Publications
Impacts of WSR-88D SAILS and MRLE VCP options on severe weather warning performance
July 31, 2024
Project Report
Published in:
MIT Lincoln Laboratory Report NOAA-36
Topic:
R&D area:
Summary
The impacts of supplemental adaptive intra-volume low-level scan (SAILS) and mid-volume rescan of low-level elevations (MRLE) usage on the Weather Surveillance Radar 1988-Doppler (WSR-88D) with respect to severe weather warning performance were evaluated. This is an update and expansion of an earlier study by Cho et al. (2022). Statistical methods applied to historical data from 2014–2022 yielded the following major results. Severe thunderstorm (SVR) warning performance metrics are shown in the figure below, where the vertical bars represent 95% confidence intervals and the numbers at the bottom correspond to the sample sizes. The results are divided according to the scanning option that is estimated to have been used at the time the decision to issue (or not issue) a warning was made. The first point to note is that probability of detection (POD), false alarm ratio (FAR), and mean lead time (MLT) improvements were associated with the usage of supplemental adaptive intra-volume low-level scan (SAILS or MRLE) in a statistically meaningful manner. As for the different sub-modes of SAILS, the multiple elevation scan option (MESO), i.e., SAILSx2 and SAILSx3, appeared to give more benefit than SAILSx1. However, the fact that the fastest base-scan update rates provided by SAILSx3 hardly yielded more benefit than SAILSx2 may indicate that the slowdown in volume scan update rates counteracted the more frequent base scans when going from SAILSx2 to SAILSx3. For POD and FAR, MRLE+4 significantly outperformed MESO-SAILS, which may also indicate that more frequent updates of elevations angle scans higher than the lowest tilt are needed by forecasters to make accurate SVR warning decisions.
Summary
The impacts of supplemental adaptive intra-volume low-level scan (SAILS) and mid-volume rescan of low-level elevations (MRLE) usage on the Weather Surveillance Radar 1988-Doppler (WSR-88D) with respect to severe weather warning performance were evaluated. This is an update and expansion of an earlier study by Cho et al. (2022). Statistical methods...
READ MORE
WSR-88D microburst detection performance evaluation
November 28, 2023
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-455
Summary
An empirical study of Weather Surveillance Radar 1988-Doppler (WSR-88D) microburst detection performance is conducted using Integrated Terminal Weather System (ITWS) microburst detections as reference. Data from 14 airport regions during 181 independent time periods spanning the years 2015–2022 are utilized for the evaluation. Results show that the detection and false alarm probabilities depend on event range from the WSR-88D. ITWS-level detection (~95%) and false alarm (~5%) probabilities are achieved for 0 to 20 km range, while at 20 to 30 km range, detection (~80%) and false alarm (~5%) rates meeting or exceeding Weather Systems Processor (WSP) microburst detection (≥80%) and false alarm (≤15%) probability requirements are observed. Beyond ~30 km from the radar, the WSR-88D microburst detection performance falls to operationally unacceptable levels. Timing analysis indicates that, on average, WSR-88D microburst detections lag ITWS microburst detections with a median value on the order of 30 s. The detection time difference distribution shows a normal symmetric form around zero with a thin tail extending in the positive lag direction, implying that the thin tail is responsible for the positive median lag time. The lag distribution tail is shown to be shortened, and the median lag time reduced to ~10 s, if the WSR-88D's slower base scan update modes are eliminated. The study shows that the WSR-88D (and its future replacement) could generate operationally useful microburst alerts for airports that are located close enough (less than ~20 km) to the radar. The long detection lag times for a small fraction of cases that are associated with WSR-88D scan strategies that have long base (lowest elevation angle) scan update periods is an issue that may need to be addressed if the current system is to be considered for operational air traffic control purposes. Also, the unavailability of output data from the first eight range gates (2 km) should be addressed for a future replacement radar by adding a minimum observation range requirement comparable to the Terminal Doppler Weather Radar's (TDWR; 0.5 km) to the follow-on radar program requirements.
Summary
An empirical study of Weather Surveillance Radar 1988-Doppler (WSR-88D) microburst detection performance is conducted using Integrated Terminal Weather System (ITWS) microburst detections as reference. Data from 14 airport regions during 181 independent time periods spanning the years 2015–2022 are utilized for the evaluation. Results show that the detection and false...
READ MORE
Radio frequency interference censoring scheme for Canadian Weather Radar
July 12, 2023
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-454
Summary
An automated scheme is developed for the upgraded S-band polarimetric Canadian weather radars to detect and censor radio frequency interference from wireless communication devices. The suite of algorithms employed in this scheme effectively identifies and edits out interference-contaminated reflectivity data, while preserving data dominated by weather signals. This scheme was implemented in the NextGen Weather Processor test reference system for continuous real-time testing, and is expected to be incorporated into the new Canadian Aviation Weather Systems.
Summary
An automated scheme is developed for the upgraded S-band polarimetric Canadian weather radars to detect and censor radio frequency interference from wireless communication devices. The suite of algorithms employed in this scheme effectively identifies and edits out interference-contaminated reflectivity data, while preserving data dominated by weather signals. This scheme was...
READ MORE
A deep learning-based velocity dealiasing algorithm derived from the WSR-88D open radar product generator
July 1, 2023
Journal Article
Published in:
Artificial Intelligence for the Earth Systems, Vol. 2, Issue 3, July 2023.
Summary
Radial velocity estimates provided by Doppler weather radar are critical measurements used by operational forecasters for the detection and monitoring of life-impacting storms. The sampling methods used to produce these measurements are inherently susceptible to aliasing, which produces ambiguous velocity values in regions with high winds and needs to be corrected using a velocity dealiasing algorithm (VDA). In the United States, the Weather Surveillance Radar-1988 Doppler (WSR-88D) Open Radar Product Generator (ORPG) is a processing environment that provides a world-class VDA; however, this algorithm is complex and can be difficult to port to other radar systems outside the WSR-88D network. In this work, a deep neural network (DNN) is used to emulate the two-dimensional WSR-88D ORPG dealiasing algorithm. It is shown that a DNN, specifically a customized U-Net, is highly effective for building VDAs that are accurate, fast, and portable to multiple radar types. To train the DNN model, a large dataset is generated containing aligned samples of folded and dealiased velocity pairs. This dataset contains samples collected from WSR-88D Level-II and Level-III archives and uses the ORPG dealiasing algorithm output as a source of truth. Using this dataset, a U-Net is trained to produce the number of folds at each point of a velocity image. Several performance metrics are presented using WSR-88D data. The algorithm is also applied to other non-WSR-88D radar systems to demonstrate portability to other hardware/software interfaces. A discussion of the broad applicability of this method is presented, including how other Level-III algorithms may benefit from this approach.
Summary
Radial velocity estimates provided by Doppler weather radar are critical measurements used by operational forecasters for the detection and monitoring of life-impacting storms. The sampling methods used to produce these measurements are inherently susceptible to aliasing, which produces ambiguous velocity values in regions with high winds and needs to be...
READ MORE
Visibility estimation through image analytics
June 20, 2023
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-453
Summary
MIT Lincoln Laboratory (MIT LL) has developed an algorithm, known as the Visibility Estimation through Image Analytics Algorithm (VEIA), that ingests camera imagery collected by the FAA Weather Cameras Program Office (WeatherCams) and estimates the meteorological visibility in statute miles. The algorithm uses the presence of edges in the imagery and the strength of those edges to provide an estimation of the meteorological visibility within the scene. The algorithm also combines the estimates from multiple camera images into one estimate for a site or location using information about the agreement between camera estimates and the position of the Sun relative to each camera's view. The final output for a site is a prevailing visibility estimate in statute miles that can be easily compared to existing automated surface observation systems (ASOS) and/or human-observed visibility. This report includes thorough discussion of the VEIA background, development methodology, and transition process to the WeatherCams office operational platform (Sections 2–4). A detailed software description with flow diagrams is also provided in Section 5. Section 6 provides a brief overview of future research and development related to the VEIA algorithm.
Summary
MIT Lincoln Laboratory (MIT LL) has developed an algorithm, known as the Visibility Estimation through Image Analytics Algorithm (VEIA), that ingests camera imagery collected by the FAA Weather Cameras Program Office (WeatherCams) and estimates the meteorological visibility in statute miles. The algorithm uses the presence of edges in the imagery...
READ MORE
Extended polarimetric observations of chaff using the WSR-88D weather radar network
June 20, 2023
Journal Article
Published in:
IEEE Transactions on Radar Systems, vol. 1, pp. 181-192, 2023.
Topic:
R&D area:
R&D group:
Summary
Military chaff is a metallic, fibrous radar countermeasure that is released by aircraft and rockets for diversion and masking of targets. It is often released across the United States for training purposes, and, due to its resonant cut lengths, is often observed on the S-band Weather Surveillance Radar–1988 Doppler (WSR-88D) network. Efforts to identify and characterize chaff and other non-meteorological targets algorithmically require a statistical understanding of the targets. Previous studies of chaff characteristics have provided important information that has proven to be useful for algorithmic development. However, recent changes to the WSR-88D processing suite have allowed for a vastly extended range of differential reflectivity, a prime topic of previous studies on chaff using weather radar. Motivated by these changes, a new dataset of 2.8 million range gates of chaff from 267 cases across the United States is analyzed. With a better spatiotemporal representation of cases compared to previous studies, new analyses of height dependence, as well as changes in statistics by volume coverage pattern are examined, along with an investigation of the new "full" range of differential reflectivity. A discussion of how these findings are being used in WSR-88D algorithm development is presented, specifically with a focus on machine learning and separation of different target types.
Summary
Military chaff is a metallic, fibrous radar countermeasure that is released by aircraft and rockets for diversion and masking of targets. It is often released across the United States for training purposes, and, due to its resonant cut lengths, is often observed on the S-band Weather Surveillance Radar–1988 Doppler (WSR-88D)...
READ MORE
Science applications of phased array radars
October 1, 2022
Journal Article
Published in:
Bull. Amer. Meteorological Soc. (BAMS), Vol. 103, No. 10, 2022, pp. E2370-E2390.
Summary
Phased array radars (PARs) are a promising observing technology, at the cusp of being available to the broader meteorological community. PARs offer near-instantaneous sampling of the atmosphere with flexible beam forming, multifunctionality, and low operational and maintenance costs and without mechanical inertia limitations. These PAR features are transformative compared to those offered by our current reflector-based meteorological radars. The integration of PARs into meteorological research has the potential to revolutionize the way we observe the atmosphere. The rate of adoption of PARs in research will depend on many factors, including (i) the need to continue educating the scientific community on the full technical capabilities and trade-offs of PARs through an engaging dialogue with the science and engineering communities and (ii) the need to communicate the breadth of scientific bottlenecks that PARs can overcome in atmospheric measurements and the new research avenues that are now possible using PARs in concert with other measurement systems. The former is the subject of a companion article that focuses on PAR technology while the latter is the objective here.
Summary
Phased array radars (PARs) are a promising observing technology, at the cusp of being available to the broader meteorological community. PARs offer near-instantaneous sampling of the atmosphere with flexible beam forming, multifunctionality, and low operational and maintenance costs and without mechanical inertia limitations. These PAR features are transformative compared to...
READ MORE
Multimodal physiological monitoring during virtual reality piloting tasks
August 25, 2022
Journal Article
Published in:
Multimodal Physiological Monitoring During Virtual Reality Piloting Tasks (version 1.0.0). PhysioNet. https://doi.org/10.13026/azwa-ge48.
Summary
This dataset includes multimodal physiologic, flight performance, and user interaction data streams, collected as participants performed virtual flight tasks of varying difficulty. In virtual reality, individuals flew an "Instrument Landing System" (ILS) protocol, in which they had to land an aircraft mostly relying on the cockpit instrument readings. Participants were presented with four levels of difficulty, which were generated by varying wind speed, turbulence, and visibility. Each of the participants performed 12 runs, split into 3 blocks of four consecutive runs, one run at each difficulty, in a single experimental session. The sequence of difficulty levels was presented in a counterbalanced manner across blocks. Flight performance was quantified as a function of horizontal and vertical deviation from an ideal path towards the runway as well as deviation from the prescribed ideal speed of 115 knots. Multimodal physiological signals were aggregated and synchronized using Lab Streaming Layer. Descriptions of data quality are provided to assess each data stream. The starter code provides examples of loading and plotting the time synchronized data streams, extracting sample features from the eye tracking data, and building models to predict pilot performance from the physiology data streams.
Summary
This dataset includes multimodal physiologic, flight performance, and user interaction data streams, collected as participants performed virtual flight tasks of varying difficulty. In virtual reality, individuals flew an "Instrument Landing System" (ILS) protocol, in which they had to land an aircraft mostly relying on the cockpit instrument readings. Participants were...
READ MORE
Fun as a strategic advantage: applying lessons in engagement from commercial games to military logistics training
July 1, 2022
Journal Article
Published in:
Train., Educ., Learn. Sci., Vol. 59, 2022, p. 180-7.
Topic:
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.
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...
READ MORE
Impact of WSR-88D intra-volume low-level scans on sever weather warning performance
July 1, 2022
Journal Article
Published in:
Weather Forecast., Vol. 37, No. 7, July 2022, p. 1169-98.
Summary
The statistical relationship between supplemental adaptive intra-volume low-level scan (SAILS) usage on the Weather Surveillance Radar-1988 Doppler and National Weather Service severe storm warning performance during 2014–20 is analyzed. Results show statistically significant improvement in severe thunderstorm (SVR), flash flood (FF), and tornado (TOR) warning performance associated with SAILS-on versus SAILS-off. Within the three possible SAILS modes of one (SAILSx1), two (SAILSx2), and three (SAILSx3) additional base scans per volume, for SVR, SAILSx2 and SAILSx3 are associated with better warning performance compared to SAILSx1; for FF and TOR, SAILSx3 is associated with better warning performance relative to SAILSx1 and SAILSx2. Two severe storm cases (one that spawned a tornado, one that did not) are presented where SAILS usage helped forecasters make the correct TOR warning decision, lending real-life credence to the statistical results. Furthermore, a statistical analysis of automated volume scan evaluation and termination effects, parsed by SAILS usage and mode, yield a statistically significant association between volume scan update rate and SVR warning lead time.
Summary
The statistical relationship between supplemental adaptive intra-volume low-level scan (SAILS) usage on the Weather Surveillance Radar-1988 Doppler and National Weather Service severe storm warning performance during 2014–20 is analyzed. Results show statistically significant improvement in severe thunderstorm (SVR), flash flood (FF), and tornado (TOR) warning performance associated with SAILS-on versus...
READ MORE