From the top of the about page (http://pressurenet.io/about/) -- "Our mission is to dramatically improve weather and climate forecasting."
How does this have to do with climate? It seems like your time scale doesn't overlap with typical climate models. I guess it feels like a speculative claim (better pressure measurements -> fine-grained model improvements at small temporal scales -> better climate model outcomes).
Also, I wonder if you have a link to a paper or presentation that details how these measurements could fit in with the assimilation models that are used in weather forecasting? I see a link to Cliff Mass' blog (as a whole), but I'm more interested in a specific reference. In particular, I wonder if it's possible to quantify how much a perfectly-accurate ground-level pressure field could constrain upper atmosphere dynamics. Has there been a session at AGU (http://fallmeeting.agu.org/2014/), for example, examining how this could work? Or is it too new for this yet?
Excellent questions. Regarding climate: there are many indications that measurements of atmospheric pressure are useful in forecasting longer-range trends. For example, the pressure over the Tibetan plateau can have a large affect on El Niño. Additionally, we've collected atmosphere data over a period of years, and we expect to find interesting climactic trends as well as shorter-term weather trends.
> I wonder if it's possible to quantify how much a perfectly-accurate ground-level pressure field could constrain upper atmosphere dynamics
Yes it is possible and we're working on this currently. There are some neat math techniques that we can use to estimate what kind of forecast accuracy increase we'll get with a dense network - but the only way to actually know is to scale up and start running experiments to find all the thresholds for improvements and diminishing returns.
I've gotten into the habit of not installing applications that ask for access to my Google accounts. I'm also curious as to why this application needs to prevent my phone from sleeping ... wouldn't waking up every 15 minutes and taking a sample be enough?
We don't ask for permission for your accounts at all actually - we just ask permission to use Google Maps, which Google unfortunately lumps together. The app is open source on GitHub so you can verify that we don't do anything weird. For example, here's our AndroidManifest.xml file that shows the permissions we list in code: https://github.com/Cbsoftware/pressureNET/blob/master/Androi...
READ_GSERVICES is the permission in question and is required for Google Maps. I'd like to switch to an open mapping tool but it's not a top priority right now.
As for the sleeping mechanism: you're correct, an in fact we do only wake the phone up every x minutes. It's off ~99% percent of the time. We require the wakelock to ensure that the phone stays on long enough for us to measure the barometer and store/transmit the data. We don't keep the device on for any longer than absolutely required.
Love the idea; naive, noobie question: since your sensor density presumably depends very much on population density, how does this affect your model? I was under the impression that regularly-spaced measurements were important but presumably not so much? Or is this still better (or will be eventually) than the national network?
Population density is indeed a problem for us. Some of the most severe weather like tornados and supercell thunderstorms (and hurricanes for that matter) don't happen in high smartphone density areas. What we're finding is that in cities we are already reaching the density required for useful weather forecasts, so we're fine for now in terms of density....for now.
However, as we grow and expand it will eventually become important to start building drones and buoys to help us collect this high-res data without smartphones. The end vision is a high-density network of sensors all over the globe to continuously feed live data to models. We'll solve this however we have to, and I think the solution is eventually a roaming drone network. We'll see.
Here's a recent paper being published by Cliff Mass and his students and colleagues: http://journals.ametsoc.org/doi/pdf/10.1175/MWR-D-13-00269.1 That's a good comment though: we should have more details and visualizations of the active research. Thanks for the heads up.
Inside vs outside isn't really a problem actually, the pressure is effectively the same. The bigger issue is altitude changes, which even small amounts can cause noise...but there are ways to filter that out.
Game Oven Studios posted this Vine yesterday about why it's so hard to develop on the fragmented Android platform: https://vine.co/v/MgWLMmmwUQQ Do you guys not run into this same problem with pressure sensors?
The Vine you link to isn't necessarily a problem with Android itself. Sure, Android runs on several different devices from lots of different vendors that all use different hardware (which is a good thing), but the compass sensor shown here is notoriously finicky. Simply having the devices near other metal (like other phones) will cause completely erroneous data.
[+] [-] mturmon|12 years ago|reply
How does this have to do with climate? It seems like your time scale doesn't overlap with typical climate models. I guess it feels like a speculative claim (better pressure measurements -> fine-grained model improvements at small temporal scales -> better climate model outcomes).
Also, I wonder if you have a link to a paper or presentation that details how these measurements could fit in with the assimilation models that are used in weather forecasting? I see a link to Cliff Mass' blog (as a whole), but I'm more interested in a specific reference. In particular, I wonder if it's possible to quantify how much a perfectly-accurate ground-level pressure field could constrain upper atmosphere dynamics. Has there been a session at AGU (http://fallmeeting.agu.org/2014/), for example, examining how this could work? Or is it too new for this yet?
[+] [-] cryptoz|12 years ago|reply
Here's a paper by Cliff and Luke regarding dense surface-level pressure observations: http://journals.ametsoc.org/doi/abs/10.1175/MWR-D-13-00269.1...
> I wonder if it's possible to quantify how much a perfectly-accurate ground-level pressure field could constrain upper atmosphere dynamics
Yes it is possible and we're working on this currently. There are some neat math techniques that we can use to estimate what kind of forecast accuracy increase we'll get with a dense network - but the only way to actually know is to scale up and start running experiments to find all the thresholds for improvements and diminishing returns.
[+] [-] smoyer|12 years ago|reply
[+] [-] cryptoz|12 years ago|reply
READ_GSERVICES is the permission in question and is required for Google Maps. I'd like to switch to an open mapping tool but it's not a top priority right now.
As for the sleeping mechanism: you're correct, an in fact we do only wake the phone up every x minutes. It's off ~99% percent of the time. We require the wakelock to ensure that the phone stays on long enough for us to measure the barometer and store/transmit the data. We don't keep the device on for any longer than absolutely required.
[+] [-] danparsonson|12 years ago|reply
[+] [-] cryptoz|12 years ago|reply
However, as we grow and expand it will eventually become important to start building drones and buoys to help us collect this high-res data without smartphones. The end vision is a high-density network of sensors all over the globe to continuously feed live data to models. We'll solve this however we have to, and I think the solution is eventually a roaming drone network. We'll see.
[+] [-] cmpb|12 years ago|reply
[+] [-] beardicus|12 years ago|reply
Do you have any examples/links to research being done with the data currently? I poked through the blog quickly and didn't see anything in depth.
[+] [-] cryptoz|12 years ago|reply
[+] [-] eutropia|12 years ago|reply
[+] [-] cryptoz|12 years ago|reply
[+] [-] unknown|12 years ago|reply
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[+] [-] torstesu|12 years ago|reply
[1] http://www.netatmo.com/en-US/product/community/station#view2
[+] [-] dandelany|12 years ago|reply
[+] [-] yellowbkpk|12 years ago|reply
[+] [-] cryptoz|12 years ago|reply
[+] [-] LamaOfRuin|12 years ago|reply
[+] [-] lazyant|12 years ago|reply
[+] [-] cryptoz|12 years ago|reply