the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Jul 2024
The impact of uncertainty in black carbon's refractive index on simulated optical depth and radiative forcing
Abstract. The radiative forcing of black carbon (BC) is subject to many complex, interconnected sources of uncertainty. Here we isolate the role of the refractive index, which determines the extent to which BC absorbs and scatters radiation. With other parameterizations held constant, varying BC's refractive index from m550nm = 1.75–0.44i to m550nm = 1.95–0.79i increases simulated absorbing aerosol optical depth (AAOD) by 42 % and the effective radiative forcing from BC-radiation interactions (BC ERFari) by 47 %. The AAOD increase is comparable to that from recent updates to aerosol emission inventories, and in BC source regions, a third as large as the difference in AAOD retrieved from MISR and POLDER-GRASP satellites. The BC ERFari increase is comparable to the scale of the uncertainty in recent literature assessments. Although model sensitivity to the choice of BC refractive index is modulated by other parameterization choices, our results highlight the importance of considering refractive index diversity in model intercomparison projects.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-1796', Anonymous Referee #1, 16 Aug 2024
This paper attempts to evaluate the impact of the uncertainty of black carbon refractive index on optical thickness and radiative forcing effects, which is a very valuable topic. However, the paper fails to thoroughly discuss the impact of the uncertainty of refractive index. Here are my comments:
(1) This paper only tests three refractive indices, whereas in reality, the refractive index of black carbon is far more complex. Firstly, the refractive index of black carbon is spectrally dependent, which the authors have not elaborated on in detail. Secondly, the refractive index of black carbon may vary within a wider range. Even when adopting the maximum refractive index suggested by Bond et al. (2006), the mass absorption cross-section simulated by the current model falls below the lower limit of the observed range. Liu et al. (2020) suggested higher refractive index values by comparing the differences between simulations and measurements.
References:
Bond, T. C., & Bergstrom, R. W. (2006). Light Absorption by Carbonaceous Particles: An Investigative Review. Aerosol Science and Technology, 40 (1),27-67.
Liu, L., & Mishchenko, M. I. (2005). Effects of aggregation on scattering and radiative properties of soot aerosols. Journal of Geophysical Research: Atmospheres,495 110 (D11).
Liu, F., Yon, J., Fuentes, A., Lobo, P., Smallwood, G. J., & Corbin, J. C. (2020). Review of recent literature on the light absorption properties of black carbon: Refractive index, mass absorption cross section, and absorption function. Aerosol Science and Technology, 54 (1), 33-51.
Kahnert, M. (2010). On the discrepancy between modeled and measured mass absorption cross sections of light absorbing carbon aerosols. Aerosol Science and Technology, 44 (6), 453-460.
Luo, J., Zhang, Y., Wang, F., & Zhang, Q. (2018). Effects of brown coatings on the absorption enhancement of black carbon: a numerical investigation. Atmospheric Chemistry and Physics, 18 (23), 16897–16914.
(2) The author's selection and simulation of refractive indices have not been rigorously discussed in conjunction with measurements.
(3) The morphology of black carbon and the choice of model can affect the uncertainty introduced by the refractive index, yet the author has not elaborated on the model used in the simulations, which I presume to be spherical. Additionally, the mixing state and particle size distribution also contribute to the uncertainty stemming from the refractive index, yet the author has not comprehensively discussed these factors in conjunction with measurements. Instead, default values from the model were utilized.
References:
Luo, J., Li, D., Wang, Y., Sun, D., Hou, W., Ren, J., . . . Qiu, J. (2023). Quantifying the effects of the microphysical properties of black carbon on the determination of brown carbon using measurements at multiple wavelengths, Atmos. Chem. Phys., 24, 427–448, https://doi.org/10.5194/acp-24-427-2024, 2024.
Luo, J., Li, Z., Zhang, C., Zhang, Q., Zhang, Y., Zhang, Y., . . . Chakrabarty, R. K. (2022). Regional impacts of black carbon morphologies on short wave aerosol–radiation interactions: a comparative study between the US and China. Atmospheric Chemistry and Physics, 22 (11), 7647–7666.
Luo, J., Zhang, Q., Luo, J., Liu, J., Huo, Y., & Zhang, Y. (2019). Optical modeling of black carbon with different coating materials: The effect of coating configurations. Journal of Geophysical Research: Atmospheres, 124 (23), 13230-13253.
(4) The author's introduction to the optical simulation of black carbon in the model is overly simplistic, failing to comprehensively study the impact of black carbon uncertainty on optical properties and discuss it in conjunction with measurements.
In summary, the current version of this manuscript is overly simplistic, testing only a few refractive index cases without adequately discussing the uncertainty in refractive index, the discrepancies between simulations and measurements, how to interpret measurements through refractive index adjustments, the spectral dependence of refractive index, the impact of microphysical properties on refractive index uncertainty, and its consequences on radiative forcing.
Citation: https://doi.org/10.5194/egusphere-2024-1796-RC1 - AC1: 'Author response to RC1', Ruth Digby, 13 Dec 2024
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RC2: 'Comment on egusphere-2024-1796', Anonymous Referee #2, 22 Sep 2024
- AC2: 'Author response to RC2', Ruth Digby, 13 Dec 2024
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