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Estimating aerodynamic roughness over complex surface terrain
Author(s) -
Nield Joanna M.,
King James,
Wiggs Giles F. S.,
Leyland Julian,
Bryant Robert G.,
Chiverrell Richard C.,
Darby Stephen E.,
Eckardt Frank D.,
Thomas David S. G.,
Vircavs Larisa H.,
Washington Richard
Publication year - 2013
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2013jd020632
Subject(s) - roughness length , surface roughness , surface finish , terrain , erosion , wind speed , aerodynamics , wind tunnel , aeolian processes , geometry , meteorology , materials science , geology , wind profile power law , mechanics , geomorphology , physics , geography , mathematics , composite material , cartography
Surface roughness plays a key role in determining aerodynamic roughness length ( z o ) and shear velocity, both of which are fundamental for determining wind erosion threshold and potential. While z o 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 z o 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 z o 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 z o . Our data suggest that, although a reasonable relationship ( R 2  > 0.79) is apparent between 3‐D roughness density and z o , the spacing of morphological elements is far less powerful in explaining variations in z o than metrics based on surface roughness height ( R 2  > 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 z o . Rather, our data show that any metric based on element protrusion height has a higher likelihood of successfully predicting z o . 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.

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