Please note that this session was withdrawn and is no longer available in the respective programme. This withdrawal might have been the result of a merge with another session.
AS3.11 | Composition-Climate Interactions
Composition-Climate Interactions
Convener: William Collins | Co-conveners: Paul Griffiths, Vichawan (Print) SakulsupichECSECS, Fiona O'Connor, James KeebleECSECS
Chemistry and aerosols play a major role in determining surface air quality, the Earth’s energy budget, and climate change. Conversely, climate change affects atmospheric abundances of trace gases and aerosols through composition-climate interactions. This session focuses on global scale atmospheric chemistry and aerosol modelling, radiative forcing, and climate change through the historical period and into the future. In particular, it aims to bring together scientists with an interest in:

• exploring Earth System feedbacks and chemistry-climate interactions in models, with a focus on climate feedbacks involving trace gases and aerosols
• quantifying the impact of emissions changes on atmospheric composition and air quality
• characterizing ERFs from historical and future changes in atmospheric composition and SLCFs emissions in global models
• the contribution of biogenic emissions to the climate impact of trace gas and aerosol concentrations

The session welcomes contributions from those currently involved in analysis of recent and ongoing CMIP6 experiments focusing on the areas above, planning complementary experiments and analyses for CMIP7, and invites submission of abstracts in the following areas:
• Global and regional evaluation of CMIP, CCMI and HTAP models and variability across different spatial and temporal scales.
• Modelling studies to understand the cause and impact of changes in atmospheric composition in the past and future periods
• Quantification of radiative forcing and feedbacks in models, including the roles of chemistry and aerosols
• Use of observational constraints to constrain relevant processes and interactions
• Emulation of complex atmospheric processes using statistical, process-based or AI techniques to reduce computational overhead

We particularly welcome contributions from the global and regional modelling and observation communities to these discussions.