Weathering Change: FastNet and the Future of UK Forecasting

In an era of increasingly unpredictable extreme weather, getting the forecast right is no longer just about what you need to wear during your morning commute. It’s about national resilience, food security, and technological sovereignty.

In this episode, host Amelia Jabry is joined by Dr Scott Hosking (Mission Director for Environmental Forecasting at the Alan Turing Institute) and Professor Kirstine Dale (Chief AI Officer at the Met Office) to introduce FastNet: a groundbreaking, home-grown AI weather model developed right here in the UK.

Together, they demystify how FastNet uses 3D geometry (specifically, an icosahedral mesh) to map our round planet, how it spots patterns across 40 years of climate data. They also explore why we still desperately need physics to prepare for unprecedented ‘Grey Swan’ climate events like a looming Super El Niño. They tackle the vital questions of making our AI sustainable, the critical importance of a diverse AI workforce, and why the UK must maintain its own independent weather modelling capabilities rather than relying on global tech giants.

Read more about FastNet here: https://www.turing.ac.uk/research/research-projects/fastnet

Chapter markers

0:00 Intro

1:04 Introducing Scott Hosking and Kirsten Dale

1:50 The Raucous Revolution in weather forecasting of 2022

04:17 how AI weather prediction models work and how they differ from traditional weather prediction models

05:15 Why traditional physics based models still remain important in forecasting

07:00 The training data AI models rely on

7:50 The uses of AI weather models and the advantages of being computationally light