How is the temperature of your pocket useful for meteorology?

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

The OpenWeather smartphone app collects temperature, humidity and air pressure information from users around the world to track weather conditions in real time.

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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120 thoughts on “How is the temperature of your pocket useful for meteorology?

  1. 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.

  2. 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?

  3. 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.

  4. Whatever climate data could be gleaned from could easily be turned into a Hockey stick with the right program. Three ring analysis?

  5. 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.

  6. Perhaps the temperature aspect is only an incentive and the real goal is the tracking infomation.

  7. 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.

  8. 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.

  9. 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.

  10. This might do what the articole says:

    “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.”

    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.

  11. 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]

  12. 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.

  13. 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.

  14. “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.

  15. *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.

  16. 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.

  17. And they say that anyone who doesn’t believe in global warming is anti-science! I could hardly contain my enthusiasm while reading this wonderful idea. Do those folks have real degrees from real universities?

  18. This is simply a publicity stunt.
    The scientific value of the experiment is precisely zero.
    But publicity stunts are what most major institutions are about these days. Sad!

  19. We all live in micro climates and most of the time we merely want to know what weather we should expect in our home/work/ leisure micro climate. What happens at the other end of the country is usually of no interest.

    The met office are no more than 15 miles from my home but their level of accuracy for our local climate is poor. This matters as we are in a tourist area.

    So my question is could the relatively inexpensive weather station my wife just bought for my birthday be linked in to say three or four others in a local area-around 15 miles square say–and be a useful and cheap way of providing a forecast tailored to exactly our local area?

    Tonyb

  20. M Courtney says:
    August 13, 2013 at 12:12 pm
    “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.”

    Great idea. This would mean we could spare the effort to invent Doppler radar.

  21. Ha, what other data are these folks inadvertently agreeing to provide?

    Who pays for this crap anyhow? Never mind…….

    I wish I could post this pic right now darnit……

    Hummm, another siting inspection service upon us? ;-)

  22. Wouldn’t it make more sense to build a network to monitor the outdoor thermometers built into most cars?

  23. 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

    ———————————————————————————————————————–

    Ahh, the good ole’ “average enough random data and all the randomness will drop out to leave something meaning” approach.

  24. DirkH says August 13, 2013 at 12:46 pm…
    Fair point for the spotting of clouds; I may have picked the wrong illustration.

    But my point still stands. Having a finer distribution of sensors for temp changes can give us more information. This isn’t junk science and it may achieve what they say. It isn’t necessarily daft. Look at what Michael J. Dunn says at August 13, 2013 at 12:30 pm.

    Also, (off topic) did you notice that I did try to respond to your comments on my socialism on that thread a while back? I didn’t respected your comments and didn’t ignore your vivacious objection to my downgrading of property rights from perfect sovereignty.

  25. M Courtney;
    This isn’t junk science and it may achieve what they say. It isn’t necessarily daft.
    >>>>>>>>>>>>>>>>

    It won’t and it is. Ask your dad. I’m betting on a snort of derision.

  26. Why are posts being lost? this is about the 5th time in so many weeks. It says “sorry this comment cannot be posted”. It’s very off-putting. 3rd time lucky!! no wait… 8th time lucky!!

  27. They will be able to predict nothing with this system. When it is cold people tend to stay in and keep warm and when it is warm ….

    If they plan on using it as a PR tool for AGW let them knock themselves out. If I look out of my window and see snow and ice and my weather app says warm, sunny and humid I know which system I am going to believe.

  28. How are they going to tell which phones are indoors and which are outside?
    How are they going to determine when a batter is being charged?

    This nonsense is worse than useless, but I’m willing to bet that 10′s of thousands of people will sign up to participate.

  29. “…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.”

    This is the same mentality that says averaging together several inaccurate climate models improves climate prediction.

  30. These tiny thermometers usually prevent smartphones from dangerously overheating….

    …and, of course, you would have to adjust temps up for that

  31. Hmmm. Here in the South in August, I stay mostly indoors or in an air conditioned car. If I go outside to do yard work, my phone stays indoors. So how does this reflect the outside temperature?

  32. davidmhoffer says at August 13, 2013 at 1:03 pm… Nope, I disagree.

    If they are taking lots of independent measurements from different meters on different phones then the calibration and measuring errors can be mitigated by taking the delta; the sign and to a lesser extent the magnitude of the change.

    Then building up a set of correlations for a very local area (each mobile phone mast range) will have predictive power.
    That is marketable. It isn’t worthless.

  33. David, UK says at August 13, 2013 at 1:16 pm

    “…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.”
    This is the same mentality that says averaging together several inaccurate climate models improves climate prediction.

    No it isn’t.
    Models are representations of ideas about reality.
    Measurements are representations of reality.

    Different ideas don’t mix. Diluted opinions get further away from the thinking that justified them.
    But what is – is, even if you don’t like it.

    This is averaging measurements of the real world. And a lot of measurements too.

  34. M Courtney;
    That is marketable. It isn’t worthless.
    >>>>>>>>>>>>

    Oh its marketable all right. So are pet rocks.

  35. This will show warming.

    http://electronics.howstuffworks.com/everyday-tech/lithium-ion-battery2.htm

    Lithium Ion batteries (common in cell phones). Will fail more frequently as the batteries age. When the batteries fail, they often get hot (seperator failure). Not to mention, as battery life drops, if the user doesn’t replace the battery, it will spend longer plugged into a charger. This will neccessarily generate higher “average” temperature readings over time.
    Of course, there is also the insulative properties of lint and dust – which would likely lead to higher readings of temperature as cell phones get older.

  36. I wonder if the researchers have taken UHI effects into consideration. (Underwear Heat Island)

  37. Michael J. Dunn says: @ August 13, 2013 at 12:30 pm

    *sigh* All the scoffers clearly don’t understand what is going on. It is the sample size effect on randomly-distributed data…..

    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.
    >>>>>>>>>>>>>>>>>>>>>>>

    The sample size is ONE. That is one of the fallacies in the CAGW global temperature data.

    Second, anyone with a cell phone knows the environment in which that phone sits generally has absolutely nothing to do with the actual temperature outside.
    Is sitting in an air conditioned house going to give you accurate information or is sitting in my black pickup truck in North Carolina without A/C, or in my pants pocket while I drive the tractor?

    The idea is a complete waste of money. I rather see a field with 100 precisely matched thermometers used to determine what the REAL error is. Only in a situation like that does ‘the sample size effect on randomly-distributed data’ work.

  38. davidmhoffer: Last point as I think we will disagree and as I set the conversation you are welcome to finish it.
    If the old shepherd who has worked the field for 50 years says “that sky means a cold night” and he says he knows because his father told him who learnt from his father who worked the same hillside and so on…

    Would you go “pah, superstition”?

    Well, this will give you that experience in lot shorter time. A thousand different shepherds every second of every day for every field.

    This idea will have a chance of working.

  39. But if you drop your cell-phone off the side of a cruise ship, will it report Trenberth’s missing heat on it’s way down into the abyss?

  40. The collected data has to be cleaned up before it can be used. That is done according to a rule set. Ask yourself who makes the rules? Do you trust them? Do you have reason to trust them? So far nobody entrusted with making the rules is above scorn because there is too much grant money at stake for getting it wrong (wrong being out of line with the political agenda. Ask Bob Carter.)

  41. Sparks says:
    August 13, 2013 at 1:03 pm

    Why are posts being lost? this is about the 5th time in so many weeks. It says “sorry this comment cannot be posted”.
    >>>>>>>>>>>>>>>>
    Try hitting the refresh button (It worked for me)

  42. Wonderful example of Post Modern Science.
    The variables are uncontrolled, the possibilities for error enormous and mostly biassed toward indicating warmer environs, the data must be corrected by values often exceeding those measured and so forth.
    But thats all good as the conclusions are preordained, right.
    As data points increase, the conclusion most likely to arise, is that most cell phone users, prefer climate controlled environs.Live in cities and do not get out into a natural environment very often.
    Further and using the same methodology, if we protect the lazy and clueless we will have more of them each year.Or that parasites do not voluntarily leave a healthy host.
    When will the scientific method come back into fashion?

  43. M Courtney says: @ August 13, 2013 at 1:52 pm
    …. If the old shepherd who has worked the field for 50 years says “that sky means a cold night” and he says he knows because his father told him who learnt from his father who worked the same hillside and so on…

    Would you go “pah, superstition”?

    Well, this will give you that experience in lot shorter time. A thousand different shepherds every second of every day for every field.
    >>>>>>>>>>>>>>>>>>>>>>>>
    Let me ask you this question.

    How often is your cell phone sitting where it is not in close proximity to your body, shaded from the sun and in the open air outside (and not in a car)?

    I work outside doing children’s entertainment or farm work and my phone is either in a pocket (mostly soaked in sweat or under a coat) or in my purse locked in a hot black truck or in an A/C house.

  44. I skimmed throuhg the comments and did not see anyone mention this. I wonder if they mean “pressure” rather than “temperature”. I saw a piece on crowdsourcing pressure from smart phones. Then when violent weather, like thunderstroms or tornadoes occurs, there is a much finer network of pressure measurements, which could be extremely useful in analysing what is happening.

  45. What someone needs to do is take a recording thermometer and dump it into a pocket or a phone case and run the experiment to determine how far off these temperatures are compared to a home type weather station. (I don’t have access to the correct type of thermometer and don’t know where to get one.)

    Perhaps someone with the money and time can run the experiment.

  46. Here are a couple of the things that a phone app can’t handle, hence making this study unless.

    1) If the person is indoors or outdoors? Rather important to know this.
    2) How is the phone being held? Based on where the battery is in relationship to how the user holds the phone will influence body heat source.

    Of course if they limit the study to only take samples when the phone is taking pictures and breaking the data into 2 groups based on if a flash was used they might be able to get some data.

  47. From the article:
    “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.”
    ====================================================
    Sez who? How do they know which ones are the accurate representation of the weather?

    I suppose that if the GPS data sorts the phone data into those who are walking outdoors and the reading is warmer than usual due to most of the phones being in peoples’ pockets, they can conclude that it’s raining. But they could also look out the window.

    If it’s just weather you’re after, just tie into all the TV stations across the region of interest. Better yet, look at live radar.

    This is a Rube Goldberg device looking for something to do.

  48. Be a fairly good way to tell how people are using their phones: how long they sit in air-conditioned rooms, how much time the phone spends in a pocket, how often they make calls, whether they’re keeping their house at a nearly-unheard-of 72° in Winter… all with a “weather” application. Neat.

  49. “A group of smartphone app developers ***

    said James Robinson, co-founder of London-based app developer OpenSignal that discovered the method ["METHOD", LOL!] . ‘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.’”

    To echo for emphasis what has been said by other WUWT commenters above, THIS IS ALL AND ONLY ABOUT SELLING A PRODUCT (and, for socialists, about more potential government control via monitoring).

    The “research” is not only applied research, but marketing-driven, end-result-driven, all the way. “How can we make some more money? Hm…. I KNOW! Let’s tell people they are saving the planet by buying our app!! haw, ha, ha, ha, haaaa……….. is that the bank up ahead? Turn left.”

    One would HOPE someone bright enough to find his or her way to work in London would think to look out the window… .

  50. I believe it is only judged to be valuable if the phone (phony) temperature is higher than normally measured.

  51. Codetech: “Wouldn’t it make more sense to build a network to monitor the outdoor thermometers built into most cars?”

    Good idea. I know the German weather bureau already do something similar with Lufthansa.

  52. I sure hope Anthony doesn’t need to run around taking pictures of people’s cell phones to put the “debunk” on this. 8-)

  53. Given the location of most people’s cellphones, you could very well call this a “junk study”.

    [rimshot]

  54. M Courtney;
    Would you go “pah, superstition”?
    >>>>>>>>>>>>>>>.

    No, because there may be a relationship that can be investigated and understood. But this idea is worse than superstition. It is taking data with inherent problems in it that are insurmountable and pretending that they aren’t.

    I’ll give your dad the last word. Ask him. Seriously.

  55. “Be sure to drink your Ovaltine… .”

    WARNING: Matt Courtney do not watch this:

    “The fate of the planet hung in the balance… .”

    “Remember! [Gaiea] is depending on you!”

  56. REPLACE above bad video link WITH (apologies!):

    WARNING: Matt Courtney do not watch this

    “The fate of the planet hung in the balance… .”

    “Remember [Gaiea] is depending on you!”

  57. We should start reporting a daily graph showing the max temp of the phones left inside the cars outdoors in the summer. Help pet owners and parents understand how hot the car gets, even with windows cracked.

  58. Please forgive me. Wow. “This video does not exist” — TWICE. Well, it DOES exist (I was listening to it play on explorer while I posted the above comment. Sigh.

    It’s the Christmas Story scene about the secret decoder ring where Ralphie is disillusioned. Just type “Christmas Story movie secret decoder ring” in the You Tube search box and it will come right up. I’m so sorry about those TWO bad links. I have NO IDEA what happened.

  59. I’d bet this has less to do with science as it has to do with Waze.
    Or more specifically, Waze getting bought for $1 billion dollars.
    Waze = crowdsourced traffic – despite all kinds of alternate traffic data available (Google was paying Inrix for traffic data, presumably not anymore).
    The above = crowdsourced weather data.

  60. It won’t be long before they start walking down the temperatures from our 1930s cell phone records.

  61. TerryT says:
    August 13, 2013 at 5:30 pm
    Could come in handy when dating, you could tell if your date is getting hot and heavy.
    >>>>>>>>>>>.

    Omigod. Worse than pet rocks. They’ve reinvented the mood ring.

  62. So for teenagers the temperature of the phone would be about right as it is always attached to the side of their heads, but for folks like me it would say the climate was a continuous 98±1F, because it is usually in my front pocket, except for right now when it is completely lost.

  63. The most ‘accurate’ way to get a temperature reading of a cellphone carrier’s environment would be to use the technology in temporal thermometers. When a call comes in, that technology kicks in and sends a time-sensitive signature of the surrounding temperature as the cellphone leaves its holding environment; is touched by a hand; that then passes the phone through the air; and up to an ear. By looking at and cataloging the values and shapes of many such ‘typical’ ways users handle their cellphones, and rejecting the outliers, it just might be possible to crowd source a temperature trend over the next century. Quick, get a grant!

  64. Michael J. Dunn says:
    August 13, 2013 at 12:30 pm

    *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.

    There is no way at all that you can measure the air temperature from a bunch of phones, however many you use. They are in pockets etc, spend most of their time indoors or in cars anyway, and will probably be kept warmer when it is either cold or wet. How can that possibly measure outside air temperature, even relatively?

  65. “In London you can go from bright and sunny to cloudy in just a matter of minutes.”

    Yeah, and vice versa.

    M. Courtney thinks measurements are representations of reality. Okay. But my pocket is a different reality than the city around me. No amount of data about the one reality will tell you anything about the other. Most cell phones are in someone’s purse or pocket, covered by 1 to 8 layers of fabric and located in a car or building. This “idea” is utterly worthless. Garbage x 1,000,000 = garbage.

  66. CodeTech says: “Wouldn’t it make more sense to build a network to monitor the outdoor thermometers built into most cars?”

    The NSA will nix this idea and will refuse to say why.

  67. “It isn’t necessarily daft.”
    Totally daft. Most folks spend very little time of the day actually outside. Most are at work 8 hours a day and asleep 8 hours a day. If it is cold outside most seek indoors for warmth. If it is hot outside, well look for the A/C. Don’t buy it for a minute.

  68. From tmonroe on August 13, 2013 at 1:40 pm:

    This will show warming.

    http://electronics.howstuffworks.com/everyday-tech/lithium-ion-battery2.htm

    Lithium Ion batteries (common in cell phones). Will fail more frequently as the batteries age.

    I love lithium ion batteries. Sure, I’m changing the set in the TV remote every two weeks, but I’m not buying or throwing out any.

    You can get a wall charger with 4 batteries for about the battery cost. Last Rayovac set was a plain black charger (#PS132), AA’s and AAA’s charge in pairs, I left them in. I noticed the batteries got rather warm, while a different charger with auto shutoff stayed cool.

    After attacking with the “tamperproof screw” driver set, I found a small transformer and two circuits from the secondary. Each was a single diode (not full wave), then the batteries in series, and an LED with a ballast resistor that would stay on whenever the batteries are in.

    No microchips, no sophisticated charging controls. Oh, and the manual says the LED’s go on to show charging, and stay on to show the batteries are charged.

    Made in China.

    It’s nice that lithium-ion batteries are, by design, now being used as heating elements when not being energy reservoirs. It clearly shows overheating Li-ion batteries are not the problem they used to be.

  69. davidmhoffer and M Courtney:

    I did not intend to comment in this thread but have been called as arbiter in your discussion.
    The scientific value of the app is clearly stated in this thread by Joseph who says at August 13, 2013 at 2:14 pm

    http://wattsupwiththat.com/2013/08/13/how-is-the-temperature-of-your-pocket-useful-for-meteorology/#comment-1388868

    Here are a couple of the things that a phone app can’t handle, hence making this study unless.

    1) If the person is indoors or outdoors? Rather important to know this.
    2) How is the phone being held? Based on where the battery is in relationship to how the user holds the phone will influence body heat source.

    Of course if they limit the study to only take samples when the phone is taking pictures and breaking the data into 2 groups based on if a flash was used they might be able to get some data.

    However, if the purpose of the app is to make money for its vendors then it may fulfill its purpose (i.e. be a financial success) because a claim that the app provides climate data suggests it can be sold to the gullible who support AGW.

    Richard

  70. Actually, the way I chose to interpret this paper was that it is a first step in the preparation and analysis of crowd-sourced environmental data. One of the key issues with the study of urban microclimate is a terribly low density of measurement. For example, a city might have one or two meteorological stations and then now and again a few short-term field campaigns but this isn’t enough to tell you about the temperature variation inside the city and inform sub-grid scale modelling. i.e. I don’t feel this is intended to tackle the issue of GLOBAL warming, it’s just a method to potentially capture the range of temperature in an urban environment. This study is a primitive first step exploring the possibility of using smart-device technology to sample, providing a network of interconnected “samplers” that are integrated already into an urban environment. In the future, perhaps phones could measure a suite of things, temperature, heat flux, pollution… Sometimes it pays not to take a piece of research as a literal finished article and consider the possible developments that could be wrought from it.

  71. I can’t see how any useful data could be obtained. As the measurements are of the battery temperature this would have a difference with actual ambiant temperature by some unknown variable x. x would be made up of systemic errors (non-calibration and distance from known calibrated temperature guage) and random; placement, battery age, proximity to other temperature differentials. Therefore error x = p*ba*pr*dt*(systemic error) No matter how many x’s you have as each is an independent variable (time and place are unique events) you will not be able to eliminate the errors or determine any trend from noise (as it will all be noise)

  72. “In London you can go from bright and sunny to cloudy in just a matter of minutes.”

    or

    “In London you can go from bright and sunny to indoors in a matter of seconds.”

    or

    “In London you can go from bright and sunny but very cold to a heated building in a matter of seconds.”

    or

    “In London you can go from bright and sunny and hot to an air-conditioned building in a matter of seconds.”

    etc…

  73. Paraphrasing Mae West — “Is that your smartphone batteries’ anomaly increasing or are you happy to see me?”

  74. Now all we need to do is give everyone in Sub-Saharan Africa a mobile phone and we’ve got an even better spread of data.

    Do mud huts have a plug point for charging your phone?…..

  75. If the phone is down inside my pants the temperature will always be smokin’ !

    Although my wife might disagree…

  76. Further to my car thermometer idea, any car with GPS and an external thermometer could be a mobile temperature station. All someone needs to do is drop a $30 Made-in-China RF module on the CanBus somewhere and, a few minutes after starting (to give you time to get out of a parkade or garage and allow for heat-soak dissipation) it would be sending a temperature reading and location at set intervals. These things are usually quite accurate and placed where they’re not very much affected by the radiator or A/C condensor.

    But, of course, that assumes that “Climate Scientists” actually want to know the real temperature. I’ve seen very little to make me think they do.

    The cell-phone idea is pure marketing hype to sell an app.

  77. This is useless for temperature trends.

    However, I predict this will be a tree-ring-quality proxy for:
    -teenager cellphone usage trends;
    -battery charging frequency;
    -latitude of where the cellphone is used;
    -

  78. Thousands temperature measurements all over major cities, though unprecise, might be very useful for studying UHI.

  79. Michael J. Dunn says August 13, 2013 at 12:30 pm

    *sigh* All the scoffers clearly don’t understand what is going on. It is the sample size effect on randomly-distributed data.

    UNTIL some big ‘event’ happens and every-one like-utilizes their iPhone/Smartphone on that occasion and/or for the week following, or new model changes/new model introductions introduce a skew (shift) in data requiring ‘adjustments’ to be made … point being not-so-random factors will be present over longer periods of time encompassing several model-lifetimes … then there is the aspect of where the temp sensor IC placed within the device as battery position in device design caries from model to model, and even composition changes in battery technology yielding different temp profiles during charge/discharge and device-use.

    .

  80. “Even the authors claim they can only get within 2.7 degrees Fahrenheit, so what is the point of having this inaccurate data?”

    Anthony, after years of writing this blog and dealing with the warmers, I’m surprised you still think they actually care about accuracy.

  81. Gail Combs says:
    August 13, 2013 at 1:56 pm
    RE: “sorry this comment cannot be posted”.
    Try hitting the refresh button (It worked for me)

    Thanks for the suggestion Gail, I originally thought it was a browser problem a date/time issue, but after looking into the problem I think it’s due to family visiting for the summer, which means nephews and nieces with their wireless Xboxes, Ipads/ipods, smart-phones and laptops fighting over the signal and my router is disconnecting idle connections such as mine.

    I basically wrote a comment explaining that I tried this with a program I wrote (about 10 years ago) that monitored the temperature of processor cores and logged the data which I could access remotely, it is possible to work out a fairly accurate environment temperature as long as it is calibrated with an actual temperature of the environment the computer was in, it looks like they have taken a decades old impractical idea and ran with it on a large scale.

  82. I looked at every comment, and of course the image that will stay in my head all day is the phrase, “except when stuffed into a thong at the beach.” Gak!

  83. 1) Glad that everyone understood the error-reduction effect inherent in multiple data readings. This is done all the time in industry.
    2) Sorry that one poor soul didn’t pick up the point of the whole idea, which is to have vastly more than “one” reading for a given geographic region (like millions in a large city).
    3) Sorry that other poor souls didn’t take the time to read the fact that the experimenters are proceeding with this because they discovered a good statistical correlation between the temperatures they obtain with this telemetry and the official temperatures. So, it’s not a matter of theory, it’s a matter of empirical evidence.
    4) All the carping about sensor placement and circumstances fails to consider the most general likelihood that all these effects will largely cancel out (random variances). Anthony’s most perfect contribution to this debate (in my opinion) is his “outing” of the imperfection of the very temperature data that everyone asserts is God’s Truth. Get over it. Either this approach will be useful, or it will not. Sometimes a grade-school ruler is as handy as, or handier than, a millimeter scale. Particularly if it gives you the ability to perform in-depth regional contouring and time-variance studies. (Hint: this is not model-based science. It is MEASUREMENT.)

  84. Had a chance to scan more of the dialogue. Apparently, there are those out there who do not understand how error is reduced by sample size. Sorry, the fact that they do not understand means only that they don’t understand a point that comes up early in any class on industrial statistical control. There is a very humorous exercise that is sometimes done to illustrate this point. An arbitrary length is drawn on the blackboard and each member of the class is asked to estimate what it is. All the estimates are taken together, the mean is taken, and—mirable dictu—it is surprsingly close to the actual length of the line (like within a few percentage points), far more accurate than any individual guess.

    As for the regional effects of Big Events, like floods, earthquakes, tornadoes, intense hailstorms…I guess conventional thermometers would be impervious to these, right?

    Alas, what mostly seems to shine through is (1) ignorance of the methodology, and (2) prejudice about its utility based on the assumed ideological mendacity of the experimenters. Pretty disgusting, folks.

  85. MJ Dunn, did I actually just see you defend this idea, and even do some name calling toward the detractors?

    So explain to me how crowd-sourcing the average temperature of where our cell phones are, which is primarily in climate controlled conditions or our pockets, can possibly be useful. Because even though I’ve tried, I can’t even imagine how that could be a useful metric.

    Maybe it’s because I live in a winter climate, where it can reach -40 during winter and +40C in summer, but the advantage of measuring indoor spaces is lost on me.

  86. Michael J. Dunn says:
    August 14, 2013 at 12:36 pm

    Had a chance to scan more of the dialogue. Apparently, there are those out there who do not understand how error is reduced by sample size. Sorry, the fact that they do not understand means only that they don’t understand a point that comes up early in any class on industrial statistical control. There is a very humorous exercise that is sometimes done to illustrate this point. An arbitrary length is drawn on the blackboard and each member of the class is asked to estimate what it is. All the estimates are taken together, the mean is taken, and—mirable dictu—it is surprsingly close to the actual length of the line (like within a few percentage points), far more accurate than any individual guess.

    Your comment makes no sense: To use YOUR example: If my task was to measure the size of the parking lot outside the building, what does estimating the size of a line on the blackboard by having a class make guesses mean?

    Now, if you said everybody WALKED OUTSIDE and took measurements independently of the same parking lot, and THEN estimated the length and width of the parking lot, you’d have a point. Not a very good point, but at least you’d have a point. But, what good does measuring the temperature of a person’s pocket indoors in a city have to do with the average AIR temperature in the country around that city?

  87. kadaka (KD Knoebel) says:

    August 13, 2013 at 11:35 pm …

    I’ve used several generations of phones with lithium ion batteries. As the phones age, battery life shortens. While charging, phones are warmer than when not charging. I mean seriously, stop me when I am wrong here… If battery life goes down, and charging time goes up, then this will induce a bias in the phone’s temperature reading. And we’re not talking just a few degrees. Every cellphone I’ve ever owned was significantly warmer while it was charging. More time charging = more warmth as the phones get older. It’s really all battery technology though… not just lithium…

    The batteries emit heat when either when they charge or discharge. And it can be a lot of heat. I seriously don’t think it is possible to correct for this type of bias.

    How about this:

    Take a brand new phone. How long does the average phone not get some software installed by the end user? Well, according to this website:

    http://www.slashgear.com/angry-birds-reaches-one-billion-downloads-09227363/

    One billion copies of Angry birds were downloaded between December 2009 and May 2012. Running angry birds increases power usage on your phone. I would posit that running Angry Birds on your phone will both cause the phone’s temperature to be higher after its installed, and also cause it to need to be charged more frequently. Since your phone probably doesn’t come with Angry birds, the day you buy the phone, its going to be cooler than the day after you install Angry Birds.

    Who cares about Angry birds?!? Well, of course, I really dont – but there is almost no way to know how much any given application that is added to a phone will bias its reading towards heating. There are at least 10′s of thousands of applications available for smartphones. Who could possibly ever tell how much each app was influencing power usage on a given phone. You don’t think that running an app on a phone has no impact, do you?!? If nothing else, just the user holding onto the phone (vs. having it whereever a user normally stores a phone) will significantly affect the temperature.

    In my experience, the radios in the phones also consume more power when they have weaker signal. I suppose as cell phone companies add towers, this would induce an apparent cooling trend… assuming of course that cell phones don’t play the cellphone version of the “cocktail conversation” game where in a crowded room, the output level increases to try to overtalk nearby cellphones…

    It’s ironic. Anthony’s site was started to document issues with weather station siting (sites that show warming from other sources due to location issues). Only a complete brain-dead idiot (or a complete charlatan) would even remotely think that putting temperature sensors in people’s pockets would produce anythng but complete and total nonsense. Yes, lets get more and more sites with extremely bad siting… that will fix the problem. Clearly no effort should be put forth on this fool’s errand until problems with the “real sites” have been addressed.

  88. I’ve had small poorly-written applications on my cell phone that caused the processor to run at unexpected times. This resulted in a warm-to-the-touch cell phone and short battery life.

    Let me guess what this study will demonstrate.

  89. “Apparently, there are those out there who do not understand how error is reduced by sample size.” [Dunn the App Salesman]

    Apparently, there is a Mr. Dunn here who does not understand that:

    Garbage x 1,000,000 = garbage.” [Jorge Kafkazar 8/13 9:20PM]

  90. It would seem to me that the law of large numbers needed to distinguish between transient effects (the outdoor game-player vs the indoor idler) will completely defeat the stated goal of greater resolution.

    I am also skeptical that they can ever compensate for human factors such as the fact that we generally come indoors when it’s raining, put on coats when it’s cold (usually covering the phone), spend less time outdoors when it’s really cold – or really hot, set the thermostat lower at night and so on. Too many situations leading to too many different types of systemic bias.

  91. I suppose averaging the readings between [device in arse-pocket in sweaty elevator] against [device in pannier of bike next to pre-frozen bottle of water] might approximate to [ghastly 'climate' ( aka ongoing efforts of planet to destroy all life, via "weather" in Scotland, where I live)]. I so looked forward to “global warming”. Seems it’s not to be.

  92. Mr. Dunn wrote;

    “Had a chance to scan more of the dialogue. Apparently, there are those out there who do not understand how error is reduced by sample size.”

    With all due respect, error is NOT reduced by sample size. NOISE is reduced by sample size. When multiple samples from a single sensor are averaged together the noise in the averaged sample is less (subject to numerous caveats like the probability distribution shape and stationary). The accuracy (difference between the readings and reality) is not increased.

    If I take a temperature sample (measurement) with a thermometer that is wrong by 1 degree, or I take a bazillion readings and average them together the result is still wrong by 1 degree.

    Your “line on a blackboard” is not an example of increasing accuracy with multiple samples, Rather, it is an example of many multiple estimates being distributed in a gaussian distribution function with the mean approaching the “consensus” length. Assuming the observers are “pretty good” at estimating the length the answer will converge to something close to reality. If the observers are all near sighted the answer will be wrong.

    In control systems the use of averaging to reduce noise is well known to reduce the “update frequency” or bandwidth. For example, if I’m extruding pasta and want the length to be 250 mm +/- 1mm I could

    1) make an accurate measuring device to tell me when to cut the pasta to length

    or

    2) make an inaccurate measuring device and average a million readings and then cut the pasta to length

    Option 1 will give me lots of pasta that is within my specifications
    Option 2 will give me a little bit of pasta that is all exactly the same wrong size

    I suggest that before you throw the “ignorance flag” and express your “disgust”, you might want to crack a textbook or two about measurement accuracy and signal-to-noise ratio. These are two totally different concepts.

    You are totally welcome for the free education.

    Cheers, Kevin

  93. CodeTech
    It’s not merely an idea, it’s a technique; they have actually tried it out. If calling someone a “poor soul” is “namecalling,” then you are welcome to it, but in my view of life, the truly ignorant are indeed poor souls.
    As for how it can be useful? I quote: “…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…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.” It helps to read before scoffing.
    As for indoor-outdoor readings, one of their problems will be to establish a seasonal calibration. Note that calibration is one of their early concerns. It may prove to be a limitation on the utility of the technique.

    RAookPE1978
    If I wanted to measure the size of the parking lot with this technique, I would indeed take the class outside and ask for guesses as to the length of its sides. I’m talking about lines on the blackboard, you want to talk about parking lots. Is that all this comes to?
    As to the correlation with air temperature, refer back to the quotation above. It all has to do with calibration against STANDARDIZED MEASUREMENTS.

    Janice Moore
    Talk to Mr. K (below), or read a text on statistical methods.

    KevinK
    Thank you that someone else out there knows what I am talking about. We need to correlate our terminology in order to avoid talking past each other. I am used to the error of a distribution function being separated into the bias error (the mean or systematic error, or accuracy) and the random error (standard deviation, or precision). All my comments have pertained to the random error, if anyone will go back and see I stipulated that large ensembles will do nothing to reduce systematic or bias error. I think we are on the same page.
    And what if there is a 1-degree bias error? From a data collection standpoint, I say “So what?” Are you trying to tell me that anything we can deduce from temperature data is so infamously sensitive that a 1-degree accuracy error will upset the applecart? That’s exactly the conceit that the Warmists invoke with all their incredible projections of climate sensitivity. In the course of a year, when temperatures swing through maybe 50-60 Fahrenheit degrees, a few degrees error is going to make a difference? The implication of having a chaotic feedback system is that we can’t predict when things will change anyway, and until they change, they will stay pretty much the same. Therefore, the error is probably insignificant. Meanwhile, this is a wonderful asset to perform spatial and temporal studies.
    The blackboard example is a commonplace, and it is used not only to show the effect of ensembles on random error reduction, but also to show that the mean error is surprisingly small (we are not so feeble a measuring instrument as we are claimed to be).
    The pasta example does not prove your point, which only means your point is wrong or misunderstood. If I made a moderately accurate sensor (no one bothers to make an inaccurate sensor), probably the size of a pinhead, and put a thousand of them in a row, and sampled them a thousand times a second for each measurement, I would probably obtain “lots of pasta that is within my specifications.” It is only statistical process control. If there is a bias error, I can find that out with the first cut and fill in a calibration correction for every succeeding cut—just as I would have to do with the “more accurate” sensor. The bias is the part that does not move around with time. If it did, it would merely be part of the random error.
    Since I do this for a living (sensor architecture error fusion), I don’t understand how I have learned anything I didn’t already know correctly.

    The Lesson
    As wonderful as this site is, you, the denizens, are not always very educated in the science you purport to defend. Read more. Opine less. Learn.
    And as much as it is very clear that the Warmists are mendacious to a fault, do not fill in your own ignorance with prejudice. There is no point to it, and you just cheapen yourselves as human beings. Not to mention sully Anthony’s reputation. Is this how you reward him, by behaving like rabble? You can do better. Of course, many if not most are gentlemen and ladies, but why not all?

    Peace be with you and a warm hearth in the coming ice age!

  94. MJ Dunn:

    I wrote before:

    So explain to me how crowd-sourcing the average temperature of where our cell phones are, which is primarily in climate controlled conditions or our pockets, can possibly be useful. Because even though I’ve tried, I can’t even imagine how that could be a useful metric.

    Although you danced around it, you have failed to make a case.

    We’ve seen quite enough of “calibrations” over the last few decades. Heck, they “calibrated” the 1930s right out of the record.

    There is no possible way to make this metric useful in any way. None. Apparently you think otherwise, but that just makes you wrong. You’ll still be measuring the climate-controlled areas, not outside. Measuring indoors and in pockets and in cars is hardly useful no matter what “calibration” technique is used. As an “index”, it might have some value. As a measurement, it has exactly zero value.

    It helps to have a clue before attempting to educate people who know more than you do.

  95. I share scepticism about this – apart from anything else, most smartphones will be inside buildings, let alone pockets, during most of the day.

    However, as a general point, the resolution of weather forecast models is continually increasing, and meteorologists are struggling to find sufficiently well-resolved observational data to initialise them with. If your surface weather stations are hundreds of kilometres apart that isn’t much help when your weather model has a grid spacing of 300m.

    There has been some good work on using GPS satellite signals to retrieve atmospheric data, and I believe there is ongoing work on extracting humidity data from mobile phone base station data.

    It might be that if you can collect enough data from enough smartphones that you can extract a useful signal from it.

  96. I want to clarify one thing before this topic drops out the bottom:

    MJ Dunn is arguing a different thing than everyone else is. Yes, having lots of measurements can increase the accuracy. The whole topic, and even its title, isn’t about the benefits of lots of sensors. The point is that what these sensors are measuring is not a useful thing to measure.

    It’s equivalent to building a climate monitoring network and putting the sensors inside climate controlled housings to ensure their safety and longevity…

  97. CodeTech
    I quote again: “…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.” It’s not modeling, it is measurement by a new technique, and they came close to the measurements of accepted sensors. The proof of the pudding is in the eating. They told Robert Goddard that rockets wouldn’t work in vacuum, either. I guess you don’t like thermometers that are accurate to only a few degrees. Can you explain to anyone why more accuracy is essential to the purpose pursued by these experimenters, and why anything less must be disdained, scorned, and cursed? Your laboratory must be an exciting place to work! Take it easy, relax, and see how it turns out. If it turns out well, you have an interesting crow to swallow. If it doesn’t, that’s only what I am waiting to find out.

  98. Michael J. Dunn says:

    August 15, 2013 at 4:29 pm

    After calibration, the team calculated air temperatures within an average of 1.5 degrees Celsius (2.7 degrees Fahrenheit) of the actual value.”

    And how many measurements did they have to make to get the actual value?

    The problem here is that although these measurements may not be intended to demonstrate man’s influence on the climate, they will in fact be used to demonstrate man’s influence on the climate (at some point) – just like all the previous measurements have been used to do – including cases where previous measurements have been adjusted to amplify recent warming.

    I have been arguing that with my experience with cell phones, I would expect a warming *trend* to come out of these measurements. Of course, the trend could be filtered out (there could be software on the phones to report back just how long the battery lasts between charges, and to somehow comphensate). At some point though, besides being tremendously invasive (the data about where you at all times would be in a database somewhere). I honestly wouldn’t trust a warmista to accurately filter out any data that didn’t support their idealogical pet.

    Finding a way to be accurate to within 5.5 degrees doens’t mean they are filtering out spurious trends, and for most of the uses of this data, I would think trend would be the most important information, wouldn’t you?

  99. I have found that it is impossible to get within two degrees even using the same brand and type of weather station. Nest door moving a pot plant caused a greater change than the claimed accuracy of the weather data used to promote climate change. I note that the manufacturer of a paint which allowed the wood to breath like the old fashioned paints used in the screens made nearly a degree temperature difference if the previous day had been raining.

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