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DeeperML
Sana Hassan@MarkTechPost
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Google has unveiled a new AI model designed to forecast tropical cyclones with improved accuracy. Developed through a collaboration between Google Research and DeepMind, the model is accessible via a newly launched website called Weather Lab. The AI aims to predict both the path and intensity of cyclones days in advance, overcoming limitations present in traditional physics-based weather prediction models. Google claims its algorithm achieves "state-of-the-art accuracy" in forecasting cyclone track and intensity, as well as details like formation, size, and shape.
The AI model was trained using two extensive datasets: one describing the characteristics of nearly 5,000 cyclones from the past 45 years, and another containing millions of weather observations. Internal testing demonstrated the algorithm's ability to accurately predict the paths of recent cyclones, in some cases up to a week in advance. The model can generate 50 possible scenarios, extending forecast capabilities up to 15 days.
This breakthrough has already seen adoption by the U.S. National Hurricane Center, which is now using these experimental AI predictions alongside traditional forecasting models in its operational workflow. Google's AI's ability to forecast up to 15 days in advance marks a significant improvement over current models, which typically provide 3-5 day forecasts. Google made the AI accessible through a new website called Weather Lab. The model is available alongside two years' worth of historical forecasts, as well as data from traditional physics-based weather prediction algorithms. According to Google, this could help weather agencies and emergency service experts better anticipate a cyclone’s path and intensity.
References :
The AI model was trained using two extensive datasets: one describing the characteristics of nearly 5,000 cyclones from the past 45 years, and another containing millions of weather observations. Internal testing demonstrated the algorithm's ability to accurately predict the paths of recent cyclones, in some cases up to a week in advance. The model can generate 50 possible scenarios, extending forecast capabilities up to 15 days.
This breakthrough has already seen adoption by the U.S. National Hurricane Center, which is now using these experimental AI predictions alongside traditional forecasting models in its operational workflow. Google's AI's ability to forecast up to 15 days in advance marks a significant improvement over current models, which typically provide 3-5 day forecasts. Google made the AI accessible through a new website called Weather Lab. The model is available alongside two years' worth of historical forecasts, as well as data from traditional physics-based weather prediction algorithms. According to Google, this could help weather agencies and emergency service experts better anticipate a cyclone’s path and intensity.
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References :
- The Official Google Blog: Today Google DeepMind and Google Research are launching a public preview of Weather Lab, an interactive website for sharing our AIweather models, and debuting our newest...
- siliconangle.com: Google LLC today detailed an artificial intelligence model that can forecast the path and intensity of tropical cyclones days in advance.
- SiliconANGLE: Google develops AI model for forecasting tropical cyclones
- AI News | VentureBeat: Google DeepMind just changed hurricane forecasting forever with new AI model
- Maginative: Google's AI Can Now Predict Hurricane Paths 15 Days Out — and the Hurricane Center Is Using It
- MarkTechPost: Google AI Unveils a Hybrid AI-Physics Model for Accurate Regional Climate Risk Forecasts with Better Uncertainty Assessment
- www.engadget.com: Google DeepMind is sharing its AI forecasts with the National Weather Service
- the-decoder.com: Google Deepmind launches Weather Lab to test AI models for tropical cyclone forecasting
Classification:
- HashTags: #AIWeather #TropicalCyclones #GoogleAI
- Company: Google
- Target: Global
- Product: Weather Lab
- Feature: Weather Forecasting
- Type: AI
- Severity: Informative