“This is a completely different approach to what people have done before. The writing’s on the wall that this is going to transform things, it’s going to be the new way of doing forecasting,” Turner said. He said the model would eventually be able to produce accurate eight-day forecasts, compared with five-day forecast at present, as well as hyper-localised predictions.

Dr Scott Hosking, the director of science and innovation for environment and sustainability at the Alan Turing Institute, said the breakthrough could “democratise forecasting” by making powerful technologies available to developing nations around the world, as well as assisting policymakers, emergency planners and industries that rely on accurate weather forecasts.

  • FizzyOrange@programming.dev
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    11 days ago

    I’d settle for detailed short term local rain forecast. It’s such a huge application and as far as I can tell (please correct me if I’m wrong!) nobody does it at all well.

    • Often ensembles are only run every 3 or 6 hours, so the predictions are needlessly out of date.
    • The ensembles have a very small number of runs (like less than 10) so you can’t get a good estimate of probabilities.
    • Usually you can’t get access to the raw data anyway and user facing sites dumb things down to a single number, so e.g. “it’s going to drizzle all day” and “it’s going to tip it down for half an hour at some point” are presented exactly the same. As are “it’s either going to rain loads or not at all” and “it’s definitely going to rain a bit”.