Microsoft says open-source tool improves forecasts two to six weeks ahead

Microsoft researchers say they have developed a lower-cost way to improve weather forecasts two to six weeks ahead. Called Probabilistic Bias Correction (PBC), the method uses machine learning to identify and correct systematic bias in existing models rather than creating a new standalone model. In the study published in Nature, PBC improved the accuracy of a physics-based weather model from the European Centre for Medium-Range Weather Forecasts (ECMWF) for 98% of precipitation targets and 92% of temperature targets, and doubled the accuracy of the ECMWF’s AI forecasting system in the analysis.

The tool is open-source and can run solely on CPUs, which the researchers say could make it easier for under-resourced weather agencies to use. Matthew Chantry, ECMWF’s strategic lead for machine learning, called the work an example of new ideas benefiting the community, but said turning research into an operational process remains challenging.