AI IN SUSTAINABILITY

According to the Met Office and Microsoft, the platform is expected to save more than 7,000 tonnes of CO₂ in its first operational year alone.

Blending physics and AI to maintain trust For all the promise of AI, Kirstine is clear that machine learning will not replace physics‐based models in the foreseeable future. Her vision is a blended system that uses both approaches in combination, exploiting their respective strengths.“ The future is going to be a blended approach that draws on the strengths of both,” she explains.

Physics‐based models provide an interpretable framework grounded in the laws of nature, helping forecasters understand why the atmosphere behaves as it does. That scientific insight is essential for trust, especially when forecasts inform critical decisions on flood defences, heatwave response and aviation safety. Physics models also generate the synthetic training data required to build robust machine learning systems, especially as climate change makes historical observations less representative of future conditions.

Machine learning models, meanwhile, excel at speed and pattern recognition, capturing subtle relationships in the data that may be difficult to express explicitly in equations. However, they are constrained by their training data and may struggle with so‐called“ grey swan” events – rare but physically possible extremes that drive many of the most serious impacts.

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“ Those grey swan events, like major heatwaves or extreme flooding, are exactly what we need to predict,” Kirstine says.“ That’ s why physics still matters.”

AI for Everyone Embedding AI into forecasting is only part of the transformation. The Met Office has launched a wider change programme called AI for Everyone, designed to bring AI tools and understanding to staff across the organisation.

“ AI for Everyone is a transformational change programme that covers everything that happens in the Met Office,” Kirstine explains.

The programme includes training, clear policies, hackathons and an annual AI for Everyone in the Street event, where teams share how they are applying AI. It spans corporate services, core science and frontline

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