AI Climate Oracle is a Bittensor subnet where miners compete to build accurate climate AI models, verified by validators against NOAA n satellite data. Decentralized, incentivized climate intelligence
AI Climate Oracle is a decentralized climate prediction subnet built on Bittensor. Miners compete to develop the most accurate climate forecasting AI models, while validators verify predictions against real-world data from 30,000+ NOAA weather stations, ECMWF numerical weather models, NASA POWER satellite observations, and OpenMeteo.
The subnet uses a multi-dimensional scoring system:
Temperature Accuracy: 40%
Precipitation Accuracy: 25%
Risk Assessment: 15%
Latency: 10%
Consistency: 10%
Miners earn a 1.5x bonus for correctly predicting extreme events (floods, heatwaves, storms). Validators use a 70/30 split between historical challenges and near-term predictions to prevent overfitting.
Target markets include parametric insurance ($14.5B), agriculture, government disaster response agencies, and smart city infrastructure.
Tech stack: Python, FastAPI, Bittensor (Yuma Consensus).
Designed complete subnet architecture with ClimateSynapse protocol for miner-validator communication
Built working API prototype with 5 endpoints: /predict, /risk-assessment, /historical, /data-sources, /subnet-info
Defined multi-dimensional scoring formula with extreme event bonus mechanism
Created detailed Subnet Design Proposal covering miner logic, validator verification, incentive mechanism, and anti-gaming strategies
Implemented risk breakdown system covering flood, heatwave, storm, and drought analysis
Documented go-to-market strategy targeting insurance and agriculture sectors
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