Soon after deployment of the NWRT PAR, it became apparent that proposed increasing needs for computational power and archiving of time-series and meteorological data were unsustainable with the original signal processing hardware. The radar signal processor was upgraded from a proprietary cluster of multiprocessor boards to a Linux-based cluster of dual-processor, dual-core nodes that communicate via a high-speed interconnect. The architecture of the new signal processor is based on distributed computing where all nodes in the cluster work toward the common goal of real-time radar signal processing. The system is designed to optimally utilize the computational resources; specifically, a load-balancing mechanism in which nodes compete to read and process sets of radar data tailors the data distribution to each node at a rate according to their capabilities. In this way, the system’s scalability is facilitated by allowing a hybrid mixture of nodes in the cluster. The signal processor cluster is complemented by a 12-TB redundant storage system (RAID) that supports simultaneous, continuous recording of time-series and meteorological data quantities for about 175 hours.
The real-time controller (RTC) is the nexus with the radar antenna, transmitter, and receiver. RTC upgrades support adaptive scanning, scheduling, and multifunction capabilities. For example, the RTC receives commands from the signal processor to perform adaptive scanning. Recent upgrades to the RTC enabled the collection of data closer the radar and the dynamic change of the pulse repetition time (PRT), which is crucial to implementing advanced adaptive scanning strategies. One example of this is the use of small sector scans to provide faster updates of storms of interest. Another example is adjusting the PRT on a beam-by-beam basis to match the maximum range of storms and thus reducing the total acquisition time.
The Radar Control Interface (RCI) is a Java-based graphical user interface that allows radar operators to complete routine tasks such as moving the antenna pedestal, selecting scanning strategies, turning the radar on and off, and controlling data archiving. In addition to these and many other basic control functions, the RCI has been significantly improved to support real-time control and monitoring of adaptive scanning, storm tracking, and multifunction algorithms. Through the RCI, NWRT PAR operators can run sequences of multiple scanning strategies with individual repeat counts, and/or dynamically modify the spatial coverage of active strategies (e.g., azimuthal sector, maximum elevation angle, beam spacing) and their acquisition parameters (e.g., pulse repetition times, pulse counts, waveforms, and). Operators can also monitor in real-time the quality of the meteorological data produced by the signal processor and the performance of adaptive scanning and storm-tracking algorithms.
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Screen capture of the new Radar Control Interface (RCI) scan-control window containing four active scan table entries (courtesy of D. Priegnitz). |
A timeline for software upgrades on the NWRT PAR is here
We recently received a second award from the National Science Foundation (NSF) for our research project "Understanding the Relationship Between Tornadoes and Debris Through Observed and Simulated Radar Data."
This fall, I had the honor and privilege to teach an OLLI class with my friend and colleague Jami Boettcher. "NEXRAD Weather Radar: How it Works and What Those Images Tell Us" kept us busy for 5 weeks this fall.
Our paper "Bootstrap Dual-Polarimetric Spectral Density Estimator" made the cover of the April 2017 issue of the IEEE Transactions on Geoscience and Remote Sensing journal.
I have accepted to serve as an associate editor for the American Meteorological Society’s Journal of Atmospheric and Oceanic Technology.
I have been chosen as the winner of the 2016 OU College of Atmospheric and Geographic Sciences Dean’s Award for Outstanding Service.
© 2020 Dr. Sebastian Torres. All rights reserved.
Last modified on 4/24/2020
