DOE Genesis Mission Selects Planette AI to Lead Effort on Forecasting Severe Thunderstorm Clusters Beyond Seven Days

Planette AI, Pacific Northwest National Laboratory, and the University of Wyoming Launch Genesis Mission Project to Improve Weeks-Ahead Forecasting of Dangerous U.S. Storm Systems

SEATTLE--(BUSINESS WIRE)--Large thunderstorm clusters cause billions in damage and supply much of the nation's warm-season rain, yet forecasters still struggle to see them coming more than a week out. Planette AI today announced the launch of DL4MCS, a Genesis Mission Phase I project supported by the U.S. Department of Energy (DOE) to improve subseasonal -- roughly 7 days to six weeks ahead -- forecasting of these storms, known as mesoscale convective systems (MCS), across the continental United States. Planette AI will collaborate with the DOE’s Pacific Northwest National Laboratory (PNNL), and the University of Wyoming on the project.

The Genesis Mission is a historic national initiative led by DOE that is building an integrated science discovery platform by bringing together government, industry, academia, and philanthropy to accelerate breakthroughs in energy, scientific discovery, and national security through AI, supercomputing, quantum systems, and advanced scientific instruments. The goal of the Genesis Mission Phase I awards is to identify promising pathways toward transformative scientific capabilities by designing and demonstrating research workflows that integrate AI with scientific investigation and testing whether those approaches can improve predictive capabilities, accelerate discovery, enhance experimentation, or generate new scientific insights.

DL4MCS — short for Deep Learning Methods to Enhance Subseasonal Predictions of Mesoscale Convective Systems by Physics-based Forecasting Systems — addresses that challenge by combining physics-based forecasting with advanced artificial intelligence methods. The project team will test whether this hybrid approach can substantially improve forecast skill for these storms at lead times of 7 days to 6 weeks, a forecasting window that remains especially difficult for today’s operational systems.

“DL4MCS reflects Planette AI’s commitment to delivering more actionable environmental intelligence for high-stakes decisions,” said Dr. Hansi Singh, Founder and CEO. “By combining state-of-the-art AI with proven physical forecasting systems, this project aims to make weeks-ahead storm risk information more useful for the sectors and communities that depend on better foresight.”

“Improving prediction of mesoscale convective systems requires advances across scales, from large-scale climate drivers to the cloud microphysics that shape storm behavior,” said Dr. Susannah Burrows, Atmospheric Scientist at Pacific Northwest National Laboratory. “This collaboration brings together complementary strengths in Earth system modeling, AI, and process-level model evaluation to explore a new path toward better subseasonal forecasts.”

“The University of Wyoming is excited to contribute its expertise in regional downscaling, as well as its responsible integration with AI forecasting, to this effort,” said Dr. Stefan Rahimi, University of Wyoming Derecho Professor. “The ability to translate coarse large-scale forecasts into higher-resolution, decision-relevant guidance is essential for improving real-world preparedness and resilience.”

About Planette AI

Planette AI develops operational seasonal and subseasonal global forecasts for weather-sensitive sectors, including energy, utilities, and insurance, with a focus on actionable environmental intelligence for decision-making. Follow us on LinkedIn.

About Pacific Northwest National Laboratory

Pacific Northwest National Laboratory is operated by Battelle and supported by the Office of Science of the U.S. Department of Energy. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit the DOE Office of Science website. For more information on PNNL, visit PNNL's News Center. Follow us on Twitter, Facebook, LinkedIn and Instagram.

About the University of Wyoming

The University of Wyoming team contributes expertise in regional modeling and dynamical downscaling of coarse-resolution Earth system model output to high-resolution weather information and its integration into AI systems.