In response to the increasing unpredictability and severity of weather patterns due to climate change, there is a growing need for more accurate and faster weather forecasts. Currently, meteorologists rely on time-consuming manual analyses of multiple weather variables.
However, recent developments in artificial intelligence (AI) systems are poised to revolutionize the field. One notable AI model, Pangu-Weather, developed by Huawei, employs deep learning to swiftly and accurately predict global weather patterns. Pangu-Weather has demonstrated performance on par with established traditional forecasting methods.
Another AI algorithm excels in predicting extreme rainfall, consistently outperforming existing models. This advancement holds the potential to enhance preparedness and response to weather-related disasters.
AI models such as Pangu-Weather, Nvidia’s FourcastNet, and Google-DeepMind’s GraphCast are reshaping the landscape of weather forecasting. The integration of AI with conventional forecasting methods is currently under exploration.
While AI systems show promise in improving weather forecasts, they still face challenges in predicting the intensity of extreme weather events accurately. Physics-based AI models like NowcastNet offer extended lead times for extreme rainfall forecasts, providing valuable preparation windows.
These AI innovations have the potential to significantly enhance short-term weather predictions, particularly for mitigating the impact of extreme rainfall events. Their practical effectiveness, however, remains a subject of ongoing study. The evolving climate system further complicates the assessment of their long-term utility in the field of weather forecasting.
Original Article: “New AI systems could speed up our ability to create weather forecasts” by Melissa Heikkilä on MIT Technology Review (Published on July 5, 2023)