Publications

Refine Results

(Filters Applied) Clear All

Tagged As

Monetized weather radar network benefits for tornado cost reduction

August 29, 2019
  |
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.
READ LESS

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...

READ MORE
Monetized weather radar network benefits for tornado cost reduction

Shining light on thermophysical Near-Earth Asteroid modeling efforts

January 22, 2019
  |
Conference Paper
Author:
Katrina C. Magno
…
Published in:
1st NEO and Debris Detection Conf., 22-24 January 2019.
Topic:
asteroids
R&D area:
R&D group:

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.
READ LESS

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...

READ MORE
Shining light on thermophysical Near-Earth Asteroid modeling efforts

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.
READ LESS

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...

READ MORE
Quantification of radar QPE performance based on SENSR network design possibilities

Forecast confidence measures for deterministic storm-scale aviation forecasts

February 5, 2014
  |
Conference Paper
Author:
Mark S. Veillette
…
Published in:
4th Aviation, Range, and Aerospace Meteorology Special Symp., 2-6 February 2014.
Topic:
aviation weather
R&D area:
R&D group:

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.
READ LESS

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...

READ MORE
Forecast confidence measures for deterministic storm-scale aviation forecasts

Review of Systems-Theoretic Process Analysis (STPA) method and results to support NextGen concept assessment and validation(664.71 KB)

October 25, 2013
  |
Project Report
Author:
Eric P. Harkleroad
…
Published in:
Project Report ATC-427, MIT Lincoln Laboratory
Topic:
modeling
R&D area:
R&D group:

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.
READ LESS

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.

READ MORE
Review of Systems-Theoretic Process Analysis (STPA) method and results to support NextGen concept assessment and validation

Sector workload model for benefits analysis and convective weather capacity prediction

June 10, 2013
  |
Conference Paper
Author:
Jerry D. Welch
…
Published in:
10th USA/Europe Air Traffic Management Research and Development Sem., ATM 2013, 10-13 June 2013.
Topic:
air traffic management
R&D area:
R&D group:

Summary

En route sector capacity is determined mainly by controller workload. The operational capacity model used by the Federal Aviation Administration (FAA) provides traffic alert thresholds based entirely on hand-off workload. Its estimates are accurate for most sectors. However, it tends to over-estimate capacity in both small and large sectors because it does not account for conflicts and recurring tasks. Because of those omissions it cannot be used for accurate benefits analysis of workload-reduction initiatives, nor can it be extended to estimate capacity when hazardous weather increases the intensity of all workload types. We have previously reported on an improved model that accounts for all workload types and can be extended to handle hazardous weather. In this paper we present the results of a recent regression of that model using an extensive database of peak traffic counts for all United States en route sectors. The resulting fit quality confirms the workload basis of en route capacity. Because the model has excess degrees of freedom, the regression process returns multiple parameter combinations with nearly identical sector capacities. We analyze the impact of this ambiguity when using the model to quantify the benefits of workload reduction proposals. We also describe recent modifications to the weather-impacted version of the model to provide a more stable normalized capacity measure. We conclude with an illustration of its potential application to operational sector capacity forecasts in hazardous weather.
READ LESS

Summary

En route sector capacity is determined mainly by controller workload. The operational capacity model used by the Federal Aviation Administration (FAA) provides traffic alert thresholds based entirely on hand-off workload. Its estimates are accurate for most sectors. However, it tends to over-estimate capacity in both small and large sectors because...

READ MORE
Sector workload model for benefits analysis and convective weather capacity prediction

Risk-based modeling to support NextGen concept assessment and validation

March 1, 2013
  |
Project Report
Author:
Eric P. Harkleroad
…
Published in:
Project Report ATC-405, MIT Lincoln Laboratory
Topic:
modeling
R&D area:
R&D group:

Summary

This report provides a brief review of major risk-based modeling (RBM) approaches, with particular emphasis on how these tools can be applied during initial Next Generation Air Transportation System (NextGen) concept development and how their use can be validated. Effective safety analysis should play a role even during a new system's concept definition and development. Elements of NextGen are currently progressing through these early phases. NextGen will increasingly rely on integrating multiple systems and information together to enable improved efficiency, safety, and reduced environmental impact. Ensuring that such complex interconnected systems are developed to meet safety goals requires corresponding advances in RBM and safety assessment approaches. This report does not cover the more detailed safety analyses that must be applied to mature system concepts. Rather, the focus is on approaches for hazard identification, scoping, and coarse risk estimation for systems in the early conceptual development stage, when details on the design and operation of the system have yet to be resolved. Risk models applied is this constrained context cannot be expected to provide the same complete, quantitative results as they do for mature systems. Following a review of prior models, this report continues with recommendations for RBM development, application, validation, and coordination between NextGen efforts. Also, a discussion on safety and concept development is provided.
READ LESS

Summary

This report provides a brief review of major risk-based modeling (RBM) approaches, with particular emphasis on how these tools can be applied during initial Next Generation Air Transportation System (NextGen) concept development and how their use can be validated. Effective safety analysis should play a role even during a new...

READ MORE
Risk-based modeling to support NextGen concept assessment and validation

Analytical workload model for estimating en route sector capacity in convective weather

June 14, 2011
  |
Conference Paper
Author:
John Y. Cho
…
Published in:
9th USA/Europe Air Traffic Management Research and Development Sem., ATM 2011, 14-17 June 2011.
Topic:
air traffic control
R&D area:
R&D group:

Summary

We have extended an analytical workload model for estimating en route sector capacity to include the impact of convective weather. We use historical weather avoidance data to characterize weather blockage, which affects the sector workload in three ways: (1) Increase in the conflict resolution task rate via reduction in available airspace, (2) increase in the recurring task load through the rerouting of aircraft around weather, and (3) increase in the inter-sector coordination rate via reduction in the mean sector transit time. Application of the extended model to observed and forecast data shows promise for future use in network flow models.
READ LESS

Summary

We have extended an analytical workload model for estimating en route sector capacity to include the impact of convective weather. We use historical weather avoidance data to characterize weather blockage, which affects the sector workload in three ways: (1) Increase in the conflict resolution task rate via reduction in available...

READ MORE
Analytical workload model for estimating en route sector capacity in convective weather

A statistical learning approach to the modeling of aircraft taxi time

October 3, 2010
  |
Conference Paper
Author:
Richard K. Jordan
…
Published in:
29th Digital Avionics Systems Conf., 3 October 2010.
Topic:
aircraft
R&D area:
R&D group:

Summary

Modeling aircraft taxi operations is an important element in understanding current airport performance and where opportunities may lie for improvements. A statistical learning approach to modeling aircraft taxi time is presented in this paper. This approach allows efficient identification of relatively simple and easily interpretable models of aircraft taxi time, which are shown to yield remarkably accurate predictions when tested on actual data.
READ LESS

Summary

Modeling aircraft taxi operations is an important element in understanding current airport performance and where opportunities may lie for improvements. A statistical learning approach to modeling aircraft taxi time is presented in this paper. This approach allows efficient identification of relatively simple and easily interpretable models of aircraft taxi time...

READ MORE
A statistical learning approach to the modeling of aircraft taxi time

Predictive modeling of forecast uncertainty in the Route Availability Planning Tool (RAPT)

July 12, 2010
  |
Conference Paper
Author:
John T. Hayward
…
Published in:
2010 Intl. Conf. on Scientific Computing, CSC, 12-15 July 2010.
Topic:
aviation weather
R&D area:
R&D group:

Summary

MIT Lincoln Laboratory has developed the Route Availability Planning Tool (RAPT), which provides automated convective weather guidance to air traffic managers of the NYC metro region. Prior studies of RAPT have shown high-accuracy guidance from forecast weather, but further refinements to prevent forecast misclassification is still desirable. An attribute set of highly correlated predictors for forecast misclassification is identified. Using this attribute set, a variety of prediction models for forecast misclassification are generated and evaluated. Rule-based models, decision trees, multi-layer perceptrons, and Bayesian prediction model techniques are used. Filtering, resampling, and attribute selection methods are applied to refine model generation. Our results show promising accuracy rates for multi-layer perceptrons trained on full attribute sets.
READ LESS

Summary

MIT Lincoln Laboratory has developed the Route Availability Planning Tool (RAPT), which provides automated convective weather guidance to air traffic managers of the NYC metro region. Prior studies of RAPT have shown high-accuracy guidance from forecast weather, but further refinements to prevent forecast misclassification is still desirable. An attribute set...

READ MORE
Predictive modeling of forecast uncertainty in the Route Availability Planning Tool (RAPT)
1-10 of 18