The barometers in most Android phones allow us to generate useful weather data that nobody has ever done at scale before. The barometers are in the phones for Google to do better indoor mapping by using the barometer as an altimeter. But over the time scale of about 4-6 hours, the data from periodic readings of the barometer becomes a clear description of the weather outside. I've made this sensor code in the app into an open source library to encourage other developers to do similar work.
This data could have some potential use in real forecast models in the future. Significant research is needed first to do data quality control and preparation for assimilation into models like WRF. I have worked on similar systems in the past (collaborations with Cliff Mass on early data for early proof-of-concept papers, he has been busy recently with other collaborations on this topic! [1]). This time around will be different for a variety of reasons, primarily that I am making 'virtual weather stations' out of the data to completely protect user privacy and improve data quality. This means, rather than store individual barometric pressure measurements, I will only keep data in a geographical region that has multiple phones in it, recording data that can be summarized in statistics like pressure mean, trend, etc, and allow the raw data with latitude/longitude pairs be thrown out - protecting user location privacy.
[1] Some recent papers by Cliff Mass and his team at UW, (not using data from this project):
Smartphone Pressure Collection and Bias Correction Using Machine Learning
There are other interesting things happening in this app that other apps aren't doing, like testing out photos of the sky as a data input to weather models. We're starting with users sending in photos of the sky with labels of what they see, and then I'll be using that as the training dataset for a machine learning classifier. The classifier, once trained with the ML model data, should be able to assign weather features to photos just by scanning the photo. I think this could make a valuable input to weather models in the future as well! Your phone should be able to 'see' clouds or rain or sunny weather and contribute that data back to the forecast model automatically. How neat would that be!
All Clear is US-only due to the difficulty I had getting international weather data. I tried really hard to make this international from the start, but it turns out global weather data is super expensive. I made this app for IBM's WeatherUnderground data feed in particular, and I was ready for the $400/month subscription to buy the data! Then they turned it off without notice and shut down the API form. No chance to buy it any more!
Then they make you wait for a phone call and then 3 weeks later they tell you the prices are 10x higher than before and there's nothing you can do about it. So I reworked the app to work with the free US NWS / NOAA data and then I launched it. So far so good. I am looking for a more economical data source for international data and I will relaunch internationally when I can!
This Android app is using sensors in phones to create new datasets about the atmosphere: using barometers in phones we can create the largest network of environmental sensors ever. One day this data could be used in active weather forecast models. (US-only)