Preprints
https://doi.org/10.5194/egusphere-2025-438
https://doi.org/10.5194/egusphere-2025-438
18 Feb 2025
 | 18 Feb 2025

Improving Fine Mineral Dust Representation from the Surface to the Column in GEOS-Chem 14.4.1

Dandan Zhang, Randall V. Martin, Xuan Liu, Aaron van Donkelaar, Christopher R. Oxford, Yanshun Li, Jun Meng, Danny M. Leung, Jasper F. Kok, Longlei Li, Haihui Zhu, Jay R. Turner, Yu Yan, Michael Brauer, Yinon Rudich, and Eli Windwer

Abstract. Accurate representation of mineral dust remains a challenge for global air quality or climate models due to inadequate parametrization of the emission scheme, removal mechanisms, and size distribution. While various studies have constrained aspects of dust emission fluxes and/or dust optical depth, surface dust concentrations still vary by factors of 5–10 among models. In this study, we focus on improving the simulation of fine dust in the GEOS-Chem chemical transport model, leveraging recent mechanistic understanding of dust source and removal, and reconciling the size differences between models and ground-based measurements. Specifically, we conduct sensitivity simulations using GEOS-Chem in its high performance configuration (GCHP) version 14.4.1 to investigate the effects of mechanism or parameter updates. The results are evaluated by comparisons versus Deep Blue satellite-based aerosol optical depth (AOD) and AErosol RObotic NETwork (AERONET) ground-based AOD for total column abundance, and versus the Surface Particulate Matter Network (SPARTAN) for surface PM2.5 dust concentrations. Reconciling modelled geometric diameter versus measured aerodynamic diameter is important for consistent comparison. The two-fold overestimation of surface fine dust in the standard model is alleviated by 36 % without degradation of total column abundance by implementing a new physics-based dust emission scheme with better spatial distribution. Further reduction by 16 % of the overestimation of surface PM2.5 dust is achieved through reducing the mass fraction of emitted fine dust based on the brittle fragmentation theory, and explicit tracking of three additional fine mineral dust size bins with updated parametrization for below-cloud scavenging. Overall, these developments reduce the normalized mean difference against surface fine dust measurements from SPARTAN from 73 % to 21 %, while retaining comparable skill of total column abundance against satellite and ground-based AOD.

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Journal article(s) based on this preprint

02 Oct 2025
Improving annual fine mineral dust representation from the surface to the column in GEOS-Chem 14.4.1
Dandan Zhang, Randall V. Martin, Xuan Liu, Aaron van Donkelaar, Christopher R. Oxford, Yanshun Li, Jun Meng, Danny M. Leung, Jasper F. Kok, Longlei Li, Haihui Zhu, Jay R. Turner, Yu Yan, Michael Brauer, Yinon Rudich, and Eli Windwer
Geosci. Model Dev., 18, 6767–6803, https://doi.org/10.5194/gmd-18-6767-2025,https://doi.org/10.5194/gmd-18-6767-2025, 2025
Short summary
Dandan Zhang, Randall V. Martin, Xuan Liu, Aaron van Donkelaar, Christopher R. Oxford, Yanshun Li, Jun Meng, Danny M. Leung, Jasper F. Kok, Longlei Li, Haihui Zhu, Jay R. Turner, Yu Yan, Michael Brauer, Yinon Rudich, and Eli Windwer

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2025-438', Anonymous Referee #1, 18 Mar 2025
  • RC2: 'Comment on egusphere-2025-438', R. L. Miller, 24 Mar 2025
  • RC3: 'Comment on egusphere-2025-438', Anonymous Referee #3, 12 Apr 2025
  • AC1: 'Comment on egusphere-2025-438', Dandan Zhang, 11 May 2025

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2025-438', Anonymous Referee #1, 18 Mar 2025
  • RC2: 'Comment on egusphere-2025-438', R. L. Miller, 24 Mar 2025
  • RC3: 'Comment on egusphere-2025-438', Anonymous Referee #3, 12 Apr 2025
  • AC1: 'Comment on egusphere-2025-438', Dandan Zhang, 11 May 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Dandan Zhang on behalf of the Authors (11 May 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (30 Jun 2025) by Samuel Remy
RR by R. L. Miller (23 Jul 2025)
RR by Anonymous Referee #3 (04 Aug 2025)
ED: Publish as is (29 Aug 2025) by Samuel Remy
AR by Dandan Zhang on behalf of the Authors (29 Aug 2025)

Journal article(s) based on this preprint

02 Oct 2025
Improving annual fine mineral dust representation from the surface to the column in GEOS-Chem 14.4.1
Dandan Zhang, Randall V. Martin, Xuan Liu, Aaron van Donkelaar, Christopher R. Oxford, Yanshun Li, Jun Meng, Danny M. Leung, Jasper F. Kok, Longlei Li, Haihui Zhu, Jay R. Turner, Yu Yan, Michael Brauer, Yinon Rudich, and Eli Windwer
Geosci. Model Dev., 18, 6767–6803, https://doi.org/10.5194/gmd-18-6767-2025,https://doi.org/10.5194/gmd-18-6767-2025, 2025
Short summary
Dandan Zhang, Randall V. Martin, Xuan Liu, Aaron van Donkelaar, Christopher R. Oxford, Yanshun Li, Jun Meng, Danny M. Leung, Jasper F. Kok, Longlei Li, Haihui Zhu, Jay R. Turner, Yu Yan, Michael Brauer, Yinon Rudich, and Eli Windwer
Dandan Zhang, Randall V. Martin, Xuan Liu, Aaron van Donkelaar, Christopher R. Oxford, Yanshun Li, Jun Meng, Danny M. Leung, Jasper F. Kok, Longlei Li, Haihui Zhu, Jay R. Turner, Yu Yan, Michael Brauer, Yinon Rudich, and Eli Windwer

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Short summary
This study develops the fine mineral dust simulation in GEOS-Chem by: 1) implementing a new dust emission scheme with further refinements; 2) revisiting the size distribution of emitted dust; 3) explicitly tracking fine dust for emission, transport and deposition in 4 size bins; 4) updating the parametrization for below-cloud scavenging. All revisions significantly reduce the overestimation of surface fine dust from 73% to 21% while retaining comparable skill in representing columnar abundance.
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