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https://doi.org/10.5194/acp-2017-1104
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2017-1104
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 04 Dec 2017

Submitted as: research article | 04 Dec 2017

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This preprint has been retracted.

Key factors affecting single scattering albedo calculation: Implications for aerosol climate forcing

Duseong S. Jo1,a,b, Rokjin J. Park1, Jaein I. Jeong1, Gabriele Curci2, Hyung-Min Lee3,c, and Sang-Woo Kim1 Duseong S. Jo et al.
  • 1School of Earth and Environmental Science, Seoul National University, Seoul, Republic of Korea
  • 2Department of Physical and Chemical Sciences, Center of Excellence for the Forecast of Severe Weather (CETEMPS), University of L'Aquila, L'Aquila, Italy
  • 3Department of Civil, Environmental, and Architectural Engineering, University of Colorado, Boulder, CO, USA
  • anow at: Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
  • bnow at: Department of Chemistry and Biochemistry, University of Colorado, Boulder, CO, USA
  • cnow at: School of Earth and Environmental Science, Seoul National University, Seoul, Republic of Korea

Abstract. Single Scattering Albedo (SSA), the ratio of scattering efficiency to total extinction efficiency, is an essential parameter used to estimate the Direct Radiative Forcing (DRF) of aerosols. However, SSA is one of the large contributors to the uncertainty of DRF estimations. In this study, we examined the sensitivity of SSA calculations to the physical properties of absorbing aerosols, in particular, Black Carbon (BC), Brown Carbon (BrC), and dust. We used GEOS-Chem 3-D global chemical transport model (CTM) simulations and a post-processing tool for the aerosol optical properties (FlexAOD). The model and input parameters were evaluated by comparison against the observed aerosol mass concentrations and the Aerosol Optical Depth (AOD) values obtained from global surface observation networks such as the global Aerosol Mass Spectrometer (AMS) dataset, the Surface Particulate Matter Network (SPARTAN), and the Aerosol Robotic Network (AERONET). The model was generally successful in reproducing the observed variability of both the Particulate Matter 2.5 μm (PM2.5) and AOD (R ~ 0.76) values, although it underestimated the magnitudes by approximately 20 %. Our sensitivity tests of the SSA calculation revealed that the aerosol physical parameters, which have generally received less attention than the aerosol mass loadings, can cause large uncertainties in the resulting DRF estimation. For example, large variations in the calculated BC absorption may result from slight changes of the geometric mean radius, geometric standard deviation, real and imaginary refractive indices, and density. The inclusion of BrC and observationally-constrained dust size distributions also significantly affected the SSA, and resulted in a remarkable improvement for the simulated SSA at 440 nm (bias was reduced by 44–49 %) compared with the AERONET observations. Based on the simulations performed during this study, we found that the global aerosol direct radiative effect was increased by 10 % after the SSA bias was reduced.

This preprint has been retracted.

Duseong S. Jo et al.

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Duseong S. Jo et al.

Duseong S. Jo et al.

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