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LES of Neutral Canopy Flows: Direction-of-Interest Aligned and Misaligned with the Mean Pressure-Gradient Force; CHATS Data and Analysis

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DataCite Commons2025-11-21 更新2026-04-25 收录
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For atmospheric turbulence, multiplying an estimate of the convection velocity with the integral time scale is useful for estimating the integral length scale. Velocity scales that have been used to estimate the convection velocity include the local mean velocity, the ratio of $e$-folding length and time scales, and the ratio of a prescribed spatial separation and the time lag at which the space-time autocorrelation peaks. A knowledge gap is the lack of evaluation of these velocity scales directly against the convection velocity, especially for canopy flows where previous studies have reported somewhat inconsistent results. The objective of this work is to assess the ability of each candidate velocity scale to estimate the convection velocity in canopy flows. Firstly, large-eddy simulation (LES) results of neutral canopy flows are used to compare these velocity scales to directly quantified convection velocity. When the direction of interest roughly aligns with the mean pressure gradient force (specifically, for an angle of $7.5^\circ$ or smaller), all candidate velocity scales other than the local mean wind component approximate the convection velocity fairly well. When the direction of interest departs from the mean pressure gradient force for more than $15^\circ$, the ability of each velocity scale to approximate the convection velocity changes substantially. Secondly, data collected during the Canopy Horizontal Array Turbulence Study (CHATS) are used as an example of interpreting estimates of the convection velocity in the field with the guidance from LES findings. Because observational periods are never perfectly neutral, the guidance does not involve direct comparison between observed and simulated velocity scales, but focuses on uncertainties of velocity scale estimates and potential caution needed when using these estimates.
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Penn State Data Commons
创建时间:
2025-11-21
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