We're thrilled to announce our groundbreaking development in lightning occurrence prediction, now featured on the Nature Communications Editors’ Highlights webpage under "AI and Machine Learning." Dive into our research freely accessible at https://lnkd.in/eYhkFU99, where we bridge traditional algorithms and AI to significantly enhance forecasting accuracy. This work, spotlighted for its innovative approach, is proudly funded by the Compagnia di San Paolo through the project AIxtreme. Explore the highlight at https://lnkd.in/eUasQCAF

For decades, the backbone of scientific prediction has relied on fully-deterministic algorithms, grounded in the well-established principles of physics. These traditional methods have provided a systematic approach to understanding and forecasting weather patterns. However, they often fall short when it comes to predicting extreme events, especially those extremely localized in space.

Enter AI-based strategies 🚀. Our MeteOcean team at UNIGE has successfully leveraged AI to enhance the predictive capabilities of the world-renowned European Centre for Medium-range Weather Forecasts (ECMWF) model.

This breakthrough demonstrates the immense potential of integrating AI with traditional forecasting methods. By harnessing the power of AI and machine learning, we're not just predicting the weather; we're redefining the future of meteorology.

Stay tuned for more updates on how we're pushing the boundaries of weather forecasting with AI! 🌐💡 

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