Friction-Velocity Estimates Using the Trace of a Scalar and the Mean Wind Speed
Document Type
Article - Abstract Only
Publication Date
4-20-2020
Keywords
Friction-velocity estimates, surface-renewal theory, wind logarithmic law
Abstract
A semi-empirical approach based on surface-renewal theory for estimating the friction velocity is tested for measurements taken in the inertial sublayer. For unstable cases, the input requirements are the mean wind speed and the high-frequency trace (10 or 20 Hz) of the air or sonic temperature. The method has been extended to traces of water vapour (H2O) and carbon dioxide (CO2) concentrations. For stable cases, the stability parameter must also be considered. The method’s performance, taking the direct friction velocity measured by sonic anemometry as a reference, was tested over a growing cotton field that included bare soil with some crop residues at the beginning of the season. In general, the proposed friction-velocity estimates are reliable. For unstable cases, the method shows the potential to outperform the wind logarithmic-law computation. Discarding cases with low wind speeds (e.g., < 0.3 m s−1 and mean wind shear < 1 Hz), the proposed approach may be recommended as an alternative method to estimating the friction velocity. There is the potential, based on the input requirements, that the proposed formulation may offer significant advantages in the estimation of the friction velocity in some marine environments.
Citation
Castellvi, F., Suvocarev, K., Reba, M. L., & Runkle, B. R. (2020). Friction-Velocity Estimates Using the Trace of a Scalar and the Mean Wind Speed. Boundary-Layer Meterology, 176, 105-123. https://doi.org/10.1007/s10546-020-00520-1
Comments
Data collection and analysis was partially funded through the US Geological Survey (USGS) under Cooperative Agreements G11AP20066 and G16AP00040 administered by the Arkansas Water Resources Center at the University of Arkansas; the US Department of Agriculture, Natural Resources Conservation Service under Cooperative Agreement 68-7103-17-119, and the National Science Foundation (NSF) under Award 1752083. This work was supported under projects CGL2015-65627-C3-1-R from the Spanish State Research Agency (Agencia Estatal de Investigación; AEI) and European Regional Development Fund (Fondo Europeo de Desarrollo Regional; FEDER) of the European Union/Unión Europea (AEI/FEDER, UE) and RTI2018-098693-B-C31 from the Ministry of Economy and Competitiveness (Ministerio de Economía y Competitividad) of Spain.