# Wind Model Validation · infrared.city

> How our AI wind model predicts pedestrian-level wind across diverse urban shapes, tested against high-fidelity CFD: Index of Agreement 0.988, mean absolute…

Source: https://infrared.city/knowledge-base/wind-model-validation

28 Apr 2026 · 1 min read

How our AI wind model predicts pedestrian-level wind across diverse urban shapes, tested against high-fidelity CFD: Index of Agreement 0.988, mean absolute error 0.31 m/s.

## Wind model validation

![Wind Model Validation, figure 1](https://infrared.city/assets/learn/img/7cf03d91670b.webp)

At infrared.city, we build AI models that predict urban wind speeds fast enough for real-time planning workflows, without waiting days for traditional CFD simulations. Today, we're sharing results from our latest model, which we tested across a wide range of urban geometries.

The new model achieves an average Index of Agreement of 0.988 and a mean absolute error of just 0.31 m/s, tested against high-fidelity CFD simulation.

### Performance at a glance

| Metric | Value |
| --- | --- |
| Mean Absolute Error (MAE) | 0.31 m/s |
| Index of Agreement (IA) | 0.988 |

Benchmarked against high-fidelity CFD simulation across diverse urban scenarios.

IA of 1.0 = perfect match.

### What we're predicting

The model takes an encoded urban geometry and outputs a full wind speed field at pedestrian level. No location-specific tuning required: the model generalises across urban typologies globally, from dense street grids to sprawling mid-rise districts.

### How we validated it

We compared predictions against CFD simulations across diverse urban scenarios. Each case was evaluated on two metrics:

- **MAE**, mean absolute wind speed error in m/s
- **Index of Agreement**, measures how closely the predicted spatial pattern matches the reference simulation, capturing both magnitude and distribution accuracy

![Wind Model Validation, figure 2](https://infrared.city/assets/learn/img/49a2725bad22.webp)

### Speed

Traditional CFD simulations can take hours to set up and run. Our model delivers a comparable wind pattern in seconds, making it practical for iterative design, early-stage masterplanning, and large-scale urban analysis.

![Wind Model Validation, figure 3](https://infrared.city/assets/learn/img/e77ac8cc8ebc.webp)

![Wind Model Validation, figure 4](https://infrared.city/assets/learn/img/b4732b5446b8.webp)

![Wind Model Validation, figure 5](https://infrared.city/assets/learn/img/a1220d925bb7.webp)

![Wind Model Validation, figure 6](https://infrared.city/assets/learn/img/ede7aa0850e1.webp)

### What comes next

We're continuing to push accuracy further and expand validation coverage. If you're working on wind comfort assessments, pedestrian safety, or urban microclimate analysis, we'd love to talk.