Articles | Volume 17, issue 21
https://doi.org/10.5194/gmd-17-7855-2024
https://doi.org/10.5194/gmd-17-7855-2024
Model description paper
 | 
07 Nov 2024
Model description paper |  | 07 Nov 2024

Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling

David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan

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Cited articles

Alapaty, K., Herwehe, J. A., Otte, T. L., Nolte, C. G., Bullock, O. R., Mallard, M. S., Kain, J. S., and Dudhia, J.: Introducing subgrid-scale cloud feedbacks to radiation for regional meteorological and climate modeling, Geophys. Res. Lett., 39, L24809, https://doi.org/10.1029/2012GL054031, 2012. a, b
Appel, K. W., Bash, J. O., Fahey, K. M., Foley, K. M., Gilliam, R. C., Hogrefe, C., Hutzell, W. T., Kang, D., Mathur, R., Murphy, B. N., Napelenok, S. L., Nolte, C. G., Pleim, J. E., Pouliot, G. A., Pye, H. O. T., Ran, L., Roselle, S. J., Sarwar, G., Schwede, D. B., Sidi, F. I., Spero, T. L., and Wong, D. C.: The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation, Geosci. Model Dev., 14, 2867–2897, https://doi.org/10.5194/gmd-14-2867-2021, 2021. a, b, c, d, e, f
Blakeslee, R. J., Mach, D. M., Bateman, M. G., and Bailey, J. C.: Seasonal variations in the lightning diurnal cycle and implications for the global electric circuit, Atmos. Res., 135–136, 228–243, https://doi.org/10.1016/j.atmosres.2012.09.023, 2014. a
Bullock Jr., O. R., Alapaty, K., Herwehe, J. A., and Kain, J. S.: A Dynamically Computed Convective Time Scale for the Kain-Fritsch Convective Parameterization Scheme, Mon. Weather Rev., 143, 2105–2120, https://doi.org/10.1175/MWR-D-14-00251.1, 2015. a
Bullock Jr., O. R., Foroutan, H., Gilliam, R. C., and Herwehe, J. A.: Adding four-dimensional data assimilation by analysis nudging to the Model for Prediction Across Scales – Atmosphere (version 4.0), Geosci. Model Dev., 11, 2897–2922, https://doi.org/10.5194/gmd-11-2897-2018, 2018. a, b
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Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.