"Artificial intelligence is bringing new power and capabilities to forecasting models, enabling scientists to detect extreme weather events with greater speed and accuracy. In August, when Google DeepMind's hurricane-forecasting tech was tested on Hurricane Erin, it not only beat out the "official" forecast from the U.S. National Hurricane Center (NHC) for the first 72 hours but also bested a number of physics-based models."
"Other tech giants like Nvidia and Huawei, as well as government agencies like the U.S. National Oceanic and Atmospheric Administration (NOAA), are already testing AI-driven weather models. AI is particularly good at two tasks vital to forecasting: handling big datasets and recognizing patterns within them. Unlike conventional models that primarily rely on current atmospheric readings, Google's AI system analyzes historical hurricane data to uncover patterns that might elude human forecasters."
"There are still limitations, of course. In its first real-time test, for Hurricane Erin, Google's forecasting model performed best at periods of 72 hours or less. But for forecasters, the three- to five-day forecast window is the most crucial, as it's when evacuation orders and hurricane preparations are set in motion. Even the most bullish technologists acknowledge that there are no panaceas and that models come with tradeoffs and limits. For example,"
Satellites in the 1960s transformed weather forecasting by providing global observations that filled gaps over oceans and remote landmasses. Artificial intelligence now offers a new leap by enhancing forecasting models to detect extreme events faster and more accurately. Google's DeepMind outperformed the U.S. National Hurricane Center and several physics-based models for the first 72 hours during Hurricane Erin testing. Major tech firms and government agencies are testing AI-driven models because AI handles large datasets and uncovers historical patterns conventional models may miss. Limitations remain, especially for the crucial three- to five-day forecast window, and models involve tradeoffs and constraints.
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