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Monetized weather radar network benefits for tornado cost reduction
August 29, 2019
Project Report
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.
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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Shining light on thermophysical Near-Earth Asteroid modeling efforts
January 22, 2019
Conference Paper
Published in:
1st NEO and Debris Detection Conf., 22-24 January 2019.
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Summary
Comprehensive thermophysical analyses of Near-Earth Asteroids (NEAs) provide important information about their physical properties, including visible albedo, diameter, composition, and thermal inertia. These details are integral to defining asteroid taxonomy and understanding how these objects interact with the solar system. Since infrared (IR) asteroid observations are not widely available, thermophysical modeling techniques have become valuable in simulating properties of different asteroid types. Several basic models that assume a spherical asteroid shape have been used extensively within the research community. As part of a program focused on developing a simulation of space-based IR sensors for asteroid search, the Near-Earth Asteroid Model (NEATM) developed by Harris, A. in 1998, was selected. This review provides a full derivation of the formulae behind NEATM, including the spectral flux density equation, consideration of the solar phase angle, and the geometry of the asteroid, Earth, and Sun system. It describes how to implement the model in software and explores the use of an ellipsoidal asteroid shape. It also applies the model to several asteroids observed by NASA's Near-Earth Object Wide-field Survey Explorer (NEOWISE) and compares the performance of the model to the observations.
Summary
Comprehensive thermophysical analyses of Near-Earth Asteroids (NEAs) provide important information about their physical properties, including visible albedo, diameter, composition, and thermal inertia. These details are integral to defining asteroid taxonomy and understanding how these objects interact with the solar system. Since infrared (IR) asteroid observations are not widely available, thermophysical...
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Quantification of radar QPE performance based on SENSR network design possibilities
April 23, 2018
Conference Paper
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.
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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Hybrid mixed-membership blockmodel for inference on realistic network interactions
April 5, 2018
Journal Article
Published in:
IEEE Trans. Netw. Sci. Eng., Vol. 6, No. 3, July-Sept. 2019.
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Summary
This work proposes novel hybrid mixed-membership blockmodels (HMMB) that integrate three canonical network models to capture the characteristics of real-world interactions: community structure with mixed-membership, power-law-distributed node degrees, and sparsity. This hybrid model provides the capacity needed for realism, enabling control and inference on individual attributes of interest such as mixed-membership and popularity. A rigorous inference procedure is developed for estimating the parameters of this model through iterative Bayesian updates, with targeted initialization to improve identifiability. For the estimation of mixed-membership parameters, the Cramer-Rao bound is derived by quantifying the information content in terms of the Fisher information matrix. The effectiveness of the proposed inference is demonstrated in simulations where the estimates achieve covariances close to the Cramer-Rao bound while maintaining good truth coverage. We illustrate the utility of the proposed model and inference procedure in the application of detecting a community from a few cue nodes, where success depends on accurately estimating the mixed-memberships. Performance evaluations on both simulated and real-world data show that inference with HMMB is able to recover mixed-memberships in the presence of challenging community overlap, leading to significantly improved detection performance over algorithms based on network modularity and simpler models.
Summary
This work proposes novel hybrid mixed-membership blockmodels (HMMB) that integrate three canonical network models to capture the characteristics of real-world interactions: community structure with mixed-membership, power-law-distributed node degrees, and sparsity. This hybrid model provides the capacity needed for realism, enabling control and inference on individual attributes of interest such as...
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The Offshore Precipitation Capability
September 16, 2016
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-430
Summary
In this work, machine learning and image processing methods are used to estimate radar-like precipitation intensity and echo top heights beyond the range of weather radar. The technology, called the Offshore Precipitation Capability (OPC), combines global lightning data with existing radar mosaics, five Geostationary Operational Environmental Satellite (GOES) channels, and several fields from the Rapid Refresh (RAP) 13 km numerical weather prediction model to create precipitation and echo top fields similar to those provided by existing Federal Aviation Administration (FAA) weather systems. Preprocessing and feature extraction methods are described to construct inputs for model training. A variety of machine learning algorithms are investigated to identify which provides the most accuracy. Output from the machine learning model is blended with existing radar mosaics to create weather radar-like analyses that extend into offshore regions. The resulting fields are validated using land radars and satellite precipitation measurements provided by the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement Mission (GPM) core observatory satellite. This capability is initially being developed for the Miami Oceanic airspace with the goal of providing improved situational awareness for offshore air traffic control.
Summary
In this work, machine learning and image processing methods are used to estimate radar-like precipitation intensity and echo top heights beyond the range of weather radar. The technology, called the Offshore Precipitation Capability (OPC), combines global lightning data with existing radar mosaics, five Geostationary Operational Environmental Satellite (GOES) channels, and...
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En route sector capacity model final report
January 29, 2016
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-426
Summary
Accurate predictions of en route sector capacity are vital when analyzing the benefits of proposed new air traffic management decision-support tools or new airspace designs. Controller workload is the main determinant of sector capacity. This report describes a new workload-based capacity model that improves upon the Federal Aviation Administration's current Monitor Alert capacity model. Analysts often use Monitor Alert sector capacities in evaluating the benefits of decision-support aids or airspace designs. However, Monitor Alert, which was designed to warn controllers of possible sector overload, sets sector capacity limits based solely on handoff workload and fixed procedural constraints. It ignores the effects of conflict workload and recurring workload (from activities such as monitoring, vectoring, spacing, and metering). Each workload type varies differently as traffic counts and airspace designs are changed. When used for benefits analysis, Monitor Alert's concentration on a single workload type can lead to erroneous conclusions. The new model considers all three workload types. We determine the relative contribution of the three workload types by fitting the model to the upper frontiers that appear in peak daily sector traffic counts from today's system. When we fit the Monitor Alert model to these same peak traffic counts, it can only explain the observed frontiers by hypothesizing large handoff workload. Large handoff workload would imply that decision-support aids should focus on handoff tasks. The new model fits the traffic data with less error, and shows that recurring tasks create significantly more workload in all sectors than do handoff tasks. The new model also shows that conflict workload dominates in very small sectors. These findings suggest that it is more beneficial to develop decision-support aids for recurring tasks and conflict tasks than for handoff tasks.
Summary
Accurate predictions of en route sector capacity are vital when analyzing the benefits of proposed new air traffic management decision-support tools or new airspace designs. Controller workload is the main determinant of sector capacity. This report describes a new workload-based capacity model that improves upon the Federal Aviation Administration's current...
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Percolation model of insider threats to assess the optimum number of rules
November 5, 2015
Journal Article
Published in:
Environ. Syst. Decis., Vol. 35, 2015, pp. 504-10.
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Summary
Rules, regulations, and policies are the basis of civilized society and are used to coordinate the activities of individuals who have a variety of goals and purposes. History has taught that over-regulation (too many rules) makes it difficult to compete and under-regulation (too few rules) can lead to crisis. This implies an optimal number of rules that avoids these two extremes. Rules create boundaries that define the latitude at which an individual has to perform their activities. This paper creates a Toy Model of a work environment and examines it with respect to the latitude provided to a normal individual and the latitude provided to an insider threat. Simulations with the Toy Model illustrate four regimes with respect to an insider threat: under-regulated, possibly optimal, tipping point, and over-regulated. These regimes depend upon the number of rules (N) and the minimum latitude (Lmin) required by a normal individual to carry out their activities. The Toy Model is then mapped onto the standard 1D Percolation Model from theoretical physics, and the same behavior is observed. This allows the Toy Model to be generalized to a wide array of more complex models that have been well studied by the theoretical physics community and also show the same behavior. Finally, by estimating N and Lmin, it should be possible to determine the regime of any particular environment.
Summary
Rules, regulations, and policies are the basis of civilized society and are used to coordinate the activities of individuals who have a variety of goals and purposes. History has taught that over-regulation (too many rules) makes it difficult to compete and under-regulation (too few rules) can lead to crisis. This...
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Wind information requirements for NextGen applications, phase 3 final report
December 15, 2014
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-422
Summary
Many NextGen applications depend on access to high accuracy wind data due to time-based control elements, such as required time of arrival at a meter fix under 4D-Trajectory-Based Operations/Time of Arrival Control procedures or compliance to an assigned spacing goal between aircraft under Interval Management procedures. Any errors in the ground and/or aircraft wind information relative to the truth winds actually flown through can significantly degrade the performance of the procedure. Unacceptable performance could be mitigated by improving wind information in the aircraft, for example, by using higher accuracy wind forecast models to generate wind inputs for the ground or airborne systems, updating wind information more frequently, or to upgrade the way winds are handled in the avionics systems. The work described in this report summarizes the activities conducted in FY14, which builds upon prior work. It (1) establishes the relationship of wind information accuracy to 4D-TBO and IM performance for a selection of operationally relevant scenarios to identify wind needs to support them, and (2) presents examples of what wind information content and update rate to the aircraft will deliver a given target performance level to help inform concept of operations development and datalink technology needs.
Summary
Many NextGen applications depend on access to high accuracy wind data due to time-based control elements, such as required time of arrival at a meter fix under 4D-Trajectory-Based Operations/Time of Arrival Control procedures or compliance to an assigned spacing goal between aircraft under Interval Management procedures. Any errors in the...
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Forecast confidence measures for deterministic storm-scale aviation forecasts
February 5, 2014
Conference Paper
Published in:
4th Aviation, Range, and Aerospace Meteorology Special Symp., 2-6 February 2014.
Summary
Deterministic storm-scale weather forecasts, such as those generated from the FAA's 0-8 hour CoSPA system, are highly valuable to aviation traffic managers. They provide forecasted characteristics of storm structure, strength, orientation, and coverage that are very helpful for strategic planning purposes in the National Airspace System (NAS). However, these deterministic weather forecasts contain inherent uncertainty that varies with the general weather scenario at the forecast issue time, the predicted storm type, and the forecast time horizon. This uncertainty can cause large changes in the forecast from update to update, thereby eroding user confidence and ultimately reducing the forecast's effectiveness in the decision-making process. Deterministic forecasts generally lack objective measures of this uncertainty, making it very difficult for users of the forecast to know how much confidence to have in the forecast during their decision-making process. This presentation will describe a methodology to provide measures of confidence for deterministic storm-scale forecasts. The method inputs several characteristics of the current and historical weather forecasts, such as spatial scale, intensity, weather type, orientation, permeability, and run-to-run variability of the forecasts, into a statistical model to provide a measure of confidence in a forecasted quantity. In this work, the forecasted quantity is aircraft blockage associated with key high-impact Flow Constrained Areas (FCAs) in the NAS. The results from the method, which will also be presented, provide the user with a measure of forecast confidence in several blockage categories (none, low, medium, and high) associated with the FCAs. This measure of forecast confidence is geared toward helping en-route strategic planners in the NAS make better use of deterministic storm-scale weather forecasts for air traffic management.
Summary
Deterministic storm-scale weather forecasts, such as those generated from the FAA's 0-8 hour CoSPA system, are highly valuable to aviation traffic managers. They provide forecasted characteristics of storm structure, strength, orientation, and coverage that are very helpful for strategic planning purposes in the National Airspace System (NAS). However, these deterministic...
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Review of Systems-Theoretic Process Analysis (STPA) method and results to support NextGen concept assessment and validation
October 25, 2013
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-427
Summary
This report provides an assessment of the applicability of Systems-Theoretic Process Analysis (STPA) to perform preliminary risk-based modeling of complex NextGen concepts, based on the observed application of STPA to Interval Management-Spacing (IM-S) as a case study. The report also considers the potential use of STPA as a formal tool for safety analysis at the Federal Aviation Administration. This report's sources include a report documenting the application of STPA performed by the MIT Systems Engineering Research Lab (SERL), previous reports, and input from other staff and aviation subject-matter experts.
Summary
This report provides an assessment of the applicability of Systems-Theoretic Process Analysis (STPA) to perform preliminary risk-based modeling of complex NextGen concepts, based on the observed application of STPA to Interval Management-Spacing (IM-S) as a case study. The report also considers the potential use of STPA as a formal tool...
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