Abstract: Leading up to 2024, rapid advances in machine learning (ML)-based weather prediction (MLWP) had produced ML-based models which exhibit less forecast error than single NWP simulations. However, these advances have focused primarily on single, deterministic forecasts which fail to represent uncertainty and estimate risk, and overall these MLWP models have remained less accurate and reliable than state-of-the-art operational NWP ensemble forecasts. This talk will present our recent work on GenCast, the first purely machine learning based probabilistic weather model to exhibit greater skill than the top operational medium-range weather forecasts.
Link to join virtually: https://cam-ac-uk.zoom.us/j/87421957265
This talk is being recorded. If you do not wish to be seen in the recording, please avoid sitting in the front three rows of seats in the lecture theatre. Any questions asked will also be included in the recording. The recording will be made available on the Department’s webpage
