Surprisingly low signal-to-noise ratio for most of the common, creative ways people come up with to detect rain. Windshield wipers on cars are another example.

The thing is, even if you did have a super reliable in situ "rain detector", how do you combine it with the existing datasets like weather radar, which is a gridded product? This is actually a really, really difficult sensor fusion problem when you then super-impose product requirements like the general location real-time detection map and the inputs necessary for whatever internal nowcasting system they use.

If you care that much buy a $100 weather station and sit it outside your window?

Actual ground observation weather stations are fairly rare outside of places like airports and major news stations.

“Is it raining here right now?” Is a harder question than you’re giving it credit for. Radar can show rainfall at as low as a couple thousand feet altitude, but if conditions are right/wrong (depending on how you look at it) it never reaches the ground.

What's wrong with devices phoning home if they don't actually send any usable data there?

I believe they send barometer information home

The AirTag comparison is interesting. AirTag tracking is clever and results in Apple not knowing the location or identity of either the AirTag or the phone reporting it. This relies on rotating keys that can be seen as random, or at least not identifiable.

But rain or other objective information? I suppose it works, maybe a bit like “limit IP address tracking” — cloudflare or other edge provider could mediate so Apple gets the data, knows it comes from an iPhone (to prevent bad data attacks), but Apple can’t tell what phone sent which data.

(the privacy concern being documentation of when you were inside/outside/etc).