Lastest Update: September 12nd, 2024

In Preparation

• Shi, S., Fan, Y., Dong, J., and Meng, H (2024). Developing a machine learning algorithm toimprove orographic snowfall retrieval from satellite passive microwave sensors.
• Shi, S., & Liu, G (2024). Investigation on the sensitivity of the snow-to-precipitation ratio to temperature based on satellite data

Published

1. 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
2. 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
3. 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
4. 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

Thesis

• PhD’s Dissertation: On the Sensitivity of Precipitation Phase to Temperature
• Master’s Thesis: Understanding the Phases of Precipitation: Climatology, Trends and Physics of the Phase Transition