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- Author or Editor: Kevin Knupp x
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Abstract
The early-evening boundary layer transition has been defined in the past using a variety of criteria, the most popular of which is the onset of a negative surface heat flux. According to this definition, the transition is an almost-instantaneous event that occurs when the positive daytime heat flux switches to the negative nighttime heat flux. This definition is simplistic, however, because the stable boundary layer does not form instantaneously over a deep layer. Other factors are involved, and many changes occur aloft during the transition period that this definition does not account for—for example, a more gradual reduction in turbulence and an increase in wind speed. The combined use of sodar data, as well as 915-MHz wind profiler, surface temperature, dewpoint, and wind data, provides a more-comprehensive definition of the early-evening boundary layer transition. Sodar backscatter is sensitive to temperature fluctuations, and therefore as the heat flux decreases, the sodar return power exhibits changes from a time-varying convective structure to a more-stratified and steady structure. A relative minimum in intensity and height of the sodar backscatter is one indication that the transition is occurring. As the boundary layer evolves from the unstable convective afternoon conditions to the more stable nocturnal conditions, the finescale temporal variations in many parameters, including temperature, the 10–2-m temperature difference, dewpoint, and wind speed, decrease. There is often a distinct steplike shape in the temperature/wind decrease or dewpoint increase within 30 min of the sodar minimum. In this paper, an analysis of sodar and surface data is presented for low-wind cases to demonstrate the efficacy of this combined sensor technique, and to illustrate the average physical characteristics of the transition period for 21 cases during the summer months (June–August) and 9 cases during the autumn months (November–December) in Huntsville, Alabama.
Abstract
The early-evening boundary layer transition has been defined in the past using a variety of criteria, the most popular of which is the onset of a negative surface heat flux. According to this definition, the transition is an almost-instantaneous event that occurs when the positive daytime heat flux switches to the negative nighttime heat flux. This definition is simplistic, however, because the stable boundary layer does not form instantaneously over a deep layer. Other factors are involved, and many changes occur aloft during the transition period that this definition does not account for—for example, a more gradual reduction in turbulence and an increase in wind speed. The combined use of sodar data, as well as 915-MHz wind profiler, surface temperature, dewpoint, and wind data, provides a more-comprehensive definition of the early-evening boundary layer transition. Sodar backscatter is sensitive to temperature fluctuations, and therefore as the heat flux decreases, the sodar return power exhibits changes from a time-varying convective structure to a more-stratified and steady structure. A relative minimum in intensity and height of the sodar backscatter is one indication that the transition is occurring. As the boundary layer evolves from the unstable convective afternoon conditions to the more stable nocturnal conditions, the finescale temporal variations in many parameters, including temperature, the 10–2-m temperature difference, dewpoint, and wind speed, decrease. There is often a distinct steplike shape in the temperature/wind decrease or dewpoint increase within 30 min of the sodar minimum. In this paper, an analysis of sodar and surface data is presented for low-wind cases to demonstrate the efficacy of this combined sensor technique, and to illustrate the average physical characteristics of the transition period for 21 cases during the summer months (June–August) and 9 cases during the autumn months (November–December) in Huntsville, Alabama.
Abstract
At the present time the only generally accepted method for detecting when a tornado is on the ground is human observation. Based on theoretical considerations combined with eyewitness testimony, there is strong reason to believe that a tornado in contact with the ground transfers a significant amount of energy into the ground. The amount of energy transferred depends upon the intensity of the tornado and the characteristics of the surface. Some portion of this energy takes the form of seismic waves, both body and surface waves. Surface waves (Rayleigh and possibly Love) represent the most likely type of seismic signal to be detected. Based on the existence of such a signal, a seismic tornado detector appears conceptually possible. The major concerns for designing such a detector are range of detection and discrimination between the tornadic signal and other types of surface waves generated by ground transportation equipment, high winds, or other nontornadic sources.
Abstract
At the present time the only generally accepted method for detecting when a tornado is on the ground is human observation. Based on theoretical considerations combined with eyewitness testimony, there is strong reason to believe that a tornado in contact with the ground transfers a significant amount of energy into the ground. The amount of energy transferred depends upon the intensity of the tornado and the characteristics of the surface. Some portion of this energy takes the form of seismic waves, both body and surface waves. Surface waves (Rayleigh and possibly Love) represent the most likely type of seismic signal to be detected. Based on the existence of such a signal, a seismic tornado detector appears conceptually possible. The major concerns for designing such a detector are range of detection and discrimination between the tornadic signal and other types of surface waves generated by ground transportation equipment, high winds, or other nontornadic sources.
Abstract
Theoretical plume growth rates depend upon the atmospheric spatial energy spectrum. Current grid-based numerical models generally resolve large-scale (synoptic) energy, while planetary boundary layer turbulence is parameterized. Energy at intermediate scales is often neglected. In this study, boundary layer radar profilers are used to examine the temporal energy spectrum, which can provide information about the atmospheric structure affecting plume growth rates. A boundary layer model (BLM) into which the radar information has been assimilated is used to drive a Lagrangian particle model (LPM) that is subsequently employed to examine plume growth rates. Profiler and aircraft data taken during the 1995 Southern Oxidants Study in Nashville, Tennessee, are used in the model study for assimilation and evaluation. The results show that the BLM without assimilation significantly underestimates the strength of the diurnal–inertial spectral peak, which in turn causes an underestimate of plume spread. Comparison with measures of plume width from aircraft data also shows that assimilation of radar information greatly improves plume spread rates predicted by the LPM.
Abstract
Theoretical plume growth rates depend upon the atmospheric spatial energy spectrum. Current grid-based numerical models generally resolve large-scale (synoptic) energy, while planetary boundary layer turbulence is parameterized. Energy at intermediate scales is often neglected. In this study, boundary layer radar profilers are used to examine the temporal energy spectrum, which can provide information about the atmospheric structure affecting plume growth rates. A boundary layer model (BLM) into which the radar information has been assimilated is used to drive a Lagrangian particle model (LPM) that is subsequently employed to examine plume growth rates. Profiler and aircraft data taken during the 1995 Southern Oxidants Study in Nashville, Tennessee, are used in the model study for assimilation and evaluation. The results show that the BLM without assimilation significantly underestimates the strength of the diurnal–inertial spectral peak, which in turn causes an underestimate of plume spread. Comparison with measures of plume width from aircraft data also shows that assimilation of radar information greatly improves plume spread rates predicted by the LPM.
Abstract
The University of Alabama in Huntsville Mobile Integrated Profiling System 915-MHz profiler was deployed in January and February of 2004 to measure vertical air velocities in finescale precipitation bands in winter cyclones. The profiler was placed to sample the “wraparound” quadrant of three winter cyclones in the central and southern United States, and it obtained high-resolution measurements of the vertical structure of a series of bands in each storm. The data revealed bands that were up to 6 km deep, 10–50 km wide, and spaced about 5–20 km apart. Measurements of vertical air motion w within these bands were retrieved from the Doppler spectra using the lower-bound method, adapted to account for the effects of spectral broadening caused by the horizontal wind, wind shear, and turbulence. Derived vertical air motions ranged from −4.3 to 6.7 m s−1, with an uncertainty of about ±0.6 m s−1. Approximately 29% of the 1515 total derived values were negative, 35% exceeded 1 m s−1, and 9% exceeded 2.0 m s−1. These values are consistent with studies in the Pacific Northwest, except that more extreme values were observed in one band than have been previously reported. There was a high correlation between values of signal-to-noise ratio (SNR) and w within each band (0.60 ≤ r ≤ 0.85), in the composite of bands from each cyclone (0.59 ≤ r ≤ 0.79), and in the overall analysis (r = 0.68). The strongest updrafts were typically between 2.0 and 4.0 m s−1 and were located near the center of each band in regions of high SNR. Regions of downdrafts within the bands had maximum values between −1.0 and −4.3 m s−1 and were typically located along the edges of the bands in regions of low SNR. These results are consistent with snow growth and sublimation processes. The magnitudes of the vertical velocities in the core of the bands were comparable to theoretical predictions for moist symmetric instability (MSI) under inviscid conditions but would appear to be somewhat larger than expected for MSI when turbulent mixing is considered, suggesting that other instabilities, such as potential instability, may have contributed to the band development in these storms.
Abstract
The University of Alabama in Huntsville Mobile Integrated Profiling System 915-MHz profiler was deployed in January and February of 2004 to measure vertical air velocities in finescale precipitation bands in winter cyclones. The profiler was placed to sample the “wraparound” quadrant of three winter cyclones in the central and southern United States, and it obtained high-resolution measurements of the vertical structure of a series of bands in each storm. The data revealed bands that were up to 6 km deep, 10–50 km wide, and spaced about 5–20 km apart. Measurements of vertical air motion w within these bands were retrieved from the Doppler spectra using the lower-bound method, adapted to account for the effects of spectral broadening caused by the horizontal wind, wind shear, and turbulence. Derived vertical air motions ranged from −4.3 to 6.7 m s−1, with an uncertainty of about ±0.6 m s−1. Approximately 29% of the 1515 total derived values were negative, 35% exceeded 1 m s−1, and 9% exceeded 2.0 m s−1. These values are consistent with studies in the Pacific Northwest, except that more extreme values were observed in one band than have been previously reported. There was a high correlation between values of signal-to-noise ratio (SNR) and w within each band (0.60 ≤ r ≤ 0.85), in the composite of bands from each cyclone (0.59 ≤ r ≤ 0.79), and in the overall analysis (r = 0.68). The strongest updrafts were typically between 2.0 and 4.0 m s−1 and were located near the center of each band in regions of high SNR. Regions of downdrafts within the bands had maximum values between −1.0 and −4.3 m s−1 and were typically located along the edges of the bands in regions of low SNR. These results are consistent with snow growth and sublimation processes. The magnitudes of the vertical velocities in the core of the bands were comparable to theoretical predictions for moist symmetric instability (MSI) under inviscid conditions but would appear to be somewhat larger than expected for MSI when turbulent mixing is considered, suggesting that other instabilities, such as potential instability, may have contributed to the band development in these storms.
Abstract
Since the advent of dual-polarization radar, methods of classifying hydrometeors by type from measured polarization variables have been developed. The deterministic approach of existing hydrometeor classification algorithms of assigning only one dominant habit to each radar sample volume does not properly consider the distribution of habits present in that volume, however. During the Profiling of Winter Storms field campaign, the “NSF/NCAR C-130” aircraft, equipped with in situ microphysical probes, made multiple passes through the comma heads of two cyclones as the Mobile Alabama X-band dual-polarization radar performed range–height indicator scans in the same plane as the C-130 flight track. On 14–15 February and 21–22 February 2010, 579 and 202 coincident data points, respectively, were identified when the plane was within 10 s (~1 km) of a radar gate. For all particles that occurred for times within different binned intervals of radar reflectivity Z HH and of differential reflectivity Z DR, the reflectivity-weighted contribution of each habit and the frequency distributions of axis ratio and sphericity were determined. This permitted the determination of habits that dominate particular Z HH and Z DR intervals; only 40% of the Z HH–Z DR bins were found to have a habit that contributes over 50% to the reflectivity in that bin. Of these bins, only 12% had a habit that contributes over 75% to the reflectivity. These findings show the general lack of dominance of a given habit for a particular Z HH and Z DR and suggest that determining the probability of specific habits in radar volumes may be more suitable than the deterministic methods currently used.
Abstract
Since the advent of dual-polarization radar, methods of classifying hydrometeors by type from measured polarization variables have been developed. The deterministic approach of existing hydrometeor classification algorithms of assigning only one dominant habit to each radar sample volume does not properly consider the distribution of habits present in that volume, however. During the Profiling of Winter Storms field campaign, the “NSF/NCAR C-130” aircraft, equipped with in situ microphysical probes, made multiple passes through the comma heads of two cyclones as the Mobile Alabama X-band dual-polarization radar performed range–height indicator scans in the same plane as the C-130 flight track. On 14–15 February and 21–22 February 2010, 579 and 202 coincident data points, respectively, were identified when the plane was within 10 s (~1 km) of a radar gate. For all particles that occurred for times within different binned intervals of radar reflectivity Z HH and of differential reflectivity Z DR, the reflectivity-weighted contribution of each habit and the frequency distributions of axis ratio and sphericity were determined. This permitted the determination of habits that dominate particular Z HH and Z DR intervals; only 40% of the Z HH–Z DR bins were found to have a habit that contributes over 50% to the reflectivity in that bin. Of these bins, only 12% had a habit that contributes over 75% to the reflectivity. These findings show the general lack of dominance of a given habit for a particular Z HH and Z DR and suggest that determining the probability of specific habits in radar volumes may be more suitable than the deterministic methods currently used.
Abstract
An airborne microwave temperature profiler (MTP) was deployed during the Texas 2000 Air Quality Study (TexAQS-2000) to make measurements of boundary layer thermal structure. An objective technique was developed and tested for estimating the mixed layer (ML) height from the MTP vertical temperature profiles. The technique identifies the ML height as a threshold increase of potential temperature from its minimum value within the boundary layer. To calibrate the technique and evaluate the usefulness of this approach, coincident estimates from radiosondes, radar wind profilers, an aerosol backscatter lidar, and in situ aircraft measurements were compared with each other and with the MTP. Relative biases among all instruments were generally less than 50 m, and the agreement between MTP ML height estimates and other estimates was at least as good as the agreement among the other estimates. The ML height estimates from the MTP and other instruments are utilized to determine the spatial and temporal evolution of ML height in the Houston, Texas, area on 1 September 2000. An elevated temperature inversion was present, so ML growth was inhibited until early afternoon. In the afternoon, large spatial variations in ML height developed across the Houston area. The highest ML heights, well over 2 km, were observed to the north of Houston, while downwind of Galveston Bay and within the late afternoon sea breeze ML heights were much lower. The spatial variations that were found away from the immediate influence of coastal circulations were unexpected, and multiple independent ML height estimates were essential for documenting this feature.
Abstract
An airborne microwave temperature profiler (MTP) was deployed during the Texas 2000 Air Quality Study (TexAQS-2000) to make measurements of boundary layer thermal structure. An objective technique was developed and tested for estimating the mixed layer (ML) height from the MTP vertical temperature profiles. The technique identifies the ML height as a threshold increase of potential temperature from its minimum value within the boundary layer. To calibrate the technique and evaluate the usefulness of this approach, coincident estimates from radiosondes, radar wind profilers, an aerosol backscatter lidar, and in situ aircraft measurements were compared with each other and with the MTP. Relative biases among all instruments were generally less than 50 m, and the agreement between MTP ML height estimates and other estimates was at least as good as the agreement among the other estimates. The ML height estimates from the MTP and other instruments are utilized to determine the spatial and temporal evolution of ML height in the Houston, Texas, area on 1 September 2000. An elevated temperature inversion was present, so ML growth was inhibited until early afternoon. In the afternoon, large spatial variations in ML height developed across the Houston area. The highest ML heights, well over 2 km, were observed to the north of Houston, while downwind of Galveston Bay and within the late afternoon sea breeze ML heights were much lower. The spatial variations that were found away from the immediate influence of coastal circulations were unexpected, and multiple independent ML height estimates were essential for documenting this feature.
