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: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

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Views and downloads (calculated since 30 Mar 2023)

Month	HTML	PDF	XML	Total
Mar 2023	68	22	4	94
Apr 2023	79	46	3	128
May 2023	77	21	4	102
Jun 2023	44	8	4	56
Jul 2023	29	12	1	42
Aug 2023	360	59	13	432
Sep 2023	88	17	2	107
Oct 2023	81	17	2	100
Nov 2023	48	8	0	56
Dec 2023	36	13	0	49
Jan 2024	53	12	3	68
Feb 2024	26	3	0	29
Mar 2024	25	7	1	33
Apr 2024	28	9	4	41
May 2024	47	15	5	67
Jun 2024	82	21	5	108
Jul 2024	55	15	6	76
Aug 2024	73	14	7	94
Sep 2024	57	6	0	63
Oct 2024	54	11	0	65
Nov 2024	47	8	1	56
Dec 2024	47	18	1	66
Jan 2025	70	21	0	91
Feb 2025	52	8	6	66
Mar 2025	48	25	2	75
Apr 2025	50	29	0	79
May 2025	100	33	1	134
Jun 2025	112	68	2	182
Jul 2025	76	58	7	141
Aug 2025	76	21	0	97
Sep 2025	116	40	7	163
Oct 2025	69	51	0	120
Nov 2025	87	88	3	178
Dec 2025	99	64	6	169
Jan 2026	121	58	14	193
Feb 2026	99	47	7	153
Mar 2026	110	47	12	169
Apr 2026	100	60	9	169
May 2026	58	38	5	101
Jun 2026	20	6	2	28

Cumulative views and downloads (calculated since 30 Mar 2023)

Month	HTML	PDF	XML	Total
Mar 2023	68	22	4	94
Apr 2023	79	46	3	128
May 2023	77	21	4	102
Jun 2023	44	8	4	56
Jul 2023	29	12	1	42
Aug 2023	360	59	13	432
Sep 2023	88	17	2	107
Oct 2023	81	17	2	100
Nov 2023	48	8	0	56
Dec 2023	36	13	0	49
Jan 2024	53	12	3	68
Feb 2024	26	3	0	29
Mar 2024	25	7	1	33
Apr 2024	28	9	4	41
May 2024	47	15	5	67
Jun 2024	82	21	5	108
Jul 2024	55	15	6	76
Aug 2024	73	14	7	94
Sep 2024	57	6	0	63
Oct 2024	54	11	0	65
Nov 2024	47	8	1	56
Dec 2024	47	18	1	66
Jan 2025	70	21	0	91
Feb 2025	52	8	6	66
Mar 2025	48	25	2	75
Apr 2025	50	29	0	79
May 2025	100	33	1	134
Jun 2025	112	68	2	182
Jul 2025	76	58	7	141
Aug 2025	76	21	0	97
Sep 2025	116	40	7	163
Oct 2025	69	51	0	120
Nov 2025	87	88	3	178
Dec 2025	99	64	6	169
Jan 2026	121	58	14	193
Feb 2026	99	47	7	153
Mar 2026	110	47	12	169
Apr 2026	100	60	9	169
May 2026	58	38	5	101
Jun 2026	20	6	2	28

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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.