NASA GISTEMP global temperature anomaly data from 1880 to 2025, rendered as a particle system. It starts measured and cold. It does not stay that way.
Each monthly temperature reading spawns particles whose color and physics are driven by the anomaly value for that month. Cool anomalies produce slow, blue-tinted particles that drift downward. Warm anomalies produce fast, orange-to-red particles that surge upward. The current year and temperature reading are displayed large in the center.
The animation plays forward through 140+ years of data. You can control the speed, pause to examine a specific period, or reset to 1880 and watch it unfold again. The shift from the pre-1950 baseline to the 2000s–2020s is obvious, and it gets more obvious as the particle behavior changes.
| Anomaly | Color |
|---|---|
| Below 0°C | Ice blue |
| 0°C – 0.5°C | Warm white/yellow |
| Above 0.5°C | Deep red to orange |
| Control | Function |
|---|---|
| Speed slider | 0.1x to 2.0x playback |
| Play/Pause | Hold on a specific year |
| Reset | Restart from 1880 |
| ? button | About modal with data links |
- Vanilla JavaScript, Canvas API
- Particle system with temperature-driven physics (velocity, color, glow)
- NASA GISTEMP CSV loaded and cached locally (no CORS proxy)
- Helvetica Neue for clean, neutral UI text
- Font Awesome for playback icons
fuse/
├── index.html # HTML shell and styles
├── script.js # Particle system, data loading, controls
├── nasa-data.csv # Local copy of NASA GISTEMP GLB.Ts+dSST.csv
└── social-card.png # 1200x630 Open Graph image
NASA publishes updated monthly figures. To pull the latest:
curl -s "https://data.giss.nasa.gov/gistemp/tabledata_v4/GLB.Ts+dSST.csv"> nasa-data.csvNASA GISS Surface Temperature Analysis (GISTEMP v4)
Dataset: GLB.Ts+dSST.csv, global mean surface temperature anomalies, monthly, 1880–present.
python3 -m http.server 8000
# open http://localhost:8000Opening index.html directly may hit CORS restrictions on the CSV. Use the server.
Luke Steuber · lukesteuber.com · @lukesteuber.com on Bluesky
Part of the data poems collection at dr.eamer.dev.
MIT