Jing-Yi Zhuo

Jing-Yi Zhuo

Postdoc Research Scientist

Publications

Publications

  1. Zhuo, J.-Y., Lorenzo M. Polvani, G. A. Vecchi, 202x: A muted eastern Pacific cooling response to Antarctic ozone depletion linked to double-ITCZ bias *In Prep.

  2. Zhuo, J.-Y., C. Lee, G. A. Vecchi, R. Seager, A. Sobel, and S. J. Camargo, 202x: Eastern Pacific cooling due to Northern Hemisphere aerosol reduction, and the role of model bias. *Under review.

  3. Zhuo, J.-Y., C. Lee, S. J. Camargo, A. Sobel, and G. A. Vecchi, 2026: Impacts of Sea Surface Temperature Warming Pattern Biases on Tropical Cyclone Activity and Hazard. *Under review

  4. Jones, K., J.-Y. Zhuo (corresponding), S. J. Camargo, K. I. Hodges, S. S. Bell, S. S. Chand 2026: Re-examining Historical Trends of Tropical Cyclone Frequency. GRL, 53, e2026GL122083. https://doi.org/10.1029/2026GL122083 [Article]

  5. X. Zhang, J.-Y. Zhuo, X. Bao, and et al., 2026: Integrating Diurnal Pulsing Signatures for AI-Driven Tropical Cyclone Intensity Prediction. *GRL, 53, e2025GL119496. https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2025GL119496 [Article]

  6. Liu, Y., J.-Y. Zhuo, K. Chu, and Z.-M. Tan, 2026: Detection of Eye Occurrence in Sequential Satellite Infrared Imagery and Its Application to Improve Deep Learning‐Based Tropical Cyclone Intensity Estimation, *JRA-ML, 3, e2025JH000816. https://doi.org/10.1029/2025JH000816 [Article]

  7. Brizuela, N. G., C.-Y. Lee, A. Sobel, R. Seager, S. J. Camargo, and J.-Y. Zhuo, 2025: Tropical thermocline powers Pacific equatorial upwelling. *J. Phys. Oceanogr., 55, 2349–2361. https://journals.ametsoc.org/view/journals/phoc/55/12/JPO-D-24-0178.1.xml [Article]

  8. Zhuo, J.-Y., C. Lee, A. Sobel, R. Seager, S. J. Camargo, Y. Lin, B. Fosu, and K. A. Reed, 2025: A more La Niña–like response to radiative forcing after flux adjustment in CESM2. *J. Climate, 38, 1037–1050. https://doi.org/10.1175/JCLI-D-24-0331.1 [Article]

  9. Lin, J., C. Lee, S. J. Camargo, A. Sobel, and J.-Y. Zhuo, 2025: The response of tropical cyclone hazard to natural and forced patterns of warming. *npj Clim Atmos Sci, 8, 109. https://doi.org/10.1038/s41612-025-00997-y [Article]

  10. Duong, Q.-P., A. Wimmers, D. Herndon, Z.-M. Tan, J.-Y. Zhuo, J. Knaff, I. A. Abdulsalam, T. Horinouchi, R. Miyata, and A. Avenas, 2023: Objective satellite methods including AI algorithms reviewed for the Tenth International Workshop on Tropical Cyclones (IWTC-10). *Tropical Cyclone Research and Review, 12(4), 259–266. [Article]

  11. Zhuo, J.-Y., and Z.-M. Tan, 2023: A deep-learning reconstruction of tropical cyclone size metrics (1981–2017): Examining trends. *J. Climate, 36, 5103–5123. https://doi.org/10.1175/JCLI-D-22-0714.1 [Article]

  12. Zhuo, J.-Y., and Z.-M. Tan, 2021: Physics-augmented deep learning to improve tropical cyclone intensity and size estimation from satellite imagery. *Mon. Wea. Rev., 149, 2097–2113. https://doi.org/10.1175/MWR-D-20-0333.1 [Article] This study has been adopted operationally by the China National Satellite Meteorological Center.