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University of Leeds AI-based environmental forecasting community
The University of Leeds is a leading centre for research and innovation in the use of machine-learning and artificial intelligence (AI) for environmental prediction. Our research brings together specialists across the university including the School of Earth and Environment, the School of Computing and the School of Mathematics. We work to bring together our understanding of environmental systems with innovation in data science, to create accurate and useful prediction models. We work on atmospheric prediction, from hours to months, and on prediction of environmental systems such as crops and natural vegetation.
News
News from across the group's projects
Thoughts shared by the Permanent Secretary
The Acting Permanent Secretary in the Ministry of Green Economy and Environment, Mr Rainford Simumbwe, addressed participants at the Weather and Climate Information Services (WISER) Early Warnings for All (EWSA) intensive testbed open day on 5 February 2025. Simumbwe said, “This testbed…marks a significant step in our efforts to enhance Zambia's ability to deliver timely,...
Intensive weather forecast testbed kicks off in Zambia, South Africa and Mozambique
A team of researchers from the University of Leeds have arrived in Zambia to play a leading role in a ground-breaking weather forecasting testbed as part of a project to create new early warning systems for vulnerable communities in Lusaka. The WISER-EWSA project is led by Doug Parker and John Marsham at Leeds and includes partners from Europe and across Southern Africa.
Blog Posts
How will AI transform weather forecasting in Africa?
Doug Parker and Michael Baidu joined a panel discussion on the question “How will AI transform weather forecasting in Africa?”, at the Turing Institute’s AI-UK...
Intensive Testbed Weekly Summary: January 27th–February 3rd, 2025
The T2-Z Intensive Testbed launched on January 30th, and will run until February 7th, 2025. Prior to the start, a three-day training programme (January 27–29)...