Estimation and Comparison of Horizontal Winds Using Various Spectral Estimation Methods on Profiler Radars

Abstract

Abstract The lower atmospheric wind profiles are obtained by the postset beam steering (PBS) technique on middle and upper (MU) atmosphere radar data. The Capon beamformer is used to improve the beam synthesizing in the desired directions within the radar transmit beamwidth. From a synthesized beam, the power spectrum is obtained by various spectral estimators, such as Fourier, multiple signal classification (MUSIC), and eigenvector (EV). The wind vector components are derived from radial velocities estimated from the power spectra of synthesized beams. As the reliability of the PBS wind estimate depends on the choice of spectral estimators, a detailed analysis is carried out to compare the performance of estimators in deriving wind profiles on the radar data. The results suggest that EV shows a better performance in deriving possible spectrum parameters and is useful for reliable wind profiling up to the lower stratosphere. The wind profiles derived by PBS with EV are more consistent with near-time observations using GPS sonde and Doppler beam swinging (DBS) methods. The study also suggests that MUSIC cannot be used to reliably estimate atmospheric spectrum parameters.