Abstract

Abstract. The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and their climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. Specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.

Highlights

  • 1.1 Motivation for AerChemMIPAerosols and chemically reactive gases in the atmosphere can exert important influences on global and regional air quality and climate

  • The diagnostics requested represent a subset of the diagnostics requested for the Aerosol Comparison (AeroCom) and ChemistryClimate Model Initiative (CCMI) model comparison activities

  • The ESMValTool will run – together with other evaluation tools such as the Program for Climate Model Diagnosis and Intercomparison (PCMDI) metrics package (PMP, Gleckler et al, 2016) – alongside the Earth System Grid Federation (ESGF) as soon as the output is submitted to the CMIP archive so that evaluation results can be made available at a time much faster than in CMIP5 (Eyring et al, 2016c)

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Summary

Motivation for AerChemMIP

Aerosols and chemically reactive gases in the atmosphere can exert important influences on global and regional air quality and climate. Anthropogenic effects on methane, aerosol and ozone abundances ( known as near-term climate forcers, NTCFs) are estimated to have been responsible for a climate forcing that is presently nearly equal in magnitude to that of CO2 (Shindell et al, 2013a; Myhre et al, 2013a) These emissions are thought to have led to a variety of global climate impacts including changes in regional patterns of temperature and precipitation (Rotstayn et al, 2015). Natural and managed ecosystems provide a large fraction of the methane and nitrous oxide emissions, and emit aerosol and ozone precursors (e.g. through emissions of soil nitrogen oxides, biogenic volatile organic compounds, and wildfires) These sources are likely to be affected by climate change, leading to a variety of feedbacks (Arneth et al, 2010) that to date have only been quantified from a limited number of studies (and models) and there is a need for a coordinated set of simulations that allows for a consistent and clean comparison between models. Uniform evaluation of the models will expose systematic biases and better constrain our overall goal of quantifying the role of aerosols and reactive gases in climate forcing

Previous work
Science questions
Experimental design
Transient historical coupled-ocean simulations
Transient historical prescribed SST simulations
Aim for much lower
Transient future coupled ocean
Transient future prescribed SST simulations
Diagnostics
Climate response
Forcing
Feedbacks
Chemistry–climate interactions
Air quality
Evaluation of model performance
Relations to other MIPs
Other MIPs
Summary
Full Text
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