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 Wm-2 (6 %) and aerosol indirect radiative forcing over the industrial period changes by -0.10 Wm-2 (10 %).
| Original language | English |
|---|---|
| Pages (from-to) | 4899-4913 |
| Number of pages | 15 |
| Journal | Geoscientific Model Development |
| Volume | 18 |
| Issue number | 15 |
| DOIs | |
| State | Published - Aug 11 2025 |
Funding
This research was supported by the U.S. Air Force Life Cycle Management Center (LCMC) collaboration with Oak Ridge National Laboratory (ORNL). The computational resources on Air Force Weather HPC11 are provided by the Oak Ridge Leadership Computing Facility (OLCF) Director's Discretion Project NWP501. The OLCF at Oak Ridge National Laboratory (ORNL) is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. Model simulations are materials produced using Met Office software. Hamish Gordon acknowledges funding from the Department of Energy's Atmospheric System Research program and from NASA. Daniel P. Grosvenor was supported by the Met Office Hadley Centre Climate Programme funded by DSIT and Daniel P. Grosvenor acknowledges support from the Centre for Environmental Modelling And Computation (CEMAC) at the University of Leeds. This work also used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the National Science Foundation Grant ACI-1548562. Specifically, it used the Bridges-2 system, which is supported by the NSF Award ACI-1928147, at the Pittsburgh Supercomputing Center (PSC). We thank David O'Neal for his assistance with the installation of the UM on this system, which was made possible through the XSEDE Extended Collaborative Support Service (ECSS) program. This work also used Bridges-2 at the PSC through allocation atm200005p from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants nos. 2138259, 2138286, 2138307, 2137603, and 2138296. This research has been supported by the U.S. Department of Energy (grant no. DE-SC0022227) and the National Aeronautics and Space Administration (grant no. 80NSSC21K1344).