Other Exeter events

Forecasting Futures

Please note this event takes place on in the basement and has no step-free access. Over 18s only
Past event - 2024
13 May Doors 6.30pm
Event 7.00-9.30pm
Mermaid, 11b Gandy Street,
Exeter EX4 3LS
Sold Out!
Join us for a feast of enlightening talks as experts delve into the forefront of climate science, agriculture, and data innovation. From a climate edition of the classic TV show 'Play Your Cards Right' to revolutionizing weather prediction with AI, this event forecasts insights into shaping a sustainable future. Don't miss the opportunity to explore the intersection of climate, food systems, and cutting-edge technology!

Activity: Play Your Climate Cards Right

James Pope (Senior Climate Scientist)
Whether you remember the classic TV gameshow or not, come on down and enjoy the
challenge of playing your climate cards right. It is higher or lower on changes in future temperature, future sea level or the observed temperature change. I am sure everyone will think you did well, and ultimately it will be nice to see you….

What does climate change mean for the UK food system?

Pete Falloon (Climate Service Lead - Food, Farming & Natural Environment (Met Office); Associate Professor - Climate-resilient food systems (University of Bristol); Sustainability Director (Food Drink Devon))
Pete will discuss what climate change means for the UK agri-food system, from farm to fork, and both in terms of adapting to a changing climate and contributing to net zero and reducing emissions. He will draw on the UK Climate Projections, the work of the Intergovernmental Panel on Climate Change (IPCC), recently published Third Climate Change Risk Assessment (CCRA3) and other sources.

AI/ML driven interactive weather forecasting

Ben Fitzpatrick (Head of Science IT Data Management and Processing)
Machine learning has started to challenge the way the world produces weather forecasts... but does it also offer some new opportunities? What can we do if we can speed up the run time (but watch out for the training time) by 10, 100, 1000, 10000x? How is the machine learning managing to solve these problems so quickly? We’ll go into the background of this exciting field and explore one very interactive application.
Map data © OpenStreetMap contributors.

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