Effective radiative forcing in the aerosol-climate model CAM5.3-MARC-ARG

TL;DR

This study evaluates the effective radiative forcing of anthropogenic aerosols in the CAM5.3-MARC-ARG model, highlighting how different aerosol representations influence climate forcing estimates and regional effects.

Contribution

It introduces and assesses a new aerosol model configuration (MARC-ARG) within CAM5.3, comparing its radiative effects to the default MAM3 scheme, emphasizing the importance of aerosol mixing state.

Findings

MARC produces stronger aerosol cooling effects than MAM3.

Global mean net ERF is more negative with MARC (-1.75 W/m²) than MAM3 (-1.57 W/m²).

Regional ERF distributions differ significantly due to aerosol representation.

Abstract

We quantify the effective radiative forcing (ERF) of anthropogenic aerosols modelled by the aerosol-climate model CAM5.3-MARC-ARG. CAM5.3-MARC-ARG is a new configuration of the Community Atmosphere Model version 5.3 (CAM5.3) in which the default aerosol module has been replaced by the two-Moment, Multi-Modal, Mixing-state-resolving Aerosol model for Research of Climate (MARC). CAM5.3-MARC-ARG uses the default ARG aerosol activation scheme, consistent with the default configuration of CAM5.3. We compute differences between simulations using year-1850 aerosol emissions and simulations using year-2000 aerosol emissions in order to assess the radiative effects of anthropogenic aerosols. We compare the aerosol column burdens, cloud properties, and radiative effects produced by CAM5.3-MARC-ARG with those produced by the default configuration of CAM5.3, which uses the modal aerosol module with three log-normal modes (MAM3). Compared with MAM3, we find that MARC produces stronger cooling via the direct radiative effect, stronger cooling via the surface albedo radiative effect, and stronger warming via the cloud longwave radiative effect. The global mean cloud shortwave radiative effect is similar between MARC and MAM3, although the regional distributions differ. Overall, MARC produces a global mean net ERF of -1.75$\pm$0.04 W m$^{-2}$, which is stronger than the global mean net ERF of -1.57$\pm$0.04 W m$^{-2}$ produced by MAM3. The regional distribution of ERF also differs between MARC and MAM3, largely due to differences in the regional distribution of the cloud shortwave radiative effect. We conclude that the specific representation of aerosols in global climate models, including aerosol mixing state, has important implications for climate modelling.