Zhan Li Email & Phone Number

Oakville, On, Ca

Hangzhou, Zhejiang, China

1. Developed AI algorithms using deep learning methods and apply for the wind speed and electric power prediction of wind farms. Completed a few POC projects and successfully supported the contract signing with our partners in the renewable energy industry.2. Developed an algorithm to predict the precipitation for the next 2-5 days using deep-learning algorithms such as U-Net and Transformer frameworks. The results show the statistical accuracy improves significantly with 20% increase.

Oakville, On, Canada

1. Led the unified nowcasting project to provide most accurate 0-6 hour forecasts of precipitation rate and type over Continental U.S. domain. The operational system was successfully launched in June 2018. The statistical verification in the summer of 2018 showed this system significantly improved the accuracy of our company’s nowcasting products of hourly forecasts. 2. Investigated and developed a new algorithm of variational data assimilation method to optimally estimate the current meteorological information at surface level.

Toronto, Canada Area

1. Led the collaborative project with The Weather Network: Using the AWS EC2 instances, a high-resolution (3-km) regional NWP system was developed with the data assimilation of Canadian and U.S. radar as well as other observations. Conducted the real-time hourly-updated running of this system over the Great Lakes region for the period of the PanAm Games 2015. The statistical results demonstrated the good performance of this real-time system.2. Conducted the Ensemble Kalman Filter (EnKF) data assimilation using Canadian radar for a lake-effect snowstorm case in 2015 through the project of MITACS post-doctoral fellowship. This experiment showed the positive impact of Canadian radar data assimilation using EnKF method for the analyses and forecasts of a lake-effect snowstorm.

Greater Salt Lake City Area

1. Studied the 4D-variational data assimilation of the airborne radar. The radar data assimilation experiment presented its significant benefits to improve the initial conditions and numerical forecasts for Typhoon Nuri’s genesis in 2008. 2. Studied the genesis of Typhoon Nuri (2008) using WRF model. The analysis of the simulation results revealed the important roles of the convection and moisture conditions for Nuri’s genesis.

Doctor Of Philosophy - Phd, Atmospheric Sciences And Meteorology

Thesis: The genesis of Typhoon Nuri (2008) with numerical simulations and data assimilation.

Bachelor'S Degree, Atmospheric Sciences And Meteorology