I can’t imagine why this project exists. We have thousands of weather stations across the world already. Disentangling the temperature of your pocket from the actual temperature seems like an exercise in futility to me. Even the authors claim they can only get within 2.7 degrees Fahrenheit, so what is the point of having this inaccurate data?
From the American Geophysical Union
Crowdsourcing weather using smartphone batteries
WASHINGTON, DC — Smartphones are a great way to check in on the latest weather predictions, but new research aims to use the batteries in those same smartphones to predict the weather.
A group of smartphone app developers and weather experts discovered a way to use the temperature sensors built into smartphone batteries to crowdsource weather information. These tiny thermometers usually prevent smartphones from dangerously overheating, but the researchers discovered the battery temperatures tell a story about the environment around them.
Crowdsourcing hundreds of thousands of smartphone temperature readings from phones running the popular OpenSignal Android app, the team estimated daily average temperatures for eight major cities around the world. After calibration, the team calculated air temperatures within an average of 1.5 degrees Celsius (2.7 degrees Fahrenheit) of the actual value, which should improve as more users join the system.
While each of the cities already has established weather stations, according to the new method’s creators it could one day make predictions possible at a much finer scale of time and space than is currently feasible. Whereas today, weather reports typically provide one temperature for an entire city and a handful of readings expected throughout a day, the technique could lead to continuously updated weather predictions at a city block resolution.
“The ultimate end is to be able to do things we’ve never been able to do before in meteorology and give those really short-term and localized predictions,” said James Robinson, co-founder of London-based app developer OpenSignal that discovered the method. “In London you can go from bright and sunny to cloudy in just a matter of minutes. We’d hope someone would be able to decide when to leave their office to get the best weather for their lunch break.”
The work was published today in Geophysical Research Letters, a journal of the American Geophysical Union.
Smartphone sensors
Robinson’s OpenSignal app collects information voluntarily sent from users’ phones to build accurate maps of cellphone coverage and Wi-Fi access points. The app boasts about 700,000 active users according to Robinson, about 90 percent of which opt in to providing statistics collected by their phones.
Robinson originally wondered whether smartphones running on newer, 4G networks ran hotter than those running on older networks. When no difference showed up, he looked for other potential uses of the temperature information available on Android-powered devices.
“Just sort of for fun we started looking to see if there was a correlation with anything else,” said Robinson. “We got some London weather data for comparison and found the two sets of temperatures were offset, but they had the same sort of shape.”
While OpenSignal is available to iPhone and iPad users, the temperature readings on those devices are not accessible like on their Android counterparts.
Cellphone thermometers
After finding the correlation between smartphone and air temperatures in London, Robinson and his fellow developers assembled temperature data from other major cities where they had a large number of users. Comparing data from Los Angeles, Paris, Mexico City, Moscow, Rome, San Paulo and Buenos Aires, Argentina, they saw the same link between the two sets of temperatures they saw in London.
“It was amazing how easily the correlation sort of popped out,” said Robinson. “We didn’t do any handpicking of data—it sort of just emerged.”
A smartphone’s environment affects its temperature, according to Robinson. On a sweltering day, a cell phone tucked in a pocket will be hotter than the same cell phone on an icy day. Weather experts helped Robinson develop a way to calculate outdoor temperatures from smartphone battery temperatures, the latter of which are typically hotter.
However, other factors unrelated to the outdoor weather can play a role. A phone outdoors running the latest 3-D game could run at 46 degrees Celsius (115 degrees Fahrenheit) while the same phone idling in an air-conditioned building nearby could be only running at 27 degrees Celsius (80 degrees Fahrenheit).
To avoid fluctuations in temperature unrelated to the real outdoor temperature, Robinson needed large amounts of data. While an individual phone might not provide an accurate representation of the weather, combining the readings from hundreds or thousands of phones together gives a more truthful overall picture. Currently Robinson collects over half a million temperature readings each day from users of his OpenWeather app. He said he plans to make the data freely available to academic researchers.
“There’s the wider promise when logging all this information that there will be something really interesting you can understand,” said Robinson. “The most obvious application is climate and weather tracking.”
Personal weather predictions
Currently weather tracking primarily takes place at weather stations, such as those at airports. However, weather stations provide only one point of reference and are rare outside of densely populated areas, forcing weather forecasters to fill in the gaps when making their predictions, reducing both accuracy and how specific an area they can make predictions for.
While Robinson says his multitude of mobile phones can provide large amounts of data, individual areas still need to be fine-tuned using existing weather stations before the incoming information can be usable for weather prediction.
“The challenge is whether we can take this technique and use it in places where we don’t already have reliable weather information to retune the model,” said Robinson. “That’s something we’re still working on.”
Robinson says some recent smartphones come with built-in sensors specifically built to measure the environment around them such as air temperature, humidity and pressure. To take advantage of these features, Robinson and his fellow developers released WeatherSignal, an app built around mobile weather watching.
As these features become commonplace in the smartphone market, Robinson foresees smartphones becoming an important tool in weather monitoring.
Notes for Journalists
Journalists and public information officers (PIOs) of educational and scientific institutions who have registered with AGU can download a PDF copy of this early view article by clicking on this link: http://onlinelibrary.wiley.com/doi/10.1002/grl.50786/abstract
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The one in my pants pocket right now probably says my office is running about 98.6 F….
They can be used to test for trends but not much else. For example, they will be warmer under winter coats and colder in light summer wear except when stuffed into a thong at the beach. All of this can be easily modeled in the field if enough grant money can be found.
CAGW needs more evidence. If all the data from the smartphones equipped with
this app is collected, then AGW can be trumpeted is a FACT. “My mobile tells me
so!”
Computers and the Internet are always right so the 15 degree sudden rise in
“measured” temperatures (from inside the global pockets) will be proof positive
the tipping point has been passed!
Accuracy? Eh? Who needs that?
In other news, boffins discover that by averaging random people’s nose length, they can predict the length of the emperor’s nose within two meters.
I can only imagine how horribly inaccurate this is.
(I’ll just whistle circus music….)
Is this Rep. Weiner’s wife’s idea?
Whatever climate data could be gleaned from could easily be turned into a Hockey stick with the right program. Three ring analysis?
If I didn’t think AGU was a sleaze outfit before, I certainly do now. This would get an F as a science fair project!
With luck any actual scientists left in AGU will be jumping ship and running screaming from this laughing stock.
Did they get a grant for this garbage??????
Perhaps the temperature aspect is only an incentive and the real goal is the tracking infomation.
Sounds about as usefull as say….. tree ring data for predicting weather…. Odd stuff.
Garbage in = Garbage out
Garbage in + massaging =? Value out
How good will the winter night time temperature recordings be? Think indoors, warm and asleep. You wake up and head off to work where it’s nice and warm. I must be missing something.
Guaranteed to support claims of global temperature rises. Only dumb bunnies stay out in the cold.
What if I put my smartphone inside a container filled with CO2?
The trick here is that they necessarily have to run the data through their very sophisticated algorithms. After which the output will tell EXACTLY the story they need.
I can see a raft of new “adjustments” coming in which the folks at NOAA have “absolute confidence”. Women tend to carry cell phones in their purses which would be cooler than pockets. However in certain neighborhoods where the “pants on the ground” style is in fashion that adjustment would need to be reduced. People talking on the phone have the phone in their hands, thus raising the temperature unless bluetooth is active, in which case back to the purse/pocket adjustment. People whose GPS history indicates they have visited a pharmacy or the pharmacy section of a supermarket recently carry a higher chance of having a fever. My word, this is almost a complicated as tree rings.
It’s going to take a little work before personal smartphone temperature data are sufficiently robust for climatological purposes. I’d say roughly about the time of the next ice age.
More away to track people?
This might do what the articole says:
That makes sense.
If 90% of phones in the range of a certain transmitter not a change in temperature at once… and then it rains in that area… and that occurs repeatedly then…
Then you can say that this change means rain in the lea of them their hills.
That would be a new skill. It might work.
I think this is the new AGW methodology.
It used to be:
“If the data don’t fit, you must omit.”,
which has been replaced by the far superior (for grant-seeking purposes):
“If the data don’t fit, you must bullsh–.”
[rimshot]
Robinson originally wondered whether smartphones running on newer, 4G networks ran hotter than those running on older networks. When no difference showed up, he looked for other potential uses of the temperature information available on Android-powered devices.
1. How much grant money did this (SNIP!) spend finding out what the design engineers for any cell phone manufacturer could have told them in seconds?
2. Is this piece of (SNIP!) of the impression that products like this go to manufacturing without knowing the answer to that question before spending hundreds of millions in manufacturing?
3. Having wasted substantive time and financial resources answering a question to which the answer was already known and easily available, this certified (SNIP!) decided to be creative about finding additional ways to waste more time and money on the same data?
Then he chose to make a complete fool of himself and the AGU by publishing it all, so I guess justice is served.
Teasing out the “real” temperature from a mobile which may be in a pocket/purse/inside/outside/charging/etc. is as impossible as teasing out temperature from tree rings – but hey! A real climate scientist will do it.
“After calibration, the team calculated air temperatures within an average of 1.5 degrees Celsius (2.7 degrees Fahrenheit) of the actual value, which should improve as more users join the system.”
*
How on Earth would the accuracy of their readings “improve” with more users joining the system? If you multiply Bad you just get more of it.
In my inner vision for the future I see Phil Jones making sense of this exciting new data by processing it all in a single Excel spreadsheet.
*sigh* All the scoffers clearly don’t understand what is going on. It is the sample size effect on randomly-distributed data. If you have a single-measurement error S and N sample measurements, the ensemble error Se = S / (N)^0.5. This doesn’t eliminate systematic (bias) errors, of course, but if you have a sample of 10,000, that will reduce the random error by a factor of 100 and allow you to find the bias error. Gradients (d/dx) and time trends (d/dt) will be unaffected by bias error.
By the way, I’m not a Warmist; I’m a practicing engineer with a background in applied physics and thermodynamics, so muffle that jeer. This is an honest innovation, so give it a chance to see where it succeeds and/or fails.
Instead of just making fun of this project – how about something constructive.
He says the data will be available to everyone – that’s a plus!
If there is a sudden change in temperature, then the phone was just moved to a new environment. What would it take to determine which of the 2 temperatures is more useful? Perhaps if it is “off hook” then it is not in some pocket. Sunny cars tend to be over 110F – pretty easy to detect.
He says that the temperatures track the official airport temperature, but does not say if they are higher or lower. It would be very interesting if an area plot showed to airport to be several degrees warmer than other parts of the city. Of course that would require some kind of location data – either gps or a tower location.
In other words, this obviously stupid idea might be just the type of data we want. Rather than throwing darts, we should take the lead on trying to make this work. If *WE* write the software, then we can keep the algorithms honest.