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

Viewed

Total article views: 4,017 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,240 1,612 165 4,017 754 174 165
  • HTML: 2,240
  • PDF: 1,612
  • XML: 165
  • Total: 4,017
  • Supplement: 754
  • BibTeX: 174
  • EndNote: 165
Views and downloads (calculated since 21 Jul 2016)
Cumulative views and downloads (calculated since 21 Jul 2016)

Cited

Latest update: 24 Apr 2025
Download
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.
Share