Model simulations of short-lived climate forcers in the Arctic

• Main Authors: Whaley, Cynthia, von Salzen, Knut, Mahmood, Rashed, Weiss-Gibbons, Tahya, Winter, Barbara, Saunders, Laura, Eckhardt, Sabine, Arnold, Stephen, Christensen, Jesper, Flanner, Mark, Fu, Joshua, Gauss, Michael, Huang, Lin, Im, Ulas, Klimont, Zbigniew, Langner, Joakim, Law, Kathy S., Onishi, Tatsuo, Watson-Parris, Duncan, Oshima, Naga, Peng, Yiran, Plummer, David, Pozzoli, Luca, Raut, Jean-Christophe, Sand, Maria, Schmale, Julia, Sharma, Sangeeta, Thomas, Manu, Tsyro, Svetlana
• Other Authors: Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Department of Physics Toronto, University of Toronto, Norwegian Institute for Air Research (NILU), School of Earth and Environment Leeds (SEE), University of Leeds, iCLIMATE Aarhus University Interdisciplinary Centre for Climate Change, Aarhus University Aarhus, Department of Climate and Space Sciences and Engineering (CLaSP), University of Michigan Ann Arbor, University of Michigan System-University of Michigan System, The University of Tennessee Knoxville, Norwegian Meteorological Institute Oslo (MET), International Institute for Applied Systems Analysis Laxenburg (IIASA), Swedish Meteorological and Hydrological Institute (SMHI), TROPO - LATMOS, Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Department of Atmospheric, Oceanic and Planetary Physics Oxford (AOPP), University of Oxford Oxford, Meteorological Research Institute Tsukuba (MRI), Japan Meteorological Agency (JMA), Tsinghua University Beijing (THU), European Commission - Joint Research Centre Ispra (JRC), Center for International Climate and Environmental Research Oslo (CICERO), University of Oslo (UiO), Extreme Environments Research Laboratory (EERL), Ecole Polytechnique Fédérale de Lausanne (EPFL)
• Format: Conference Object
• Language: English
• Published: HAL CCSD 2021
• Subjects: [PHYS.PHYS.PHYS-AO-PH]Physics [physics]/Physics [physics]/Atmospheric and Oceanic Physics [physics.ao-ph]; Arctic; AMAP; black carbon
• Online Access: https://hal-insu.archives-ouvertes.fr/insu-03746668

International audience The Arctic Council’s Arctic Monitoring and Assessment Programme (AMAP) is preparing an assessment of short-lived climateforcers (SLCFs) to report on the distribution, trends, and impacts of SLCFs on climate, health, and ecosystems in the Arctic. Aspart of this effort, several atmospheric and Earth system models were run to simulate SLCFs globally and in the Arctic.Participating models, using the ECLIPSE v6b anthropogenic emissions, simulated atmospheric concentrations and deposition ofSLCFs such as black carbon, sulfate, ozone, methane, and ozone precursors, as well as optical properties of aerosols, and cloudproperties.To provide confidence in the modelled impacts of SLCFs and understand their uncertainties, all model simulations wereevaluated against a vast set of measurements. These include surface monitoring networks, aircraft- and ship-based campaigns,and ground-based and satellite remote sensing. While the focus of the AMAP SLCF report is on the near surface Arctic region,the model evaluation includes the entire Northern Hemisphere from the surface to the upper-troposphere/lower-stratosphere inorder to assess long-range transport of SLCFs in addition to the local and regional emissions.Our results suggest that models have recently improved in their ability to simulate aerosol seasonal cycles in the Arctic.However, the vertical distribution of black carbon still show large variability among models, sometimes varying by a coupleorders of magnitude. Generally, models show similar spatial patterns in their biases, but with greater variability in the Arctic.Trends in Arctic surface concentrations (1990-2015) were well-modelled over that time period compared to measurements. Allshowed a decrease in black carbon and sulfate over that time period, and little-to-no change in the mixing ratio of ground-levelozone. Deposition remains a significant source of uncertainty, with large variability between models. This has implications forthe long-range transport of SLCFs in models.