Lastest Update: May 26th, 2026
In Review
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Shi, S.*, He, C., Abolafia-Rosenzweig, R., & Zaitchik, B. (2026). Atmospheric Profile Information Improves Rain-Snow Partitioning Accuracy. (Submitted to Geophysical Research Letters)
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Shi, S.*, Liu, G., and Zaitchik, B. (2026). The climatology and temperature sensitivity of the snow-to-precipitation ratio based on satellite observations (*Water Resource Research*, under review).
Published
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Shi, S., & Liu, G. (2024). Improvements on phase classification using atmospheric melting and refreezing energy based on soundings. Journal of Geophysical Research: Atmospheres, 129, e2023JD040030. https://doi.org/10.1029/2023JD040030
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Jeoung, H., Shi, S., & Liu, G. (2022). A Novel Approach to Validate Satellite Snowfall Retrievals by Ground-Based Point Measurements. Remote Sensing, 14(3), Article 3. https://doi.org/10.3390/rs14030434
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Shi, S., & Liu, G. (2021). The latitudinal dependence in the trend of snow event to precipitation event ratio. Scientific Reports, 11(1), 18112. https://doi.org/10.1038/s41598-021-97451-9
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Shi, S., & Misra, V. (2020). The role of extreme rain events in Peninsular Florida’s seasonal hydroclimate variations. Journal of Hydrology, 589, 125182. https://doi.org/10.1016/j.jhydrol.2020.125182
In Preparation
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Shi, S., Zhang, Y.*, & Zaitchik, B. An Energetic Classification of Regimes of Precipitation Changes (In preparation).
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Nie, W., Zaitchik, B., Shi, S., Sleeman, J. A., & Brett, J. AI-Enabled Modeling of Amazon Monsoon Tipping Behavior under Deforestation and Drought (Presented at HydroML workshop).
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Hu, X., Miao, X.*, Guo, W., Shi, S., Guo, Q., Wang, L., Li, Y. Impact of the Warming-wetting Trend on Snowfall Change over the Tibetan Plateau (To be submitted).
Open-source Software
- Shi, S. (2025). ENERGYPHASE, precipitation phase partitioning method incorporated with atmospheric information. https://zenodo.org/records/15033215, GitHub link.