The Climate Modelling research group at Oxford combines climate and computer science to build better models of the climate on Earth and other planets. We do research on numerical modelling, machine learning and high-performance computing for efficient predictions of future climates; data compression and information theory; and software engineering to build next-generation climate models.
Project Highlights
SpeedyWeather.jl
An interactive, flexible atmospheric model built to accelerate climate research.
Data compression and BitInformation
Compressing atmospheric data into its real information content
Testing generalisation of Machine Learning-based models
Machine learning has to respect the physics to generalise to future climates
News
- 26/01 - Welcome to Hannah-Jane and Greg as new members of our group!
- 26/01 - New paper is out in Nature Communications Earth & Environment on aviation efficiency!
- 25/11 - New preprint on differentiable programming with Enzyme applied to different Earth-System model components, including SpeedyWeather and Oceananigans!
- 25/10 - New paper on hybrid physics-machine learning model with Maximilian Gelbrecht and Niklas Boers has been published in JAMES!
- 25/10 - Milan was invited to give the annual lecture of Oxford’s Doctoral Training Centre on interactive climate modelling – live coding included, of course.