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Fun as a strategic advantage: applying lessons in engagement from commercial games to military logistics training

July 1, 2022
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Journal Article
Author:
Jesslyn D. Alekseyev
…
Published in:
Train., Educ., Learn. Sci., Vol. 59, 2022, p. 180-7.
Topic:
serious games
R&D area:
R&D group:

Summary

Digital games offer many elements to augment traditional classroom lectures and reading assignments. They enable players to explore concepts through repeat play in a low-risk environment, and allow players to integrate feedback given during gameplay and evaluate their own performance. Commercial games leverage a number of features to engage players and hold their attention. But do those engagement-improving methods have a place in instructional environments with a captive and motivated audience? Our experience building a logistics supply chain training game for the Marine Corps University suggests that yes; applying lessons in engagement from commercial games can both help improve player experience with the learning environment, and potentially improve learning outcomes.
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Summary

Digital games offer many elements to augment traditional classroom lectures and reading assignments. They enable players to explore concepts through repeat play in a low-risk environment, and allow players to integrate feedback given during gameplay and evaluate their own performance. Commercial games leverage a number of features to engage players...

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Fun as a strategic advantage: applying lessons in engagement from commercial games to military logistics training

Radar coverage analysis for the Terminal Precipitation on the Glass Program

March 4, 2022
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Project Report
Author:
John Y. Cho
…
Published in:
MIT Lincoln Laboratory Report ATC-450
Topic:
radar
R&D area:
R&D group:

Summary

The Terminal Precipitation on the Glass (TPoG) program proposes to improve the STARS precipitation depiction by adding an alternative precipitation product based on a national weather-radar-based mosaic, i.e., the NextGen Weather System (aka NextGen Weather Processor [NWP] and Common Support Services Weather [CSS-Wx]). This report describes spatial and temporal domain analyses conducted over the 146 terminal radar approach control (TRACON) airspaces that are within scope of TPoG to identify and quantify future TPoG benefits, as well as potential operational issues.
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Summary

The Terminal Precipitation on the Glass (TPoG) program proposes to improve the STARS precipitation depiction by adding an alternative precipitation product based on a national weather-radar-based mosaic, i.e., the NextGen Weather System (aka NextGen Weather Processor [NWP] and Common Support Services Weather [CSS-Wx]). This report describes spatial and temporal domain...

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Radar coverage analysis for the Terminal Precipitation on the Glass Program

CoSPA data product description

November 1, 2021
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Project Report
Author:
Diana L. Klingle-Wilson
…
Published in:
MIT Lincoln Laboratory Report ATC-449
Topic:
aviation weather
R&D area:
R&D group:

Summary

This document contains a description of Consolidated Storm Prediction for Aviation (CoSPA) data products that are packaged and distributed for external users. As described in Rappa and Troxel, 2013 [1] for Corridor Integrated Weather System (CIWS) data products, CoSPA products are categorized as gridded and non-gridded. Gridded products are typically expressed as rectangular arrays whose elements contain a data value coinciding with uniformly-spaced observations or computed results on a 2-D surface. Gridded data arrays map to the earth's surface through a map projection, for example, Lambert Conformal or Lambert Azimuthal Equal-Area. CoSPA generates only gridded products; there are no non-gridded data for CoSPA.
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Summary

This document contains a description of Consolidated Storm Prediction for Aviation (CoSPA) data products that are packaged and distributed for external users. As described in Rappa and Troxel, 2013 [1] for Corridor Integrated Weather System (CIWS) data products, CoSPA products are categorized as gridded and non-gridded. Gridded products are typically...

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CoSPA data product description

Demand and capacity modeling for advanced air mobility

August 2, 2021
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Conference Paper
Author:
Luis E. Alvarez
…
Published in:
AIAA Aviation 2021 Conf., 2-6 August 2021.
Topic:
air traffic control
R&D area:
R&D group:

Summary

Advanced Air Mobility encompasses emerging aviation technologies that transport people and cargo between local, regional, or urban locations that are currently underserved by aviation and other transportation modalities. The disruptive nature of these technologies has pushed industry, academia, and governments to devote significant investments to understand their impact on airspace risk, operational procedures, and passengers. A flexible framework was designed to assess the operational viability of these technologies and the sensitivity to a variety of assumptions. This framework is used to simulate air taxi traffic within New York City by replacing a portion of the city's taxi requests with trips taken with electric vertical takeoff and landing vehicles and evaluate the sensitivity of passenger trip time to a variety of system wide assumptions. In particular, the paper focuses on the impact of the passenger capacity, landing site vehicle capacity, and fleet size. The operation density is then compared with the current air traffic to assess operation constraints that will challenge the network UAM operations.
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Summary

Advanced Air Mobility encompasses emerging aviation technologies that transport people and cargo between local, regional, or urban locations that are currently underserved by aviation and other transportation modalities. The disruptive nature of these technologies has pushed industry, academia, and governments to devote significant investments to understand their impact on airspace...

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Demand and capacity modeling for advanced air mobility

The need for spectrum and the impact on weather observations

July 1, 2021
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Journal Article
Author:
Robert D. Palmer
…
Published in:
Bull. Am. Meteorol. Soc., Vol. 102, No. 7, July 2021, E1402-7.
Topic:
radar
R&D area:
R&D group:

Summary

One of the most significant challenges—and potential opportunities—for the scientific community is society's insatiable need for the radio spectrum. Wireless communication systems have profoundly impacted the world's economies and its inhabitants. Newer technological uses in telemedicine, Internet of Things, streaming services, intelligent transportation, etc., are driving the rapid development of 5G/6G (and beyond) wireless systems that demand ever-increasing bandwidth and performance. Without question, these wireless technologies provide an important benefit to society with the potential to mitigate the economic divide across the world. Fundamental science drives the development of future technologies and benefits society through an improved understanding of the world in which we live. Often, these studies require use of the radio spectrum, which can lead to an adversarial relationship between ever evolving technology commercialization and the quest for scientific understanding. Nowhere is this contention more acute than with atmospheric remote sensing and associated weather forecasts (Saltikoff et al. 2016; Witze 2019), which was the theme for the virtual Workshop on Spectrum Challenges and Opportunities for Weather Observations held in November 2020 and hosted by the University of Oklahoma. The workshop focused on spectrum challenges for remote sensing observations of the atmosphere, including active (e.g., weather radars, cloud radars) and passive (e.g., microwave imagers, radiometers) systems for both spaceborne and ground-based applications. These systems produce data that are crucial for weather forecasting—we chose to primarily limit the workshop scope to forecasts up to 14 days, although some observations (e.g., satellite) cover a broader range of temporal scales. Nearly 70 participants from the United States, Europe, South America, and Asia took part in a concentrated and intense discussion focused not only on current radio frequency interference (RFI) issues, but potential cooperative uses of the spectrum ("spectrum sharing"). Equally important to the workshop's international makeup, participants also represented different sectors of the community, including academia, industry, and government organizations. Given the importance of spectrum challenges to the future of scientific endeavor, the U.S. National Science Foundation (NSF) recently began the Spectrum Innovation Initiative (SII) program, which has a goal to synergistically grow 5G/6G technologies with crucial scientific needs for spectrum as an integral part of the design process. The SII program will accomplish this goal in part through establishing the first nationwide institute focused on 5G/6G technologies and science. The University of California, San Diego (UCSD), is leading an effort to compete for NSF SII funding to establish the National Center for Wireless Spectrum Research. As key partners in this effort, the University of Oklahoma (OU) and The Pennsylvania State University (PSU) hosted this workshop to bring together intellectual leaders with a focus on impacts of the spectrum revolution on weather observations and numerical weather prediction.
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Summary

One of the most significant challenges—and potential opportunities—for the scientific community is society's insatiable need for the radio spectrum. Wireless communication systems have profoundly impacted the world's economies and its inhabitants. Newer technological uses in telemedicine, Internet of Things, streaming services, intelligent transportation, etc., are driving the rapid development of...

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The need for spectrum and the impact on weather observations

Towards the next generation operational meteorological radar

July 1, 2021
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Journal Article
Author:
Mark E. Weber
…
Published in:
Bull. Am. Meteorol. Soc., Vol. 102, No. 7, July 2021, pp. E1357-82.
Topic:
radar
R&D area:
R&D group:

Summary

This article summarizes research and risk reduction that will inform acquisition decisions regarding NOAA's future national operational weather radar network. A key alternative being evaluated is polarimetric phased-array radar (PAR). Research indicates PAR can plausibly achieve fast, adaptive volumetric scanning, with associated benefits for severe-weather warning performance. We assess these benefits using storm observations and analyses, observing system simulation experiments, and real radar-data assimilation studies. Changes in the number and/or locations of radars in the future network could improve coverage at low altitude. Analysis of benefits that might be so realized indicates the possibility for additional improvement in severe weather and flash-flood warning performance, with associated reduction in casualties. Simulations are used to evaluate techniques for rapid volumetric scanning and assess data quality characteristics of PAR. Finally, we describe progress in developing methods to compensate for polarimetric variable estimate biases introduced by electronic beam-steering. A research-to-operations (R2O) strategy for the PAR alternative for the WSR-88D replacement network is presented.
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Summary

This article summarizes research and risk reduction that will inform acquisition decisions regarding NOAA's future national operational weather radar network. A key alternative being evaluated is polarimetric phased-array radar (PAR). Research indicates PAR can plausibly achieve fast, adaptive volumetric scanning, with associated benefits for severe-weather warning performance. We assess these...

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Towards the next generation operational meteorological radar

Mobile capabilities for micro-meteorological predictions: FY20 Homeland Protection and Air Traffic Control Technical Investment Program

March 26, 2021
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Project Report
Author:
Michael D. McPartland
…
Published in:
MIT Lincoln Laboratory Report TIP-146
Topic:
UAS
R&D area:
R&D group:

Summary

Existing operational numerical weather forecast systems are geographically too coarse and not sufficiently accurate to adequately support future needs in applications such as Advanced Air Mobility, Unmanned Aerial Systems, and wildfire forecasting. This is especially true with respect to wind forecasts. Principal factors contributing to this are the lack of observation data within the atmospheric boundary layer and numerical forecast models that operate on low-resolution grids. This project endeavored to address both of these issues. Firstly, by development and demonstration of specially equipped fixed-wing drones to collect atmospheric data within the boundary layer, and secondly by creating a high-resolution weather research forecast model executing on the Lincoln Laboratory Supercomputing Center. Some success was achieved in the development and flight testing of the specialized drones. Significant success was achieved in the development of the high-resolution forecasting system and demonstrating the feasibility of ingesting atmospheric observations from small airborne platforms.
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Summary

Existing operational numerical weather forecast systems are geographically too coarse and not sufficiently accurate to adequately support future needs in applications such as Advanced Air Mobility, Unmanned Aerial Systems, and wildfire forecasting. This is especially true with respect to wind forecasts. Principal factors contributing to this are the lack of...

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Mobile capabilities for micro-meteorological predictions: FY20 Homeland Protection and Air Traffic Control Technical Investment Program

Advanced Air Mobility assessment framework: FY20 Homeland Protection and Air Traffic Control Technical Investment Program

March 24, 2021
  |
Project Report
Author:
Luis E. Alvarez
…
Published in:
MIT Lincoln Laboratory Report TIP-145
R&D area:
R&D group:

Summary

Advanced Air Mobility encompasses emerging aviation technologies that transport people and cargo between local, regional, or urban locations that are currently underserved by aviation and other transportation modalities. The disruptive nature of these technologies has pushed industry, academia, and governments to devote significant investments to understand their impact on airspace risk, operational procedures, and passengers. A flexible framework was designed to assess the operational viability of these technologies and the sensitivity to a variety of assumptions. This framework is used to simulate an initial AAM implementation scenario in New York City. This scenario was created by replacing a portion of NYC taxi requests with electric vertical takeoff and landing vehicles. The framework was used to assess the sensitivity of this scenario to a variety of system assumption.
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Summary

Advanced Air Mobility encompasses emerging aviation technologies that transport people and cargo between local, regional, or urban locations that are currently underserved by aviation and other transportation modalities. The disruptive nature of these technologies has pushed industry, academia, and governments to devote significant investments to understand their impact on airspace...

READ MORE
Advanced Air Mobility assessment framework: FY20 Homeland Protection and Air Traffic Control Technical Investment Program

Geospatial QPE accuracy dependence on weather radar network configurations

October 27, 2020
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Journal Article
Author:
James M. Kurdzo
…
Published in:
J. Appl. Meteor. Climatol., Vol. 59, No. 1, 2020, pp. 1773-92.
Topic:
radar
R&D area:
R&D group:

Summary

The relatively low density of weather radar networks can lead to low-altitude coverage gaps. As existing networks are evaluated for gap-fillers and new networks are designed, the benefits of low-altitude coverage must be assessed quantitatively. This study takes a regression approach to modeling quantitative precipitation estimation (QPE) differences based on network density, antenna aperture, and polarimetric bias. Thousands of cases from the warm-season months of May–August 2015–2017 are processed using both the specific attenuation [R(A)] and reflectivity-differential reflectivity [R(Z,ZDR)] QPE methods and are compared against Automated Surface Observing System (ASOS) rain gauge data. QPE errors are quantified based on beam height, cross-radial resolution, added polarimetric bias, and observed rainfall rate. The collected data are used to construct a support vector machine regression model that is applied to the current WSR-88D network for holistic error quantification. An analysis of the effects of polarimetric bias on flash-flood rainfall rates is presented. Rainfall rates based on 2-year/1-hr return rates are used for a CONUS-wide analysis of QPE errors in extreme rainfall situations. These errors are then re-quantified using previously proposed network design scenarios with additional radars that provide enhanced estimate capabilities. Finally, a gap-filling scenario utilizing the QPE error model, flash-flood rainfall rates, population density, and potential additional WSR-88D sites is presented, exposing the highest-benefit coverage holes in augmenting the WSR-88D network (or a future network) relative to QPE performance.
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Summary

The relatively low density of weather radar networks can lead to low-altitude coverage gaps. As existing networks are evaluated for gap-fillers and new networks are designed, the benefits of low-altitude coverage must be assessed quantitatively. This study takes a regression approach to modeling quantitative precipitation estimation (QPE) differences based on...

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Geospatial QPE accuracy dependence on weather radar network configurations

Weather radar network benefit model for nontornadic thunderstorm wind casualty cost reduction

September 28, 2020
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Journal Article
Author:
John Y. Cho
…
Published in:
Wea. Climate Soc., Vol. 12, No. 4, October 2020, pp. 789-804.
Topic:
radar
R&D area:
R&D group:

Summary

An econometric geospatial benefit model for nontornadic thunderstorm wind casualty reduction is developed for meteorological radar network planning. Regression analyses on 22 years (1998–2019) of storm event and warning data show, likely for the first time, a clear dependence of nontornadic severe thunderstorm warning performance on radar coverage. Furthermore, nontornadic thunderstorm wind casualty rates are observed to be negatively correlated with better warning performance. In combination, these statistical relationships form the basis of a cost model that can be differenced between radar network configurations to generate geospatial benefit density maps. This model, applied to the current contiguous U.S. weather radar network, yields a benefit estimate of $207 million (M) yr^-1 relative to no radar coverage at all. The remaining benefit pool with respect to enhanced radar coverage and scan update rate is about $36M yr^-1. Aggregating these nontornadic thunderstorm wind results with estimates from earlier tornado and flash flood cost reduction models yields a total benefit of $1.12 billion yr^-1 for the present-day radars and a remaining radar-based benefit pool of $778M yr^-1.
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Summary

An econometric geospatial benefit model for nontornadic thunderstorm wind casualty reduction is developed for meteorological radar network planning. Regression analyses on 22 years (1998–2019) of storm event and warning data show, likely for the first time, a clear dependence of nontornadic severe thunderstorm warning performance on radar coverage. Furthermore, nontornadic...

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Weather radar network benefit model for nontornadic thunderstorm wind casualty cost reduction
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