Articles | Volume 17, issue 9
https://doi.org/10.5194/gmd-17-3579-2024
https://doi.org/10.5194/gmd-17-3579-2024
Model evaluation paper
 | 
03 May 2024
Model evaluation paper |  | 03 May 2024

Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec

Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou

Related authors

NH3 spatiotemporal variability over Paris, Mexico City, and Toronto, and its link to PM2.5 during pollution events
Camille Viatte, Rimal Abeed, Shoma Yamanouchi, William C. Porter, Sarah Safieddine, Martin Van Damme, Lieven Clarisse, Beatriz Herrera, Michel Grutter, Pierre-Francois Coheur, Kimberly Strong, and Cathy Clerbaux
Atmos. Chem. Phys., 22, 12907–12922, https://doi.org/10.5194/acp-22-12907-2022,https://doi.org/10.5194/acp-22-12907-2022, 2022
Short summary
Validation of methane and carbon monoxide from Sentinel-5 Precursor using TCCON and NDACC-IRWG stations
Mahesh Kumar Sha, Bavo Langerock, Jean-François L. Blavier, Thomas Blumenstock, Tobias Borsdorff, Matthias Buschmann, Angelika Dehn, Martine De Mazière, Nicholas M. Deutscher, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Michel Grutter, James W. Hannigan, Frank Hase, Pauli Heikkinen, Christian Hermans, Laura T. Iraci, Pascal Jeseck, Nicholas Jones, Rigel Kivi, Nicolas Kumps, Jochen Landgraf, Alba Lorente, Emmanuel Mahieu, Maria V. Makarova, Johan Mellqvist, Jean-Marc Metzger, Isamu Morino, Tomoo Nagahama, Justus Notholt, Hirofumi Ohyama, Ivan Ortega, Mathias Palm, Christof Petri, David F. Pollard, Markus Rettinger, John Robinson, Sébastien Roche, Coleen M. Roehl, Amelie N. Röhling, Constantina Rousogenous, Matthias Schneider, Kei Shiomi, Dan Smale, Wolfgang Stremme, Kimberly Strong, Ralf Sussmann, Yao Té, Osamu Uchino, Voltaire A. Velazco, Corinne Vigouroux, Mihalis Vrekoussis, Pucai Wang, Thorsten Warneke, Tyler Wizenberg, Debra Wunch, Shoma Yamanouchi, Yang Yang, and Minqiang Zhou
Atmos. Meas. Tech., 14, 6249–6304, https://doi.org/10.5194/amt-14-6249-2021,https://doi.org/10.5194/amt-14-6249-2021, 2021
Short summary

Related subject area

Atmospheric sciences
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024,https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024,https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024,https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024,https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024,https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary

Cited articles

Bartholomé, E. and Belward, A. S.: GLC2000: a new approach to global land cover mapping from Earth observation data, Int. J. Remote Sens., 26, 1959–1977, https://doi.org/10.1080/01431160412331291297, 2005. a
Batisse, E., Goudreau, S., Baumgartner, J., and Smargiassi, A.: Socio-economic inequalities in exposure to industrial air pollution emissions in Quebec public schools, Can. J. Publ. He., 108, e503–e509, https://doi.org/10.17269/CJPH.108.6166, 2017. a
Boutahar, J., Lacour, S., Mallet, V., Quélo, D., Roustan, Y., and Sportisse, B.: Development and validation of a fully modular platform for numerical modelling of air pollution: POLAIR, Int. J. Environ. Pollut., 22, 17–28, 2004. a
Brand, A., McLean, K. E., Henderson, S. B., Fournier, M., Liu, L., Kosatsky, T., and Smargiassi, A.: Respiratory hospital admissions in young children living near metal smelters, pulp mills and oil refineries in two Canadian provinces, Environ. Int., 94, 24–32, https://doi.org/10.1016/j.envint.2016.05.002, 2016. a
Buteau, S., Shekarrizfard, M., Hatzopolou, M., Gamache, P., Liu, L., and Smargiassi, A.: Air pollution from industries and asthma onset in childhood: A population-based birth cohort study using dispersion modeling, Environ. Res., 185, 109180, https://doi.org/10.1016/j.envres.2020.109180, 2020. a
Download
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.