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.
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.
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.
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.
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.
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.
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.
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.
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.
Do you know if weatherspark used public or private data sources? I've been working on some open source data visualization tools and if the data sets were public perhaps we could build something with weather data sets in mind.
After WeatherSpark shut down I spent a few minutes poking around weather data sources before getting overwhelmed and giving up. It looks like they get all their historical data from Weather.gov. (WeatherSpark lists their data sources here: https://weatherspark.com/about ...and weather.gov appears to have their data available for download from NOAA:
https://www.ncdc.noaa.gov/)
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.
I only have a minor complaint: It only lets you view real time data and forecasts up to 2 weeks out; there's no archived data like earth.nullschool.net (which has data going back to 12/2013). If there were a site like that, or even a way of creating a DIY site that uses archived numerical data but maintains a similar UI/visual appeal as Ventusky (e.g. the wind streamlines, which I think look much more appealing than on nullschool), I would pay actual real money for this product.
I think making sense of the scale of weather would be aided by an accurate world map like the peters projection or something of that nature that doesn't do Eurocentric seafaring things like put Greenland as being the same size as Africa when Africa is like 11 times larger in reality. For example, with a proper map, the fact that much of the northern Atlantic landmass is heated by the sea would make more sense -- it's a much smaller area in reality than is represented.
I remember using this site to watch the projected path of the last hurricane that happened (I forget it's name). It was an amazing visualization tool. Forgot about it since then.
Warm is not necessarily bad if it's not humid. The San Francisco Bay area gets up in to the 90's sometimes in the summer, but it's quite bearable because it's not very humid (don't know why, since it's so close to water). In New York and further south on the East Coast, it gets to be as hot or hotter, but with 100% humidity -- it's torture.
No. I live in Spain, in an area close to a river delta where it is very, very windy. I also lived in a windy island for many years.
Wind, when it is strong enough, can be very uncomfortable, even dangerous.
I guess that what you are looking for are places with a sustained sea breeze in summer. However, these places tend to have high relative humidity, which is not comfortable.
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.