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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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Airport Wind Observations Architectural Analysis(2.4 MB)

Published in:
Project Report ATC-443, MIT Lincoln Laboratory

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

Published in:
Project Report ATC-441, MIT Lincoln Laboratory

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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Preliminary UAS Weather Research Roadmap(1.51 MB)

Published in:
Project Report ATC-438, MIT Lincoln Laboratory

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 Weather Information Gap Analysis for UAS Operations(4.88 MB)

Published in:
Project Report ATC-437, MIT Lincoln Laboratory

Summary

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report documents a preliminary quick-look identification and assessment of gaps in current weather decision support for UAS operations.
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Summary

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report...

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Preliminary weather information gap analysis for UAS operations, revision 1

Published in:
MIT Lincoln Laboratory Report ATC-437-REV-1

Summary

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report documents a preliminary quick-look identification and assessment of gaps in current weather decision support for UAS operations. An initial set of surveys and interviews with UAS operators identified 12 major gaps. These gaps were then prioritized based on the importance of the weather phenomena to UAS operations and the current availability of adequate weather information to UAS operators. Low altitude UAS operations are of particular concern. The lack of observations of ceiling, visibility, and winds near most low altitude UAS operational locations causes the validation of numerical weather forecasts of weather conditions for those locations to be the highest priority. Hazardous weather alerting for convective activity and strong surface winds are a major concern for UAS operations that could be addressed in part by access to existing FAA real time conventional aircraft weather products.
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Summary

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report...

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UAS weather research roadmap

Published in:
MIT Lincoln Laboratory Report ATC-438

Summary

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing, and the trend is expected to continue as regulations are refined to allow broader access to the airspace. The unique characteristics of UAS (e.g., extensive operations in populated areas at altitudes below 500 feet, speed capability, and control systems) may drive the need for new and unique operational strategies, many of which are highly dependent on weather conditions. The objective of this study is to identify information gaps in the ability of current weather products to meet the needs of UAS operations, and provide a roadmap of research required to fill the gaps. There are several trends in the information gaps that surfaced repeatedly. A key item is the availability of weather observations, and forecasts tailored for on-airport operations are not necessarily sufficient for off-airport operations. Surveyed users indicated that airport-specific weather information (e.g., METAR, TAFs, etc.) do not readily translate to conditions at remote launch locations, which may be 10-30 miles from the nearest airport, and are influenced by local terrain, vegetation, and water sources. Moreover, the results show significantly less weather information available to support low-altitude flight than for typical manned-flight profiles. Beyond Visual Line of Sight (BVLOS) operations are found to have higher need for weather forecasts, uncertainty information, and contingency planning than Visual Line of Sight (VLOS) operations. Furthermore, the study identifies specific gaps related to how the airspace should be managed to mitigate safety and efficiency impacts to UAS operations. The research roadmap is composed of research recommendations that are derived from the aforementioned weather information gaps. In total, there are 14 specific recommendations that define the roadmap. The first two recommendations are not explicitly tied to specific gaps; rather they are based on lessons learned through the course of research in this study. The remaining recommendations are ordered such that their priority is based on their overall significance to the operation, the maturity of the operation, and any dependence among other recommendations.
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Summary

Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing, and the trend is expected to continue as regulations are refined to allow broader access to the airspace. The unique characteristics of UAS (e.g., extensive operations in populated areas at altitudes below 500 feet, speed capability...

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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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