
I built a wind map with WebGL (2017) - bhousel
https://blog.mapbox.com/how-i-built-a-wind-map-with-webgl-b63022b5537f
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dbrgn
Slightly offtopic, but the windy.com service referenced in the article is
really a fantastic resource if you learn to use it properly. I rely on it for
paragliding a lot, the animated winds are much easier to understand for the
brain than static map. Comparing different weather models helps to assess the
accuracy of the prediction.

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hyperpallium
[http://windy.com](http://windy.com)

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adameast1978
This is the reason I got more serious about programming. This is really
awesome.

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mourner
Author here — very happy to see this resurfacing on HN! So, ask me anything!

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lbutler
I am just adding a second thanks for all the work you've done for the mapping
community. I've made a decent amount of spatial apps over the years, and they
wouldn't be possible without your work with Mapbox GL JS, Leaflet and the
algorithms you've shared.

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mourner
Thank you very much!

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bradleysmith
(This is a bit off-topic from the subject of the article about particular
methodology of rendering data as opposed to usage of these kind of wind maps)

I worked on X’s project loon in operations for a spell. We were interacting
with balloons in flight regularly. The referenced nullschool wind map was
unendingly useful.

Something I always wanted for using nullschool or other similar publicly
available “tools” was more granularity between wind layers, or derived
estimations of data between wind layers.

When putting any flight systems in the atmosphere, having visualizations (even
estimates) of wind direction and speed estimations at more altitude levels is
more valuable than visualizing more particles more efficiently, IMO.

I wish similar thought and processing power was put towards smoothing out
guesses at wind speeds at different altitudes.

Tl;dr: I wish this demo map had an altitude slider, even if it was smoothed
out guestimates between available data layers.

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th0ma5
I briefly looked into this, and from what I remember these were all always
based on the "satellite" based wind models which were interpolations of
predictions at a very low resolution based on infrared. Winds aloft, as I'm
sure you know, are often measured by radiosondes, but the subtle thing being
that these samplings only make it into aeronautical forecasts, and at least in
the US, stay US only, and don't bubble up to global summaries. These global
data sets are not granular at all, and wouldn't provide the detail at
different elevations. I wish such a data set was available... perhaps with the
global satellite based ADS-B someone could do some kind of sampling based on
live flight data, but I'm sure it would be a private (and costly) dataset.

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fogetti
I really don't know if it's open to the public or not but windguru definitely
has the dataset that you described. You might want to contact them to figure
it out :)

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boyadjian
Very nice work. The result is visually speaking.

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tobyhinloopen
Cool

