Very neat, I wish the water areas showed water temperature, not air temperature.
Ventusky – Weather data visualization
31–40 of 117 posts
Re: Ventusky – Weather data visualization
#32Very 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-)
If ISO dates is a measure for being in the 21st century, it should probably really be defaulting to Kelvin, no? 8-)
No. Kelvin was never intended for this sort of use. ISO dates were.
Re: Ventusky – Weather data visualization
#33Looks very similar to Windytv ( https://www.windytv.com/ ). Are these websites somehow related?
They are both very similar to https://earth.nullschool.net/ which is open source: https://github.com/cambecc/earth
It is not any longer, the last update on github was made 3 years ago. Now Cameron works is not publishing new features on github.
Re: Ventusky – Weather data visualization
#34Looks very similar to Windytv ( https://www.windytv.com/ ). Are these websites somehow related?
They are not, the only common thing is that they are Czech companies. Windytv provides ECMWF model (for free), which beats Ventusky in big way.
Re: Ventusky – Weather data visualization
#35While 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.
Re: Ventusky – Weather data visualization
#36Check out how you can embed a snapshot and it keeps the animation! All in the code, too!
Re: Ventusky – Weather data visualization
#37This 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.
Re: Ventusky – Weather data visualization
#38Number one criteria I look for in weather sites is that they pin my CPU to 100%.
You co-locate a lot of other workloads with your novelty weather visualizations, do you?
Re: Ventusky – Weather data visualization
#39This 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 rang…
Windytv (http://windytv.com) provides ECMWF 9km global model, NAM 4km for CONUS, NEMS 4km for Europe and also GFS. Info about data sources used at Windytv https://community.windytv.com/topic/12/what-source-of-weathe...
Windytv created new version where you can see fine details for many different overlays.
Re: Ventusky – Weather data visualization
#40While 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. [1] https://en.m.wikipedia.org/wiki/Meteogram
Completely agree. The value of being able to compare individual parameters across models over time, especially with an NWS forecast overlaid is tremendous.
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....