Multi‐Receiver Augmentation to Advanced Indian MST Radar (AIR)—Implementation of Spaced Antenna Technique

Abstract

Newly acquired multi‐receiver capability of Advanced Indian MST radar has been utilized to implement the spaced antenna (SA) technique for profiling of winds and turbulence. Two experiments were conducted. In Experiment 1, in addition to the traditional Full Correlation Analysis (FCA), SA analysis is also performed on off‐vertical beam measurements (hereafter Oblique Spaced Antenna [OSA]) and the products are evaluated against those retrieved with Doppler Beam Swinging (DBS) and collocated GPS radiosonde. In Experiment 2, the dependence of height coverage on antenna aperture is examined. The synchronization and phase matching of receiving channels are found to be well within the designed values. The consensus averaged zonal and meridional wind velocities obtained by FCA and OSA compare very well with DBS and radiosonde measurements with correlation coefficients >0.85 and root mean square error (RMSE) < 2 ms−1. The mean value of antenna parameter, ah, extracted from correlation of different antenna pairs compare well with the theoretical estimate. The efficacy of ah in quality controlling the SA derived winds has been examined. Imposing ah condition has certainly removed several outliers and reduced the RMSE (relative to reference) considerably, but it also reduced useful data by 50%. The consensus averaging of winds is found to be more effective in removing outliers and reducing the RMSE. The wind variances estimated by DBS (after accounting the non‐turbulent contributions) and SA agree quite well with a correlation coefficient of 0.95. Utilization of a bigger array increased the height coverage from 10‐12 to 20 km.

A Quality Control Method and Implementation Process of Wind Profiler Radar Data

“…For example, Barbré [24] introduced a signal-processing system, which uses a median filter to remove spurious Doppler spectral data and constrains the search for the atmospheric signal by a first guess and get good results. Kumar, S. [25] proposed that the averaging of winds is found to be more effective in removing outliers and reducing the RMSE. In the study proposed by Zhang, Y.…”