Researchers improve weather forecasts with the help of AI looking two to six weeks out. Really!

Climate and weather are very complex, interrelated natural phenomena that are still poorly understood!

However, there is no doubt that ML & AI will improve weather forecasting in the near term!

Notice ML & AI is not directly applied to forecasting but to forecasting error correction!

Notice the frequent usage of the word "skill" here. Like it is a killer!

Notice the expression "unprecedented accuracy" here. Meaning in this context still very inaccurate and unreliable!

From the abstract:

"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 as far as 2 weeks thanks to steady advances in physics-based dynamical models and data-driven artificial intelligence models.

However, model skill [???] drops precipitously at subseasonal timescales (2–6 weeks ahead) due to compounding errors, systemic model biases and the chaotic nature of the atmosphere.

To counter this degradation, we introduce probabilistic bias correction, a machine learning framework that substantially reduces systematic error by learning to correct historical probabilistic forecasts.

When applied to the leading dynamical and artificial intelligence models from the European Centre for Medium-Range Weather Forecasts (ECMWF), probabilistic bias correction doubles the modest 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 probabilistic bias correction for operational deployment, and, in the 2025 real-time forecasting competition of ECMWF, its global forecasts were the best for all weather variables and lead times, outperforming the dynamical models from six operational forecasting centres, an international dynamical multimodel ensemble, the AI Forecasting System of ECMWF 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."

Researchers improve weather forecasts looking two to six weeks out | MIT News | Massachusetts Institute of Technology "A new machine-learning approach broke records for weather forecasting for an important time frame in emergency planning."

Advancing subseasonal forecasting with machine learning (open access)