Estimating aerodynamic roughness over complex surface terrain
Estimating aerodynamic roughness over complex surface terrain
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DOI：
10.1002/2013jd020632
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发表时间：
2013-12
期刊：
影响因子：
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通讯作者：
J. Nield;J. King;G. Wiggs;J. Leyland;Dr Robert Bryant;R. Chiverrell;S. Darby;F. Eckardt;D. Thomas;L. H. Vircavs;R. Washington
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文献类型：
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作者：
J. Nield;J. King;G. Wiggs;J. Leyland;Dr Robert Bryant;R. Chiverrell;S. Darby;F. Eckardt;D. Thomas;L. H. Vircavs;R. Washington
表面粗糙度在确定空气动力学粗糙度长度 (zo) 和剪切速度方面起着关键作用，这两者对于确定风蚀阈值和潜力至关重要。虽然 zo 可以通过风测量来量化，但大部分容易遭受风蚀的表面仍然太遥远，这不是一种可行的方法。因此，替代方法寻求将 zo 与形态粗糙度度量联系起来。然而，扬尘景观通常由复杂的小规模表面粗糙度图案组成，并且这些表面几乎不存在可用于预测 zo 来模拟风蚀潜力的指标。在本研究中，地面激光扫描用于表征典型扬尘表面（普拉亚和桑德尔）的粗糙度，其中元件突出高度范围为 1 至 199 毫米，收集垂直风速剖面以估算 zo。我们的数据表明，虽然 3-D 粗糙度密度和 zo 之间存在明显的合理关系（R2 > 0.79），但形态元素的间距在解释 zo 变化方面远不如基于表面粗糙度高度的度量（R2 > 0.92）那么有力。这一发现与风蚀模型并列，风蚀模型假设较大规模的孤立粗糙度元素的间距对于确定 zo 最重要。相反，我们的数据表明，任何基于元素突出高度的度量都有更高的可能性成功预测 zo。这一发现对于风蚀和粉尘排放模型的开发具有重要意义，这些模型旨在预测偏远陆地和行星环境中风成过程的效率。
Surface roughness plays a key role in determining aerodynamic roughness length (zo) and shear velocity, both of which are fundamental for determining wind erosion threshold and potential. While zo can be quantified from wind measurements, large proportions of wind erosion prone surfaces remain too remote for this to be a viable approach. Alternative approaches therefore seek to relate zo to morphological roughness metrics. However, dust‐emitting landscapes typically consist of complex small‐scale surface roughness patterns and few metrics exist for these surfaces which can be used to predict zo for modeling wind erosion potential. In this study terrestrial laser scanning was used to characterize the roughness of typical dust‐emitting surfaces (playa and sandar) where element protrusion heights ranged from 1 to 199 mm, over which vertical wind velocity profiles were collected to enable estimation of zo. Our data suggest that, although a reasonable relationship (R2 > 0.79) is apparent between 3‐D roughness density and zo, the spacing of morphological elements is far less powerful in explaining variations in zo than metrics based on surface roughness height (R2 > 0.92). This finding is in juxtaposition to wind erosion models that assume the spacing of larger‐scale isolated roughness elements is most important in determining zo. Rather, our data show that any metric based on element protrusion height has a higher likelihood of successfully predicting zo. This finding has important implications for the development of wind erosion and dust emission models that seek to predict the efficiency of aeolian processes in remote terrestrial and planetary environments.