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Abstract
Stratocumulus (Sc) clouds occur frequently over the cold waters of the southeastern Pacific Ocean. Data collected during two Pan American Climate Study research cruises in the tropical eastern Pacific illuminate many aspects of this Sc-topped marine boundary layer (MBL). Here the focus is on understanding gaps in detectable wind-profiler reflectivities during two boreal autumn cruises. After rigorous quality control that included applying the Riddle threshold of minimum signal-to-noise ratio (SNR) detectability, there are many instances with no measurable atmospheric signals through a depth of up to several hundred meters, often lasting for an hour or more. Rain gauge data from the autumn 2004 cruise are used to calibrate the profiler, which allows SNR to be converted to both equivalent reflectivity and the structure-function parameter of the index of refraction 
Abstract
Stratocumulus (Sc) clouds occur frequently over the cold waters of the southeastern Pacific Ocean. Data collected during two Pan American Climate Study research cruises in the tropical eastern Pacific illuminate many aspects of this Sc-topped marine boundary layer (MBL). Here the focus is on understanding gaps in detectable wind-profiler reflectivities during two boreal autumn cruises. After rigorous quality control that included applying the Riddle threshold of minimum signal-to-noise ratio (SNR) detectability, there are many instances with no measurable atmospheric signals through a depth of up to several hundred meters, often lasting for an hour or more. Rain gauge data from the autumn 2004 cruise are used to calibrate the profiler, which allows SNR to be converted to both equivalent reflectivity and the structure-function parameter of the index of refraction
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 experiment combining wind profiler and polarimetric radar analyses of intense, but shallow, tropical thunderstorms has been performed. These storms are important as they are very common along many tropical coasts and islands and are sometimes the precursors to large intense multicellular storms such as occur over the Tiwi Islands north of Darwin, Australia. All the storms sampled had a similar structure, with intense updrafts on the periphery of the cells producing significant-sized hail and downdrafts in the storm center. The hail concentrations are relatively small, but have a large effect on the radar reflectivity and polarimetric measurands because of the size (10–20 mm). It is this hail melting that produces characteristic Z DR columns in the polarimetric radar data.
Abstract
An experiment combining wind profiler and polarimetric radar analyses of intense, but shallow, tropical thunderstorms has been performed. These storms are important as they are very common along many tropical coasts and islands and are sometimes the precursors to large intense multicellular storms such as occur over the Tiwi Islands north of Darwin, Australia. All the storms sampled had a similar structure, with intense updrafts on the periphery of the cells producing significant-sized hail and downdrafts in the storm center. The hail concentrations are relatively small, but have a large effect on the radar reflectivity and polarimetric measurands because of the size (10–20 mm). It is this hail melting that produces characteristic Z DR columns in the polarimetric radar data.
Abstract
One limiting factor in atmospheric radar observations is the inability to distinguish the often weak atmospheric signals from fluctuations of the noise. This study presents a minimum threshold of usability, SNRmin, for signal-to-noise ratios obtained from wind profiling radars. The basic form arises from theoretical considerations of radar noise; the final form includes empirical modifications based on radar observations. While SNRmin was originally developed using data from the 50-MHz profiler at Poker Flat, Alaska, it works well with data collected from a wide range of locations, frequencies, and parameter settings. It provides an objective criterion to accept or reject individual spectra, can be quickly applied to a large quantity of data, and has a false-alarm rate of approximately 0.1%. While this threshold’s form depends on the methods used to calculate SNR and spectral moments, variations of the threshold could be developed for use with data processed by other methods.
Abstract
One limiting factor in atmospheric radar observations is the inability to distinguish the often weak atmospheric signals from fluctuations of the noise. This study presents a minimum threshold of usability, SNRmin, for signal-to-noise ratios obtained from wind profiling radars. The basic form arises from theoretical considerations of radar noise; the final form includes empirical modifications based on radar observations. While SNRmin was originally developed using data from the 50-MHz profiler at Poker Flat, Alaska, it works well with data collected from a wide range of locations, frequencies, and parameter settings. It provides an objective criterion to accept or reject individual spectra, can be quickly applied to a large quantity of data, and has a false-alarm rate of approximately 0.1%. While this threshold’s form depends on the methods used to calculate SNR and spectral moments, variations of the threshold could be developed for use with data processed by other methods.
Abstract
Doppler radar profilers are widely used for routine measurement of wind, especially in the lower troposphere. The same profilers with minor modifications are useful tools for precipitation research. Specifically, the profilers are now increasingly being used to explore the structure of precipitating cloud systems and to provide calibration and validation of other instruments used in precipitation research, including scanning radars and active and passive satellite-borne sensors. A vertically directed profiler is capable of resolving the vertical structure of precipitating cloud systems that pass overhead. Standard profiler measurements include reflectivity, reflectivity-weighted Doppler velocity, and spectral width. This paper presents profiler observations of precipitating cloud systems observed during Tropical Rainfall Measuring Mission (TRMM) Ground Validation field campaigns. The observations show similarities and differences between convective systems observed in Florida; Brazil; and Kwajalein, Republic of the Marshall Islands. In addition, it is shown how a profiler can be calibrated using a collocated Joss–Waldvogel disdrometer, how the profiler can then be used to calibrate a scanning radar, and how the profiler may be used to retrieve drop size distributions.
Abstract
Doppler radar profilers are widely used for routine measurement of wind, especially in the lower troposphere. The same profilers with minor modifications are useful tools for precipitation research. Specifically, the profilers are now increasingly being used to explore the structure of precipitating cloud systems and to provide calibration and validation of other instruments used in precipitation research, including scanning radars and active and passive satellite-borne sensors. A vertically directed profiler is capable of resolving the vertical structure of precipitating cloud systems that pass overhead. Standard profiler measurements include reflectivity, reflectivity-weighted Doppler velocity, and spectral width. This paper presents profiler observations of precipitating cloud systems observed during Tropical Rainfall Measuring Mission (TRMM) Ground Validation field campaigns. The observations show similarities and differences between convective systems observed in Florida; Brazil; and Kwajalein, Republic of the Marshall Islands. In addition, it is shown how a profiler can be calibrated using a collocated Joss–Waldvogel disdrometer, how the profiler can then be used to calibrate a scanning radar, and how the profiler may be used to retrieve drop size distributions.
Abstract
Comparisons of data taken by collocated Doppler wind profilers using 100-, 500-, and 1000-m pulse lengths show that the velocity profiles obtained with the longer pulses are displaced in height from contemporaneous profiles measured with the shorter pulses. These differences are larger than can be expected from random measurement errors. In addition, there is evidence that the 500-m pulse may underestimate the wind speed when compared with the 100-m pulse.
The standard radar equation does not adequately account for the conditions under which observations are made. In particular, it assumes that atmospheric reflectivity is constant throughout the pulse volume and that observations can be assigned to the peak of the range-weighting function. However, observations from several tropical profilers show that reflectivity gradients with magnitudes greater than 10 dB km−1 are common. Here, a more general radar equation is used to simulate the radar response to the atmosphere. The simulation shows that atmospheric reflectivity gradients cause errors in the range placement. Observed reflectivity gradients can be used to calculate a correction to the range location of the observations that helps to reduce these errors.
Examples of these errors and the application of the correction to selected cases are shown. The evidence presented shows that reflectivity gradients are the main cause of the pervasive differences observed between the different radar observations.
Abstract
Comparisons of data taken by collocated Doppler wind profilers using 100-, 500-, and 1000-m pulse lengths show that the velocity profiles obtained with the longer pulses are displaced in height from contemporaneous profiles measured with the shorter pulses. These differences are larger than can be expected from random measurement errors. In addition, there is evidence that the 500-m pulse may underestimate the wind speed when compared with the 100-m pulse.
The standard radar equation does not adequately account for the conditions under which observations are made. In particular, it assumes that atmospheric reflectivity is constant throughout the pulse volume and that observations can be assigned to the peak of the range-weighting function. However, observations from several tropical profilers show that reflectivity gradients with magnitudes greater than 10 dB km−1 are common. Here, a more general radar equation is used to simulate the radar response to the atmosphere. The simulation shows that atmospheric reflectivity gradients cause errors in the range placement. Observed reflectivity gradients can be used to calculate a correction to the range location of the observations that helps to reduce these errors.
Examples of these errors and the application of the correction to selected cases are shown. The evidence presented shows that reflectivity gradients are the main cause of the pervasive differences observed between the different radar observations.
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.
Abstract
A method is presented that increases the detectability of weak clear-air signals by averaging Doppler spectra from coplanar wind profiler beams. The method, called coplanar spectral averaging (CSA), is applied to both simulated wind profiler spectra and to 1 yr of archived spectra from a UHF profiler at Christmas Island (1 October 1999–30 September 2000). A collocated 50-MHz wind profiler provides a truth for evaluating the CSA technique.
In the absence of precipitation, it was found that CSA, when combined with a fuzzy logic quality control, increases the height coverage of the 1-hourly averaged UHF profiler winds by over 600 m (two range gates). CSA also increased the number of good wind estimates at each observation range by about 10%–25% over the standard consensus method.
Abstract
A method is presented that increases the detectability of weak clear-air signals by averaging Doppler spectra from coplanar wind profiler beams. The method, called coplanar spectral averaging (CSA), is applied to both simulated wind profiler spectra and to 1 yr of archived spectra from a UHF profiler at Christmas Island (1 October 1999–30 September 2000). A collocated 50-MHz wind profiler provides a truth for evaluating the CSA technique.
In the absence of precipitation, it was found that CSA, when combined with a fuzzy logic quality control, increases the height coverage of the 1-hourly averaged UHF profiler winds by over 600 m (two range gates). CSA also increased the number of good wind estimates at each observation range by about 10%–25% over the standard consensus method.
Abstract
Profilers operating in the UHF range are sensitive to both Bragg scattering from radio refractive index structure and to Rayleigh scattering from small point targets. Identification of the scattering process is critical for proper interpretation of these observations, especially the data collected from the vertical incident beam. This study evaluates the performance of Doppler velocity thresholds as a means to separate air motions from hydrometeor motions in vertical incident profiler observations. This evaluation consists of three different steps. First, using two collocated profilers operating at different frequencies, the observations are unambiguously identified as Bragg or Rayleigh scattering processes. Second, the observations are separated into either air or hydrometeor motion using only the data from one profiler. The third step quantitatively evaluates the performance of the single profiler separation techniques by counting the number of correct classifications and adjusting the count by the number of incorrect classifications.
Constant Doppler velocity threshold methods are acceptable methods to separate air motions from hydrometeor motions only after the correct threshold is determined. This study presents a cluster analysis method that robustly and objectively separates air from hydrometeor motions. The introduced cluster analysis produces two thresholds. The first threshold is a Doppler velocity threshold that is a function of reflectivity. The second threshold is the maximum reflectivity in which the Doppler velocity threshold divides the observations into two statistical distributions using the Kolmogorov–Smirnov statistical test. The cluster analysis method quantitatively performs better than constant Doppler velocity threshold methods, and is a repeatable, self-adapting, statistically based procedure.
Abstract
Profilers operating in the UHF range are sensitive to both Bragg scattering from radio refractive index structure and to Rayleigh scattering from small point targets. Identification of the scattering process is critical for proper interpretation of these observations, especially the data collected from the vertical incident beam. This study evaluates the performance of Doppler velocity thresholds as a means to separate air motions from hydrometeor motions in vertical incident profiler observations. This evaluation consists of three different steps. First, using two collocated profilers operating at different frequencies, the observations are unambiguously identified as Bragg or Rayleigh scattering processes. Second, the observations are separated into either air or hydrometeor motion using only the data from one profiler. The third step quantitatively evaluates the performance of the single profiler separation techniques by counting the number of correct classifications and adjusting the count by the number of incorrect classifications.
Constant Doppler velocity threshold methods are acceptable methods to separate air motions from hydrometeor motions only after the correct threshold is determined. This study presents a cluster analysis method that robustly and objectively separates air from hydrometeor motions. The introduced cluster analysis produces two thresholds. The first threshold is a Doppler velocity threshold that is a function of reflectivity. The second threshold is the maximum reflectivity in which the Doppler velocity threshold divides the observations into two statistical distributions using the Kolmogorov–Smirnov statistical test. The cluster analysis method quantitatively performs better than constant Doppler velocity threshold methods, and is a repeatable, self-adapting, statistically based procedure.
Postdeployment Calibration of a Tropical UHF Profiling Radar via Surface- and Satellite-Based MethodsAbstract
Wind profiling radars are usually not calibrated with respect to reflectivity because such calibrations are both unnecessary for good wind measurements and costly. However, reflectivity from calibrated profilers can reveal many atmospheric attributes beyond winds. Establishing ways to calibrate these radars even after they have been taken out of service would expand the utility of archived profiler data. We have calibrated one operating mode of a 915-MHz profiler deployed at Manus, Papua New Guinea (1992–2001), using two methods. The first method adjusts a radar parameter until the profiler’s estimate of rainfall during stratiform events closely matches surface observations. The second adjusts the parameter so that mean brightband heights observed by the profiler (July 1992–August 1994) match the mean brightband reflectivities over the profiler as observed by the TRMM Precipitation Radar (January 1998–July 2001). The results differ by about 5% and yield very similar precipitation errors during tested stratiform events. One or both of these methods could be used on many other wind profilers, whether they have been decommissioned or are currently operational. Data from such calibrated profilers will enable research employing the equivalent reflectivity factor observed by profilers to be compared with that from other radars, and will also enable turbulent studies with C n 2.
Abstract
Wind profiling radars are usually not calibrated with respect to reflectivity because such calibrations are both unnecessary for good wind measurements and costly. However, reflectivity from calibrated profilers can reveal many atmospheric attributes beyond winds. Establishing ways to calibrate these radars even after they have been taken out of service would expand the utility of archived profiler data. We have calibrated one operating mode of a 915-MHz profiler deployed at Manus, Papua New Guinea (1992–2001), using two methods. The first method adjusts a radar parameter until the profiler’s estimate of rainfall during stratiform events closely matches surface observations. The second adjusts the parameter so that mean brightband heights observed by the profiler (July 1992–August 1994) match the mean brightband reflectivities over the profiler as observed by the TRMM Precipitation Radar (January 1998–July 2001). The results differ by about 5% and yield very similar precipitation errors during tested stratiform events. One or both of these methods could be used on many other wind profilers, whether they have been decommissioned or are currently operational. Data from such calibrated profilers will enable research employing the equivalent reflectivity factor observed by profilers to be compared with that from other radars, and will also enable turbulent studies with C n 2.
