Publications
ECP 0857P final report for the NEXRAD ROC: Modified VCP 35
September 18, 2024
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-456
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Summary
This report responds to a request by the NEXRAD ROC through the FAA to close out ECP0857P in their records. It details the motivation for the modification to the radar coverage pattern called VCP 35, its deployment, and use coordinated with nearby in situ ICICLE flight missions or independent of those. Recommendations are included for future considerations to modify VCP 35.
Summary
This report responds to a request by the NEXRAD ROC through the FAA to close out ECP0857P in their records. It details the motivation for the modification to the radar coverage pattern called VCP 35, its deployment, and use coordinated with nearby in situ ICICLE flight missions or independent of...
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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
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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...
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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...
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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.
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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)...
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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...
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The 2017 Buffalo Area Icing and Radar Study (BAIRS II)
May 14, 2020
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-447
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The second Buffalo Area Icing and Radar Study (BAIRS II) was conducted during the winter of 2017. The BAIRS II partnership between Massachusetts Institute of Technology (MIT) Lincoln Laboratory (LL), the National Research Council of Canada (NRC), and Environment and Climate Change Canada (ECCC) was sponsored by the Federal Aviation Administration (FAA). It is a follow-up to the similarly sponsored partnership of the original BAIRS conducted in the winter of 2013. The original BAIRS provided in situ verification and validation of icing and hydrometeors, respectively, within the radar domain in support of a hydrometeor-classification-based automated icing hazard algorithm. The BAIRS II motivation was to: --Collect additional in situ verification and validation data, --Probe further dual polarimetric radar features associated with icing hazard, --Provide foundations for additions to the icing hazard algorithm beyond hydrometeor classifications, and --Further characterize observable microphysical conditions in terms of S-band dual polarimetric radar data. With BAIRS II, the dual polarimetric capability is provided by multiple Next Generation Weather Radar (NEXRAD) S-band radars in New York State, and the verification of the icing hazard with microphysical and hydrometeor characterizations is provided by NRC's Convair-580 instrumented research plane during five icing missions covering about 21 mission hours. The ability to reliably interpret the NEXRAD dual polarization radar-sensed thermodynamic phase of the hydrometeors (solid, liquid, mix) in the context of cloud microphysics and precipitation physics makes it possible to assess the icing hazard potential to aviation. The challenges faced are the undetectable nature of supercooled cloud droplets (for Sband) and the isotropic nature of Supercooled Large Drops (SLD). The BAIRS II mission strategy pursued was to study and probe radar-identifiable, strongly anisotropic crystal targets (dendrites and needles) with which supercooled water (and water saturated conditions) are physically linked as a means for dual polarimetric detection of icing hazard. BAIRS II employed superior optical array probes along with state and microphysical instrumentation; and, using again NEXRAD-feature-guided flight paths, was able to make advances from the original BAIRS helpful to the icing algorithm development. The key findings that are given thorough treatment in this report are: --Identification of the radar-detectable "crystal sandwich" structure from two anisotropic crystal types stratified by in situ air temperature in association with varying levels of supercooled water --with layer thicknesses observed to 2 km, --over hundred-kilometer scales matched with the mesoscale surveillance of the NEXRAD radars, --Development and application of a multi-sensor cloud phase algorithm to distinguish between liquid phase, mixed phase, and glaciated (no icing) conditions for purposes of a "truth" database and improved analysis in BAIRS II, --Development of concatenated hydrometeor size distributions to examine the in situ growth of both liquid and solid hydrometeors over a broad size spectrum; used, in part, to demonstrate differences between maritime and continental conditions, and --The Icing Hazard Levels (IHL) algorithm’s verification in icing conditions is consistent with previous work and, new, is documented to perform well when indicating "glaciated" (no icing) conditions.
Summary
The second Buffalo Area Icing and Radar Study (BAIRS II) was conducted during the winter of 2017. The BAIRS II partnership between Massachusetts Institute of Technology (MIT) Lincoln Laboratory (LL), the National Research Council of Canada (NRC), and Environment and Climate Change Canada (ECCC) was sponsored by the Federal Aviation...
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Polarimetric observations of chaff using the WSR-88D network
May 1, 2018
Journal Article
Published in:
J. Appl. Meteor. Climatol., Vol. 57, No. 5, 1 May 2018, pp. 1063-1081.
Summary
Chaff is a radar countermeasure typically used by military branches in training exercises around the United States. Chaff within view of the S-band WSR-88D radars can appear prominently on radar users displays. Knowledge of chaff characteristics is useful for radar users to discriminate between chaff and weather echoes and for automated algorithms to do the same. The WSR-88D network provides dual-polarimetric capabilities across the United States, leading to the collection of a large database of chaff cases. The database is analyzed to determine the characteristics of chaff in terms of the reflectivity factor and polarimetric variables on large scales. Particular focus is given to the dynamics of differential reflectivity (ZDR) in chaff and its dependence on height. Contrary to radar data observations of chaff for a single event, this study is able to reveal a repeatable and new pattern of radar chaff observations. A discussion regarding the observed characteristics is presented, and hypotheses for the observed ZDR dynamics are put forth.
Summary
Chaff is a radar countermeasure typically used by military branches in training exercises around the United States. Chaff within view of the S-band WSR-88D radars can appear prominently on radar users displays. Knowledge of chaff characteristics is useful for radar users to discriminate between chaff and weather echoes and for...
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Development of a new inanimate class for the WSR-88D hydrometeor classification algorithm
August 31, 2017
Conference Paper
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.
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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WSR-88D chaff detection and characterization using an optimized hydrometeor classification algorithm
January 23, 2017
Conference Paper
Published in:
18th Conf. on Aviation, Range, and Aerospace Meteorology, 23-26 January 2017.
Summary
Chaff presents multiple issues for aviation, air traffic controllers, and the FAA, including false weather identification and areas where flight paths may need to be altered. Chaff is a radar countermeasure commonly released from aircraft across the United States and is comprised of individual metallic strands designed to reflect certain wavelengths. Chaff returns tend to look similar to weather echoes in the reflectivity factor and radial velocity fields, and can appear as clutter, stratiform precipitation, or deep convection to the radar operator or radar algorithms. When polarimetric fields are taken into account, however, discrimination between weather and non-weather echoes has relatively high potential for success. In this work, the operational Hydrometeor Classification Algorithm (HCA) on the WSR-88D is modified to include a chaff class that can be used as input to a Chaff Detection Algorithm (CDA). This new class is designed using human-truthed chaff datasets for the collection and quantification of variable distributions, and the collected chaff cases are leveraged in the tuning of algorithm weights through the use of a metaheuristic optimization. A final CDA uses various image processing techniques to deliver a filtered output. A discussion regarding WSR-88D observations of chaff on a broad scale is provided, with particular attention given to observations of negative differential reflectivity during different stages of chaff fallout. Numerous cases are presented for analysis and characterization, both as an HCA class and as output from the filtered CDA.
Summary
Chaff presents multiple issues for aviation, air traffic controllers, and the FAA, including false weather identification and areas where flight paths may need to be altered. Chaff is a radar countermeasure commonly released from aircraft across the United States and is comprised of individual metallic strands designed to reflect certain...
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Evaluation of the baseline NEXRAD icing hazard project
September 17, 2015
Conference Paper
Published in:
37th Conference on Radar Meteorology, 14-18 September 2015
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MIT Lincoln Laboratory has developed an icing hazard product that is now operational throughout the NEXRAD network. This initial version of the Icing Hazard Levels (IHL) algorithm is predicated on the presence of graupel as determined by the NEXRAD Hydrometeor Classification Algorithm (HCA). Graupel indicates that rime accretion on ice crystal aggregates is present. It is inferred that the riming process occurs at the altitude that HCA reports graupel as well as to some vertical depth above. To capture some of that depth, temperature and relative humidity interest fields are computed from meteorological model data based on the technique used in the National Center for Atmospheric Research's Current Icing Potential Product and utilized within IHL as warranted. A critical aspect of the IHL development has focused on the verification of the presence of icing. Two methods are used. For the first, pilot reports of icing (PIREPs) are used to score the performance of IHL. Since PIREPs are provided with inherent time and space uncertainties, a buffer of influence is associated with each PIREP when scoring IHL. Results show the IHL as configured is an effective indicator of a potential icing hazard when HCA graupel classifications are present. Results also show the importance of radar volume coverage pattern selection in detecting weak returns in winter weather. For the second, in situ icing missions were performed within range of a dual pol NEXRAD to provide quantitative data to identify the presence of supercooled liquid water. Comparisons of in situ data to HCA classifications show that HCA graupel indications do not fully expose the icing hazard and these findings are being used to direct future attention of IHL development. This paper will describe the verification method and performance assessment of the IHL initial capability.
Summary
MIT Lincoln Laboratory has developed an icing hazard product that is now operational throughout the NEXRAD network. This initial version of the Icing Hazard Levels (IHL) algorithm is predicated on the presence of graupel as determined by the NEXRAD Hydrometeor Classification Algorithm (HCA). Graupel indicates that rime accretion on ice...
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