First the authors divide the planet’s surface into a grid with a six-sided cube (top left) and then flatten out the six sides into a 2-D shape, like in a paper model (bottom left). This new technique let the authors use standard machine learning techniques, developed for 2-D images, for weather forecasting. Weyn et al./ Journal of Advances in Modeling Earth Systems
First the authors divide the planet's surface into a grid with a six-sided cube ( top left ) and then flatten out the six sides into a 2-D shape, like in a paper model ( bottom left ). This new technique let the authors use standard machine learning techniques, developed for 2-D images, for weather forecasting. Weyn et al. Journal of Advances in Modeling Earth Systems Today's weather forecasts come from some of the most powerful computers on Earth. The huge machines churn through millions of calculations to solve equations to predict temperature, wind, rainfall and other weather events. A forecast's combined need for speed and accuracy taxes even the most modern computers. The future could take a radically different approach.
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