Articles | Volume 15, issue 7
https://doi.org/10.5194/gmd-15-2773-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-2773-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
06 Apr 2022
Development and technical paper |
| 06 Apr 2022
| 06 Apr 2022
Implementation of an ensemble Kalman filter in the Community Multiscale Air Quality model (CMAQ model v5.1) for data assimilation of ground-level PM2.5
Soon-Young Park
School of Earth Sciences and Environmental Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 61005, Republic of
Korea
Institute of Environmental Studies, Pusan National University, Busan,
46241, Republic of Korea
Uzzal Kumar Dash
School of Earth Sciences and Environmental Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 61005, Republic of
Korea
Jinhyeok Yu
School of Earth Sciences and Environmental Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 61005, Republic of
Korea
Keiya Yumimoto
Research Institute for Applied Mechanics, Kyushu University, Fukuoka,
816-8580, Japan
Itsushi Uno
Research Institute for Applied Mechanics, Kyushu University, Fukuoka,
816-8580, Japan
Chul Han Song
CORRESPONDING AUTHOR
School of Earth Sciences and Environmental Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 61005, Republic of
Korea
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Short summary
An EnKF was applied to CMAQ for assimilating ground PM2.5 observations from China and South Korea. The EnKF performed better than that without assimilation and even superior to 3D-Var. The reduced MBs in 24 h predictions were 48 % and 27 % by improving ICs and BCs, respectively.
An EnKF was applied to CMAQ for assimilating ground PM2.5 observations from China and South...
