@LesterMackey
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In @Nature this week, our new research shows how machine learning can improve weather forecasts two to six weeks out, a timeframe that's historically been very difficult to predict.View quoted post on X
It's exciting to see the potential of this work to help us better prepare for extreme weather, manage natural resources, and make more informed decisions in agriculture.
There's a broader lesson here... the future may not just be about ever-more-capable models, but about building intelligent verification systems around them: systems that learn where models are systematically wrong, reason about cause and effect, and continuously calibrate predictions against reality.
Read more: microsoft.com/en-us/research…
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www.nature.com Advancing subseasonal forecasting with machine learning Nature - The AI framework probabilistic bias correction is shown to correct weather forecast errors 2 to 6 weeks ahead and boost forecast skill, making it promising for improved... Weather forecasts are unreliable past two weeks, leaving a crucial gap for farmers and others. Probabilistic Bias Correction improves extended forecasting, taking top honors in a global competition and showing promise for real-world use: msft.it/6013aseY9
IMAGE CREDIT: Cooperative Institute for Research in the Atmosphere at Colorado State University and the National Oceanic and Atmospheric Administration (CSU/CIRA & NOAA)View quoted post on X
