He will share this prestigious role with Professor Serge Guillas from UCL Statistical Science, and both will work closely with the Co-chair at the Met Office, Theo McCaie, Head of the Met Office Informatics Lab and Technology Lead for Data Science.
Professor Brierley specialises in understanding past climate dynamics to inform future climate projections.
His research focuses on reducing uncertainties in climate models, particularly by studying past warm periods such as the Pliocene, when CO2 levels were last as high as today.
Professor Brierley commented: “I’m really looking forward to helping steer Met Office research and its links with UCL over the coming year. I’d love to stretch our connections well beyond meteorology and into social science and climate adaptation.”
"I'm really looking forward to helping steer Met Office research and its links with UCL over the coming year."
About the Met Office Academic Partnership
The Met Office Academic Partnership (MOAP) is a collaboration between the Met Office and leading UK universities.
It aims to take a cross-disciplinary approach to advancing weather and climate science by combining academic knowledge with applied expertise.
Part of the Met Office’s Research and Innovation Strategy, MOAP is helping to deliver innovative solutions for predicting weather and climate by bringing together research from a wide variety of fields, including health, technology, artificial intelligence, and social sciences.
The appointment marks Professor Brierley’s contributions to climate science through collaborative research and the importance of both in addressing the global climate crisis.
Climate modeller exploring uncertainty in climate models and past warm periods, particularly the Pliocene.
Learn more about MOAP
Discover how the Met Office Academic Partnership connects UCL with leading UK universities to advance climate and weather research.
Visit the Met OfficeExplore the Met Office Informatics
Find out how the Met Office is using artificial intelligence and data science to transform weather and climate forecasting.
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