Characterization of the Real Part of Dry Aerosol Refractive Index Over North America From the Surface to 12 km
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Aldhaif_et_al-2018-Journal_of_ ...
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Final Published version
Author
Aldhaif, Abdulmonam M.Stahl, Connor
Braun, Rachel A.
Moghaddam, Mohammad A.
Shingler, Taylor
Crosbie, Ewan
Sawamura, Patricia
Dadashazar, Hossein
Ziemba, Luke
Jimenez, Jose L.
Campuzano-Jost, Pedro
Sorooshian, Armin
Affiliation
Univ Arizona, Dept Chem & Environm EngnUniv Arizona, Dept Hydrol & Atmospher Sci
Issue Date
2018-08-16
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AMER GEOPHYSICAL UNIONCitation
Aldhaif, A. M., Stahl, C., Braun, R. A., Moghaddam, M. A., Shingler, T., Crosbie, E., et al. (2018). Characterization of the real part of dry aerosol refractive index over North America from the surface to 12 km. Journal of Geophysical Research: Atmospheres, 123, 8283–8300. https://doi.org/10.1029/2018JD028504Rights
© 2018. American Geophysical Union. All Rights Reserved.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
This study reports a characterization of the real part of dry particle refractive index (n) at 532nm based on airborne measurements over the United States, Canada, the Pacific Ocean, and the Gulf of Mexico from the 2012 Deep Convective Clouds and Chemistry (DC3) and 2013 Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC(4)RS) campaigns. Effective n values are reported, with the limitations and uncertainties discussed. Eight air mass types were identified based on criteria related to gas-phase tracer concentrations, location, and altitude. Average values of n for these air types ranged from 1.50 to 1.53. Values of n for the organic aerosol (OA) fraction (n(OA)) were calculated using a linear mixing rule for each air mass type, with 1.52 shown to be a good approximation for all OA. Case studies detailing vertical structure revealed that n and n(OA) increased with altitude, simultaneous with enhancements in the mass fraction of OA. Values of n(OA) were positively (negatively) correlated with the O:C (H:C) ratio in the absence of biomass burning influence; in contrast, the cumulative data set revealed a slight decrease in n(OA) as a function of the O:C ratio. The performance of parametric (multiple linear regression) and nonparametric (Gaussian process regression) methods in predicting n based on aerosol composition data is discussed. It is shown that even small perturbations in n values significantly impact aerosol optical depth retrievals, radiative forcing, and optical sizing instruments, emphasizing the importance of further improving the understanding of this important aerosol property.Note
6 month embargo; published online: 13 July 2018ISSN
2169897XVersion
Final published versionSponsors
National Aeronautics and Space Administration [NNX12AC10G, NNX14AP75G]; United States Navy Office of Naval Research [N00014-10-1-0811]; NASA Earth and Space Science Fellowship [NNX14AK79H]; NASA [NNX12AC03G, NNX15AT96G]; Visiting Scientist Program at the National Institute of Aerospace (NIA)Additional Links
http://doi.wiley.com/10.1029/2018JD028504ae974a485f413a2113503eed53cd6c53
10.1029/2018JD028504
