Articles | Volume 20, issue 15
https://doi.org/10.5194/acp-20-9311-2020
https://doi.org/10.5194/acp-20-9311-2020
Research article
 | 
07 Aug 2020
Research article |  | 07 Aug 2020

Development and application of the WRFDA-Chem three-dimensional variational (3DVAR) system: aiming to improve air quality forecasting and diagnose model deficiencies

Wei Sun, Zhiquan Liu, Dan Chen, Pusheng Zhao, and Min Chen

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Cited articles

Bannister, R.: A review of operational methods of variational and ensemble-variational data assimilation, Q. J. Roy. Meteor. Soc., 143, 607–633, 2017. 
Chen, D., Liu, Z., Fast, J., and Ban, J.: Simulations of sulfate–nitrat–ammonium (SNA) aerosols during the extreme haze events over northern China in October 2014, Atmos. Chem. Phys., 16, 10707–10724, https://doi.org/10.5194/acp-16-10707-2016, 2016. 
Chen, D., Liu, Z., Ban, J., Zhao, P., and Chen, M.: Retrospective analysis of 2015–2017 wintertime PM2.5 in China: response to emission regulations and the role of meteorology, Atmos. Chem. Phys., 19, 7409–7427, https://doi.org/10.5194/acp-19-7409-2019, 2019. 
Chen, F. and Dudhia, J.: Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: Model implementation and sensitivity, Mon. Weather Rev., 129, 569–585, 2001. 
Chou, M.-D. and Suarez, M. J.: An efficient thermal infrared radiation parameterization for use in general circulation models, NASA Tech. Memo, TM 104606, 3, 25 pp., NASA Goddard Space Flight Cent., Greenbelt, MD, USA, 1994. 
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Short summary
A new aerosol and gas pollutant assimilation capability is developed within the WRFDA system with the 3D variational algorithm and MOSAIC (Model for Simulating Aerosol Interactions and Chemistry) aerosol scheme. By assimilating surface PM2.5, PM10, SO2, NO2, O3, and CO, it improves 24 h air quality forecasting. Based on this system, model deficiencies are explored. Parameterization in the newly added inorganic aerosol heterogeneous reactions should be adjusted and verified by data assimilation.
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