Evaluation of an In-Canopy Wind and Wind Adjustment Factor Model for Wildfire Spread Applications Across Scales

Abstract

The representation of vegetative sub-canopy wind is critical in numerical weather prediction (NWP) models for the determination of the air-surface exchange processes of heat, momentum, and trace gases. Because of the relationship between wind speed and fire behaviors, the influence of the canopy on near-surface wind speed is critical for prognostic fire spread models used in regional NWP models. In practice, the wind speed at the midflame point of fires (midflame wind speed) is used to determine the rate of fire spread. However, the wind speeds from most in situ measurements and NWP models are taken at some reference height above the canopy and fire flames. Hence, this study develops a modular and computationally-efficient one-dimensional model set composed of a canopy wind model and a wind adjustment factor (WAF) model for NWP applications across scales. The model set uses prescribed foliage shape functions to represent the vertical vegetation profile and its impacts on the three-dimensional structure of horizontal wind speeds. Results from the canopy wind model well agree with ground-based observations with average mean absolute bias, root mean square error and determination coefficients around 0.18 m s⁻¹, 0.40 m s⁻¹and 0.90, respectively. The WAF model provides midflame wind speeds by estimating the WAF based on canopy, fire and flame characteristics. Various user-definable options provide flexibility to adapt to variations in canopy characteristics and additional complexities associated with wildfires. The model set is expected to improve NWP models by providing an improved representation of the sub-grid wind flows at any spatial scale.