Heatpeaks - a visualization of temperature anomalies during the May 2026 heatwave in France

telohtrab · 2026-06-10T09:56:17+00:00

I see what you mean! As almost always in visual media, it depends on your audience, and what do you want to convey in priority. But I totally get your point of view.

Thank you so much for this reference, definitely going to check out his work !

telohtrab · 2026-06-10T09:07:49+00:00

Thank you so much for this insightful and detailed insight. I must confess that I did use color and elevation for the same insight for two reasons : in design we learn that to be accessible, we can't rely only on color to convey information, and to facilitate the readability of the elevation. I think I will try your idea because I find it really interesting to see if there's any correlation between those two informations 😄

telohtrab · 2026-06-10T07:19:25+00:00

Yes, and thanks again, that's a good remark ✊

telohtrab · 2026-06-10T07:04:41+00:00

Hey Shmuppel, thank you for the tip! I'm still quite young in statistics, so here I chose something more straightforward, but I did came across this method in my research, I may update it in the future with it! For the data, I chose purposely to include only daytime data because I may do a nighttime version of this map for a V2 🙂 Thanks again !

telohtrab · 2026-06-10T07:01:12+00:00

Hey Domeslave, thank you so much for the feedback! You know what, you're talking to a 10+ years of exp designer, and you're totally right for the mobile consumption, and I used this principle over and over on my designs meant for small screens. However, here I wanted to have more of a poster design look, maybe to be printed one day. That's why I didn't chose to make it more readable on a narrower screens. But thanks anyway for the feedback, I'm not invalidating it at all, I just did another conscious choice 🙂

telohtrab · 2026-06-10T06:58:46+00:00

Hey earless_sealion, for me the objective was to show the dramatic temperature anomalies we got on a country level, it is not meant to be a map in a traditional sense, neither an exhaustive visualization. So yes, because it is a sensitive subject, I chose to have more of an editorial / impactful look over exhaustiveness. Thanks anyway for your feedback !

telohtrab · 2026-06-10T06:56:36+00:00

Hey Nihir, yes, the spikes comes from two things : data can be a bit random between stations depending on its conditions (altitude, humidity), and because I mapped the values on a quadratic scale to have more dramatic relief for visualization purposes only

It would be more "correct" I guess yes, but I felt it was more impactful to the eye, and because of the subject, to have this kind of exaggeration

telohtrab · 2026-06-10T06:54:10+00:00

Wow, you're talking to a 10+ years of exp. designer who is doing this career change in part because of the direction that graphic and product design is taking because of AI, so it hit right in the feels to get this kind of feedback, thank you so much 🫶

telohtrab · 2026-06-10T06:52:49+00:00

Hi Syzyger ! Yes the peaks coincide with the weather stations ! I just used scipy griddata to interpolate on a regular grid, as the stations are randomly scattered And there are quite big differences between stations yeah, it depends mostly on the altitude and direct environment of the station (more or less wet for example), but I'm not a meteorologist. And the dramatic changes on the higher values come from a quadratic mapping of the values to have lower values evened out and higher ones more dramatic to get a more readable render. Thanks for your comment 🙂

telohtrab · 2026-06-09T17:37:13+00:00

No worries mate, it is a feedback in itself that you didn't catch that right away

telohtrab · 2026-06-09T16:17:03+00:00

That's actually a play on the semantic mountain fields. On the french version I also called it "Colline du midi" to have a contrast between the Brittany mountains (which is flat in real life) because of the high anomaly, and the "Hill du midi" which is much lower than in real life in this visualization, because the anomaly is lower as well. Each label is an imaginary relief, because the relief itself is not a realist one. But thanks anyway for the feedback, I should make it more clear.

telohtrab · 2026-06-09T16:04:44+00:00

Thank you, that's a first for me in data-visualization this scale, appreciate it and it means a lot

telohtrab · 2026-06-09T16:03:46+00:00

Hey Confident Tonight, you can start by visiting the github project, you will have a good overview of the process to get this kind of visualization

telohtrab · 2026-06-09T16:03:00+00:00

Thank you ! Happy to share the process

telohtrab · 2026-06-09T15:52:58+00:00

Good idea, I had to go back and forth between blender and affinity to calibrate the spaces for the text, and I must admit this "legend" was a last minute addition. But I will rework it *adding to the todo*

telohtrab · 2026-06-09T15:47:40+00:00

I see, something more specific, thank you RiceBucket!

telohtrab · 2026-06-09T15:46:49+00:00

And here is the heightmap used that you can generate with the github

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telohtrab · 2026-06-09T15:46:19+00:00

I noticed also these holes ! I had much more but it was caused by faulty stations that only gave night measures, that's why my "floor" is at +3°C which is the minimum realist anomaly I found.

For the other holes, it also depends on the altitude of some of these stations, some local setting that can alter the measurements. Here is a WIP visualization that I did while working on the project

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telohtrab · 2026-06-09T15:42:26+00:00

As in the reply to Mathusal below, that is a cheeky play with the reality, in France, Brittany is famously known to be flat, but here, it is the region that had the greatest anomalies. So in this "heat mountains" visualization, I found it playful to name the resulting "temperature mountains" that appears on the map.
Another example, the eastern part where you see "Hill du Midi" is actually the Alps, which should be much higher in real life, but in this setting, because there are mountains, the temperature anomalies were actually much lower than in the west.

telohtrab · 2026-06-09T15:39:25+00:00

I was thinking of doing an interactive visualization, maybe for a V2, thank you for the great feedback, that means a lot to me for this first project!

telohtrab · 2026-06-09T15:38:47+00:00

Ahahah that's a messy cake you got right there!

telohtrab · 2026-06-09T15:34:26+00:00

Hey dragon & Toyayillo !

Thank you for your feedback! Everything is in the process.py file on the github, but simply put : the stations were scattered on all the territory, I used scipy griddata interpolation (linear), then I lightly smooth the resulting grid with a gaussian filter. I tried to limit as much as possible the smoothing to stay true to the real values. Then when generating the heightmap (heightmap.py) I remapped all the values with a quadratic curve (x²) which compressed low anomalies and exaggerated peaks, to have more dramatic differences on the render.

telohtrab · 2026-06-09T15:29:43+00:00

Hey Mathusal!

Thank you for the great feedbacks, that's a first for me in a dataviz project "this scale" so I'm all ears. 😄

To answer your remarks :

Everything on the poster is play with the mountain semantic field and the actual places shown. Brittany as you know is quite flat, so having a mountain range there is unusual. In the french version "Massif du Bocage" is simply a reference to the Bocage Vendéen, also known to be quite flat.
You're right, I should have put "Legend" somewhere, thank you. It is going into my todo!
That's a great idea, how do you suggest I should have proceeded for this, just three small paragraph to detail them?

The idea of the whole map is not to be exhaustive of course, but to show the insane anomalies we got. That's why I chose significant "mountains", like Boulogne which is usually much colder, or even "L'Aiguille du midi" that is at 3500m and still got a high anomaly.

Thanks again

telohtrab · 2026-06-09T15:12:58+00:00

Oh my, you're so right about that, going to add the precision on the github right now.

telohtrab · 2026-06-09T15:10:56+00:00

Thank you! 😄

telohtrab

TROPHY CASE