Advancing AI-Based Forecasts for Wildfire Management

Wind is one of the most critical — and least predictable — drivers of catastrophic wildfires. A single gust can turn a small, containable brushfire into a fast-moving firestorm that threatens communities, infrastructure, and lives. 

Traditional weather models often struggle to accurately capture key details such as the precise timing, speed, and direction of winds, especially when those winds are shaped by complex atmospheric conditions over terrain sometimes thousands of miles away. 

To address this challenge, MITRE developed Ponderosa, an agile AI tool designed to improve accuracy in wind forecasting for wildfire management. The tool was trained on terabytes of publicly available meteorological data using our supercomputer: NVIDIA DGX H100 SuperPOD™ with 248 NVIDIA H100 GPUs and 9 PB of storage. It spent 345,000 hours of GPU runtime to generate a first-of-its-kind, high-resolution weather dataset. 

The novel Weather 1K dataset is the highest resolution AI training dataset publicly available. Rather than replacing existing weather models, Ponderosa feeds them critical data, significantly enhancing their ability to forecast wind behavior. 

Ponderosa’s key advantage is its ability to account for dynamic terrain and localized microclimates. By filling coverage gaps and sharpening the scope of how wind will move across complex landscapes, it enables more precise forecasts. 

Fire weather management officials can visualize these improved predictions on geospatial maps, helping them anticipate how winds are likely to drive a fire’s path under changing conditions. 

The system draws on MITRE’s strengths: deep engineering and AI expertise, mission-focused work in the national interest, and an end-to-end systems engineering approach that integrates data, sensors, computing, and automation.

—Communications and External Affairs (Joshua Gottschling and Catherine Trifiletti)