Performance comparisons of the three data assimilation methods for improved predictability of PM2·5: Ensemble Kalman filter, ensemble square root filter, and three-dimensional variational methods
- DOI
- 10.1016/j.envpol.2023.121099
- Published
- 2023-04
- Container
- Environmental Pollution
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.envpol.2023.121099,
title = {Performance comparisons of the three data assimilation methods for improved predictability of PM2·5: Ensemble Kalman filter, ensemble square root filter, and three-dimensional variational methods},
author = {Uzzal Kumar Dash and Soon-Young Park and Chul Han Song and Jinhyeok Yu and Keiya Yumimoto and Itsushi Uno},
year = {2023},
journal = {Environmental Pollution},
doi = {10.1016/j.envpol.2023.121099},
url = {https://doi.org/10.1016/j.envpol.2023.121099}
}RIS
TY - JOUR TI - Performance comparisons of the three data assimilation methods for improved predictability of PM2·5: Ensemble Kalman filter, ensemble square root filter, and three-dimensional variational methods AU - Uzzal Kumar Dash AU - Soon-Young Park AU - Chul Han Song AU - Jinhyeok Yu AU - Keiya Yumimoto AU - Itsushi Uno PY - 2023 JO - Environmental Pollution DO - 10.1016/j.envpol.2023.121099 UR - https://doi.org/10.1016/j.envpol.2023.121099 ER -
APA
Dash, U. K., Park, S., Song, C. H., Yu, J., Yumimoto, K., & Uno, I. (2023). Performance comparisons of the three data assimilation methods for improved predictability of PM2·5: Ensemble Kalman filter, ensemble square root filter, and three-dimensional variational methods. Environmental Pollution. https://doi.org/10.1016/j.envpol.2023.121099
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- crossref · retrieved 2026-11-10T09:50:48.546Z