Jing-Yi Zhuo

Jing-Yi Zhuo

Postdoc Research Scientist

Publications

Publications

  1. Zhuo, J.-Y., C. Lee, S. J. Camargo, A. Sobel, and G. A. Vecchi, 2026: Impact of Sea Surface Temperature Trend Bias on the Simulation of Tropical Cyclone Response. *Ready to submit

  2. Jones, K., J.-Y. Zhuo, and S. J. Camargo, 2026: Examining Historical Tropical Cyclone Frequency Trends Using Reanalysis Datasets. *Ready to submit

  3. Liu, S., J.-Y. Zhuo, I. Baxter, and J. Butler, 2025: Does AI weather forecasts show flow dependency?. In prep.

  4. Zhuo, J.-Y., C. Lee, G. A. Vecchi, R. Seager, A. Sobel, and S. J. Camargo, 2025: Eastern Pacific cooling due to Northern Hemisphere aerosol reduction, and the role of model bias. *Under review.

  5. Liu, Y., Zhuo, J.-Y., K. Chu, and Z.-M. Tan, 2025: Using evolution of eye to improve deep learning tropical cyclone intensity estimates. *Under review.

  6. X. Zhang, Zhuo, J.-Y., X. Bao, and et al., 2025: Integrating Diurnal Pulsing Signatures for AI-Driven Tropical Cyclone Intensity Prediction. *Under review

  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. *Under review. [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. [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.[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. [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. [Article] This study has been adopted operationally by the China National Satellite Meteorological Center.