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    Climate and air quality impacts due to mitigation of non-methane near-term climate forcers
    (Katlenburg-Lindau : EGU, 2020) Allen, Robert J.; Turnock, Steven; Nabat, Pierre; Neubauer, David; Lohmann, Ulrike; Olivié, Dirk; Oshima, Naga; Michou, Martine; Wu, Tongwen; Zhang, Jie; Takemura, Toshihiko; Schulz, Michael; Tsigaridis, Kostas; Bauer, Susanne E.; Emmons, Louisa; Horowitz, Larry; Naik, Vaishali; van Noije, Twan; Bergman, Tommi; Lamarque, Jean-Francois; Zanis, Prodromos; Tegen, Ina; Westervelt, Daniel M.; Le Sager, Philippe; Good, Peter; Shim, Sungbo; O’Connor, Fiona; Akritidis, Dimitris; Georgoulias, Aristeidis K.; Deushi, Makoto; Sentman, Lori T.; John, Jasmin G.; Fujimori, Shinichiro; Collins, William J.
    It is important to understand how future environmental policies will impact both climate change and air pollution. Although targeting near-term climate forcers (NTCFs), defined here as aerosols, tropospheric ozone, and precursor gases, should improve air quality, NTCF reductions will also impact climate. Prior assessments of the impact of NTCF mitigation on air quality and climate have been limited. This is related to the idealized nature of some prior studies, simplified treatment of aerosols and chemically reactive gases, as well as a lack of a sufficiently large number of models to quantify model diversity and robust responses. Here, we quantify the 2015-2055 climate and air quality effects of non-methane NTCFs using nine state-of-the-art chemistry-climate model simulations conducted for the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Simulations are driven by two future scenarios featuring similar increases in greenhouse gases (GHGs) but with weak (SSP3-7.0) versus strong (SSP3-7.0-lowNTCF) levels of air quality control measures. As SSP3-7.0 lacks climate policy and has the highest levels of NTCFs, our results (e.g., surface warming) represent an upper bound. Unsurprisingly, we find significant improvements in air quality under NTCF mitigation (strong versus weak air quality controls). Surface fine particulate matter (PM2:5) and ozone (O3) decrease by 2:20:32 ugm3 and 4:60:88 ppb, respectively (changes quoted here are for the entire 2015-2055 time period; uncertainty represents the 95% confidence interval), over global land surfaces, with larger reductions in some regions including south and southeast Asia. Non-methane NTCF mitigation, however, leads to additional climate change due to the removal of aerosol which causes a net warming effect, including global mean surface temperature and precipitation increases of 0:250:12K and 0:030:012mmd1, respectively. Similarly, increases in extreme weather indices, including the hottest and wettest days, also occur. Regionally, the largest warming and wetting occurs over Asia, including central and north Asia (0:660:20K and 0:030:02mmd1), south Asia (0:470:16K and 0:170:09mmd1), and east Asia (0:460:20K and 0:150:06mmd1). Relatively large warming and wetting of the Arctic also occur at 0:590:36K and 0:040:02mmd1, respectively. Similar surface warming occurs in model simulations with aerosol-only mitigation, implying weak cooling due to ozone reductions. Our findings suggest that future policies that aggressively target non-methane NTCF reductions will improve air quality but will lead to additional surface warming, particularly in Asia and the Arctic. Policies that address other NTCFs including methane, as well as carbon dioxide emissions, must also be adopted to meet climate mitigation goals. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.
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    The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6
    (München : European Geopyhsical Union, 2016) O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.; Eyring, Veronika; Friedlingstein, Pierre; Hurtt, George; Knutti, Reto; Kriegler, Elmar; Lamarque, Jean-Francois; Lowe, Jason; Meehl, Gerald A.; Moss, Richard; Riahi, Keywan; Sanderson, Benjamin M.
    Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2°C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.