气候变化领域集成服务门户(CCPortal): On the relationship between cloud water composition and cloud droplet number concentration

CCPortal

DOI	10.5194/acp-20-7645-2020
	On the relationship between cloud water composition and cloud droplet number concentration
	MacDonald A.B.; Hossein Mardi A.; Dadashazar H.; Azadi Aghdam M.; Crosbie E.; Jonsson H.H.; Flagan R.C.; Seinfeld J.H.; Sorooshian A.
发表日期	2020
ISSN	1680-7316
起始页码	7645
结束页码	7665
卷号	20 期号:13
英文摘要	Aerosol cloud interactions are the largest source of uncertainty in quantifying anthropogenic radiative forcing. The large uncertainty is, in part, due to the difficulty of predicting cloud microphysical parameters, such as the cloud droplet number concentration (Nd). Even though rigorous first-principle approaches exist to calculate Nd, the cloud and aerosol research community also relies on empirical approaches such as relating Nd to aerosol mass concentration. Here we analyze relationships between Nd and cloud water chemical composition, in addition to the effect of environmental factors on the degree of the relationships. Warm, marine, stratocumulus clouds off the California coast were sampled throughout four summer campaigns between 2011 and 2016. A total of 385 cloud water samples were collected and analyzed for 80 chemical species. Single- and multispecies log log linear regressions were performed to predict Nd using chemical composition. Single-species regressions reveal that the species that best predicts Nd is total sulfate (R2 adj D 0:40). Multispecies regressions reveal that adding more species does not necessarily produce a better model, as six or more species yield regressions that are statistically insignificant. A commonality among the multispecies regressions that produce the highest correlation with Nd was that most included sulfate (either total or non-seasalt), an ocean emissions tracer (such as sodium), and an organic tracer (such as oxalate). Binning the data according to turbulence, smoke influence, and in-cloud height allowed for examination of the effect of these environmental factors on the composition Nd correlation. Accounting for turbulence, quantified as the standard deviation of vertical wind speed, showed that the correlation between Nd with both total sulfate and sodium increased at higher turbulence conditions, consistent with turbulence promoting the mixing between ocean surface and cloud base. Considering the influence of smoke significantly improved the correlation with Nd for two biomass burning tracer species in the study region, specifically oxalate and iron. When binning by in-cloud height, non-sea-salt sulfate and sodium correlated best with Nd at cloud top, whereas iron and oxalate correlated best with Nd at cloud base. © 2020 Copernicus GmbH. All rights reserved.
语种	英语
scopus关键词	chemical composition; cloud droplet; cloud microphysics; cloud water; concentration (composition); environmental factor; radiative forcing; stratocumulus; volcanic cloud; California; United States
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/247677
作者单位	Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, United States; Science Systems and Applications, Inc., Hampton, VA, United States; NASA Langley Research Center, Hampton, VA, United States; Naval Postgraduate School, Monterey, CA, United States; Department of Chemical Engineering, California Institute of Technology, Pasadena, CA, United States; Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, United States
推荐引用方式 GB/T 7714	MacDonald A.B.,Hossein Mardi A.,Dadashazar H.,et al. On the relationship between cloud water composition and cloud droplet number concentration[J],2020,20(13).
APA	MacDonald A.B..,Hossein Mardi A..,Dadashazar H..,Azadi Aghdam M..,Crosbie E..,...&Sorooshian A..(2020).On the relationship between cloud water composition and cloud droplet number concentration.ATMOSPHERIC CHEMISTRY AND PHYSICS,20(13).
MLA	MacDonald A.B.,et al."On the relationship between cloud water composition and cloud droplet number concentration".ATMOSPHERIC CHEMISTRY AND PHYSICS 20.13(2020).