Forest Fire Model

Overview

The forest fire model takes into account fire weather (with a climate change signal), maximum wind speed and vapour pressure deficit (VPD), the difference between the absolute humidity and the water vapour saturation point for a given temperature, ground fuel mapping, and ground fuel attenuation. Forest fires can destroy buildings and infrastructure through direct flame or intense radiant heat. Assets considered to be at risk are those under or surrounded by trees, or close enough to trees to be affected by intense thermal radiation should the forest catch on fire. Grass fires are not covered by this model. The key elements are: • a fire weather metric from climate simulations • a Forest Fire Exposure Factor (FFEF), which accounts for density of ground fuel in the surrounding area, and ground fuel attenuation maps which are used to reduce the risk of damaging fires occurring of propagating • probability of ignition and the probability of a fully exposed asset being destroyed, given forest and ground fuel present and fire weather conditions • burn Probability which accounts for the probability that a property will actually catch on fire if there is a forest fire in the immediate vicinity

Local Context Data Use

The Forest Fire Exposure Factor (FFEF) is based on context data that attempts to capture a location's exposure to flammable vegetation and likely protection from fire services. The forest fire hazard data context layers in the Climate Risk Engines use density of ground fuel in the surrounding area, and ground fuel attenuation maps which are used to reduce the risk of damaging fires occurring or propagating.

Baseline Hazard Data

The driving parameters of forest fire are temperature, humidity, wind speeds and forest-fire prone land. The Hot-Dry-Windy index (HDW) of fire weather is based on maximum wind speed and vapour pressure deficit (VPD), the difference between the absolute humidity and the water vapour saturation point for a given temperature.

Climate Change Projections

Gridded projections for future epochs, based on GCM/RCMs, or CMIP6 directly can be used to project the changes to the key inputs for HDW.