Advanced Unified Radar Architecture
Next-generation tornado detection and 3D visualization. AURA fuses multiple radar sources into a unified volumetric picture — giving meteorologists and emergency managers a complete view of storm anatomy in real time.
Research in Progress: Project AURA is an active research initiative. The capabilities described reflect our development goals and current approach. Specific implementation details, model architectures, and processing methods are proprietary and not disclosed publicly. We share what the system does — not how it does it.
30,000-Point Tornado Reconstruction
Drag to orbit. Use the slider to see how AI prediction transforms raw radar data into a clean volumetric model.
Tornadoes are 3D. Radar is still 2D.
Current radar systems scan storms one flat slice at a time. Meteorologists mentally reconstruct 3D structure from these 2D sweeps — but that takes experience, time, and leaves room for error. In severe weather, every second of delay costs lives.
AURA changes the equation. By fusing data from multiple radar sources and applying AI to fill gaps and reduce noise, the system builds a complete 3D model of storm anatomy. Wall clouds, funnel structures, debris fields, rear-flank downdrafts — all visible in a single volumetric view that updates in real time.
The result: faster detection, clearer situational awareness, and more lead time for warnings. Not replacing meteorologists — giving them a better picture to work with.
What AURA is built to deliver
Full spatial reconstruction of wall clouds, funnels, and debris fields
From raw radar sweep to updated 3D model in sub-second intervals
Multiple radar sources merged into a single gap-free picture
ML models that clean noise and forecast storm evolution in real time
What the system does
Real-Time 3D Reconstruction
Transform flat radar scans into volumetric 3D models of severe weather. Meteorologists see the full anatomy of a storm — not just a slice.
AI-Enhanced Prediction
Machine learning models refine raw radar data to predict tornado behavior before it happens. Noisy signals become clean, actionable intelligence.
Volumetric Radar Fusion
Combine multiple radar sources into a single unified picture. Gaps between sensors get filled. Blind spots disappear.
Automated Detection Alerts
AI-driven alerts that trigger faster than traditional methods. Earlier warnings mean more time for emergency response and evacuation.
Multi-Sensor Integration
Ingest data from different radar types and sensor networks simultaneously. More input sources mean a more complete picture of what the storm is doing.
Sub-Second Processing
Process incoming radar sweeps and generate updated 3D models in under a second. Real-time means real-time — not close enough.
Active research phase
AURA is in active development. Early prototypes are producing promising 3D reconstructions from multi-source radar data, and our AI models are showing meaningful improvements in noise reduction and prediction accuracy compared to raw inputs alone.
We are not yet sharing specific performance metrics or benchmark data — the system is still being validated across a range of storm types and geographic conditions. When we publish numbers, they will be well-tested and honest.
Project AURA — Common Questions
Interested in next-gen weather detection?
If you work in meteorology, emergency management, or severe weather research — we would love to hear how better 3D storm visualization could help your work.