Adaptive array processing techniques can be applied to phased array radar to improve angular resolving capability beyond the Fourier limit. Thus, enhanced details of weather phenomena can be realized in terms of reflectivity, radial velocity, and spectrum width. In addition, it should be possible to simultaneously detect/track aircraft while surveying weather hazards, providing multi-function capabilities. This paper compares the performance of both conventional and adaptive array processing based methods versus deconvolution techniques, which make use of the knowledge of the beam pattern in order to enhance resolution. In particular, comparisons will be made between Fourier/Capon beamforming and Capon deconvolution. Our phased array concept uses a wide transmit beam in both angular directions to illuminate a large field of view and is thus an imaging radar. The receiver is made up of individual antenna elements placed in a planar configuration. Time series signals for each antenna element are generated using a realistic radar simulator based on point-target scatterers, which flow and scatter according to a simulated environment produced from the Advanced Regional Prediction System (ARPS). Simulation results show that while the adaptive Capon processing techniques introduce negative bias in the reflectivity values compared to Fourier-based techniques, due in part to uncertainties in the actual form of the adaptive beam pattern, the resolution is significantly improved and meteorological interpretation is enhanced. It will also be shown that adaptive beamforming methods outperform adaptive deconvolution methods in terms of resolution enhancement.