Assessing modifications to the Abdul-Razzak and Ghan aerosol activation parameterization (version ARG2000) to improve simulated aerosol–cloud radiative effects in the UK Met Office Unified Model (UM version 13.0)

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), the 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 the improvements in the UM and compared simulated global cloud droplet concentrations with satellite observations. The simulated cloud radiative effect changes by −1.43 W m−2 (6 %) and aerosol indirect radiative forcing over the industrial period changes by −0.10 W m−2 (10 %).

Authors

Institutions

Publication Details

Journal
Geoscientific model development
Published
2025-08-11
DOI
https://doi.org/10.5194/gmd-18-4899-2025
Citations
4
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
5.20

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing modifications to the Abdul-Razzak and Ghan aerosol activation parameterization (version ARG2000) to improve simulated aerosol–cloud radiative effects in the UK Met Office Unified Model (UM version 13.0)

Pratapaditya Ghosh, Min Xu, Hyun‐Gyu Kang, Salil Mahajan et al.
4 citations
Geoscientific model development
Atmospheric chemistry and aerosols
5.20
article

Assessing modifications to the Abdul-Razzak and Ghan aerosol activation parameterization (version ARG2000) to improve simulated aerosol–cloud radiative effects in the UK Met Office Unified Model (UM version 13.0)

Pratapaditya Ghosh, Min Xu, Hyun‐Gyu Kang, Salil Mahajan, Daniel Peter Grosvenor, Katherine J. Evans, Hamish Gordon, Wei Zhang
article en
4 citations

Abstract

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), the 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 the improvements in the UM and compared simulated global cloud droplet concentrations with satellite observations. The simulated cloud radiative effect changes by −1.43 W m−2 (6 %) and aerosol indirect radiative forcing over the industrial period changes by −0.10 W m−2 (10 %).

Geoscientific model developmentVol. 18(15)
Oak Ridge National Laboratory (US), Met Office (GB), University of Leeds (GB), Carnegie Mellon University (US)
U.S. Department of Energy, National Aeronautics and Space Administration
Climate action
Openalex Percentile: Top 4%
Atmospheric chemistry and aerosols
5.20
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.