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Monetized weather radar network benefits for tornado cost reduction

Author:
Published in:
MIT Lincoln Laboratory Report NOAA-35

Summary

A monetized tornado benefit model is developed for arbitrary weather radar network configurations. Geospatial regression analyses indicate that improvement in two key radar coverage parameters--fraction of vertical space observed and cross-range horizontal resolution--lead to better tornado warning performance as characterized by tornado detection probability and false alarm ratio. Previous experimental results showing faster volume scan rates yielding greater warning performance, including increased lead times, are also incorporated into the model. Enhanced tornado warning performance, in turn, reduces casualty rates. In combination, then, it is clearly established that better and faster radar observations reduce tornado casualty rates. Furthermore, lower false alarm ratios save costs by cutting down on people's time lost when taking shelter.
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Summary

A monetized tornado benefit model is developed for arbitrary weather radar network configurations. Geospatial regression analyses indicate that improvement in two key radar coverage parameters--fraction of vertical space observed and cross-range horizontal resolution--lead to better tornado warning performance as characterized by tornado detection probability and false alarm ratio. Previous experimental...

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Weather radar network benefit model for tornadoes

Author:
Published in:
J. Appl. Meteor. Climatol., 22 April 2019, doi:10.1175/JAMC-D-18-0205.1.

Summary

A monetized tornado benefit model is developed for arbitrary weather radar network configurations. Geospatial regression analyses indicate that improvement of two key radar parameters--fraction of vertical space observed and cross-range horizontal resolution--lead to better tornado warning performance as characterized by tornado detection probability and false alarm ratio. Previous experimental results showing faster volume scan rates yielding greater warning performance are also incorporated into the model. Enhanced tornado warning performance, in turn, reduces casualty rates. In addition, lower false alarm ratios save cost by cutting down on work and personal time lost while taking shelter. The model is run on the existing contiguous United States weather radar network as well as hypothetical future configurations. Results show that the current radars provide a tornado-based benefit of ~$490M per year. The remaining benefit pool is about $260M per year that is roughly split evenly between coverage- and rapid-scanning-related gaps.
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Summary

A monetized tornado benefit model is developed for arbitrary weather radar network configurations. Geospatial regression analyses indicate that improvement of two key radar parameters--fraction of vertical space observed and cross-range horizontal resolution--lead to better tornado warning performance as characterized by tornado detection probability and false alarm ratio. Previous experimental results...

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Polarimetric observations of chaff using the WSR-88D network

Published in:
J. Appl. Meteor. Climatol., Vol. 57, No. 5, 1 May 2018, pp. 1063-1081.

Summary

Chaff is a radar countermeasure typically used by military branches in training exercises around the United States. Chaff within view of the S-band WSR-88D radars can appear prominently on radar users displays. Knowledge of chaff characteristics is useful for radar users to discriminate between chaff and weather echoes and for automated algorithms to do the same. The WSR-88D network provides dual-polarimetric capabilities across the United States, leading to the collection of a large database of chaff cases. The database is analyzed to determine the characteristics of chaff in terms of the reflectivity factor and polarimetric variables on large scales. Particular focus is given to the dynamics of differential reflectivity (ZDR) in chaff and its dependence on height. Contrary to radar data observations of chaff for a single event, this study is able to reveal a repeatable and new pattern of radar chaff observations. A discussion regarding the observed characteristics is presented, and hypotheses for the observed ZDR dynamics are put forth.
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Summary

Chaff is a radar countermeasure typically used by military branches in training exercises around the United States. Chaff within view of the S-band WSR-88D radars can appear prominently on radar users displays. Knowledge of chaff characteristics is useful for radar users to discriminate between chaff and weather echoes and for...

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Quantification of radar QPE performance based on SENSR network design possibilities

Published in:
2018 IEEE Radar Conf., RadarConf, 23-27 April 2018.

Summary

In 2016, the FAA, NOAA, DoD, and DHS initiated a feasibility study for a Spectrum Efficient National Surveillance Radar (SENSR). The goal is to assess approaches for vacating the 1.3- to 1.35-GHz radio frequency band currently allocated to FAA/DoD long-range radars so that this band can be auctioned for commercial use. As part of this goal, the participating agencies have developed preliminary performance requirements that not only assume minimum capabilities based on legacy radars, but also recognize the need for enhancements in future radar networks. The relatively low density of the legacy radar networks, especially the WSR-88D network, had led to the goal of enhancing low-altitude weather coverage. With multiple design metrics and network possibilities still available to the SENSR agencies, the benefits of low-altitude coverage must be assessed quantitatively. This study lays the groundwork for estimating Quantitative Precipitation Estimation (QPE) differences based on network density, array size, and polarimetric bias. These factors create a pareto front of cost-benefit for QPE in a new radar network, and these results will eventually be used to determine appropriate tradeoffs for SENSR requirements. Results of this study are presented in the form of two case examples that quantify errors based on polarimetric bias and elevation, along with a description of eventual application to a national network in upcoming expansion of the work.
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Summary

In 2016, the FAA, NOAA, DoD, and DHS initiated a feasibility study for a Spectrum Efficient National Surveillance Radar (SENSR). The goal is to assess approaches for vacating the 1.3- to 1.35-GHz radio frequency band currently allocated to FAA/DoD long-range radars so that this band can be auctioned for commercial...

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Command and control for multifunction phased array radar

Published in:
IEEE Trans. Geosci. Remote Sens., Vol. 55, No. 10, October 2017, pp. 5899-5912.

Summary

We discuss the challenge of managing the Multifunction Phased Array Radar (MPAR) timeline to satisfy the requirements of its multiple missions, with a particular focus on weather surveillance. This command and control (C2) function partitions the available scan time among these missions, exploits opportunities to service multiple missions simultaneously, and utilizes techniques for increasing scan rate where feasible. After reviewing the candidate MPAR architectures and relevant previous research, we describe a specific C2 framework that is consistent with a demonstrated active array architecture using overlapped subarrays to realize multiple, concurrent receive beams. Analysis of recently articulated requirements for near-airport and national-scale aircraft surveillance indicates that with this architecture, 40–60% of the MPAR scan timeline would be available for the high-fidelity weather observations currently provided by the Weather Service Radar (WSR-88D) network. We show that an appropriate use of subarray generated concurrent receive beams, in concert with previously documented, complementary techniques to increase the weather scan rate, could enable MPAR to perform full weather volume scans at a rate of 1 per minute. Published observing system simulation experiments, human-in-the-loop studies and radar-data assimilation experiments indicate that high-quality weather radar observations at this rate may significantly improve the lead time and reliability of severe weather warnings relative to current observation capabilities.
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Summary

We discuss the challenge of managing the Multifunction Phased Array Radar (MPAR) timeline to satisfy the requirements of its multiple missions, with a particular focus on weather surveillance. This command and control (C2) function partitions the available scan time among these missions, exploits opportunities to service multiple missions simultaneously, and...

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Development of a new inanimate class for the WSR-88D hydrometeor classification algorithm

Published in:
38th Conf. on Radar Meteorology, 27 August-1 September 2017.

Summary

The current implementation of the Hydrometeor Classification Algorithm (HCA) on the WSR-88D network contains two non-hydrometeor-based classes: ground clutter/anomalous propagation and biologicals. A number of commonly observed non-hydrometeor-based phenomena do not fall into either of these two HCA categories, but often are misclassified as ground clutter, biologicals, unknown, or worse yet, weather hydrometeors. Some of these phenomena include chaff, sea clutter, combustion debris and smoke, and radio frequency interference. In order to address this discrepancy, a new class (nominally named "inanimate") is being developed that encompasses many of these targets. Using this class, a distinction between non-biological and biological non-hydrometeor targets can be made and potentially separated into sub-classes for more direct identification. A discussion regarding the fuzzy logic membership functions, optimization of membership weights, and class restrictions is presented, with a focus on observations of highly stochastic differential phase estimates in all of the aforementioned targets. Recent attempts to separate the results into sub-classes using a support vector machine are presented, and examples of each target type are detailed. Details concerning eventual implementation into the WSR-88D radar product generator are addressed.
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Summary

The current implementation of the Hydrometeor Classification Algorithm (HCA) on the WSR-88D network contains two non-hydrometeor-based classes: ground clutter/anomalous propagation and biologicals. A number of commonly observed non-hydrometeor-based phenomena do not fall into either of these two HCA categories, but often are misclassified as ground clutter, biologicals, unknown, or worse...

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A new radio frequency interference filter for weather radars

Author:
Published in:
J. Atmos. Ocean. Technol., Vol. 34, No. 7, 1 July 2017, pp. 1393-1406.

Summary

A new radio frequency interference (RFI) filter algorithm for weather radars is proposed in the two-dimensional (2D) range-time/sample-time domain. Its operation in 2D space allows RFI detection at lower interference-to-noise or interference-to-signal ratios compared to filters working only in the sample-time domain while maintaining very low false alarm rates. Simulations and real weather radar data with RFI are used to perform algorithm comparisons. Results are consistent with theoretical considerations and show the 2D RFI filter to be a promising addition to the signal processing arsenal against interference with weather radars. Increased computational burden is the only drawback relative to filters currently used by operational systems.
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Summary

A new radio frequency interference (RFI) filter algorithm for weather radars is proposed in the two-dimensional (2D) range-time/sample-time domain. Its operation in 2D space allows RFI detection at lower interference-to-noise or interference-to-signal ratios compared to filters working only in the sample-time domain while maintaining very low false alarm rates. Simulations...

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A polarization technique for mitigating low-grazing-angle radar sea clutter

Published in:
IEEE Int. Microwave Symp., 4-9 June 2017.

Summary

Traditional detection schemes in conventional maritime surveillance radars may suffer serious performance degradation due to sea clutter, particularly in low-grazing-angle (LGA) geometries. In such geometries, typical statistical assumptions regarding sea clutter backscatter do not hold. Trackers can be overwhelmed by false alarms, while objects of interest can be challenging to detect. Despite several decades of attempts to devise a means of mitigating the effects of LGA sea clutter on traditional detection schemes, minimal progress has been made in developing an approach that is both robust and practical. To supplement work exploring whether polarization information might offer an effective means of enhancing target detection in sea clutter, MIT Lincoln Laboratory (MIT LL) collected a fully polarimetric X-band radar dataset on the Atlantic coast of Massachusetts Cape Ann in October 2015. Leveraging this dataset, MIT LL developed Polarimetric Co-location Layering (PCL), an algorithm that uses a fundamental polarimetric characteristic of sea clutter to retain detections on objects of interest while reducing the number of false alarms in a conventional singlepolarization radar by as many as two orders of magnitude. PCL is robust across waveform bandwidths, pulse repetition frequencies, and sea states. Moreover, PCL is practical: It can plug directly into the standard radar signal processing chain.
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Summary

Traditional detection schemes in conventional maritime surveillance radars may suffer serious performance degradation due to sea clutter, particularly in low-grazing-angle (LGA) geometries. In such geometries, typical statistical assumptions regarding sea clutter backscatter do not hold. Trackers can be overwhelmed by false alarms, while objects of interest can be challenging to...

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Wind turbine interference mitigation using a waveform diversity radar

Summary

Interference from the proliferation of wind turbines is becoming a problem for ground-based medium-to-high pulse repetition frequency (PRF) pulsed–Doppler air surveillance radars. This paper demonstrates that randomizing some parameters of the transmit waveform from pulse to pulse, a filter can be designed to suppress both the wind turbine interference and the ground clutter. Furthermore, a single coherent processing interval (CPI) is sufficient to make an unambiguous range measurement. Therefore, multiple CPIs are not needed for range disambiguation, as in the staggered PRFs techniques. First, we consider a waveform with fixed PRF but diverse (random) initial phase applied to each transmit pulse. Second, we consider a waveform with diverse (random) PRF. The theoretical results are validated through simulations and analysis of experimental data. Clutter-plus-interference suppression and range disambiguation in a single CPI may be attractive to the Federal Aviation Administration and coastal radars.
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Summary

Interference from the proliferation of wind turbines is becoming a problem for ground-based medium-to-high pulse repetition frequency (PRF) pulsed–Doppler air surveillance radars. This paper demonstrates that randomizing some parameters of the transmit waveform from pulse to pulse, a filter can be designed to suppress both the wind turbine interference and...

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WSR-88D chaff detection and characterization using an optimized hydrometeor classification algorithm

Published in:
18th Conf. on Aviation, Range, and Aerospace Meteorology, 23-26 January 2017.

Summary

Chaff presents multiple issues for aviation, air traffic controllers, and the FAA, including false weather identification and areas where flight paths may need to be altered. Chaff is a radar countermeasure commonly released from aircraft across the United States and is comprised of individual metallic strands designed to reflect certain wavelengths. Chaff returns tend to look similar to weather echoes in the reflectivity factor and radial velocity fields, and can appear as clutter, stratiform precipitation, or deep convection to the radar operator or radar algorithms. When polarimetric fields are taken into account, however, discrimination between weather and non-weather echoes has relatively high potential for success. In this work, the operational Hydrometeor Classification Algorithm (HCA) on the WSR-88D is modified to include a chaff class that can be used as input to a Chaff Detection Algorithm (CDA). This new class is designed using human-truthed chaff datasets for the collection and quantification of variable distributions, and the collected chaff cases are leveraged in the tuning of algorithm weights through the use of a metaheuristic optimization. A final CDA uses various image processing techniques to deliver a filtered output. A discussion regarding WSR-88D observations of chaff on a broad scale is provided, with particular attention given to observations of negative differential reflectivity during different stages of chaff fallout. Numerous cases are presented for analysis and characterization, both as an HCA class and as output from the filtered CDA.
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Summary

Chaff presents multiple issues for aviation, air traffic controllers, and the FAA, including false weather identification and areas where flight paths may need to be altered. Chaff is a radar countermeasure commonly released from aircraft across the United States and is comprised of individual metallic strands designed to reflect certain...

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