Development and Evaluation of Automated Algorithm for Estimation of Winds from Wind Profiler Spectra

National Atmospheric Research Laboratory (NARL) hosts several atmospheric measurements of which, MST Radar is being treated as a work horse, for which the wind observations up to an altitude of 100km is recorded. It is a great tool for studying the atmospheric dynamics. These radars are capable of measuring air motions over a wide range of heights with good spatial and temporal resolutions. The derivation of wind components from spectral data includes noise level estimation and then moment estimation. In the present context, Hildebrand and Sekhon method is utilized for noise level estimation for each range bin employing the physical properties of white noise. The interference due to stationary targets is reflected as the dc components which can be removed using conventional methods such as replacing the spectral power at zero frequency with the average of the power at adjacent spectral points and it is very important for distinguishing between the actual signals from interference echoes. In the light of automation of data analysis so as to obtain the wind components, it is mandatory to develop algorithms for the characterization of signal and interference echoes. In this work, an Automated Algorithm is developed for estimation of moments and is applied to Real Time Radar data from MST region near Gadanki, Tirupati.