EnsDiff: Ensemble Precipitation Nowcasting with Diffusion

The Hong Kong University of Science and Technology
Department of Computer Science and Engineering


MPhil Thesis Defence


Title: "EnsDiff: Ensemble Precipitation Nowcasting with Diffusion"

By

Mr. Chi Ho WONG


Abstract:

Operational numerical weather prediction precipitation nowcasting usually 
considers forecast reliability by utilizing an ensemble of model 
forecasts. Existing data-driven methods often optimize MSE 
deterministically or resort to probabilistic forecasting with generative 
models. However, they only emphasize the optimization of the point 
forecast metrics, which makes it challenging to balance the trade-off 
between the optimization of accuracy and uncertainty. Human experts can 
hardly make an appropriate decision with an ensemble forecast when 
forecast calibration and sharpness are not considered. In this paper, we 
propose EnsDiff, which models the probability distribution to produce 
ensemble diffusion predictions. Not only does it outperform the SOTA model 
on a proper scoring rule, Continuous Ranked Probability Score (CRPS), but 
it also outperforms other models on the deterministic metrics. Extensive 
experiments show that EnsDiff can enhance probabilistic and deterministic 
skills, outperforming state-of-the-art models.


Date:                   Wednesday, 22 January 2025

Time:                   10:00am - 12:00noon

Venue:                  Room 3494
                        Lifts 25/26

Chairman:               Prof. Raymond WONG

Committee Members:      Prof. Dit-Yan YEUNG (Supervisor)
                        Dr. Dan XU