Preprints
https://doi.org/10.5194/egusphere-2024-2423
https://doi.org/10.5194/egusphere-2024-2423
17 Oct 2024
 | 17 Oct 2024
Status: this preprint is open for discussion.

Modifying the Abdul-Razzak & Ghan aerosol activation parameterization (version ARG2000) impacts simulated cloud radiative effects (shown in the UK Met Office Unified Model, version 13.0)

Pratapaditya Ghosh, Katherine J. Evans, Daniel P. Grosvenor, Hyun-Gyu Kang, Salil Mahajan, Min Xu, Wei Zhang, and Hamish Gordon

Abstract. The representation of aerosol activation is a key source of uncertainty in global composition-climate model simulations of aerosol-cloud interactions. The Abdul-Razzak and Ghan (ARG) activation parameterization is used in several global and regional models that employ modal aerosol microphysics schemes. In this study, we investigate the ability of the ARG parameterization to reproduce simulations with a cloud parcel model, and find its performance is sensitive to the geometric standard deviations (widths) of the lognormal aerosol modes. We recommend adjustments to three constant parameters in the ARG equations, which improve the performance of the parameterization for small mode widths and its ability to simulate activation in polluted conditions. For the accumulation mode width of 1.4 used in the Met Office Unified Model (UM), our modifications decrease the mean bias in the activated fraction of aerosols compared to a cloud parcel model from -6.6 % to +1.2 %. We implemented our improvements in the UM and compared simulated global cloud droplet concentrations with satellite observations. The simulated cloud radiative effect changes by -1.43 Wm-2 and aerosol indirect radiative forcing over the industrial period changes by -0.10 Wm-2.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Pratapaditya Ghosh, Katherine J. Evans, Daniel P. Grosvenor, Hyun-Gyu Kang, Salil Mahajan, Min Xu, Wei Zhang, and Hamish Gordon

Status: open (until 16 Dec 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Pratapaditya Ghosh, Katherine J. Evans, Daniel P. Grosvenor, Hyun-Gyu Kang, Salil Mahajan, Min Xu, Wei Zhang, and Hamish Gordon

Data sets

Improving the Abdul-Razzak & Ghan (2000) aerosol activation parameterization impacts simulated cloud radiative effects (shown in the Unified Model, version 13.0) Pratapaditya Ghosh, Katherine Evans, Daniel Grosvenor, Hyun-Gyu Kang, Salil Mahajan, Min Xu, Wei Zhang, and Hamish Gordon https://doi.org/10.5281/zenodo.13112444

Model code and software

Improving the Abdul-Razzak & Ghan (2000) aerosol activation parameterization impacts simulated cloud radiative effects (shown in the Unified Model, version 13.0) Pratapaditya Ghosh, Katherine Evans, Daniel Grosvenor, Hyun-Gyu Kang, Salil Mahajan, Min Xu, Wei Zhang, and Hamish Gordon https://doi.org/10.5281/zenodo.13112444

Interactive computing environment

Improving the Abdul-Razzak & Ghan (2000) aerosol activation parameterization impacts simulated cloud radiative effects (shown in the Unified Model, version 13.0) Pratapaditya Ghosh, Katherine Evans, Daniel Grosvenor, Hyun-Gyu Kang, Salil Mahajan, Min Xu, Wei Zhang, and Hamish Gordon https://doi.org/10.5281/zenodo.13112444

Pratapaditya Ghosh, Katherine J. Evans, Daniel P. Grosvenor, Hyun-Gyu Kang, Salil Mahajan, Min Xu, Wei Zhang, and Hamish Gordon

Viewed

Total article views: 217 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
166 45 6 217 25 1 2
  • HTML: 166
  • PDF: 45
  • XML: 6
  • Total: 217
  • Supplement: 25
  • BibTeX: 1
  • EndNote: 2
Views and downloads (calculated since 17 Oct 2024)
Cumulative views and downloads (calculated since 17 Oct 2024)

Viewed (geographical distribution)

Total article views: 188 (including HTML, PDF, and XML) Thereof 188 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Nov 2024
Download
Short summary
The most popular algorithm for calculating cloud droplet number concentrations in climate models is sensitive to parameters that control simulated aerosol particle number concentrations at different sizes. We recommend small modifications to functions in the algorithm to improve its performance. Implementing our changes in the UK Met Office climate model reduced average bias in simulated global droplet number concentrations, leading to more reflected solar radiation and a net cooling effect.