Application of Radar Signal Processing Deriving the Lower Atmospheric Wind Parameters
Radio waves at VHF and UHF are often utilized to study the atmospheric parameters within the lowest atmosphere levels, owing to their dependency on scattering mechanisms under explicit and disturbing weather conditions. In particular, the UHF lower atmospheric wind profiler is a potential tool for studying the wind parameters under clear conditions (based on Bragg scattering) and rain events under disturbed weather conditions (based on Rayleigh scattering).Lower Atmospheric Wind Profiler (LAWP) is a remote sensing instrument to study the wind parameters up to a height of typically 7 km. This L-band wind profiler is being operated at 1280 MHz with a peak output power of 1.2 kW. LAWP employs a fully active array comprising 256 microstrip patch antenna elements arranged as 16 x 16 grid configurations. These elements, fed by dedicated solid-state transceiver modules, are utilized to operate the radar continuously in DBS mode to calculate the moments (viz., signal power, Doppler shift and Doppler width) in three directions. Doppler shift is utilized to calculate the radial velocities used to retrieve the wind components in three directions: zonal, meridional, and vertical. The spectral widths are finally used in investigating the variation of turbulence caused due to the convective and rainfall events. The data products derived from this radar include information about the melting layer, the height at which the ice crystals are melted into a supercooled water state, or vice versa, typically 3 to 4 km in the tropics. To study these parameters, the data must be carefully analyzed to estimate the moments. But very often, the moment estimation is affected significantly due to technical noise called interference.
The present study focuses on refining digital signal processing algorithmsto reduce the interference noise level and increase signal detectability. This would be useful is better estimating the moments and thereby deriving the wind components. The study about the diurnal variation in wind parameters helps understand various atmospheric derivable and apply in diverse fields viz., atmospheric pollution, forecasting, aviation etc.