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Weather radar network benefit model for flash flood casualty reduction

April 1, 2020
  |
Journal Article
Author:
John Y. Cho
…
Published in:
J. Appl. Meteor. Climatol., Vol. 59, No. 4, April 2020, pp. 589-604.
Topic:
radar
R&D area:
R&D group:

Summary

A monetized flash flood casualty reduction benefit model is constructed for application to meteorological radar networks. Geospatial regression analyses show that better radar coverage of the causative rainfall improves flash flood warning performance. Enhanced flash flood warning performance is shown to decrease casualty rates. Consequently, these two effects in combination allow a model to be formed that links radar coverage to flash flood casualty rates. When this model is applied to the present-day contiguous U.S. weather radar network, results yield a flash-flood-based benefit of $316 million (M) yr-1. The remaining benefit pools are more modest ($13M yr-1 for coverage improvement and $69M yr-1 maximum for all areas of radar quantitative precipitation estimation improvements), indicative of the existing weather radar network's effectiveness in supporting the flash flood warning decision process.
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Summary

A monetized flash flood casualty reduction benefit model is constructed for application to meteorological radar networks. Geospatial regression analyses show that better radar coverage of the causative rainfall improves flash flood warning performance. Enhanced flash flood warning performance is shown to decrease casualty rates. Consequently, these two effects in combination...

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Weather radar network benefit model for flash flood casualty reduction

Wind information requirements for NextGen applications phase 7 report

February 12, 2020
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Project Report
Author:
Christopher Edwards
…
Published in:
MIT Lincoln Laboratory Report ATC-444
Topic:
air traffic control
R&D area:
R&D group:

Summary

This report details the Required Time of Arrival (RTA) performance of B757 aircraft arriving at various meter fixes across a range of altitudes from 33,000' down to 3,000' above ground level (AGL). The system tested demonstrated less than ±10 second arrival error in at least 95% of flights at meter fixes down to 7,000' AGL regardless of the forecast quality provided. Below 7,000' AGL, RTA performance significantly degraded demonstrating around 80% compliance under the best forecast and operating conditions. This report also provides a comprehensive lexicon of aviation and air traffic control related "wind" terms.
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Summary

This report details the Required Time of Arrival (RTA) performance of B757 aircraft arriving at various meter fixes across a range of altitudes from 33,000' down to 3,000' above ground level (AGL). The system tested demonstrated less than ±10 second arrival error in at least 95% of flights at meter...

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Wind information requirements for NextGen applications phase 7 report

Monetized weather radar network benefits for tornado cost reduction

August 29, 2019
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Project Report
Author:
John Y. Cho
…
Published in:
MIT Lincoln Laboratory Report NOAA-35
Topic:
modeling
R&D area:
R&D group:

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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Monetized weather radar network benefits for tornado cost reduction

A neural network approach for waveform generation and selection with multi-mission radar

April 22, 2019
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Conference Paper
Author:
James M. Kurdzo
…
Published in:
2019 IEEE Radar Conf., 22-26 April 2019.
R&D area:
R&D group:

Summary

Nonlinear frequency modulated (NLFM) pulse compression waveforms have become a mainstream methodology for radars across multiple sectors and missions, including weather observation, target tracking, and target detection. NLFM affords the ability to generate a low-sidelobe autocorrelation function and matched filter while avoiding aggressive amplitude modulation, resulting in more power incident on the target. This capability can lead to significantly lower system design costs due to the possibility of sensitivity gains on the order of 3 dB or more compared with traditional, amplitude-modulated linear frequency modulated (LFM) waveforms. Generation of an optimal NLFM waveform, however, can be an arduous task, and may involve complex optimization and non-closed-form solutions. For a multimission or cognitive radar, which may utilize a wide combination of frequencies, pulse lengths, and amplitude modulations (among other factors), this could lead to an extremely large waveform table for selection. This paper takes a neural network approach to this problem by optimizing a set of over 100 waveforms spanning a wide space and using the results to interpolate the waveform possibilities to a higher resolution. A modified form of a previous NLFM method is combined with a four-hidden-layer neural network to show the integrated and peak range sidelobes of the generated waveforms across the model training space. The results are applicable to multi-mission and cognitive radars that need precise waveform specifications in rapid succession. The expected waveform generation times are addressed and quantified, and the potential applicability to multi-mission and cognitive radars is discussed.
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Summary

Nonlinear frequency modulated (NLFM) pulse compression waveforms have become a mainstream methodology for radars across multiple sectors and missions, including weather observation, target tracking, and target detection. NLFM affords the ability to generate a low-sidelobe autocorrelation function and matched filter while avoiding aggressive amplitude modulation, resulting in more power incident...

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A neural network approach for waveform generation and selection with multi-mission radar

Weather radar network benefit model for tornadoes

February 21, 2019
  |
Journal Article
Author:
John Y. Cho
…
Published in:
J. Appl. Meteor. Climatol., 22 April 2019, doi:10.1175/JAMC-D-18-0205.1.
Topic:
radar
R&D area:
R&D group:

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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Weather radar network benefit model for tornadoes

Airport Wind Observations Architectural Analysis(2.4 MB)

July 10, 2018
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Project Report
Author:
David A. Clark
…
Published in:
Project Report ATC-443, MIT Lincoln Laboratory
Topic:
weather
R&D area:
R&D group:

Summary

Airport wind information is critical for ensuring safe aircraft operations and for managing runway configurations. Airports across the National Airspace System (NAS) are served by a wide variety of wind sensing systems that have been deployed over many decades. This analysis presents a survey of existing systems and user requirements, identifies potential shortfalls, and offers recommendations for improvements to support the long-term goals of the FAA NextGen system.
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Summary

Airport wind information is critical for ensuring safe aircraft operations and for managing runway configurations. Airports across the National Airspace System (NAS) are served by a wide variety of wind sensing systems that have been deployed over many decades. This analysis presents a survey of existing systems and user requirements...

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Airport Wind Observations Architectural Analysis

CoSPA and Traffic Flow Impact Operational Demonstration for the 2017 Convective Season(4.48 MB)

May 7, 2018
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Project Report
Author:
Joseph C. Venuti
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Published in:
Project Report ATC-441, MIT Lincoln Laboratory
Topic:
weather
R&D area:
R&D group:

Summary

MIT Lincoln Laboratory personnel conducted field observations of the Consolidated Storm Prediction for Aviation (CoSPA) 8-hr deterministic convective forecast, and the decision support tool, Traffic Flow Impact (TFI), from 6 June to 31 October 2017. Four field observations were performed during the demonstration period.
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Summary

MIT Lincoln Laboratory personnel conducted field observations of the Consolidated Storm Prediction for Aviation (CoSPA) 8-hr deterministic convective forecast, and the decision support tool, Traffic Flow Impact (TFI), from 6 June to 31 October 2017. Four field observations were performed during the demonstration period.

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CoSPA and Traffic Flow Impact Operational Demonstration for the 2017 Convective Season

Polarimetric observations of chaff using the WSR-88D network

May 1, 2018
  |
Journal Article
Author:
James M. Kurdzo
…
Published in:
J. Appl. Meteor. Climatol., Vol. 57, No. 5, 1 May 2018, pp. 1063-1081.
Topic:
radar
R&D area:
R&D group:

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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Polarimetric observations of chaff using the WSR-88D network

Quantification of radar QPE performance based on SENSR network design possibilities

April 23, 2018
  |
Conference Paper
Author:
James M. Kurdzo
…
Published in:
2018 IEEE Radar Conf., RadarConf, 23-27 April 2018.
Topic:
modeling
R&D area:
R&D group:

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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Quantification of radar QPE performance based on SENSR network design possibilities

Preliminary UAS Weather Research Roadmap(1.51 MB)

November 3, 2017
  |
Project Report
Author:
Scot E. Campbell
…
Published in:
Project Report ATC-438, MIT Lincoln Laboratory
Topic:
UAS
R&D area:
R&D group:

Summary

A companion Lincoln Laboratory report (ATC-437, “Preliminary Weather Information Gaps for UAS Operations”) identified initial gaps in the ability of current weather products to meet the needs of UAS operations. Building off of that work, this report summarizes the development of a proposed initial roadmap for research to fill the gaps that were identified.
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Summary

A companion Lincoln Laboratory report (ATC-437, “Preliminary Weather Information Gaps for UAS Operations”) identified initial gaps in the ability of current weather products to meet the needs of UAS operations. Building off of that work, this report summarizes the development of a proposed initial roadmap for research to fill the...

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Preliminary UAS Weather Research Roadmap
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