Articles | Volume 22, issue 9
https://doi.org/10.5194/acp-22-5775-2022
https://doi.org/10.5194/acp-22-5775-2022
Research article
 | 
04 May 2022
Research article |  | 04 May 2022

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

Cynthia H. Whaley, Rashed Mahmood, Knut von Salzen, Barbara Winter, Sabine Eckhardt, Stephen Arnold, Stephen Beagley, Silvia Becagli, Rong-You Chien, Jesper Christensen, Sujay Manish Damani, Xinyi Dong, Konstantinos Eleftheriadis, Nikolaos Evangeliou, Gregory Faluvegi, Mark Flanner, Joshua S. Fu, Michael Gauss, Fabio Giardi, Wanmin Gong, Jens Liengaard Hjorth, Lin Huang, Ulas Im, Yugo Kanaya, Srinath Krishnan, Zbigniew Klimont, Thomas Kühn, Joakim Langner, Kathy S. Law, Louis Marelle, Andreas Massling, Dirk Olivié, Tatsuo Onishi, Naga Oshima, Yiran Peng, David A. Plummer, Olga Popovicheva, Luca Pozzoli, Jean-Christophe Raut, Maria Sand, Laura N. Saunders, Julia Schmale, Sangeeta Sharma, Ragnhild Bieltvedt Skeie, Henrik Skov, Fumikazu Taketani, Manu A. Thomas, Rita Traversi, Kostas Tsigaridis, Svetlana Tsyro, Steven Turnock, Vito Vitale, Kaley A. Walker, Minqi Wang, Duncan Watson-Parris, and Tahya Weiss-Gibbons

Data sets

NAPS dataset Environment and Climate Change Canada https://open.canada.ca/data/en/dataset/1b36a356-defd-4813-acea-47bc3abd859b

MOPITT dataset UCAR https://www2.acom.ucar.edu/mopitt/products

Model code and software

CanAM5-PAM model code Canadian Centre for Climate Modelling and analysis https://gitlab.com/cccma

CESM2 model code UCAR https://www.cesm.ucar.edu/models/cesm2/

GEOS-Chem model code Harvard University http://wiki.seas.harvard.edu/geos-chem/index.php/GEOS-Chem_12#12.3.2

GISS-E2.1 model code NASA https://www.giss.nasa.gov/tools/modelE/

NorESM model code NorESM Climate Modeling Consortium https://github.com/NorESMhub/NorESM

OsloCTM model code Section for Meteorology and Oceanography (MetOs) https://github.com/NordicESMhub/OsloCTM3

Model evaluation programs C. Whaley, R. Mahmood, and L. Saunders https://gitlab.com/cynwhaley/amap-slcf-model-evaluation

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Short summary
Air pollutants, like ozone and soot, play a role in both global warming and air quality. Atmospheric models are often used to provide information to policy makers about current and future conditions under different emissions scenarios. In order to have confidence in those simulations, in this study we compare simulated air pollution from 18 state-of-the-art atmospheric models to measured air pollution in order to assess how well the models perform.
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