Even more complicated and less obvious than some of the other sorts of Earth observations that the author talks about.

I could write about this all day, but I'll start with the obvious: you're competing against a forecast that may have been made 30 minutes ago, an hour ago, 6 hours ago, 24 hours ago, or sometimes even more. So in some cases, at best you might be alerting people that something they already expected to happen is, now, actually happening. How useful that is depends on the context. Detecting a wildfire as it ignites? Cool - but most likely, if it's near an urban area, people already saw the smoke, or people were already ready to react because a Red Flag warning was posted. Lightning strikes? Folks already heard the thunder, and hopefully would've seen a risk of thunderstorms in the forecast earlier in the day or prior.

Carefully and succinctly incorporating narrow weather observations into existing forecast and alerting systems as a way to buttress them, decrease noise/boost signal, or otherwise capture a tiny bit more value than what was already there might work. But beyond that I struggle to see massive amounts of value for most of the use cases that many industries or communities wrestle with regarding weather alerting.

Weather data is usually derived from geostationary satellites which is sort of an adjacent field to the lower-orbit imagery the article is based on (i believe?)... but i know of a couple of projects doing analytics here - not sure about commercial potential though, they're early stage startups or academia.