I am Yunji Zhang, an Assistant Professor in the Department of Meteorology and Atmospheric Science at the Pennsylvania State University. I am also affiliated with the Penn State Center for Advanced Data Assimilation and Predictability Techniques (ADAPT), and the Alliance for Education, Science, Engineering and Design with Africa (AESEDA).
I look at the dynamics and predictability of convectively driven severe weather and associated hazards, and how we can enhance our current capability to accurately predict them and better mitigate them by assimilating readily available, under-utilized observations.
My primary research interests involve mesoscale severe convective weather, including what environmental and internal processes contribute to the hazards that they bring on, for how long can we accurately forecast them, and how can we improve our current forecast capabilities. A notable part of my research also focuses on ensemble-based data assimilation (e.g., ensemble Kalman filter) of remote-sensing observations from satellites and radars, especially those that are readily available from current observational platforms but are underutilized by operational global and regional numerical weather prediction models. My research combines high-resolution computer modeling, ensemble data assimilation and forecasting, remote sensing, and mesoscale meteorology.
If you are interested in my research and would like to work with me and pursue an M.S. or Ph.D. in Meteorology, please feel free to contact me via email.