Publications
* Bold notes lead author
(first, co-first, corresponding)
2026
Tak, S., Seo, E., Reichle, R. H., & Lee, M. I. (2026). Multi-Satellite Data Assimilation for Global Soil Moisture Estimation Using the Local Ensemble Transform Kalman Filter, Remote Sensing of Environment. (in revision)
Moon, J., Kim, D., Balaguru, K., Leung, R., & Seo, E. (2026). Joint Influence of Supportive and Unsupportive Environmental Conditions on Tropical Cyclone Rapid Intensification in two HighResMIP simulations, Geophysical Research Letters. (in revision)
Choi, N., Stan, C., Lee, B., & Seo, E. (2026). Potential sources of predictability for the surface air temperature over the CONUS during boreal winter, Journal of Climate. (in revision)
Hsu, H., Findell, K., Dirmeyer, P., Lo, M. H., Feldman, A., Zhou, S., Seo, E., Miralles, D., & Fueglistaler, S. (2026). Evapotranspiration Changes Driven by Soil Moisture are Misrepresented in Climate Models, Communications Earth & Environment. (in revision)
Han, J., Seo, E., & Dirmeyer, P. (2026). Adjusting Diurnal Error in In-Situ Soil Moisture Measurements via Fourier Time-Filtering Using Land Surface Model Datasets, Hydrology and Earth System Sciences. (in revision)
Seo, E., Dirmeyer, P. A., & Tak, S. (2026). Implementation of a multi-layer snow scheme in a seasonal forecast system: Impacts on land–atmosphere interactions and climatological biases. Geoscientific Model Development. (in revision)
2025
[20] Lee, Y., Kim, M., & Seo, E. (2025). Explaining Street-Level Thermal Variability Through Semantic Segmentation and Explainable AI: Toward Climate-Responsive Building and Urban Design. Atmosphere. (doi: 10.3390/atmos16121413)
2024
[19] Lee, J., Lee, M. I., Tak, S., Seo, E., & Lee, Y. K. (2024). Assimilation of snow water equivalent from AMSR2 and IMS satellite data utilizing the local ensemble transform Kalman filter. Geoscientific Model Development. (doi: 10.5194/gmd-17-8799-2024)
[18] Yoon, D., Chen, J. H., & Seo, E. (2024). Land–atmosphere coupling in 2022 CONUS compound drought–heatwave events: Analysis and Forecasting. Weather and Climate Extremes. (doi: 10.1016/j.wace.2024.100722)
[17] Ham, Y. G., Jeong, Y., & Seo, E. (2024). Distinct soil moisture responses between the two strongest multiyear droughts in the Korean peninsula. Environmental Research Letters. (doi: 10.1029/2024GL109927)
[16] Hsu, H., Dirmeyer, P. A., & Seo, E. (2024). Exploring the mechanisms of the soil moisture-air temperature hypersensitive coupling regime. Water Resource Research, 60(7), e2023WR036490. (doi: 10.1029/2023WR036490)
[15] Tak, S., Seo, E., Dirmeyer, P. A., & Lee, M. I. (2024). The role of soil moisture-temperature coupling for the 2018 Northern European heatwave in a subseasonal forecast. Weather and Climate Extremes, 100670. (doi: 10.1016/j.wace.2024.100670)
[14] Findell, K. L., Yin, Z., Seo, E., Dirmeyer, P. A., Arnold, N. P., Chaney, N., ... & Santanello Jr, J. A. (2024). Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output. Geoscientific Model Development, 17, 1869–1883. (doi: 10.5194/gmd-17-1869-2024)
[13] Park, D. S. R., Seo, E., Lee, M., Cha, D. H., Kim, D., Ho, C. H., ... & Min, S. K. (2024). Sea surface temperature warming to inhibit mitigation of tropical cyclone destructiveness over East Asia in El Niño. npj Climate and Atmospheric Science, 7(1), 24. (doi: 10.1038/s41612-023-00556-3)
[12] Seo, E., Dirmeyer, P. A., Barlage, M., Wei, H., & Ek, M. (2024). Evaluation of land–atmosphere coupling processes and climatological bias in the UFS global coupled model. Journal of Hydrometeorology, 25(1), 161-175. (doi: 10.1175/JHM-D-23-0097.1)
2023
[11] Yoon, D., Kang, T., Cha, D. H., Song, C. K., Lee, M. I., Min, K. H., ... & Seo, E. (2023). Role of Land–Atmosphere Interaction in the 2016 Northeast Asia Heat Wave: Impact of Soil Moisture Initialization. Journal of Geophysical Research: Atmospheres, 128(2), e2022JD037718. (doi: 10.1029/2022JD037718)
2022
[10] Park, S., Lee, J., Yeom, J., Seo, E., & Im, J. (2022). Performance of Drought Indices in Assessing Rice Yield in North Korea and South Korea under the Different Agricultural Systems. Remote Sensing, 14(23), 6161. (doi: 10.3390/rs14236161)
[9] Seo, E., & Dirmeyer, P. A. (2022). Understanding the diurnal cycle of land–atmosphere interactions from flux site observations. Hydrology and Earth System Sciences, 26(20), 5411-5429. (doi: 10.5194/hess-26-5411-2022)
[8] Lee, J., Park, S., Im, J., Yoo, C., & Seo, E. (2022). Improved soil moisture estimation: Synergistic use of satellite observations and land surface models over CONUS based on machine learning. Journal of Hydrology, 609, 127749. (doi: 10.1016/j.jhydrol.2022.127749)
[7] Seo, E., & Dirmeyer, P. A. (2022). Improving the ESA CCI daily soil moisture time series with physically based land surface model datasets using a Fourier time-filtering method. Journal of Hydrometeorology, 23(3), 473-489. (doi: 10.1175/JHM-D-21-0120.1)
2021
[6] Seo, E., Lee, M. I., & Reichle, R. H. (2021). Assimilation of SMAP and ASCAT soil moisture retrievals into the JULES land surface model using the Local Ensemble Transform Kalman Filter. Remote sensing of Environment, 253, 112222. (doi: 10.1016/j.rse.2020.112222)
2020
[5] Seo, E., Lee, M. I., Schubert, S. D., Koster, R. D., & Kang, H. S. (2020). Investigation of the 2016 Eurasia heat wave as an event of the recent warming. Environmental Research Letters, 15(11), 114018. (doi: 10.1088/1748-9326/abbbae)
2019
[4] Seo, E., Lee, M. I., Kim, D., Lim, Y. K., Schubert, S. D., & Kim, K. M. (2019). Inter‐annual variation of tropical cyclones simulated by GEOS‐5 AGCM with modified convection scheme. International Journal of Climatology, 39(10), 4041-4057. (doi: 10.1002/joc.6058)
[3] Seo, E., Lee, M. I., Jeong, J. H., Koster, R. D., Schubert, S. D., Kim, H. M., ... & Scaife, A. A. (2019). Impact of soil moisture initialization on boreal summer subseasonal forecasts: mid-latitude surface air temperature and heat wave events. Climate dynamics, 52, 1695-1709. (doi: 10.1007/s00382-018-4221-4)
[2] Kim, D., Lee, M. I., & Seo, E. (2019). Improvement of soil respiration parameterization in a dynamic global vegetation model and its impact on the simulation of terrestrial carbon fluxes. Journal of Climate, 32(1), 127-143. (doi: 10.1175/JCLI-D-18-0018.1)
2018
[1] Park, S., Seo, E., Kang, D., Im, J., & Lee, M. I. (2018). Prediction of drought on pentad scale using remote sensing data and MJO index through random forest over East Asia. Remote Sensing, 10(11), 1811. (doi: 10.3390/rs10111811)