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- Author or Editor: W. J. Shaw x
- Journal of Atmospheric and Oceanic Technology x
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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.
Abstract
Recent advances in electronics miniaturization have allowed the commercial development of sensor/datalogger combinations that are sufficiently inexpensive and appear to be sufficiently accurate to deploy in measurement arrays to resolve local atmospheric structure over periods of weeks to months. As part of an extended wintertime field experiment in the Columbia Basin of south-central Washington, laboratory and field tests were performed on one such set of battery-powered temperature dataloggers (HOBO H8 Pro from Onset Computer, Bourne, Massachusetts). Five loggers were selected for laboratory calibration. These were accurate to within 0.26°C over the range from −5° to +50°C with a resolution of 0.04°C or better. Sensor time constants were 122 ± 6 s. Sampling intervals can be varied over a wide range, with onboard data storage of more than 21 000 data points. Field experiences with a set of 15 dataloggers are also described. The loggers appear to be suitable for a variety of meteorological applications.
Abstract
Recent advances in electronics miniaturization have allowed the commercial development of sensor/datalogger combinations that are sufficiently inexpensive and appear to be sufficiently accurate to deploy in measurement arrays to resolve local atmospheric structure over periods of weeks to months. As part of an extended wintertime field experiment in the Columbia Basin of south-central Washington, laboratory and field tests were performed on one such set of battery-powered temperature dataloggers (HOBO H8 Pro from Onset Computer, Bourne, Massachusetts). Five loggers were selected for laboratory calibration. These were accurate to within 0.26°C over the range from −5° to +50°C with a resolution of 0.04°C or better. Sensor time constants were 122 ± 6 s. Sampling intervals can be varied over a wide range, with onboard data storage of more than 21 000 data points. Field experiences with a set of 15 dataloggers are also described. The loggers appear to be suitable for a variety of meteorological applications.
Abstract
A method is demonstrated for deriving a correction for the effects of an infrared window when used to weatherproof a radiometrically calibrated thermal infrared imager. The technique relies on initial calibration of two identical imagers without windows and subsequently operating the imagers side by side: one with a window and one without. An equation is presented that expresses the scene radiance in terms of through-window radiance and the transmittance, reflectance, and emissivity of the window. The window’s optical properties are determined as a function of angle over the imager’s field of view through a matrix inversion using images observed simultaneously with and without a window. The technique is applied to calibrated sky images from infrared cloud imager systems. Application of this window correction algorithm to data obtained months before or after the algorithm was derived leads to an improvement from 0.46 to 0.91 for the correlation coefficient between data obtained simultaneously from imagers with and without a window. Once the window correction has been determined, the windowed imager can operate independently and provide accurate measurements of sky radiance.
Abstract
A method is demonstrated for deriving a correction for the effects of an infrared window when used to weatherproof a radiometrically calibrated thermal infrared imager. The technique relies on initial calibration of two identical imagers without windows and subsequently operating the imagers side by side: one with a window and one without. An equation is presented that expresses the scene radiance in terms of through-window radiance and the transmittance, reflectance, and emissivity of the window. The window’s optical properties are determined as a function of angle over the imager’s field of view through a matrix inversion using images observed simultaneously with and without a window. The technique is applied to calibrated sky images from infrared cloud imager systems. Application of this window correction algorithm to data obtained months before or after the algorithm was derived leads to an improvement from 0.46 to 0.91 for the correlation coefficient between data obtained simultaneously from imagers with and without a window. Once the window correction has been determined, the windowed imager can operate independently and provide accurate measurements of sky radiance.
