New AI Systems Enhance Speed and Accuracy of Weather Forecasts

– New AI systems have the potential to expedite the process of creating weather forecasts and improve their accuracy.

– Two papers published in Nature present advancements in AI technology for weather prediction.

– Huawei's AI model, Pangu-Weather, can quickly predict weekly weather patterns worldwide with comparable accuracy to traditional methods.

– A deep-learning algorithm outperformed other methods in predicting extreme rainfall, ranking first in around 70% of tests.

– These AI models can complement conventional forecasting methods, aiding authorities in preparing for adverse weather conditions.

– Pangu-Weather utilizes a deep neural network trained on 39 years of reanalysis data, analyzing weather variables simultaneously in seconds.

– The model demonstrated the ability to track tropical cyclones accurately, even without specific training data on cyclones.

– Other AI models, such as NowcastNet, can predict extreme rain up to three hours in advance, surpassing existing methods.

– NowcastNet incorporates data from various weather radars and is rooted in the principles of atmospheric physics, resulting in more comprehensive predictions.

– While AI can help determine the path of tropical cyclones, it may underestimate the intensity of extreme weather events.

– The performance of these AI systems in practical applications is yet to be fully assessed, considering the changing climate and potential unknowns.

– AI-based weather forecasting shows promise in improving predictions and providing timely information for preparations against extreme rain and other weather events.

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