Atmospheric Wind Estimation Using Adaptive Block James–Stein Technique for Higher Range Coverage in MST Radar

Abstract

Measuring atmospheric winds over longer ranges using VHF-MST radar is extremely useful for studying stratosphere-troposphere exchange. The present study uses an adaptive block technique (ABlockJS), a mixed model of a parametric technique, and a few non-parametric techniques to address this aspect. The signal estimates are substantiated with five moments and six quality-related parameters while deriving three wind components along with horizontal wind speed and direction. The parametric part of the technique improves the signal, while the non-parametric part lowers noise variance. This technique is established using NARL MST Radar experimental data. The computed wind components derived from this technique are verified with the independent wind components acquired from the concurrent GPS radiosonde in-situ observations. It is observed that this analytical technique can deliver wind components more precisely and consistently, covering longer ranges of 25.20 km. It enhances the benchmark range coverage of 21.45 km attained using Fourier-based estimators on the MST dataset. The complete procedure is developed in C# from scratch without using any standard routine from available packages, thus, it fits acquisition-time application needs fine. It benefits various atmospheric research which demands higher range coverage using VHF radar.