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- Author or Editor: James M. Wilczak x
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Abstract
A new method for estimating the mixing depth of the atmosphere's convective boundary layer is developed for use with wind-profiling radars. This method applies “fuzzy logic” methods to give an improved determination of the atmospheric signal in radar spectra. The method then applies fuzzy logic again to calculate the depth of the convective boundary layer, using vertical profiles of both radar-derived signal-to-noise ratio and variance of vertical velocity. A comparison with independent boundary layer depth observations at two radar wind profiler sites shows that the new method gives significantly more accurate estimates of the boundary layer depth (correlation coefficients of 0.91 and 0.96) than does a standard method (correlation coefficients of 0.14 and 0.80). Also, the new method reduces the absolute error of the mixing-depth estimates to a level similar to the vertical range resolution of the profilers.
Abstract
A new method for estimating the mixing depth of the atmosphere's convective boundary layer is developed for use with wind-profiling radars. This method applies “fuzzy logic” methods to give an improved determination of the atmospheric signal in radar spectra. The method then applies fuzzy logic again to calculate the depth of the convective boundary layer, using vertical profiles of both radar-derived signal-to-noise ratio and variance of vertical velocity. A comparison with independent boundary layer depth observations at two radar wind profiler sites shows that the new method gives significantly more accurate estimates of the boundary layer depth (correlation coefficients of 0.91 and 0.96) than does a standard method (correlation coefficients of 0.14 and 0.80). Also, the new method reduces the absolute error of the mixing-depth estimates to a level similar to the vertical range resolution of the profilers.
Abstract
The construction, calibration, and application of a microbarometer that is capable of accurately measuring turbulence pressure fluctuations is described. The microbarometer consists of a quad-disk pressure probe and a highly sensitive high-pass pressure sensor. The accuracy of the instrument is tested by evaluating the budget of streamwise horizontal heat flux in the atmospheric surface layer. In this budget, shear and stratification production balance a pressure covariance term and a small turbulent transport term. The measured pressure covariance term is found to close the heat flux budget to within approximately 15%.
Abstract
The construction, calibration, and application of a microbarometer that is capable of accurately measuring turbulence pressure fluctuations is described. The microbarometer consists of a quad-disk pressure probe and a highly sensitive high-pass pressure sensor. The accuracy of the instrument is tested by evaluating the budget of streamwise horizontal heat flux in the atmospheric surface layer. In this budget, shear and stratification production balance a pressure covariance term and a small turbulent transport term. The measured pressure covariance term is found to close the heat flux budget to within approximately 15%.
Abstract
In this paper a Gabor transform–based algorithm is applied to identify and eliminate intermittent signal contamination in UHF wind profiling radars, such as that produced by migrating birds. The algorithm is applied in the time domain, and so it can be used to improve the accuracy of UHF radar wind profiler data in real time—an essential requirement if these wind profiler data are to be assimilated into operational weather forecast models. The added value of using a moment-level Weber–Wuertz pattern recognition scheme that follows the Gabor transform processing is demonstrated.
Abstract
In this paper a Gabor transform–based algorithm is applied to identify and eliminate intermittent signal contamination in UHF wind profiling radars, such as that produced by migrating birds. The algorithm is applied in the time domain, and so it can be used to improve the accuracy of UHF radar wind profiler data in real time—an essential requirement if these wind profiler data are to be assimilated into operational weather forecast models. The added value of using a moment-level Weber–Wuertz pattern recognition scheme that follows the Gabor transform processing is demonstrated.
Abstract
Dispersion models of the convectively driven atmospheric boundary layer (ABL) often require as input meteorological parameters that are not routinely measured. These parameters usually include the surface fluxes of heat and momentum ρCp
Abstract
Dispersion models of the convectively driven atmospheric boundary layer (ABL) often require as input meteorological parameters that are not routinely measured. These parameters usually include the surface fluxes of heat and momentum ρCp
Abstract
A wind profiler-radio acoustic sounding system at Denver collected hourly wind and virtual-temperature data through the boundary layer in the latter half of 1989. Analyzed monthly averages of 24-h time-height cross sections of the daily measurements show a number of significant features. The growth of the nocturnal temperature inversion is observed, followed by a rapid transition to a deep daytime mixed layer. The progression from a strong diurnal temperature signal in the summer to weak diurnal variability in the winter is documented. A mean upslope wind component is found in the middle-to-late afternoon in the summer and autumn months, with a reverse, return flow aloft. Boundary-layer winds show a strong inertial oscillation, with the phase closely following the diurnal heating cycle. Perturbation winds in the return-flow region aloft oscillate almost 180° out of phase with the boundary-layer winds.
Abstract
A wind profiler-radio acoustic sounding system at Denver collected hourly wind and virtual-temperature data through the boundary layer in the latter half of 1989. Analyzed monthly averages of 24-h time-height cross sections of the daily measurements show a number of significant features. The growth of the nocturnal temperature inversion is observed, followed by a rapid transition to a deep daytime mixed layer. The progression from a strong diurnal temperature signal in the summer to weak diurnal variability in the winter is documented. A mean upslope wind component is found in the middle-to-late afternoon in the summer and autumn months, with a reverse, return flow aloft. Boundary-layer winds show a strong inertial oscillation, with the phase closely following the diurnal heating cycle. Perturbation winds in the return-flow region aloft oscillate almost 180° out of phase with the boundary-layer winds.
Abstract
Uncertainties in the evaluation of the atmospheric heat budget, in which the turbulent heat flux divergence term is calculated as a residual, are investigated for a triangular array of 915-MHz wind profilers—radio acoustic sounding systems (RASS) using a surface-integral method. A scaling analysis of the residual error heat budget equation reveals the basic characteristics and magnitudes of the uncertainties. These values are verified with a Monte Carlo simulation technique for synthetic datasets in which the triangle size is of the order of 30 km (meso-γ scale). The uncertainties depend on measurement errors, atmospheric stability, mean wind speed, triangle size, and averaging time. In addition, we estimate the effects of baroclinity and mean wind divergence on the accuracy of the calculation of the heat budget.
Idealized, barotropic, and divergence-free conditions are studied to investigate the influence of various instrument accuracies on profiles of the turbulent virtual potential temperature flux divergence term. Results show that this term can be computed as a residual of the other terms with an uncertainty that varies from approximately 0.4 to 1.6 K h−1 for typical ranges of mean wind speed and stability, given current accuracies for 1-h averages of wind profiler—RASS. Uncertainties of the remaining terms in the equation are smaller. Although the uncertainties found are of about the same magnitude as typical maximum daytime boundary layer turbulent sensible heat flux divergences, 1.2 K h−1, it is found that under favorable conditions meaningful turbulent heat flux divergences can be obtained. The computations, however, become very uncertain under conditions of strong baroclinity or wind divergence.
Abstract
Uncertainties in the evaluation of the atmospheric heat budget, in which the turbulent heat flux divergence term is calculated as a residual, are investigated for a triangular array of 915-MHz wind profilers—radio acoustic sounding systems (RASS) using a surface-integral method. A scaling analysis of the residual error heat budget equation reveals the basic characteristics and magnitudes of the uncertainties. These values are verified with a Monte Carlo simulation technique for synthetic datasets in which the triangle size is of the order of 30 km (meso-γ scale). The uncertainties depend on measurement errors, atmospheric stability, mean wind speed, triangle size, and averaging time. In addition, we estimate the effects of baroclinity and mean wind divergence on the accuracy of the calculation of the heat budget.
Idealized, barotropic, and divergence-free conditions are studied to investigate the influence of various instrument accuracies on profiles of the turbulent virtual potential temperature flux divergence term. Results show that this term can be computed as a residual of the other terms with an uncertainty that varies from approximately 0.4 to 1.6 K h−1 for typical ranges of mean wind speed and stability, given current accuracies for 1-h averages of wind profiler—RASS. Uncertainties of the remaining terms in the equation are smaller. Although the uncertainties found are of about the same magnitude as typical maximum daytime boundary layer turbulent sensible heat flux divergences, 1.2 K h−1, it is found that under favorable conditions meaningful turbulent heat flux divergences can be obtained. The computations, however, become very uncertain under conditions of strong baroclinity or wind divergence.
Abstract
A previous study showed success in determining the convective boundary layer depth with radar wind-profiling radars using fuzzy logic methods, and improvements to the earlier work are discussed. The improved method uses the Vaisala multipeak picking (MPP) procedure to identify the atmospheric signal in radar spectra in place of a fuzzy logic peak picking procedure that was previously used. The method then applies fuzzy logic techniques to calculate the depth of the convective boundary layer. The planetary boundary layer depth algorithm is improved with respect to the one used in the previous study in that it adds information obtained from the small-scale turbulence (vertical profiles of the spectral width of the vertical velocity), while also still using vertical profiles of the radar-derived refractive index structure parameter C 2 n and the variance of vertical velocity. Modifications to the fuzzy logic rules (especially to those using vertical velocity data) that improve the algorithm’s accuracy in cloudy boundary layers are incorporated. In addition, a reliability threshold value to the fuzzy logic–derived score is applied to eliminate PBL depth data values with low score values. These low score values correspond to periods when the PBL structure does not match the conceptual model of the convective PBL built into the algorithm. Also, as a final step, an optional temporal continuity test on boundary layer depth has been developed that helps improve the algorithm’s skill. A comparison with independent boundary layer depth estimations made “by eye” by meteorologists at two radar wind-profiler sites, significantly different in their characteristics, shows that the new improved method gives significantly more accurate estimates of the boundary layer depth than does the previous method, and also much better estimates than the simpler “standard” method of selecting the peak of C 2 n . The new method produces an absolute error of the mixing-depth estimates comparable to the vertical range resolution of the profilers.
Abstract
A previous study showed success in determining the convective boundary layer depth with radar wind-profiling radars using fuzzy logic methods, and improvements to the earlier work are discussed. The improved method uses the Vaisala multipeak picking (MPP) procedure to identify the atmospheric signal in radar spectra in place of a fuzzy logic peak picking procedure that was previously used. The method then applies fuzzy logic techniques to calculate the depth of the convective boundary layer. The planetary boundary layer depth algorithm is improved with respect to the one used in the previous study in that it adds information obtained from the small-scale turbulence (vertical profiles of the spectral width of the vertical velocity), while also still using vertical profiles of the radar-derived refractive index structure parameter C 2 n and the variance of vertical velocity. Modifications to the fuzzy logic rules (especially to those using vertical velocity data) that improve the algorithm’s accuracy in cloudy boundary layers are incorporated. In addition, a reliability threshold value to the fuzzy logic–derived score is applied to eliminate PBL depth data values with low score values. These low score values correspond to periods when the PBL structure does not match the conceptual model of the convective PBL built into the algorithm. Also, as a final step, an optional temporal continuity test on boundary layer depth has been developed that helps improve the algorithm’s skill. A comparison with independent boundary layer depth estimations made “by eye” by meteorologists at two radar wind-profiler sites, significantly different in their characteristics, shows that the new improved method gives significantly more accurate estimates of the boundary layer depth than does the previous method, and also much better estimates than the simpler “standard” method of selecting the peak of C 2 n . The new method produces an absolute error of the mixing-depth estimates comparable to the vertical range resolution of the profilers.
Abstract
Observations and a numerical model have been used to investigate the structure of an elevated mixed layer (EML) that formed in the lee of the Rocky Mountains over eastern Colorado. The EML formed as a dry convective boundary layer over the higher mountainous terrain of western Colorado, and then advected eastward, producing upper-level warming over the eastern plains. This upper-level warming generated a strong capping inversion at the top of a surface-based plains convective boundary layer that formed concurrently with the EML. A model trajectory analysis indicated that air from the plains boundary layer was detrained into the EML in a zone of convergence along the foothills of the Front Range of the Rocky Mountains.
Specific physical processes responsible for meso-β-scale EML development were examined using a two-dimensional version of the mesoscale numerical model. Blocking of the plateau-level winds by the plains breeze proved to be the primary constraint on advection of the EML and its underlying lid over the adjacent plains. Such blocking was minimized for large-scale conditions that prevented the plains mixed layer from growing to elevations significantly above the plateau surface. Both greater plateau height and increased plains surface moisture availability contribute to keeping the plains boundary layer below the plateau height, and thus favor generation of a meso-β-scale EML and lid.
Abstract
Observations and a numerical model have been used to investigate the structure of an elevated mixed layer (EML) that formed in the lee of the Rocky Mountains over eastern Colorado. The EML formed as a dry convective boundary layer over the higher mountainous terrain of western Colorado, and then advected eastward, producing upper-level warming over the eastern plains. This upper-level warming generated a strong capping inversion at the top of a surface-based plains convective boundary layer that formed concurrently with the EML. A model trajectory analysis indicated that air from the plains boundary layer was detrained into the EML in a zone of convergence along the foothills of the Front Range of the Rocky Mountains.
Specific physical processes responsible for meso-β-scale EML development were examined using a two-dimensional version of the mesoscale numerical model. Blocking of the plateau-level winds by the plains breeze proved to be the primary constraint on advection of the EML and its underlying lid over the adjacent plains. Such blocking was minimized for large-scale conditions that prevented the plains mixed layer from growing to elevations significantly above the plateau surface. Both greater plateau height and increased plains surface moisture availability contribute to keeping the plains boundary layer below the plateau height, and thus favor generation of a meso-β-scale EML and lid.
Abstract
Previous field investigations of the wave-induced pressure field have focused on determination of the momentum input from wind to the surface waves. This is useful for the estimation of wave growth rate and, in particular, the wave growth parameter β. Due to the difficult nature of experimental study of airflow very close to the wave surface, it has been necessary to extrapolate elevated measurements of the wave-induced pressure field to the surface. This practice may be incorrect without adequate knowledge of the complex vertical structure of the pressure field. In addition, the wave-induced pressure and velocity fields are coupled to the near-surface turbulence. Hence, understanding the nature of the wave-induced flow fields is critical for modeling of the near-surface wind and wave fields.
Utilizing a simple similarity hypothesis, detailed vertical structure of the wave-induced pressure and velocity components is examined. Results of this analysis are presented using data obtained in the spring and fall of 1994 during the Risø Air–Sea Experiment program. These results demonstrate that, when compared to theory, simple extrapolation of measurements of the wave-induced pressure field from a fixed height above the surface may contribute to the uncertainty of measured growth rates. In addition, it is demonstrated that an analogous similarity relationship for the wave-induced vertical velocity field yields results that are consistent with previous laboratory studies.
Abstract
Previous field investigations of the wave-induced pressure field have focused on determination of the momentum input from wind to the surface waves. This is useful for the estimation of wave growth rate and, in particular, the wave growth parameter β. Due to the difficult nature of experimental study of airflow very close to the wave surface, it has been necessary to extrapolate elevated measurements of the wave-induced pressure field to the surface. This practice may be incorrect without adequate knowledge of the complex vertical structure of the pressure field. In addition, the wave-induced pressure and velocity fields are coupled to the near-surface turbulence. Hence, understanding the nature of the wave-induced flow fields is critical for modeling of the near-surface wind and wave fields.
Utilizing a simple similarity hypothesis, detailed vertical structure of the wave-induced pressure and velocity components is examined. Results of this analysis are presented using data obtained in the spring and fall of 1994 during the Risø Air–Sea Experiment program. These results demonstrate that, when compared to theory, simple extrapolation of measurements of the wave-induced pressure field from a fixed height above the surface may contribute to the uncertainty of measured growth rates. In addition, it is demonstrated that an analogous similarity relationship for the wave-induced vertical velocity field yields results that are consistent with previous laboratory studies.
Abstract
Persistent cold pools form as layers of cold stagnant air within topographical depressions mainly during wintertime, when the near-surface air cools and/or the air aloft warms and daytime surface heating is insufficient to mix out the stable layer. An area often affected by persistent cold pools is the Columbia River basin in the Pacific Northwest, when a high pressure system east of the Cascade Range promotes radiative cooling and easterly flow. The only major outflow for the easterly flow is through the narrow Columbia River Gorge that cuts through the north–south-oriented Cascade Range and often experiences very strong gap flows. Observations collected during the Second Wind Forecast Improvement Project (WFIP2) are used to study a persistent cold pool in the Columbia River basin between 10 and 19 January 2017 that was associated with a strong gap flow. We used data from various remote sensing and in situ instruments and an optimal estimation physical retrieval to obtain thermodynamic profiles to address the temporal and spatial characteristics of the cold pool and gap flow and to investigate the physical processes involved during formation, maintenance, and decay. While large-scale temperature advection occurred during all phases, we found that the cold-pool vertical structure was modulated by the existence of low-level clouds and that turbulent shear-induced mixing and downslope wind storms likely played a role during its decay.
Abstract
Persistent cold pools form as layers of cold stagnant air within topographical depressions mainly during wintertime, when the near-surface air cools and/or the air aloft warms and daytime surface heating is insufficient to mix out the stable layer. An area often affected by persistent cold pools is the Columbia River basin in the Pacific Northwest, when a high pressure system east of the Cascade Range promotes radiative cooling and easterly flow. The only major outflow for the easterly flow is through the narrow Columbia River Gorge that cuts through the north–south-oriented Cascade Range and often experiences very strong gap flows. Observations collected during the Second Wind Forecast Improvement Project (WFIP2) are used to study a persistent cold pool in the Columbia River basin between 10 and 19 January 2017 that was associated with a strong gap flow. We used data from various remote sensing and in situ instruments and an optimal estimation physical retrieval to obtain thermodynamic profiles to address the temporal and spatial characteristics of the cold pool and gap flow and to investigate the physical processes involved during formation, maintenance, and decay. While large-scale temperature advection occurred during all phases, we found that the cold-pool vertical structure was modulated by the existence of low-level clouds and that turbulent shear-induced mixing and downslope wind storms likely played a role during its decay.
