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

Phased array radar (PAR) is being explored as a potential candidate for the replacement upon the retirement of the current dish-based WSR-88D radar network across the United States. A PAR is constructed of many individual antenna elements which can be electronically manipulated into various desired scanning strategies (such as digital beamforming, imaging, or beam multiplexing), offering a level of flexibility and adaptability unmatched by traditional dish radars. Specifically, all-digital PAR architecture allows for maximum flexibility, given its capability of a wide variety of scanning strategies and the ability to easily switch between these strategies. As a result of this architecture and adaptive scanning capability, PAR can offer greater temporal resolution than the WSR-88D network. This poses particular importance in the detection and characterization of 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, which has been particularly evident in impacts to the aviation industry. They evolve on a scale of seconds and last only a couple minutes in duration, too fine a temporal resolution to be accurately observed by the WSR-88D network. Given its ability for much greater temporal resolution, all-digital PAR can be useful in accurately detecting and characterizing these rapidly evolving phenomena.

Previously a framework was developed to study downburst detection by all-digital architecture through the use of a radar simulator (RSim). This framework was then applied to explore the tradeoffs presented by implementing different scanning strategies using an all-digital, mechanically rotating, planar PAR architecture to investigate the detection of downbursts and their precursor signatures. RSim was applied to qualitatively and quantitively investigate the performance of several scanning strategies in detecting downburst precursor signatures, including descending reflectivity cores (DRCs), mid-level radial convergence, and specific differential phase (Kdp) cores. It was found that spoiling factors greater than 5 degrees provided no benefit for effectively analyzing these signatures, based on significant data degradation and loss of representativeness of these signatures at greater spoils.

This presentation focuses on research that builds upon and expands this RSim framework in order to provide a more robust analysis of the detection and characterization of downburst precursor signatures using these different scanning strategies of PAR. The framework is utilized to examine more downburst cases (modeled using CM1), including both dry downbursts and more wet downbursts. The same signatures (DRCs, Kdp columns, and mid-level radial convergence) are investigated and compared to those found in the preliminary findings for a more robust analysis. Moreover, RSim itself is modified to include practical considerations such as velocity aliasing, range folding, and ground clutter, which were not considered in the initial framework. The effects that these different considerations have on the ability to detect these downburst signatures are presented. Moreover, different strategies like beam multiplexing are implemented and explored for comparison and analysis.