in microphysical processes in low-level warm clouds. In this study, the warm-cloud physics parameterizations in the singe-column configurations of NCAR Community Atmospheric Model version 6 and 5 (SCAM6 and SCAM5, respectively) are evaluated using ground-based and airborne observations from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign near the Azores islands during 2017–2018. The 8-month single-column model (SCM) simulations show that both SCAM6 and SCAM5 can generally reproduce marine boundary layer cloud structure, major macrophysical properties, and their transition. The improvement in warm-cloud properties from the Community Atmospheric Model 5 and 6 (CAM5 to CAM6) physics can be found through comparison with the observations. Meanwhile, both physical schemes underestimate cloud liquid water content, cloud droplet size, and rain liquid water content but overestimate surface rainfall. Modeled cloud condensation nuclei (CCN) concentrations are comparable with aircraft-observed ones in the summer but are overestimated by a factor of 2 in winter, largely due to the biases in the long-range transport of anthropogenic aerosols like sulfate. We also test the newly recalibrated autoconversion and accretion parameterizations that account for vertical variations in droplet size. Compared to the observations, more significant improvement is found in SCAM5 than in SCAM6. This result is likely explained by the introduction of subgrid variations in cloud properties in CAM6 cloud microphysics, which further suppresses the scheme's sensitivity to individual warm-rain microphysical parameters. The predicted cloud susceptibilities to CCN perturbations in CAM6 are within a reasonable range, indicating significant progress since CAM5 which ... |
format |
Article in Journal/Newspaper |
author |
Y. Wang X. Zheng X. Dong B. Xi Y. L. Yung |
author_facet |
Y. Wang X. Zheng X. Dong B. Xi Y. L. Yung |
author_sort |
Y. Wang |
title |
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 |
title_short |
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 |
title_full |
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 |
title_fullStr |
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 |
title_full_unstemmed |
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 |
title_sort |
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 |
publisher |
Copernicus Publications |
publishDate |
2023 |
url |
https://doi.org/10.5194/acp-23-8591-2023 https://doaj.org/article/94195f21d0434c04ae581df46d2a183c |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
Atmospheric Chemistry and Physics, Vol 23, Pp 8591-8605 (2023) |
op_relation |
https://acp.copernicus.org/articles/23/8591/2023/acp-23-8591-2023.pdf https://doaj.org/toc/1680-7316 https://doaj.org/toc/1680-7324 doi:10.5194/acp-23-8591-2023 1680-7316 1680-7324 https://doaj.org/article/94195f21d0434c04ae581df46d2a183c |
op_doi |
https://doi.org/10.5194/acp-23-8591-2023 |
container_title |
Atmospheric Chemistry and Physics |
container_volume |
23 |
container_issue |
15 |
container_start_page |
8591 |
op_container_end_page |
8605 |
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1775353186385657856 |