Characterization of the Real Part of Dry Aerosol Refractive Index Over North America From the Surface to 12 km. Issue 15 (3rd August 2018)

• Record Type: Journal Article
• Authors: 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
• Is Part Of: Journal of geophysical research. Volume 123:Issue 15(2018)
• Page Start: 8283
• Page End: 8300
• Publication Date: 2018-08-03
• Subjects: aerosol -- refractive index -- radiative forcing -- aerosol optical depth -- SEAC4RS -- DC3; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2018JD028504
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: This study reports a characterization of the real part of dry particle refractive index ( n ) at 532 nm 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. Key Points: Average values of the real part of dry aerosol refractive index ( n ) varied between 1.50 and 1.53 for various air mass types A characteristic value of 1.52 is shown to apply to organic aerosol ( n OA ) for the cumulative data set Values of n OA were positively (negatively) correlated with the O:C (H:C) ratio in the absence of biomass burning