Ranking weather models by how their forecasts turned out
Weather apps all claim to be accurate but never show their work. So I built a scoreboard that checks: it takes the forecasts each model published (ECMWF, GFS, ICON, AIFS and others, plus Apple Weather, Foreca, OpenWeather and Visual Crossing), waits for the weather to happen, and scores temperature, wind and rain against observations. A few things that surprised me: - AIFS performs very well, yet almost no commercial apps give you access to it or uses it in their blend (I suspect some do without disclosing it tho) - Foreca scores surprisingly well compared to other apps and raw models - ICON…
What it does
In the maker’s words, at launch
Weather apps all claim to be accurate but never show their work. So I built a scoreboard that checks: it takes the forecasts each model published (ECMWF, GFS, ICON, AIFS and others, plus Apple Weather, Foreca, OpenWeather and Visual Crossing), waits for the weather to happen, and scores temperature, wind and rain against observations. A few things that surprised me: - AIFS performs very well, yet almost no commercial apps give you access to it or uses it in their blend (I suspect some do without disclosing it tho) - Foreca scores surprisingly well compared to other apps and raw models - ICON is very accurate around the mediterranean, but performs quite poor everywhere else There's also a history page that scores each model back through its full archive (about 5 years for GFS) to see if forecasts have actually gotten better. It's a static page and open-source: https://github.com/NickLeenders/verisky-scoreboard. Public models are scored in your browser against Open-Meteo's archive. Commercial scores come as small aggregates from my server, because those providers' terms don't allow redistributing raw forecasts. It powers an app that does the same per location in more detail, link is on the page. Happy to answer questions about the scoring method.
Does the same job
all alternatives →- WWWeather Watching2025 · walzr.com · ▲94
I was walking around New York last month during some light rain and noticed about half the people had umbrellas open. When the rain picked up a few minutes later, that number jumped closer to 80%. It got me thinking it'd be cool to track this somehow, so I built a website! I am taking a sidewalk livestream, feeding it into a YOLO model for people tracking, then sending a frame of each detected person to Gemini 2.0 Flash, which returns structured JSON about each person's clothing and if they're holding an umbrella. I also had fun making the site look like a TV weather channel. I showed some…
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the category →- TL
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Hi HN, I built Eigendrum, a web tool that solves the 2D wave equation for arbitrary shapes so you can hear what they sound like as drums. How it works: * Solves -∇²u = λu using finite element analysis (Kφ = λMφ) on a triangle mesh. * Validated to <0.1% error against closed-form solutions for circles (Bessel zeros) and rectangles. * Sound model factors in strike location, Rayleigh damping, and mallet width. * Includes Kac drums I & II to demonstrate identical sound spectra from different geometries. * No frameworks, build steps, or dependencies. Repo and tests:…
Life & fun · 27d ago · baselashraf81.github.io
Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io
- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com