[counters]

They already did begin exploring this field, starting with precipitation nowcasting - like every other AI shop out there (see https://www.deepmind.com/blog/nowcasting-the-next-hour-of-ra...).

Numerical weather prediction is a _very_ well established field. In fact, large tranches of modern computer science and computing in general owe their existence in direct ways to the importance of numerical weather prediction, since this was one of the original applications of digital computers! Modern weather forecasting models are extraordinarily sophisticated scientific and engineering achievements. It's not obvious that AI actually offers any significant, immediate benefit over these tools save for niche, simplified forecasts (e.g. precipitation nowcasts) - certainly, given the prowess of modern NWP, the ROI is likely to be very low for research investments into general purpose AI weather forecasts.

One might then argue that perhaps AI can be useful to help refine or post-process these existing forecast systems? But of course - we've been doing just that since the 1970's. In fact, even the basic weather forecast that you might get from your national weather service these days is based on a sophisticated statistically post-processed machinery applied to not one but dozens of weather forecasts.

Weather prediction is unlikely to be a field where AI practitioners stumble across a significant improvement to the status quo. It would be far wiser to work closely with meteorology experts to solve practical and _useful_ weather forecast problems - like, is that thunderstorm I see on radar likely to produce a tornado in the next 45 minutes?