D. A. Carter

Removing Ground and Intermittent Clutter Contamination from Wind Profiler Signals Using Wavelet Transforms

Abstract New algorithms for removing ground and intermittent clutter contamination from wind profiler data are presented. The techniques use wavelet transforms to “filter” the contribution of clutter to the wind profiler signals. Examples of typical clutter contamination using simulated and actual signals are presented. The corresponding Doppler spectra before and after wavelet filtering are compared. The authors find that wavelet filtering can reduce the clutter-to-clear-air signal power by as much as 40 dB, even when the clutter and clear-air peaks cannot be resolved in the Doppler spectrum. The enhancement in clear-air signal detectability in the presence of clutter is due to the more efficient separation of clutter and clear-air energy in the wavelet domain.

Evaluation of Three-Beam and Four-Beam Profiler Wind Measurement Techniques Using a Five-Beam Wind Profiler and Collocated Meteorological Tower

In this paper a five-beam wind profiler and a collocated meteorological tower are used to estimate the accuracy of four-beam and three-beam wind profiler techniques in measuring horizontal components of the wind. In the traditional three-beam technique, the horizontal components of wind are derived from two orthogonal oblique beams and the vertical beam. In the less used four-beam method, the horizontal winds are found from the radial velocities measured with two orthogonal sets of opposing coplanar beams. In this paper the observations derived from the two wind profiler techniques are compared with the tower measurements using data averaged over 30 min. Results show that, while the winds measured using both methods are in overall agreement with the tower measurements, some of the horizontal components of the three-beam-derived winds are clearly spurious when compared with the tower-measured winds or the winds derived from the four oblique beams. These outliers are partially responsible for a larger 30-min, threebeam standard deviation of the profiler/tower wind speed differences (2. 2ms 1 ), as opposed to that from the four-beam method (1.2 m s 1 ). It was also found that many of these outliers were associated with periods of transition between clear air and rain, suggesting that the three-beam technique is more sensitive to small-scale variability in the vertical Doppler velocity because of its reliance on the point measurement from the vertical beam, while the four-beam method is surprisingly robust. Even after the removal of the rain data, the standard deviation of the wind speed error from the three-beam method (1.5 m s 1 ) is still much larger than that from the four-beam method. Taken together, these results suggest that the spatial variability of the vertical airflow in nonrainy periods or hydrometeor fall velocities in rainy periods makes the vertical beam velocities significantly less representative over the area across the three beams, and decreases the precision of the three-beam method. It is concluded that profilers utilizing the four-beam wind profiler technique have better reliability than wind profilers that rely on the three-beam wind profiler technique.

Range Errors in Wind Profiling Caused by Strong Reflectivity Gradients

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 at...

The Christmas Island Wind Profiler: A Prototype VHF Wind-Profiling Radar for the Tropics

Abstract After a decade of development, VHF wind profilers are being used for atmospheric research at several locations in the tropical Pacific. A prototype 50-MHz wind profiler was installed on Christmas Island in 1985 and has operated continuously since March 1986 to monitor tropical wind fields in the altitude range 1.8–1 8 km. This paper presents an overview of the Christmas Island wind profiler and reviews its performance. A survey of sample wind observations and a brief climatology of the observed winds are included.

A Minimum Threshold for Wind Profiler Signal-to-Noise Ratios

AbstractOne 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.

Improving Wind Profiler–Measured Winds Using Coplanar Spectral Averaging

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.