DeepMind’s Algorithm Predicts Upcoming Weather with Great Accuracy
According to a story on TechnologyReview.com, DeepMind has developed a weather algorithm that’s proven to be better at making short-term weather predictions than other systems.
“In a blind comparison with existing tools, several dozen experts judged DGMR’s forecasts to be the best across a range of factors—including its predictions of the location, extent, movement, and intensity of the rain—89% of the time.”
The results were published in a Nature paper on September 29. Based in London, DeepMind’s deep-learning tool called DGMR (deep generative model of rainfall) can accurately predict the rain in the next 90 minutes—an achievement in weather forecasting. According to the story:
“Forecasting rain, especially heavy rain, is crucial for a lot of industries, from outdoor events to aviation to emergency services. But doing it well is hard. Figuring out how much water is in the sky, and when and where it’s going to fall, depends on a number of weather processes, such as changes in temperature, cloud formation, and wind.”
Current weather predicting systems use massive computer simulations of atmospheric physics that are accurate for longer-term forecasting but fall short in “nowcasting” weather within 90 minutes. Other deep-learning techniques are good at predicting the location of weather, but not the intensity.
“The nowcasting of precipitation remains a substantial challenge for meteorologists,” says Greg Carbin, chief of forecast operations at the NOAA Weather Prediction Center in the U.S., who was not involved in the work.
The system relies on radar data and tracks cloud formations every five minutes.
read more at technologyreview.com