Parameterization of size of organic and  secondary inorganic aerosol for efficient  representation of global aerosol optical properties

Zhu, Haihui; Martin, Randall V.; Croft, Betty; Zhai, Shixian; Li, Chi; Bindle, Liam; Pierce, Jeffrey R.; Chang, Rachel Y.-W.; Anderson, Bruce E.; Ziemba, Luke D.; Hair, Johnathan W.; Ferrare, Richard A.; Hostetler, Chris A.; Singh, Inderjeet; Chatterjee, Deepangsu; Jimenez, Jose L.; Campuzano-Jost, Pedro; Nault, Benjamin A.; Dibb, Jack E.; Schwarz, Joshua S.; Weinheimer, Andrew

doi:https://doi.org/10.5194/acp-23-5023-2023

Articles | Volume 23, issue 9

https://doi.org/10.5194/acp-23-5023-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-23-5023-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 9

Research article

|

04 May 2023

Research article |

| 04 May 2023

Parameterization of size of organic and secondary inorganic aerosol for efficient representation of global aerosol optical properties

Haihui Zhu, Randall V. Martin, Betty Croft, Shixian Zhai, Chi Li, Liam Bindle, Jeffrey R. Pierce, Rachel Y.-W. Chang, Bruce E. Anderson, Luke D. Ziemba, Johnathan W. Hair, Richard A. Ferrare, Chris A. Hostetler, Inderjeet Singh, Deepangsu Chatterjee, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jack E. Dibb, Joshua S. Schwarz, and Andrew Weinheimer

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Final revised paper (published on 04 May 2023)
Preprint (discussion started on 13 Dec 2022)

Interactive discussion

Status: closed

RC1: 'Comment on egusphere-2022-1292', Anonymous Referee #1, 18 Jan 2023

The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-1292/egusphere-2022-1292-RC1-supplement.pdf

Citation: https://doi.org/10.5194/egusphere-2022-1292-RC1
RC2:
'Comment on egusphere-2022-1292', Anonymous Referee #2, 01 Mar 2023
Here the authors present work on the use of observations and global size-resolved model output to parameterize and improve representation of particle dry effective radius in bulk aerosol simulations. Data from two airborne campaigns is used to fit R_eff to two chosen predictive covariates: total mass of SNA and OM particulates, and OM/SNA ratio. On the whole I find this work to be an interesting, well-composed, and valuable contribution to the aerosol modeling literature, and have only a few concerns and questions for the authors before publication.

While the bulk modeling is done on a relatively high resolution cubed-sphere grid, much of the parameterization relies on output from a much coarser 4x5 TOMAS simulation. While I recognize the computational time limitations inherent to high resolution global simulations, I'm a little concerned that important features may be completely washed out in such coarse output. It would be helpful to see a comparison between key metrics for the 4x5 run and a higher resolution alternative, even if just for a selected month or two.

I don't see any mention of spinup time preceding analyzed model output. Please include this modeling detail in section 2.2.

One part of the parameterization process selects for locations dominated by Msnaom. However, if I understand Figure 3 correctly, this subset excludes a very large fraction of the surface from the calculation, and I'm unclear on the intent and consequences of this when the resulting parameterizations are applied over areas that were excluded from fitting. Is the resulting parameterization only subsequently applied to the SNA+OM fraction of particulate mass? How is this combined with other aerosol species in terms of radiative properties in the bulk simulation? The description of this process in 3.3 does not adequately cover some of these details.

I have some concerns over the presentation of Figure 4. First, the chosen color scheme strikes me as somewhat odd, as it uses a diverging bar centered in very light hues at around 110 nm. This creates some (potentially unintended?) artifacts in the perception of differences between values near the center vs differences at the extremes of the displayed size range. Unless there is a compelling reason to use a diverging scheme centered at 110, I would recommend a more balanced sequential scheme. Based on the text description, it also appears that the colorbar is saturated fairly aggressively, potentially washing out model differences at the extremes. This presentation choice should be more clearly described, and the behavior outside of the saturated bounds should be discussed as needed.

Finally, while I recognize this parameterization as a potentially valuable addition over current defaults used in bulk aerosol schemes, I couldn't help but wonder about how the chosen parameter covariates relate to the overall mass distribution, rather than just the resulting R_eff. While a full examination of this may be unnecessary and out of scope, it would be helpful to have some context regarding the size distributions shifts surrounding the Reff differences associated with SNA+OM and OM/SNA. Are the changes in R_eff mostly driven by shifts in the heavy tail? Are the mean changes more proportionally seen across the size distribution? A little bit more info here would be very interesting, and also suggestive of possibilities for future work stemming from this manuscript.
Citation: https://doi.org/10.5194/egusphere-2022-1292-RC2
AC1: 'Comment on egusphere-2022-1292', Haihui Zhu, 27 Mar 2023

Thank both reviewers for comments. Our responses are attached.

Citation: https://doi.org/10.5194/egusphere-2022-1292-AC1

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Haihui Zhu on behalf of the Authors (27 Mar 2023) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (12 Apr 2023) by Fangqun Yu

AR by Haihui Zhu on behalf of the Authors (12 Apr 2023) Manuscript

Short summary

Particle size of atmospheric aerosol is important for estimating its climate and health effects, but simulating atmospheric aerosol size is computationally demanding. This study derives a simple parameterization of the size of organic and secondary inorganic ambient aerosol that can be applied to atmospheric models. Applying this parameterization allows a better representation of the global spatial pattern of aerosol size, as verified by ground and airborne measurements.