Developed by Dr. Gary Johnson and others at Spatial Informatics Group, GridFire is a next-generation wildfire modeling system designed to support dynamic, large-scale simulations of fire behavior under uncertain weather conditions. Developed to enhance operational planning and hazard forecasting in California and beyond, GridFire leverages probabilistic approaches and high-performance computing to produce realistic fire spread scenarios in both near-term (e.g., daily to weekly) and long-term (e.g., seasonal to decadal) timeframes.

At its core, GridFire integrates forecasted weather from observation or model and ignitions derived from historical patterns or user-defined scenarios. Fires are simulated as ensembles with hundreds of possible outcomes to capture uncertainty in ignition timing, location, and meteorological conditions. Outputs include fire perimeters, burn probabilities, and arrival times, offering detailed spatial and temporal insights into potential wildfire impacts.