This is a great visualization of free data, although not the first in this style, but it's usefulness in actual forecasting or nowcasting is rather limited.
Interpolation between sparse grid points can result in missing fine details, like the subtle boundaries that kick off the most violent storms in the central Plains.
Limiting to just GFS and GEM make sense from a proof of concept level, however these are long range models that play in the 10-16 day range. GFS in particular uses a 13km spaced grid that isn't convection allowing, meaning it can't model individual storms well. GFS is typically only output every 6 hours as well so it can easily get out of sync on forecasts for the day of.
It would be great to see these types of visualizations incorporate something fast and higher resolution like the HRRR or even one of the NAM/WRF 4km variants, but that is a lot more data than what is currently being ingested.
The best weather information (for US citizens) hands down is still your local NWS office. I'd recommend everyone bookmarking their site and following them on social media.
In my region (Portugal) their predictions regarding rain on 2-3 days are correct enough to make people come and ask me.. and the temperatures are optimized towards 'mildy'. E.g: You see 30C, count with 32-33C; 5C expect 3C. Note that only their GFS 27km model is updated and trustable on free mode.
> This is a great visualization of free data, although not the first in this style, but it's usefulness in actual forecasting or nowcasting is rather limited.
Indeed, it reminds me of this, which has been around for years:
Will GOES-16 improve the existing models? Or is the plan to create new models? I'm really curious to know how the higher resolution images will be used.
Very nice, although default of Fahrenheit, really? The date format is ISO rather than US by default. Maybe a master switch [US|Countries in the 21st Century] 8-)
Does it make sense to anyone that this kind of data should be layered on regular mapping applications (directions, traffic, shops)? Or is it too much?
I like the idea of visiting Google Maps, for example, and being able to toggle snippets of this kind of weather data onto the map itself. Other useful, one-click, toggles could include:
1. Real Estate Listings for a given area
2. Demographics
3. Forecasts & Historical weather info
4. Crime data
5. Local Events
6. Low-bandwidth settings
7. Access to publicly available real-time streaming cameras
While it is undeniably both beautiful and really cool, I've yet to see anything that beats a meteogram[1] when it comes to actually understanding at a glance what the weather is likely to do over the next couple of days.
Completely agree. The value of being able to compare individual parameters across models over time, especially with an NWS forecast overlaid is tremendous.
Cool! This reminds me a bit of weatherspark, which used to have a fantastic tool for visualizing long term trends. What were the 10th/50th/90th percentile temps for a given day over the last 30 years, etc. I wonder if the data sets here could be used to build something similar.
Everyone misses weatherspark. It's been a year since they went down and there's still no replacement for their historical weather viewer. I know they decided to stop because their flash based API for the radar map was depreciated but even just the historical and predicted line plots of weather data I'd pay money for.
Ventusky is no weatherspark replacement and I don't think the models they're drawing their data from would work for one.
Sure seems to be a lot of Fahrenhate here... Hey, look at it this way - the more granular Fahrenheit degrees (roughly half (5/9) a Celsius degree) are more useful for determining comfort - including setting a thermostat: I've had a couple of European cars that clearly used degrees Celsius for their setpoint (even if displaying degrees F, usually skipping by twos). Way too often, it simply wasn't possible to set the AC comfortably - it was either too warm or too cool. This matters in Texas...
I would guess it's a standard propagating structure.
For other readers: winds at 80km/h rotating with a diameter of ~2000km.
Pressure drops at 935hpa in the center
edit: at 10m above the ground. at higher altitudes, it's quite faster and with a different shape
For remote locations I find the NASA worldview pretty accurate for weather predictions. Just came back from the Seychelles, basically any weather forecast was completely off.
Just by looking at the NASA satellite images you could roughly predict the cloud movements for the next day and though next sunshine :)
Well, I for one find this pretty cool, especially the part where you can select the altitude. As a licensed remote pilot, this gives me a good idea of winds aloft at-a-glance without having to parse an entire full-briefing with all METARs, PIREPs, AIRMETs, and whatnot. My main question is the "altitude" in this AGL (above ground level) or MSL (mean sea level)?
Just so you know, wind in Spanish is "viento", and "ventusqui" is an informal way to call the wind. So yep, they've copied both the concept AND the name of windytv.
[+] [-] lllr_finger|9 years ago|reply
Interpolation between sparse grid points can result in missing fine details, like the subtle boundaries that kick off the most violent storms in the central Plains.
Limiting to just GFS and GEM make sense from a proof of concept level, however these are long range models that play in the 10-16 day range. GFS in particular uses a 13km spaced grid that isn't convection allowing, meaning it can't model individual storms well. GFS is typically only output every 6 hours as well so it can easily get out of sync on forecasts for the day of.
It would be great to see these types of visualizations incorporate something fast and higher resolution like the HRRR or even one of the NAM/WRF 4km variants, but that is a lot more data than what is currently being ingested.
The best weather information (for US citizens) hands down is still your local NWS office. I'd recommend everyone bookmarking their site and following them on social media.
[+] [-] tomslavkovsky|9 years ago|reply
Windytv created new version where you can see fine details for many different overlays.
[+] [-] galfarragem|9 years ago|reply
In my region (Portugal) their predictions regarding rain on 2-3 days are correct enough to make people come and ask me.. and the temperatures are optimized towards 'mildy'. E.g: You see 30C, count with 32-33C; 5C expect 3C. Note that only their GFS 27km model is updated and trustable on free mode.
[+] [-] morganvachon|9 years ago|reply
Indeed, it reminds me of this, which has been around for years:
https://earth.nullschool.net/#current/wind/surface/level/ort...
[+] [-] alexose|9 years ago|reply
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[+] [-] hrodriguez|9 years ago|reply
I like the idea of visiting Google Maps, for example, and being able to toggle snippets of this kind of weather data onto the map itself. Other useful, one-click, toggles could include:
1. Real Estate Listings for a given area
2. Demographics
3. Forecasts & Historical weather info
4. Crime data
5. Local Events
6. Low-bandwidth settings
7. Access to publicly available real-time streaming cameras
[+] [-] maxerickson|9 years ago|reply
http://www.nws.noaa.gov/gis/kmlpage.htm
[+] [-] knz|9 years ago|reply
Real estate would be a little easier via the MLS (I suspect the cost is prohibitive though) and demographic data is easily available.
[+] [-] jameshart|9 years ago|reply
[+] [-] dagw|9 years ago|reply
[1] https://en.m.wikipedia.org/wiki/Meteogram
[+] [-] lllr_finger|9 years ago|reply
If anyone is interested, IEM has a site that is rather easy to use once you find your local station ID and know how to plug it in: http://www.meteor.iastate.edu/~ckarsten/bufkit/image_loader....
[+] [-] anotheryou|9 years ago|reply
[+] [-] sccxy|9 years ago|reply
I'm fan of Windytv. They also offer free API: http://api.windyty.com/
So I made tracker for around the world sailing race (Vendee Globe): https://gis.ee/vg/
It makes so much easier to follow big weather patterns.
[+] [-] a-ve|9 years ago|reply
On a side note, you can see the Himalayas doing their job: https://www.ventusky.com/?p=32.15;78.51;6&l=pressure
[+] [-] CalRobert|9 years ago|reply
[+] [-] superkuh|9 years ago|reply
Ventusky is no weatherspark replacement and I don't think the models they're drawing their data from would work for one.
[+] [-] dublin|9 years ago|reply
[+] [-] xjay|9 years ago|reply
Warning: Sound is on by default. Disable by clicking Sound in the menu on the lower left.
[1] http://blitzortung.org/
[+] [-] datl25|9 years ago|reply
Is it even possible?
[+] [-] dest|9 years ago|reply
edit: at 10m above the ground. at higher altitudes, it's quite faster and with a different shape
[+] [-] brockwhittaker|9 years ago|reply
[+] [-] unknown|9 years ago|reply
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[+] [-] mrestko|9 years ago|reply
[+] [-] TallGuyShort|9 years ago|reply
[+] [-] philfrasty|9 years ago|reply
Just by looking at the NASA satellite images you could roughly predict the cloud movements for the next day and though next sunshine :)
EDIT: link https://worldview.earthdata.nasa.gov
[+] [-] opticalflow|9 years ago|reply
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[+] [-] maxerickson|9 years ago|reply
http://forecast.weather.gov/MapClick.php?lat=40.6936&lon=-89...
No geoip, but a lot of information, right from the source.
The NWS radar pages are also pretty good (and again straight from the source):
http://radar.weather.gov/radar.php?rid=ilx&product=N0R&overl...
There's 4 different display options for each radar, I usually use the simple loop one:
http://radar.weather.gov/ridge/radar_lite.php?rid=ILX&produc...
They also have regional overview pages:
http://radar.weather.gov/ridge/Conus/centgrtlakes_lite_loop....
Click to zoom to a local radar page.
[+] [-] omegote|9 years ago|reply
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[+] [-] madhorse|9 years ago|reply