Journal of Advances in Modeling Earth Systems · 2024 · 10 citations · 79 references
Natural ResourcesEarth SciencesForestryFire EcologyFire ManagementNumerical Weather PredictionFire ModelingFire SimulationFire Spread ProcessesFire WeatherLand Surface ModelingWildfire EcologyCanopy Wind ProfileFire SpreadFire Spread ModellingFire Spread ModelsFire Spread PredictionWildland Fire ModelingWindWind-driven Fire Spread
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 −1 and 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.
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Michael Ek, Kenneth E. Mitchell, Ying Lin et al. · Journal of Geophysical Research Atmospheres · 2003 · 3.3K citations · Full text
Guo‐Yue Niu, Zong‐Liang Yang, Kenneth E. Mitchell et al. · Journal of Geophysical Research Atmospheres · 2011 · 3.1K citations · Full text
A Description of the Advanced Research WRF Model Version 4
C. Skamarock, B. Klemp, Jimy Dudhia et al. · 2019 · 2.3K citations · Full text
Natural Sciences, Computer Science, Numerical Weather Prediction +5