• much appreciated

The red line is a parcel ascent. Drag the purple slider to the right, and this will change. The concept is that as the surface temperature increases, the energy of a rising parcel of also increases (known as CAPE). By comparing the red curve with the existing temperature profile, you can diagnose the instability (likelihood of showers, thunderstorms etc) of the atmosphere. In theory, you can even use this to predict the exact onset times of convective clouds, or even afternoon thunderstorms. Just google "radiosonde parcel ascent", "convective available potential energy", or "lifted index" to get started.

There was a bug in my plugin that showed the error "TypeError: Plugin.instance is not a function" and you fixed this. Can you remember what the bug was? I'll need to patch in the fix to my original version.

windy-plugin-readlevels

Do not worry I will make dataLoader, so far I am finishing one big thing on Windy

Pascent = [ 1000, 950, 925, 900, 850, 800, 700, 600, 500, 400, 300, 250, 200, 150 ]

Though I see you also use "surface" and "100m" instead of 1000hPa, so by all means use that if you also have temperature and relative humidity at those levels.

Then Tascent is the temperature (shortname is "T" in the ECMWF docs), U is the U-velocity (shortname "U"), V is the V-velocity (shortname "V").

One thing I'm now realising is that I used an equation to convert the humidity into the dewpoint while generating the sample data, so you'll need to add this into plugin.html. To get Tdascent (the dewpoint temperature ascent), relative humidity (shortname is "R" at ECMWF, and the Windy is named "Humidity") must be converted to dew point using this formula:

for (var p = 0; p < Pascent.length; p++) {
Tdascent[p] = 243.04*(Math.log(R[p]/100)+((17.625Tascent[p])/(243.04+Tascent[p])))/(17.625-Math.log(R[p]/100)-((17.625T)/(243.04+T)))
}