Articles | Volume 9, issue 10
https://doi.org/10.5194/gmd-9-3671-2016
https://doi.org/10.5194/gmd-9-3671-2016
Model evaluation paper
 | 
17 Oct 2016
Model evaluation paper |  | 17 Oct 2016

Computationally efficient air quality forecasting tool: implementation of STOPS v1.5 model into CMAQ v5.0.2 for a prediction of Asian dust

Wonbae Jeon, Yunsoo Choi, Peter Percell, Amir Hossein Souri, Chang-Keun Song, Soon-Tae Kim, and Jhoon Kim

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Cited articles

Byun, D. and Schere, K. L.: Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system, Appl. Mech. Rev., 59, 51–77, https://doi.org/10.1115/1.2128636, 2006.
Choi, H.-J., Lee, H. W., Jeon, W.-B., and Lee, S.-H.: The numerical modeling the sensitivity of coastal wind and ozone concentration to different SST forcing, Atmos. Environ., 46, 554–567, https://doi.org/10.1016/j.atmosenv.2011.06.068, 2012.
Choi, M., Kim, J., Lee, J., Kim, M., Park, Y.-J., Jeong, U., Kim, W., Hong, H., Holben, B., Eck, T. F., Song, C. H., Lim, J.-H., and Song, C.-K.: GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign, Atmos. Meas. Tech., 9, 1377–1398, https://doi.org/10.5194/amt-9-1377-2016, 2016.
Choi, Y.-J. and Fernando, H. J. S.: Implementation of a windblown dust parameterization into MODELS-3/CMAQ: Application to episodic PM events in the US/Mexico border, Atmos. Environ., 42, 6039–6046, https://doi.org/10.1016/j.atmosenv.2008.03.038, 2008.
Chun, Y., Boo, K.-O., Kim, J., Park, S.-U., and Lee, M.: Synopsis, transport, and physical characteristics of Asian dust in Korea, J. Geophys. Res., 106, 18461–18469, https://doi.org/10.1029/2001JD900184, 2001.
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Short summary
This study suggests a new hybrid Lagrangian–Eulerian modeling tool (the Screening Trajectory Ozone Prediction System, STOPS) for an accurate/fast prediction of Asian dust events. The STOPS is a moving nest (Lagrangian approach) between the source and the receptor inside Eulerian model. We run STOPS, instead of running a time-consuming Eulerian model, using constrained PM concentration from remote sensing aerosol optical depth, reflecting real-time dust particles. STOPS is for unexpected events.