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-)
Call me weird, but I hate when a program or service uses regions or locales to determine stuff like temperatures or languages.
First of all, it often does it wrong - especially when using geographical location, which is one of the dumbest idea I've seen in computing. GPS fails when people are traveling (just because I'm in Germany right now, doesn't mean I want to see websites in German, etc.). GeoIP fails for various reasons, including VPNs and weird ISP shenanigans.
Second of all, as a person fluent in English, I especially don't want to see a translation of your originally English site. Most software and website translations suck hard. My most common gripe: using the same word in translated language for things named by different words in original, or vice versa.
ECMWF has been producing the best global forecasts in the world for many years. This will end in few years, but at the moment IFS, the model used at ECMWF, is the best in the world.
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 :)
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.
The android app Yr, from the Norwegian met centre will give you an up to date basic meteogram for most of the world. They (yr.no) also have an API if you want to download just the image for your own uses.
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.
just returned from the canaries where windytv proficiently helped me to pick my bikeroutes, adapted to the prevailing wind conditions.
these winds change fast and seem unpredictable and although the connection between general weather and wind is somehow limited it seems clear to me that it must be hard to make any accurate predictions.
I used to be married to a military forecaster. It was always interesting to hear about how this stuff works, and it seems to me that "models not fitting reality" comprised at least 50% of their office drama. Forecasters have their own preference for models and "past experience" which leads them to very different conclusions. And climate change is making these models much less effective over time, adding even more excitement.
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.
Current models ingest new data from a variety of sources, including surface observations, buoys, airplanes, and GOES-derived data. The derived data might be more accurate and might be used more extensively going forward - I'm not entirely sure.
IMO (as an amateur) the bigger impact is for convective meteorologists that are continually watching satellite imagery and the work that places like CIMSS are doing in analyzing satellite imagery and detecting patterns indicative of severe weather. These detection algorithms will have a higher degree of confidence and can be triggered several minutes earlier now - possibly providing earlier warning for tornadoes.
GOES-16 will provide the data to allow a significant improvement in forecasts, especially of extreme weather events. Because it can have a variable scan pattern, it can do wide area scans and higher frequency scans tracking storms. The new lightning sensor allows better measurement of storm intensity. It also has finer discrimination for spectral information, 4x increase in resolution, etc.
We have some internal models that will benefit from the new GOES 16 data. Particularly the cloud mask product and the higher spatial/temporal resolution will be interesting. We develop our own internal cloudmasks using a custom tool and I'm interested to see how they differ. In anticipation of the higher spatial/temporal resolution data, we're updating our tools to reduce the memory footprint.
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:
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
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
116 comments
[ 2.6 ms ] story [ 299 ms ] threadhttp://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.
It was you, Minnesota.
windows: en-ca chrome: EN-US Physically in Canada
First of all, it often does it wrong - especially when using geographical location, which is one of the dumbest idea I've seen in computing. GPS fails when people are traveling (just because I'm in Germany right now, doesn't mean I want to see websites in German, etc.). GeoIP fails for various reasons, including VPNs and weird ISP shenanigans.
Second of all, as a person fluent in English, I especially don't want to see a translation of your originally English site. Most software and website translations suck hard. My most common gripe: using the same word in translated language for things named by different words in original, or vice versa.
I'd personally prefer that programs just acknowledge they're stupid and give me, the user, more control.
Possibly the locale detection is limited/imperfect, with °F as a fallback.
[0] https://darksky.net/
On a side note, you can see the Himalayas doing their job: https://www.ventusky.com/?p=32.15;78.51;6&l=pressure
Warning: Sound is on by default. Disable by clicking Sound in the menu on the lower left.
[1] http://blitzortung.org/
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
i won't switch from meteoblue which has more features, a similar ui and more and much better models, at least for europe.
I use this for backpacking and astrophotography to figure out precipitation and cloud patterns (as to not waste a drive out). Very helpful!
[1] https://en.m.wikipedia.org/wiki/Meteogram
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....
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.
Windytv created new version where you can see fine details for many different overlays.
these winds change fast and seem unpredictable and although the connection between general weather and wind is somehow limited it seems clear to me that it must be hard to make any accurate predictions.
IMO (as an amateur) the bigger impact is for convective meteorologists that are continually watching satellite imagery and the work that places like CIMSS are doing in analyzing satellite imagery and detecting patterns indicative of severe weather. These detection algorithms will have a higher degree of confidence and can be triggered several minutes earlier now - possibly providing earlier warning for tornadoes.
CIMSS proving ground: https://cimss.ssec.wisc.edu/goes_r/proving-ground/SPC/SPC.ht...
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.
Indeed, it reminds me of this, which has been around for years:
https://earth.nullschool.net/#current/wind/surface/level/ort...
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
http://www.nws.noaa.gov/gis/kmlpage.htm
Real estate would be a little easier via the MLS (I suspect the cost is prohibitive though) and demographic data is easily available.
There is a play button in the bottom left to animated the currently selected heat map over time.
Is it even possible?
edit: at 10m above the ground. at higher altitudes, it's quite faster and with a different shape