Wei-Ting Hung, Patrick C. Campbell, Zachary Moon, Rick Saylor, John Kochendorfer, Temple R. Lee, William Massman
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引用次数: 0
摘要
在数值天气预报(NWP)模型中,植被冠层下风的表示对于确定热量、动量和痕量气体的空地交换过程至关重要。由于风速与火灾行为之间的关系,冠层对近地面风速的影响对于区域 NWP 模型中使用的预报火灾蔓延模型至关重要。在实践中,火灾中燃点的风速(中燃风速)被用来确定火灾蔓延速度。然而,大多数现场测量和 NWP 模型中的风速都是在树冠和火焰上方的某个参考高度测量的。因此,本研究开发了一种模块化、计算效率高的一维模型集,由树冠风模型和风调整因子模型组成,适用于不同尺度的 NWP 应用。该模型集使用规定的叶形函数来表示垂直植被剖面及其对水平风速三维结构的影响。冠层风模型的结果与地面观测结果非常吻合,平均绝对偏差、均方根误差和判定系数分别约为 0.18 m s-1、0.40 m s-1 和 0.90。WAF 模型根据冠层、火和火焰特征估算 WAF,从而提供火焰中间风速。各种用户可定义的选项提供了灵活性,以适应树冠特征的变化和与野火相关的更多复杂性。预计该模型集可改进任何空间尺度的子网格风流,从而改进 NWP 模型。
Evaluation of an In-Canopy Wind and Wind Adjustment Factor Model for Wildfire Spread Applications Across Scales
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.
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