Abstract
An advantage of phased-array radars that has not been fully investigated is the application of digital beamforming for weather observations. With adaptive beamforming, the radar can change the beam pattern to reduce the impact of ground clutter and other interference on the estimation of meteorological variables. Many adaptive beamforming methods have been developed for applications involving signals that can be modeled as point sources. However, the received signal by weather radars is from distributed targets, namely the hydrometeors that fill spaces much larger than the radar resolution volume. Thus, direct application of adaptive beamforming methods intended for point sources to weather radars could lead to significant biases in estimated signal parameters. An initial study to demonstrate the feasibility of utilizing adaptive beamforming for weather observation was conducted using data collected by the Atmospheric Imaging Radar. These data are the first high-resolution (both temporal and spatial) simultaneous cross-section measurements through rapidly evolving storms.
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