Where infrared.city fits
3,204,804 simulations run on Infrared Core (as of 29 Oct 2026).
infrared.city runs 12 models from one engine, Infrared Core, among them wind, wind comfort, sun, daylight, radiant heat and felt heat (UTCI). It works on real 3D building and terrain meshes, in a browser app, through an API and SDK, and in plugins for Grasshopper, QGIS and ArcGIS. Felt heat for 1 km² takes about 5 s once the geometry is uploaded, and 400 km² took 44 s as four 100 km² runs in parallel. Run times are not like for like across tools: area, grid, simulated hours and physics differ. Sun, sky and radiant heat come from ray tracing. Wind comes from an AI model trained on CFD results, not from a CFD run for each request. It answers a design question at street level: how hot a street or square feels, hour by hour, and what changes with trees, shade, materials or another design option.
- You need to know how hot a street or square feels, on a 1 m grid, and what to change.
- You compare design options: trees, shade, materials and building forms.
- You need wind comfort and sun together with the heat.
Use both
Risk analytics show which assets face climate risk over the coming decades. infrared.city shows how a design changes felt heat and wind at street level.
Facts side by side
| infrared.city | Jupiter Intelligence | |
|---|---|---|
| What you get | Simulated felt heat (UTCI), radiant heat, wind, sun and shade at street level | Asset-level, multi-peril physical risk projections |
| Measured or simulated | Simulation, for the city as it is and for design options | Modelled from global climate models |
| Time | Hourly forecast (live layer), typical year, 2050 weather | Now to 2100, scenarios in 5-year steps |
The infrared.city values repeat the full comparison. Each value for Jupiter Intelligence comes from the sources below.
Sources
- Jupiter Intelligence home page , accessed 30 Oct 2026.