Search Results
Abstract
Velocities produced by energetic waves can contaminate direct covariance estimates of near-bottom turbulent shear stress and turbulent heat flux. A new adaptive filtering technique is introduced to minimize the contribution of wave-induced motions to measured covariances. The technique requires the use of two sensors separated in space and assumes that the spatial coherence scale of the waves is much longer than the spatial coherence scale of the turbulence. The proposed technique is applied to an extensive set of data collected in the bottom boundary layer of the New England shelf. Results from the oceanic test demonstrate that the technique succeeds at removing surface-wave contamination from shear stress and heat flux estimates using pairs of sensors separated in the vertical dimension by a distance of approximately 5 times the height of the lower sensor, even during the close passage of hurricanes. However, the technique fails at removing contamination caused by internal motions that occur occasionally in the dataset. The internal case is complicated by the facts that the motions are highly intermittent; the internal-wave period is comparable to the Reynolds-averaging period; the height of the internal-wave boundary layer is on the order of the height of measurement; and, specifically for heat flux estimates, nonlinear effects are large. The presence of internal motions does not pose a significant problem for estimating turbulent shear stress, because contamination caused by them is limited to frequencies lower than those of the stress-carrying eddies. In contrast, the presence of internal motions does pose a problem for estimating turbulent heat flux, because the contamination extends into the range of the heat flux–carrying eddies.
Abstract
Velocities produced by energetic waves can contaminate direct covariance estimates of near-bottom turbulent shear stress and turbulent heat flux. A new adaptive filtering technique is introduced to minimize the contribution of wave-induced motions to measured covariances. The technique requires the use of two sensors separated in space and assumes that the spatial coherence scale of the waves is much longer than the spatial coherence scale of the turbulence. The proposed technique is applied to an extensive set of data collected in the bottom boundary layer of the New England shelf. Results from the oceanic test demonstrate that the technique succeeds at removing surface-wave contamination from shear stress and heat flux estimates using pairs of sensors separated in the vertical dimension by a distance of approximately 5 times the height of the lower sensor, even during the close passage of hurricanes. However, the technique fails at removing contamination caused by internal motions that occur occasionally in the dataset. The internal case is complicated by the facts that the motions are highly intermittent; the internal-wave period is comparable to the Reynolds-averaging period; the height of the internal-wave boundary layer is on the order of the height of measurement; and, specifically for heat flux estimates, nonlinear effects are large. The presence of internal motions does not pose a significant problem for estimating turbulent shear stress, because contamination caused by them is limited to frequencies lower than those of the stress-carrying eddies. In contrast, the presence of internal motions does pose a problem for estimating turbulent heat flux, because the contamination extends into the range of the heat flux–carrying eddies.
