Dr. Rackhun Son


Main Focus

- Fire and other extreme climate/weather events
- Machine learning application to Earth observation 
- Hybrid modeling approach bridging deep learning and numerical Earth system modeling

Curriculum Vitae

- 2019-2022, PhD, Atmospheric Science, Gwangju Institute of Science and Technology, South Korea
- 2017-2019, MS, Atmospheric Science, Gwangju Institute of Science and Technology, South Korea
- 2006-2014, BS, Industrial Engineering & Mathematics, Hanyang University, South Korea


Son, R., Kim, H. C., Yoon, J. H., & Stratoulias, D. (2023) Estimation of surface PM2.5 concentrations from atmospheric gas species retrieved from TROPOMI using deep learning: Impacts of fire on air pollution over Thailand. Atmospheric Pollution Research, https://doi.org/10.1016/j.apr.2023.101875

Son, R., Ma, P. L., Wang, H., Rasch, P. J., Wang, S. Y. S., Kim, H., Jeong, J. H., Lim, K. S. S., & Yoon, J. H., (2022). Deep learning provides substantial improvements to county-level fire weather forecasting over the western United States. Journal of Advances in Modeling Earth Systems, 14(10), e2022MS002995. https://doi.org/10.1029/2022MS002995

Son, R., H. Kim, S.-Y. Wang, J.-H. Jeong, S. Woo, J.-Y. Jeong, B.-D. Lee, S.-H. Kim, M. LaPlante, C.-G. Kwon, & J.-H. Yoon. (2021). Changes in fire weather climatology under 1.5°C and 2.0°C warming. Environmental Research Letters, 16(3), 034058, DOI:10.1088/1748- 9326/abe675

Son, R., Wang, S. Y. S., Kim, S. H., Kim, H., Jeong, J. H., & Yoon, J. H. (2021). Recurrent pattern of extreme fire weather in California. Environmental Research Letters, 16(9), 094031, DOI:10.1088/1748-9326/ac1f44

Son, R., S.-Y. Wang, W.-L. Tseng, C. W. B. Schuler, E. Becker, & J.-H. Yoon. (2019). Climate diagnostics of the extreme floods in Peru during early 2017. Climate Dynamics, 54(1), 935-945, DOI:10.1007/s00382-019-05038-y

Jeong, J. Y., S. H. Woo, R. H. Son, J. H. Yoon, J. H. Jeong, S. J. Lee, & B. D. Lee. (2018). Spring forest-fire variability over Korea associated with large-scale climate factors. Atmosphere, 28(4), 457–467, DOI:10.14191/Atmos.2018.28.4.457

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