There are thousands of sensors around the city. You can get a sense of shade-vs-sun temperatures by the spread of numbers you see (on cloudy days, the reported temperatures will be much closer together, while on sunny days, sensors in the sun will report elevated temperatures.)
You do need to make sure to disable indoor sensors, and keep in mind that some sensors are faulty. (I've seen some that have been reporting a constant temperature for years.)
I don't understand why it includes indoor sensors at all let alone by default. Why would I want to know the temperature inside some random building?
Add location_type=0 to only get outdoor sensors
Footer should say "Data from PurpleAir API" instead of "Data from SF Microclimates API"...
Mr. Chilly is one of those niche apps that sparks joy and reminds me of the early app days.
It's an excellent iOS app: https://mr-chilly.com/
My goal was to do something similar as a Claude Code skill
Only suggestion: separate Inner and Outer Sunset since there can be a massive difference between near Ocean Beach and near Irving/9th Ave in autumn (ie. SF's hottest season).
Edit: nevermind, just saw both inner_sunset and outer_sunset in /neighborhoods. I'd assumed it was merged based on the human readable list on the landing page. Thanks for the fun API!
Usually what I want the weather for is to choose what to wear, not to put in a bash script or an LLM or something.
Made it in about 5 minutes with v0.
"Temperature, estimated using a formula temp = 1.0227 * raw_temp_f - 9.3755 developed by Lance Wallace to account for heat generated by the WiFi module and other electronics in a PurpleAir sensor. This will not be accurate for all situations. More information can be found in Lance Wallace's notes."
I used to ride a motorcycle every day from the Haight (home) to the Financial District (work), and the temperature grade changes were palpable.
Your point is also completely correct, of course. :)
https://v0-weather-app-one-coral.vercel.app/
Surprisingly, Lands End is the highest temp right now.
Kinda neat!
(Thank you to those who maintain public sensors!)
I do notice that in my neighborhood (Noe Valley) a lot of the sensors are very incorrect or often offline. I've resorted to taking the median and throwing outliers away, but even this often doesn't work. This is the challenge of relying on crowdsourced data I suppose...
note that I also have a system where if the temperature seems outlier compared to direct neighbors it averages the 3 nearest neighbors. this usually occurs in neighborhoods with a single sensor that can skew the results heavily at certain times of the day, etc.
Is that the source of the data?
You should use Purple Air if you want to make it more focused https://www2.purpleair.com/