Better Weather Forecasting Thanks to AI
With the help of Artificial Intelligence, it is possible to predict warm weather more accurately. Atmospheric scientist Chiem van Straaten developed a method that learns from incorrect weather predictions and leads to more reliable information.
Weather forecasts are often unreliable. However, to reduce the impact of extreme weather, such as drought or heat, it is important to know in advance when extreme weather is approaching. Van Straaten uses a combination of physical and statistical weather models for this purpose. He demonstrates that the distribution of cold and warm air can be better predicted when looking at longer periods and larger areas.
Using machine learning techniques, Van Straaten and his fellow researchers discovered that processes in the Pacific Ocean are essential in influencing the distribution between cold and warm air. This link in the climate system was found to be missing in the model used by many weather apps for predictions. They developed a method that statistically corrects that model and makes it more useful.
This method also provides more insights into the errors in weather predictions, including by comparing forecasts with actual measured weather. According to Van Straaten, this method is a clear way in which classical, physics-based weather models can be improved with AI. "All users of weather forecasts, from water boards to farmers to ordinary citizens, can benefit from it. They will have access to reliable information earlier."
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