Qualification Type: | PhD |
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Location: | Leeds |
Funding for: | UK Students, International Students |
Funding amount: | £19,237 - please see advert |
Hours: | Full Time |
Placed On: | 11th October 2024 |
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Closes: | 15th November 2024 |
Project Link: Accelerating Atmospheric Simulations with High-Order Methods | Project Opportunities | PhD | University of Leeds
Funding: School of Computer Science Studentship consisting of the award of fees, together with a tax-free maintenance grant of £19,237 per year for 3.5 years.
Lead Supervisor’s full name & email address
Dr. Massimiliano Fasi: m.fasi@leeds.ac.uk
Co-supervisor name
Stéphane Gaudreault (Research Manager, Environment and Climate Change Canada)
Project summary
Don't miss out on this exciting opportunity to advance weather forecasting with next-generation numerical methods!
Currently, numerical weather and climate models rely on multi-scale finite-difference methods to solve the complex equations governing atmospheric motion. This approach is essential in weather forecasting, but it requires a trade-off between accuracy and performance, and it often struggles with the finer resolutions that are necessary to capture highly localized weather phenomena. This project aims to explore a novel approach that leverages mixed precision to bring about a new generation of weather models.
The impact of this research extends beyond improving weather forecasts. High-fidelity atmospheric simulations are crucial for climate modeling, as they allow us to understand and predict the effects of climate change with greater accuracy. These advancements can also benefit a number of diverse applications governed by the same equations, such asair quality forecasting, dispersion models for atmospheric pollutants, and wind energy predictions.
Join us in this exciting journey! This project offers a unique opportunity to collaborate with leading researchers at both the University of Leeds and Environment and Climate Change Canada in order to develop next-generation numerical weather and climate models. Your work has the potential to significantly improve weather forecasts, impacting a wide range of sectors and fostering a deeper understanding of our planet's atmospheric processes.
Please state your entry requirements plus any necessary or desired background
A first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline.
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