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Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study

Cynthia H. Whaley 1, * Rashed Mahmood 2, 3 Knut von Salzen 1 Barbara Winter 1 Sabine Eckhardt 4 Stephen Arnold 5 Stephen Beagley 6 Silvia Becagli 7 Rong-You Chien 8 Jesper Christensen 9 Sujay M. Damani 1 Xinyi Dong 8 Kostas Eleftheriadis 10 Nikolaos Evangeliou 4 Gregory S. Faluvegi 11, 12 Mark Flanner 13 Joshua S. Fu 8 Michael Gauss 7 Fabio Giardi 14 Wanmin Gong 6 Jens Liengaard Hjorth 9 Lin Huang 6 Ulas Im 9 Yugo Kanaya 15 Srinath Krishnan 16 Zbigniew Klimont 17 Thomas Kühn 18, 19 Joakim Langner 20 Kathy S. Law 21 Louis Marelle 22 Andreas Massling 9 Dirk Olivié 7 Tatsuo Onishi 21 Naga Oshima 23 Yiran Peng 24 David A. Plummer 1 Olga Popovicheva 25 Luca Pozzoli 26 Jean-Christophe Raut 21 Maria Sand 16 Laura N. Saunders 27 Julia Schmale 28 Sangeeta Sharma 6 Ragnhild Bieltvedt Skeie 16 Henrik Skov 9 Fumikazu Taketani 15 Manu A. Thomas 20 Rita Traversi 14 Kostas Tsigaridis 11, 12 Svetlana Tsyro 7 Steven Turnock 29, 5 Vito Vitale 26 Kaley A. Walker 27 Minqi Wang 24 Duncan Watson-Parris 30 Tahya Weiss-Gibbons 1 
* Corresponding author
LATMOS - Laboratoire Atmosphères, Milieux, Observations Spatiales
Abstract : While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their represen- tation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014– 2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, sea- sonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO2−), the mmm was within ±25 % of the 4 measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.
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Submitted on : Saturday, May 21, 2022 - 7:02:11 PM
Last modification on : Friday, August 5, 2022 - 6:22:04 PM


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Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, et al.. Model evaluation of short-lived climate forcers for the Arctic Monitoring and Assessment Programme: a multi-species, multi-model study. Atmospheric Chemistry and Physics, European Geosciences Union, 2022, 22 (9), pp.5775-5828. ⟨10.5194/acp-22-5775-2022⟩. ⟨insu-03454867v2⟩



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