@Rudolpher
In "settings"
try this (set it off) ... it may helps

Thank you but that is not the issue, rather the inaccuracies caused by local variability in intensity which is averaged by interpolation. While @stéfan has posted raw imagery to demonstrate the difference and explain why the radar display in Windy might show strong precipitation while not a single drop falls, I can't do the same for Norway since I've been unable to find an open source for it - they're all processed before release it seems.

As an example:
It might be raining heavily a few hundred meters east and west of my location, unprocessed radar imagery would show that. However interpolation smooths this out and might end up displaying moderate to strong precipitation right where I'm standing, while not a single drop falls.

I've noticed this same thing many times before, Windy showing strong rain yet not a single drop falls at that exact location. Thought it was caused by a slightly misaligned overlay, however this explanation makes much more sense. Highly localized and spacially separated cells of intense rain causing a larger area to display as a uniform structure of high precipitation.

If not raw imagery, perhaps there's other algorithms that do a better job of avoiding these localized oddities?

Thanks for teaching me this, @stéfan

Ah OK I thought you was.

Thank you

Compared to the Météo-France map, the data provider, I don't see such a significant difference.

Windy at the same time

You create artificial datas …

I create nothing, I’m not in the Windy team. Just a Windy user …
Then, is Météociel an absolute reference ? At least you should show a radar map from Météo France.

Look here and the reality

some places are not under precipitations. You create artificial datas on area where nothing occurs.

That's what I try to explain.

“Animation fluide de radar et satellite” in French

Thank you for your response. However, I believe there is a misunderstanding regarding the nature of my request. I am not referring to the smoothing of values (averaging), but to the temporal morphing and motion advection used for your animations.

From a meteorological standpoint, precipitation is often cellular and highly variable. Your current interpolation algorithm creates a "smearing effect" between two radar scans. By trying to achieve a fluid visual transition, you are artificially spreading high-intensity pixels over areas that are actually dry or experiencing much lighter rain as the picture shows discrete pixels.

This leads to a violation of the Mass Conservation principle:
If a pixel represents 50 mm/h at Time T at coordinates (x,y), and moves to (x+1, y) at Time T+1, your interpolation displays a continuous path of high intensity between these two points. For the user, the Picker tool then displays a high rain rate where, in reality, there is no water falling at that micro-moment.

This visual candy masks the true spatial variability and creates misleading ghost rain. Scientifically, the pixelated raw data is the only ground truth. A striking example occurred during the recent snowfall in Paris. Your map displayed high-intensity radar echoes over my specific area for several minutes, yet not a single snowflake was falling.

This was a direct result of spatial smearing : there were high-intensity pixels (likely amplified by the size of frozen hydrometeors) on both sides of my location. Your interpolation algorithm filled the gap between these cells, creating a bridge of heavy snow on the screen that did not exist in reality. This proves that your smoothing logic creates false positives by artificially connecting distinct precipitation cells.

Could you please consider adding a "Disable Interpolation" or "Raw Data" toggle in the layers settings? This would allow users to see the actual radar grid and the true structure of convective cells.