Publications

Refine Results

(Filters Applied) Clear All

Tagged As

Impacts of WSR-88D SAILS and MRLE VCP options on severe weather warning performance

July 31, 2024
  |
Project Report
Author:
John Y. Cho
…
Published in:
MIT Lincoln Laboratory Report NOAA-36
Topic:
radar
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.
READ LESS

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
Impacts of WSR-88D SAILS and MRLE VCP options on severe weather warning performance

WSR-88D microburst detection performance evaluation

November 28, 2023
  |
Project Report
Author:
John Y. Cho
…
Published in:
MIT Lincoln Laboratory Report ATC-455
Topic:
radar
R&D area:
R&D group:

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.
READ LESS

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
WSR-88D microburst detection performance evaluation

Visibility estimation through image analytics

June 20, 2023
  |
Project Report
Author:
Michael P. Matthews
Published in:
MIT Lincoln Laboratory Report ATC-453
Topic:
algorithms
R&D area:
R&D group:

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.
READ LESS

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
Visibility estimation through image analytics

Impact of WSR-88D intra-volume low-level scans on sever weather warning performance

July 1, 2022
  |
Journal Article
Author:
John Y. Cho
…
Published in:
Weather Forecast., Vol. 37, No. 7, July 2022, p. 1169-98.
Topic:
weather
R&D area:
R&D group:

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.
READ LESS

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
Impact of WSR-88D intra-volume low-level scans on sever weather warning performance

Radar coverage analysis for the Terminal Precipitation on the Glass Program

March 4, 2022
  |
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.
READ LESS

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...

READ MORE
Radar coverage analysis for the Terminal Precipitation on the Glass Program

Towards the next generation operational meteorological radar

July 1, 2021
  |
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:

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.
READ LESS

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...

READ MORE
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
  |
Project Report
Author:
Michael D. McPartland
…
Published in:
MIT Lincoln Laboratory Report TIP-146
Topic:
UAS
R&D area:

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.
READ LESS

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...

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

Geospatial QPE accuracy dependence on weather radar network configurations

October 27, 2020
  |
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.
READ LESS

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...

READ MORE
Geospatial QPE accuracy dependence on weather radar network configurations

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

September 28, 2020
  |
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.
READ LESS

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...

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

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
1-10 of 148