Wednesday, 17 January 2007: 4:15 PM
Optimization of weather update time and data quality using phased-array radar
217A (Henry B. Gonzalez Convention Center)
Fast update of weather information is often needed not only to increase the warning lead time but also to advance the understanding of fast evolving weather systems. Although the fast update can be achieved by increasing antenna's rotational rate, the statistical error of radar estimates (reflectivity, mean Doppler velocity, and spectrum width) will increase due to a decrease in the number of samples used for processing. This fundamental limitation can be addressed by a phased array radar through a novel scanning strategy termed beam multiplexing (BMX). BMX is developed to exploit the idea of collecting independent samples and maximizing the usage of radar resources. The radar will revisit the location of interest after the signals become uncorrelated. During the revisit time, the radar can be scheduled to scan other locations or to perform other tasks such as aircraft tracking to maximize the usage of the radar resources. As a result, the radar beam will be multiplexed over a designated region to provide measurements with low statistical error in a shorter period of time.
Applications of BMX to weather observations are demonstrated by the S-band Phased Array Radar (PAR) at the National Weather Radar Testbed (NWRT). Statistical analysis is performed to verify the theoretical variance of signal power and mean velocity estimates using both BMX and conventional scanning strategy. It is shown theoretically that fast update without comprising data quality can be achieved using BMX, especially at small spectrum width and high signal-to-noise ratio (SNR). Furthermore, the experimental results have demonstrated that the update time can be improved using BMX by an averaged factor of two to four for SNR is higher than 10 dB.