Extreme weather events are intensifying worldwide—but forecasting them remains a stubborn challenge. Even with state-of-the-art models, meteorologists often struggle to provide accurate, timely warnings for rainfall extremes, heatwaves, and severe storms.
To address this gap, NASA has awarded Planette—a leader in long-range weather prediction—a new contract to develop QubitCast, a next-generation AI-powered forecasting system. The platform aims to push the boundaries of subseasonal-to-seasonal (S2S) forecasting, delivering predictions from two weeks up to two years in advance, with a strong focus on extreme weather detection.
Beyond the 10-Day Forecast
Traditional weather models top out at about 10 days of reliable lead time, relying on massive physics-based simulations that demand significant computational resources. Climate models, on the other hand, focus on long-term projections spanning decades.
That leaves a critical information gap: the mid-range, or subseasonal-to-seasonal window, which is vital for planning in agriculture, energy, infrastructure, and disaster response.
Planette’s approach layers physics-based models with AI, integrating atmospheric, oceanic, and land data to deliver predictive insights up to a year ahead.
Quantum-Inspired AI Without the Quantum Hardware
At the heart of QubitCast is a quantum-inspired AI algorithm that can explore multiple scenarios in parallel—an approach drawn from quantum physics but not dependent on quantum computers.
“You can think of it like reading the entire history of Earth’s systems all at once,” said Dr. Kalai Ramea, Planette’s co-founder and CTO. “Instead of scanning year by year and missing anomalies, our method allows us to detect signals for extreme events much faster and more accurately—while consuming far less energy than traditional AI models.”
This efficiency addresses two pressing challenges in modern forecasting: the massive computing costs of physics-driven simulations and the scaling limitations of conventional AI models when analyzing highly complex, high-dimensional Earth system data.
Practical Impact: From Crops to the Grid
By providing early and actionable forecasts, QubitCast has broad implications across industries:
- Agriculture: Farmers can plan planting and harvesting cycles around predicted droughts or rainfall extremes.
- Disaster Preparedness: Emergency managers gain longer lead times for hurricanes, floods, or wildfires.
- Energy & Utilities: Grid operators can anticipate heatwaves or storms to better balance supply and demand.
“Too many critical decisions are made in the dark because reliable long-range forecasts simply haven’t been available,” said Dr. Hansi Singh, co-founder and CEO of Planette. “QubitCast changes that equation by making S2S forecasting not just more accurate, but practical to deploy at scale.”
Building Momentum in AI Weather Intelligence
NASA’s award adds to Planette’s accelerating momentum. Earlier this year, the company secured a Phase I SBIR grant from the National Science Foundation to advance NIVA, its foundational AI Earth systems model. Planette also launched Eddy, a free tool delivering long-range weather forecasts to the public for the first time.
With QubitCast, the company is now targeting the holy grail of weather prediction: actionable, energy-efficient, long-range forecasts that can save industries billions of dollars and protect vulnerable communities from the mounting risks of climate extremes.
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