Analysis of the New Nexrad Spectrum Width Estimator

Recently, the US network of weather surveillance radars (NEXRAD) was upgraded with the Open Radar Data Acquisition (ORDA) subsystem which includes new receivers, signal processors, and control subsystems (Patel and Macemon 2004). Before this upgrade, the legacy RDA estimated the spectrum width using the standard pulse-pair technique. The new signal processor implements a similar spectrum width estimator, but relies on a Discrete Fourier Transform (DFT)-based estimator to compute the first few lags of the time-series autocorrelation function. Initial evaluation of the upgraded system demonstrated that, if combined with a tapered data window, the DFT-based estimator produces results that are acceptable but exhibit about 30% larger errors compared to the legacy RDA. This paper demonstrates that, in general, the new and legacy autocorrelation estimators are not equivalent, resulting in inconsistent spectrum width estimates. Theoretical, simulation, and data analyses show that the new spectrum width estimator on non-windowed data is positively biased, especially for narrow spectrum widths. Given that biased estimates would negatively impact the performance of algorithms that rely on the spectrum width (e.g., the radar echo classifier, or the new turbulence detection algorithm), we propose changes to the new spectrum width estimator to make it unbiased, mathematically equivalent to the pulse-pair implementation, and naturally able to handle data window effects.