The popular Galaxy S3 has a pressure senros |
Well, this project is really taking off and I encourage any of you with the right smartphones (see list below) to sign up for the app and join the network. Right now, we at the University of Washington are acquiring the data every hour and plotting the location of the smarphone pressure observations hourly. Below is one from today. You can see the urban areas as dense collection areas, but back east there are plenty in rural areas. Right now we are getting 3000-4000 observations per hour over the domain shown below. Wow!
But to make this the revolutionary effort it could be, we need many more observations--like 100x more.
The following smartphones and pads have pressure sensors:
Samsung Galaxy Nexus (tablet), Samsung Galaxy S3 and Motorola Xoom (tablet)
The Galaxy S3 is a hot item now, with millions sold in North America alone. The clear potential is for millions of observations per hour over North America alone.
Samsung Nexus |
Recently, Cumulonimbus, Inc. released PressureNet3, with substantially increase capabilities, including fun graphics for seeing your own and other's pressure observations.
So if you have one of the units, please considering downloading the app, and if you are in the market for a smartphone or tablet, seriously consider one of the above choices. Personal information is NOT put in the database.
Why am I so excited about these observations? Because surface pressure is a uniquely valuable surface observation since it reflects the atmosphere above (surface pressure reflects the weight of the air above the sensor). Recent research has revealed that with sufficient surface pressure senors and a sophisticated model-based data assimilation system, one can accurately reconstruct the three-dimensional structure of the atmosphere.
Pressure observations can be taken in buildings or cars and don't suffer exposure problems like temperature and wind.
A graduate student of mine and Professor Greg Hakim, Luke Madaus, is working on assimilating both pressure AND pressure change in high-resolution numerical forecast models using traditional and non-traditional pressure observing networks. The early work is very promising. We plan to use the dense observations from smartphones, but first have to figure how to do quality control and to determine which smartphones are moving and remaining stationary (remember we have position-GPS- and pressure from each of them). And we will test our new capabilities on a range of examples, including Midwest convection (thunderstorms) and Pacific Northwest features (like the pesky convergence zone).
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