I am Pan Jing, an incoming PhD student at The Hong Kong University of Science and Technology (Guangzhou), starting in September 2024. Notably, using deep learning (DL) for weather forecasting has shown good predictive performance in various studies. However, as a purely data-driven approach, DL has a lack of physical processes and interpretability and heavily rely on the training datasets. Therefore, they tend to perform poorly in predicting extreme events which are underrepresented in the training data samples. My research interest lies in utilizing a hybrid approach that combines DL with process-based models to address the challenges.