Local scale meteorology, vegetation fuel type, fuel arrangement and distribution, complex firing ignition patterns, fire intensity and it’s effect on fire behavior, fire effects, and smoke plume loft and dispersion is critical to prescribed fire management and Go No/Go decision protocols.

Weather forecasting for prescribed burns relies on synoptic-scale data and forecast products to determine burn days. In complex meteorological situations, such as those found at the land/sea interface, and in complex terrain covered by volatile coastal chaparral, experience has shown this task to be anything but trivial. For example, at Fort Ord, located in Monterey County on the Central California Coast, approximately 100 miles south of San Francisco, the influences of a land/sea interface, complex terrain, non homogenous vegetative fire fuels, and a large nearby population, prescribed burns in the past have escaped, and created negative smoke impacts on several occasions. Synoptic-scale weather patterns do not reflect the local-scale winds and stability, and how they directly influence flammability, fire intensity, fire spread potential, smoke plume loft, and smoke transport and dispersion.

Flammability and fire intensity of coastal chaparral is directly influenced by minute variations in wind, live and dead fuel moisture, solar preheating, and complex aerial ignitions. Asynoptic wind flows and horizontal wind shear over complex terrain and populations surrounding the burn units compound the challenge of predictive reliability.

A High Resolution Meteorological Team, working in conjunction with the Naval Postgraduate School Meteorology Department, has developed a coupled model ensemble and a Fire/Smoke Signature Profile protocol that is capable of reliable predictive accuracy for making crucial Go/No Go prescribed burn decisions. Synoptic and refined scale winds are monitored and coupled with vegetation data and calculated fire intensity created by multiple complex aerial ignitions to derive fire consumption and behavior values used to predict fire effects and minimum smoke plume loft and dispersion characteristics in real and near real time.

The Fire/Smoke Signature Profile Model can provide valuable predictive capability to prescribed fire managers where traditional fire models (BEHAVE, FARSITE) and smoke models (CALPUFF) prove inadequate.