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Enhancing AI and Dynamical Subseasonal Forecasts with Probabilistic Bias Correction

Guan, Hannah, Mouatadid, Soukayna, Orenstein, Paulo, Cohen, Judah, Dong, Haiyu, Ni, Zekun, Berman, Jeremy, Flaspohler, Genevieve, Lu, Alex, Schloer, Jakob, Talib, Joshua, Weyn, Jonathan A., Mackey, Lester

arXiv.org Machine Learning

Decision-makers rely on weather forecasts to plant crops, manage wildfires, allocate water and energy, and prepare for weather extremes. Today, such forecasts enjoy unprecedented accuracy out to two weeks thanks to steady advances in physics-based dynamical models and data-driven artificial intelligence (AI) models. However, model skill drops precipitously at subseasonal timescales (2 - 6 weeks ahead), due to compounding errors and persistent biases. To counter this degradation, we introduce probabilistic bias correction (PBC), a machine learning framework that substantially reduces systematic error by learning to correct historical probabilistic forecasts. When applied to the leading dynamical and AI models from the European Centre for Medium-Range Weather Forecasts (ECMWF), PBC doubles the subseasonal skill of the AI Forecasting System and improves the skill of the operationally-debiased dynamical model for 91% of pressure, 92% of temperature, and 98% of precipitation targets. We designed PBC for operational deployment, and, in ECMWF's 2025 real-time forecasting competition, its global forecasts placed first for all weather variables and lead times, outperforming the dynamical models from six operational forecasting centers, an international dynamical multi-model ensemble, ECMWF's AI Forecasting System, and the forecasting systems of 34 teams worldwide. These probabilistic skill gains translate into more accurate prediction of extreme events and have the potential to improve agricultural planning, energy management, and disaster preparedness in vulnerable communities.


Microsoft's Copilot AI goes head-to-head with China's DeepSeek in Africa

The Japan Times

Microsoft's Copilot AI goes head-to-head with China's DeepSeek in Africa Microsoft is investing 5.4 billion South African rand ($330 million) to expand its cloud and AI capacity in the country by the end of next year, and it also has plans to build a geothermal-powered data center in Kenya. Microsoft is making a push for more Africans to adopt its artificial-intelligence tools as the U.S. technology giant competes with China's DeepSeek for customers from the world's youngest and fastest-growing population. The Redmond, Washington-based company plans to train 3 million Africans on its AI technology this year, in partnership with schools, universities and other institutions, with a focus on South Africa, Kenya, Nigeria and Morocco. It's also partnered with MTN Group, Africa's biggest telecommunications firm, to sell the Microsoft 365 suit of apps together with its Copilot digital assistant to its 300 million subscribers. The Microsoft Elevate training initiative aims to make sure cost is not a barrier to building AI literacy at scale," Middle East and Africa President Naim Yazbeck said in an interview. Chinese technology is active in Africa and our job is to compete."



Using Statisticsto Automate Stochastic Optimization

Neural Information Processing Systems

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