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Abstract
Principal component analysis (PCA) is applied to wind profiler observations to study the vertical profile of the wind field and its temporal evolution. The rationale for decomposing time–height wind profiler data using PCA is twofold. The orthogonal vertical profile vectors are determined empirically from the variance of the observations, and the time evolutions of these vectors are not simple sinusoids, but are temporal varying signals that can be directly related to other measurements. As an example of its utility, PCA is used to compare the annual and interannual variation of zonal wind measured with a 50-MHz VHF wind profiler above Christmas Island, Kiribati, with the difference between surface pressures measured at Tahiti, French Polynesia, and Darwin, Australia. The high correlation coefficients relate the vertical profile of zonal wind observed in the central Pacific with the variation of convection in the western Pacific. Complex PCA (C-PCA) allows the analysis of data consisting of amplitude and phase information. It can describe the phase progression of oscillations embedded within the data. The C-PCA is applied to VHF wind profiler observations to study the seasonal behavior of the diurnal meridional wind observed above Biak, Indonesia, and the oscillatory structures of the vertical wind during a convective precipitation event observed above Darwin.
Abstract
Principal component analysis (PCA) is applied to wind profiler observations to study the vertical profile of the wind field and its temporal evolution. The rationale for decomposing time–height wind profiler data using PCA is twofold. The orthogonal vertical profile vectors are determined empirically from the variance of the observations, and the time evolutions of these vectors are not simple sinusoids, but are temporal varying signals that can be directly related to other measurements. As an example of its utility, PCA is used to compare the annual and interannual variation of zonal wind measured with a 50-MHz VHF wind profiler above Christmas Island, Kiribati, with the difference between surface pressures measured at Tahiti, French Polynesia, and Darwin, Australia. The high correlation coefficients relate the vertical profile of zonal wind observed in the central Pacific with the variation of convection in the western Pacific. Complex PCA (C-PCA) allows the analysis of data consisting of amplitude and phase information. It can describe the phase progression of oscillations embedded within the data. The C-PCA is applied to VHF wind profiler observations to study the seasonal behavior of the diurnal meridional wind observed above Biak, Indonesia, and the oscillatory structures of the vertical wind during a convective precipitation event observed above Darwin.
Reflectivity and Liquid Water Content Vertical Decomposition Diagrams to Diagnose Vertical Evolution of Raindrop Size DistributionsAbstract
This study consists of two parts. The first part describes the way in which vertical air motions and raindrop size distributions (DSDs) were retrieved from 449-MHz and 2.835-GHz (UHF and S band) vertically pointing radars (VPRs) deployed side by side during the Midlatitude Continental Convective Clouds Experiment (MC3E) held in northern Oklahoma. The 449-MHz VPR can measure both vertical air motion and raindrop motion. The S-band VPR can measure only raindrop motion. These differences in VPR sensitivities facilitates the identification of two peaks in 449-MHz VPR reflectivity-weighted Doppler velocity spectra and the retrieval of vertical air motion and DSD parameters from near the surface to just below the melting layer.
The second part of this study used the retrieved DSD parameters to decompose reflectivity and liquid water content (LWC) into two terms, one representing number concentration and the other representing DSD shape. Reflectivity and LWC vertical decomposition diagrams (Z-VDDs and LWC-VDDs, respectively) are introduced to highlight interactions between raindrop number and DSD shape in the vertical column. Analysis of Z-VDDs provides indirect measure of microphysical processes through radar reflectivity. Analysis of LWC-VDDs provides direct investigation of microphysical processes in the vertical column, including net raindrop evaporation or accretion and net raindrop breakup or coalescence. During a stratiform rain event (20 May 2011), LWC-VDDs exhibited signatures of net evaporation and net raindrop coalescence as the raindrops fell a distance of 2 km under a well-defined radar bright band. The LWC-VDD is a tool to characterize rain microphysics with quantities related to number-controlled and size-controlled processes.
Abstract
This study consists of two parts. The first part describes the way in which vertical air motions and raindrop size distributions (DSDs) were retrieved from 449-MHz and 2.835-GHz (UHF and S band) vertically pointing radars (VPRs) deployed side by side during the Midlatitude Continental Convective Clouds Experiment (MC3E) held in northern Oklahoma. The 449-MHz VPR can measure both vertical air motion and raindrop motion. The S-band VPR can measure only raindrop motion. These differences in VPR sensitivities facilitates the identification of two peaks in 449-MHz VPR reflectivity-weighted Doppler velocity spectra and the retrieval of vertical air motion and DSD parameters from near the surface to just below the melting layer.
The second part of this study used the retrieved DSD parameters to decompose reflectivity and liquid water content (LWC) into two terms, one representing number concentration and the other representing DSD shape. Reflectivity and LWC vertical decomposition diagrams (Z-VDDs and LWC-VDDs, respectively) are introduced to highlight interactions between raindrop number and DSD shape in the vertical column. Analysis of Z-VDDs provides indirect measure of microphysical processes through radar reflectivity. Analysis of LWC-VDDs provides direct investigation of microphysical processes in the vertical column, including net raindrop evaporation or accretion and net raindrop breakup or coalescence. During a stratiform rain event (20 May 2011), LWC-VDDs exhibited signatures of net evaporation and net raindrop coalescence as the raindrops fell a distance of 2 km under a well-defined radar bright band. The LWC-VDD is a tool to characterize rain microphysics with quantities related to number-controlled and size-controlled processes.
Abstract
The 50-MHz profiler operating near Darwin, Northwest Territory, Australia, is sensitive to both turbulent clear-air (Bragg) and hydrometeor (Rayleigh) scattering processes. Below the radar bright band, the two scattering peaks are observed as two well-separated peaks in the Doppler velocity spectra. The Bragg scattering peak corresponds to the vertical air motion and the Rayleigh scattering peak corresponds to the hydrometeor motion. Within the radar bright band, the Rayleigh scattering peak intensity increases and the downward velocity decreases causing the hydrometeor peak to overlap or merge with the air motion peak. If the overlap of the two peaks is not taken into account, then the vertical air motion estimate will be biased downward. This study describes a filtering procedure that identifies and removes the downward bias in vertical air motions caused by hydrometeor contamination. This procedure uses a second collocated profiler sensitive to hydrometeor motion to identify contamination in the 50-MHz profiler spectra. When applied to four rain events during the Tropical Warm Pool-International Cloud Experiment (TPW-ICE), this dual-frequency filtering method showed that approximately 50% of the single-frequency method vertical air motion estimates within the radar bright band were biased downward due to hydrometeor contamination.
Abstract
The 50-MHz profiler operating near Darwin, Northwest Territory, Australia, is sensitive to both turbulent clear-air (Bragg) and hydrometeor (Rayleigh) scattering processes. Below the radar bright band, the two scattering peaks are observed as two well-separated peaks in the Doppler velocity spectra. The Bragg scattering peak corresponds to the vertical air motion and the Rayleigh scattering peak corresponds to the hydrometeor motion. Within the radar bright band, the Rayleigh scattering peak intensity increases and the downward velocity decreases causing the hydrometeor peak to overlap or merge with the air motion peak. If the overlap of the two peaks is not taken into account, then the vertical air motion estimate will be biased downward. This study describes a filtering procedure that identifies and removes the downward bias in vertical air motions caused by hydrometeor contamination. This procedure uses a second collocated profiler sensitive to hydrometeor motion to identify contamination in the 50-MHz profiler spectra. When applied to four rain events during the Tropical Warm Pool-International Cloud Experiment (TPW-ICE), this dual-frequency filtering method showed that approximately 50% of the single-frequency method vertical air motion estimates within the radar bright band were biased downward due to hydrometeor contamination.
Abstract
Polarimetric weather radars offer the promise of accurate rainfall measurements by including polarimetric measurements in rainfall estimation algorithms. Questions still remain on how accurately polarimetric measurements represent the parameters of the raindrop size distribution (DSD). In particular, this study propagates polarimetric radar measurement uncertainties through a power-law median raindrop diameter D 0 algorithm to quantify the statistical uncertainties of the power-law regression. For this study, the power-law statistical uncertainty of D 0 ranged from 0.11 to 0.17 mm. Also, the polarimetric scanning radar D 0 estimates were compared with the median raindrop diameters retrieved from two vertically pointing profilers observing the same radar volume as the scanning radar. Based on over 900 observations, the standard deviation of the differences between the two radar estimates was approximately 0.16 mm. Thus, propagating polarimetric measurement uncertainties through D 0 power-law regressions is comparable to uncertainties between polarimeteric and profiler D 0 estimates.
Abstract
Polarimetric weather radars offer the promise of accurate rainfall measurements by including polarimetric measurements in rainfall estimation algorithms. Questions still remain on how accurately polarimetric measurements represent the parameters of the raindrop size distribution (DSD). In particular, this study propagates polarimetric radar measurement uncertainties through a power-law median raindrop diameter D 0 algorithm to quantify the statistical uncertainties of the power-law regression. For this study, the power-law statistical uncertainty of D 0 ranged from 0.11 to 0.17 mm. Also, the polarimetric scanning radar D 0 estimates were compared with the median raindrop diameters retrieved from two vertically pointing profilers observing the same radar volume as the scanning radar. Based on over 900 observations, the standard deviation of the differences between the two radar estimates was approximately 0.16 mm. Thus, propagating polarimetric measurement uncertainties through D 0 power-law regressions is comparable to uncertainties between polarimeteric and profiler D 0 estimates.
Rain Drop Size Distributions Estimated from NOAA Snow-Level Radar DataAbstract
Using NOAA’s S-band High-Power Snow-Level Radar (HPSLR), a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter Dm from the measured reflectivity Z produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. This estimation technique was applied to 19 h of observations from Hankins, North Carolina. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.
Abstract
Using NOAA’s S-band High-Power Snow-Level Radar (HPSLR), a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter Dm from the measured reflectivity Z produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. This estimation technique was applied to 19 h of observations from Hankins, North Carolina. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.
Abstract
An algorithm has been developed that classifies precipitating clouds into either stratiform, mixed stratiform/convective, deep convective, or shallow convective clouds by analyzing the vertical structure of reflectivity, velocity, and spectral width derived from measurements made with the vertical beam of a 915-MHz Doppler wind profiler. The precipitating clouds classified as stratiform and convective clouds match the physical and radar properties deduced by Doppler weather radars in the GATE and EMEX programs. The mixed stratiform/convective cloud category is a hybrid regime containing a melting-layer signature associated with stratiform clouds yet is turbulent above the melting level similar to convective clouds. Shallow convective clouds have hydrometeors confined entirely below the melting level implying that warm rain processes are occurring exclusively. The algorithm is illustrated by classifying precipitating clouds from 10 months of observations at Manus Island (2°S, 147°E) in the western Pacific. The sensitivity of the algorithm to threshold criteria is investigated using the Manus Island data.
Abstract
An algorithm has been developed that classifies precipitating clouds into either stratiform, mixed stratiform/convective, deep convective, or shallow convective clouds by analyzing the vertical structure of reflectivity, velocity, and spectral width derived from measurements made with the vertical beam of a 915-MHz Doppler wind profiler. The precipitating clouds classified as stratiform and convective clouds match the physical and radar properties deduced by Doppler weather radars in the GATE and EMEX programs. The mixed stratiform/convective cloud category is a hybrid regime containing a melting-layer signature associated with stratiform clouds yet is turbulent above the melting level similar to convective clouds. Shallow convective clouds have hydrometeors confined entirely below the melting level implying that warm rain processes are occurring exclusively. The algorithm is illustrated by classifying precipitating clouds from 10 months of observations at Manus Island (2°S, 147°E) in the western Pacific. The sensitivity of the algorithm to threshold criteria is investigated using the Manus Island data.
Abstract
This paper describes a method of absolutely calibrating and routinely monitoring the reflectivity calibration from a scanning weather radar using a vertically profiling radar that has been absolutely calibrated using a collocated surface disdrometer. The three instruments have different temporal and spatial resolutions, and the concept of upscaling is used to relate the small resolution volume disdrometer observations with the large resolution volume scanning radar observations. This study uses observations collected from a surface disdrometer, two profiling radars, and the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) scanning weather radar during the Texas–Florida Underflight-phase B (TEFLUN-B) ground validation field campaign held in central Florida during August and September 1998.
The statistics from the 2062 matched profiling and scanning radar observations during this 2-month period indicate that the WSR-88D radar had a reflectivity 0.7 dBZ higher than the disdrometer-calibrated profiler, the standard deviation was 2.4 dBZ, and the 95% confidence interval was 0.1 dBZ. This study implies that although there is large variability between individual matched observations, the precision of a series of observations is good, allowing meaningful comparisons useful for calibration and monitoring.
Abstract
This paper describes a method of absolutely calibrating and routinely monitoring the reflectivity calibration from a scanning weather radar using a vertically profiling radar that has been absolutely calibrated using a collocated surface disdrometer. The three instruments have different temporal and spatial resolutions, and the concept of upscaling is used to relate the small resolution volume disdrometer observations with the large resolution volume scanning radar observations. This study uses observations collected from a surface disdrometer, two profiling radars, and the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) scanning weather radar during the Texas–Florida Underflight-phase B (TEFLUN-B) ground validation field campaign held in central Florida during August and September 1998.
The statistics from the 2062 matched profiling and scanning radar observations during this 2-month period indicate that the WSR-88D radar had a reflectivity 0.7 dBZ higher than the disdrometer-calibrated profiler, the standard deviation was 2.4 dBZ, and the 95% confidence interval was 0.1 dBZ. This study implies that although there is large variability between individual matched observations, the precision of a series of observations is good, allowing meaningful comparisons useful for calibration and monitoring.
Abstract
The Department of Energy Atmospheric Radiation Measurement (ARM) Program has recently initiated a new research avenue toward a better characterization of the transition from cloud to precipitation. Dual-wavelength techniques applied to millimeter-wavelength radars and a Rayleigh reference have a great potential for rain-rate retrievals directly from dual-wavelength ratio measurements. In this context, the recent reconfiguration of the ARM 915-MHz wind profilers in a vertically pointing mode makes these instruments the ideal candidate for providing the Rayleigh reflectivity/Doppler velocity reference. Prior to any scientific study, the wind profiler data must be carefully quality checked. This work describes the signal postprocessing steps that are essential for the delivery of high-quality reflectivity and mean Doppler velocity products—that is, the estimation of the noise floor from clear-air echoes, the absolute calibration with a collocated disdrometer, the dealiasing of Doppler velocities, and the merging of the different modes of the wind profiler. The improvement added by the proposed postprocessing is confirmed by comparison with a high-quality S-band profiler deployed at the ARM Southern Great Plains site during the Midlatitude Continental Convective Clouds Experiment. With the addition of a vertically pointing mode and with the postprocessing described in this work in place, besides being a key asset for wind research wind profilers observations may therefore become a centerpiece for rain studies in the years to come.
Abstract
The Department of Energy Atmospheric Radiation Measurement (ARM) Program has recently initiated a new research avenue toward a better characterization of the transition from cloud to precipitation. Dual-wavelength techniques applied to millimeter-wavelength radars and a Rayleigh reference have a great potential for rain-rate retrievals directly from dual-wavelength ratio measurements. In this context, the recent reconfiguration of the ARM 915-MHz wind profilers in a vertically pointing mode makes these instruments the ideal candidate for providing the Rayleigh reflectivity/Doppler velocity reference. Prior to any scientific study, the wind profiler data must be carefully quality checked. This work describes the signal postprocessing steps that are essential for the delivery of high-quality reflectivity and mean Doppler velocity products—that is, the estimation of the noise floor from clear-air echoes, the absolute calibration with a collocated disdrometer, the dealiasing of Doppler velocities, and the merging of the different modes of the wind profiler. The improvement added by the proposed postprocessing is confirmed by comparison with a high-quality S-band profiler deployed at the ARM Southern Great Plains site during the Midlatitude Continental Convective Clouds Experiment. With the addition of a vertically pointing mode and with the postprocessing described in this work in place, besides being a key asset for wind research wind profilers observations may therefore become a centerpiece for rain studies in the years to come.
Abstract
This paper develops a technique for retrieving snowflake size distributions (SSDs) from a vertically pointing 915-MHz vertical profiler. Drop size distributions (DSDs) have been retrieved from 915-MHz profilers for several years using least squares minimization to determine the best-fit DSD to the observed Doppler spectra. This same premise is used to attempt the retrieval of SSDs. A nonlinear search, the Levenberg–Marquardt (LM) method, is used to search the physically realistic solution space and arrive at a best-fit SSD from the Doppler spectra of the profiler. The best fit is assumed to be the minimum of the squared difference of the log of the observed and modeled spectrum power over the precipitation portion of the spectrum. A snowflake video imager (SVI) disdrometer was collocated with the profiler and provided surface estimates of the SSDs. The SVI also provided estimates of crystal type, which is critical in attempting to estimate the density–size relationship. A method to vary the density–size relationship during the event was developed as well. This was necessary to correctly scale the SVI SSDs for comparison to the profiler-estimated distributions. Five events were examined for this study, and good overall agreement was found between the profiler and SVI for the lowest profiler gate (225 m AGL). Vertical profiles of SSDs were also produced and appear to be physically reasonable. Uncertainty estimates using simulated Doppler spectra show that the retrieval uncertainties are larger than that for rainfall and can approach and exceed 100% for situations with large spectral broadening as a result of atmospheric turbulence. The larger uncertainties are attributed to the lack of unique Doppler spectra for quite different SSDs, resulting in a less well-behaved solution space than that of rainfall retrievals.
Abstract
This paper develops a technique for retrieving snowflake size distributions (SSDs) from a vertically pointing 915-MHz vertical profiler. Drop size distributions (DSDs) have been retrieved from 915-MHz profilers for several years using least squares minimization to determine the best-fit DSD to the observed Doppler spectra. This same premise is used to attempt the retrieval of SSDs. A nonlinear search, the Levenberg–Marquardt (LM) method, is used to search the physically realistic solution space and arrive at a best-fit SSD from the Doppler spectra of the profiler. The best fit is assumed to be the minimum of the squared difference of the log of the observed and modeled spectrum power over the precipitation portion of the spectrum. A snowflake video imager (SVI) disdrometer was collocated with the profiler and provided surface estimates of the SSDs. The SVI also provided estimates of crystal type, which is critical in attempting to estimate the density–size relationship. A method to vary the density–size relationship during the event was developed as well. This was necessary to correctly scale the SVI SSDs for comparison to the profiler-estimated distributions. Five events were examined for this study, and good overall agreement was found between the profiler and SVI for the lowest profiler gate (225 m AGL). Vertical profiles of SSDs were also produced and appear to be physically reasonable. Uncertainty estimates using simulated Doppler spectra show that the retrieval uncertainties are larger than that for rainfall and can approach and exceed 100% for situations with large spectral broadening as a result of atmospheric turbulence. The larger uncertainties are attributed to the lack of unique Doppler spectra for quite different SSDs, resulting in a less well-behaved solution space than that of rainfall retrievals.
Abstract
A 3-GHz profiler has been developed by the National Oceanic and Atmospheric Administration’s Aeronomy Laboratory to observe the evolution and vertical structure of precipitating cloud systems. The profiler is very portable, robust, and relatively inexpensive, so that continuous, unattended observations of overhead precipitation can be obtained, even at remote locations. The new profiler is a vertically looking Doppler radar that operates at S band, a commonly used band for scanning weather radars (e.g., WSR-88D). The profiler has many features in common with the 915-MHz profiler developed at the Aeronomy Laboratory during the past decade primarily for measurement of lower-tropospheric winds in the Tropics. This paper presents a description of the new profiler and evaluates it in the field in Illinois and Australia in comparison with UHF lower-tropospheric profilers. In Illinois, the new profiler was evaluated alongside a collocated 915-MHz profiler at the Flatland Atmospheric Observatory. In Australia it was evaluated alongside a 920-MHz profiler during the Maritime Continent Thunderstorm Experiment. The results from these campaigns confirm the approximate 20-dB improvement in sensitivity, as expected for Rayleigh scatter. The results show that the new profiler provides a substantial improvement in the ability to observe deep cloud systems in comparison with the 915-MHz profilers.
Abstract
A 3-GHz profiler has been developed by the National Oceanic and Atmospheric Administration’s Aeronomy Laboratory to observe the evolution and vertical structure of precipitating cloud systems. The profiler is very portable, robust, and relatively inexpensive, so that continuous, unattended observations of overhead precipitation can be obtained, even at remote locations. The new profiler is a vertically looking Doppler radar that operates at S band, a commonly used band for scanning weather radars (e.g., WSR-88D). The profiler has many features in common with the 915-MHz profiler developed at the Aeronomy Laboratory during the past decade primarily for measurement of lower-tropospheric winds in the Tropics. This paper presents a description of the new profiler and evaluates it in the field in Illinois and Australia in comparison with UHF lower-tropospheric profilers. In Illinois, the new profiler was evaluated alongside a collocated 915-MHz profiler at the Flatland Atmospheric Observatory. In Australia it was evaluated alongside a 920-MHz profiler during the Maritime Continent Thunderstorm Experiment. The results from these campaigns confirm the approximate 20-dB improvement in sensitivity, as expected for Rayleigh scatter. The results show that the new profiler provides a substantial improvement in the ability to observe deep cloud systems in comparison with the 915-MHz profilers.
