Characterization and Detection of Downburst Precursor Signatures in Environments of Ground Clutter using Adaptive Scanning Strategies from All-digital Phased Array Radar (PAR)

Phased array radar (PAR), an arrangement of many individual antenna elements that can be used to electronically create and steer a radar beam, is being explored as a potential candidate for the replacement of the current dish-based WSR-88D radar network across the United States. Electronic steering from all-digital PAR architecture offers a level of flexibility and adaptability in scanning strategies (e.g., imaging, beam multiplexing, multi-beam) unmatched by traditional dish radars. As a result, PAR can offer greater temporal resolution than the WSR-88D network, which can help in the detection and characterization of rapidly evolving mesoscale phenomena like downbursts. Downbursts, areas of strong downward motion in thunderstorms which cause strong radially divergent winds at the surface, pose a significant risk of damage to life and property. Given that downbursts evolve on the scale of seconds, an all-digital PAR can be useful in accurately detecting and characterizing these rapidly evolving phenomena.

However, tradeoffs arise with each adaptive scanning strategy, particularly with respect to data quality and the representativeness of the downburst signatures. Contamination from ground clutter can further impact these, particularly since downbursts and their precursor signatures evolve in the low- to midlevels. For example, the presence of a stationary clutter target at the location where a downburst touches down can diminish the surface divergence signature seen in radial velocity. The impacts that ground clutter has on these signatures varies by scanning strategy. Imaging beams with greater spoiling in elevation produce more contaminated signatures due to higher vertical sidelobe levels, but frequency filtering (such as Gaussian Model Adaptive Processing, GMAP) can be applied to suppress ground clutter signals to reduce these impacts. Beam multiplexing can increase data quality at the same temporal resolution, but frequency filtering cannot be applied. Applying the multi-beam technique can provide the benefits of increased temporal resolution without the introduction of higher vertical sidelobes, while still allowing for clutter filtering. Understanding how ground clutter impacts the downburst and its precursor signatures in each scanning strategy is critical to determining the optimal scanning method for downburst detection using an all-digital PAR.

This work leverages a previously developed radar simulator framework (RSim) for downburst detection to assess the impacts of different adaptive scanning strategies in an all-digital PAR architecture in the presence of ground clutter. Two wet downburst cases (modeled in CM1) are analyzed through the RSim framework, which enables investigation both qualitatively and quantitively into the performance of detecting downburst precursor signatures, including descending reflectivity cores (DRCs), midlevel radial convergence, and specific differential phase (K_DP) cores, by several different scanning strategies, including spoiled beams of 3, 6, and 9 degrees, beam multiplexing, and the multi-beam technique with three beams in a trident-shape configuration. A variety of different ground clutter contaminations are applied to the emulations, including uniform fields with strong, medium, and weak contaminations, and a showcase using real ground clutter data collected from a WSR-88D radar. Performance and tradeoffs are discussed for each case and strategy, with recommendations given for best practices for potential future operational adoption.