I really love the idea of crowdsourced meteorological data. I can envision a world where every smartphone has a lower power barometer and ambient temperature and humidity sensors. Combine this with lower power GPS and you could have the majority of the world's citizens constantly transmitting basic atmospheric data 24/7. As sensors become more advanced and cheaper, one can even envision a time when smartphones also include things like air quality sensors and so forth.
I can't imagine how accurate our weather forecasting would become if we had constant access to this incredible amount of real-time data.
I don't think ambient temperature and humidity sensors would work very well because people usually aren't outside and when they are, phone is usually in pocket.
I love this idea too though. I'm guessing pressure is one of the least effected by being inside or in a pocket, while still being highly useful for weather prediction.
It would be interesting to study this. I wonder if there are ways to normalize the data and still extract some useful data even if the devices are in the users' pockets.
Longer term, I can see these sensors being embedded in glasses or contacts, which could be an easier problem.
The problem is that the effect of being in a pocket is not zero-biased when it comes to temperature (and possibly also humidity). You'd see temperatures being pulled towards normal body temperature on average.
Yes, but in my rudimentary understanding of weather the importance is the pressure differential rather than the absolute pressure.
I believe the data in aggregate will provide a pretty good map of the pressure gradient which could then be fixed to the more accurate dedicated weather stations. Think of it like the 10,000 year clock which uses a clock known to drift in conjunction with a solar time fix to calibrate.
You may be right about pressure, but btown is talking about temperature and that's going to have much worse systematic bias exactly as he says. Your comment and his are nearly completely unrelated.
>one can even envision a time when smartphones also include things like air quality sensors and so forth.
How-about ambient light sensors so we can accurately predict potential solar power in a given area? Correlated with NOAA data this could be very valuable to companies looking for good solar data.
Luminosity/temperature/humidity inside a house or office is usually very different from the value outside. So these data are usefull for the user but not for a weather modeler.
But pressure inside a house is usually almost equal to the pressure outside. So it can be crowdsourced.
Sadly even if we had one sensor per cubic foot of the troposphere nonlinearity would quickly swamp any predictive value, I'm not sure we will ever have accurate forecasts past a few days.
Right, it's generally believed that forecasting will never be effective beyond about 15 days, due to amplification of small uncertainties by the nonlinear atmosphere dynamics. Predictability is better in the tropics by a couple of days, and better in the northern hemisphere winter by a couple of days.
It's worth noting that the pressures measured, even if they could be calibrated, would be almost entirely on land, and only at the surface of the Earth, not at higher altitudes (it is, of course, a 3D problem). And also, a lot more than just pressure is needed -- temperature, wind velocity, clouds, aerosols, irradiance, ocean currents, wave height, soil moisture, ...
I really love the idea of crowdsourced meteorological data. I can envision a world where every smartphone has a lower power barometer and ambient temperature and humidity sensors. Combine this with lower power GPS and you could have the majority of the world's citizens constantly transmitting basic atmospheric data 24/7. As sensors become more advanced and cheaper, one can even envision a time when smartphones also include things like air quality sensors and so forth.
I can't imagine how accurate our weather forecasting would become if we had constant access to this incredible amount of real-time data.