Examining sub-daily tornado warning performance and associated environmental characteristics

2021 ◽  
Author(s):  
Makenzie J. Krocak ◽  
Matthew D. Flournoy ◽  
Harold E. Brooks
Keyword(s):  
False Alarm ◽  
Probability Of Detection ◽  
Broad Sense ◽  
False Alarms ◽  
Environmental Characteristics ◽  
False Alarm Ratio ◽  
Intermediate Products ◽  
Tornado Warning ◽  
Operational Goal

AbstractIncreasing tornado warning skill in terms of the probability of detection and false alarm ratio remains an important operational goal. Although many studies have examined tornado warning performance in a broad sense, less focus has been placed on warning performance within sub-daily convective events. In this study, we use the NWS tornado verification database to examine tornado warning performance by order-of-tornado within each convective day. We combine this database with tornado reports to relate warning performance to environmental characteristics. On convective days with multiple tornadoes, the first tornado is warned significantly less often than the middle and last tornadoes. More favorable kinematic environmental characteristics, like increasing 0–1-km shear and storm-relative helicity, are associated with better warning performance related to the first tornado of the convective day. Thermodynamic and composite parameters are less correlated to warning performance. During tornadic events, over half of false alarms occur after the last tornado of the day decays, and false alarms are twice as likely to be issued during this time than before the first tornado forms. These results indicate that forecasters may be better “primed” (or more prepared) to issue warnings on middle and last tornadoes of the day, and must overcome a higher threshold to warn on the first tornado of the day. To overcome this challenge, using kinematic environmental characteristics and intermediate products on the watch-to-warning scale may help.

scholarly journals Long-Term Performance Metrics for National Weather Service Tornado Warnings

2018 ◽  
Vol 33 (6) ◽  
pp. 1501-1511 ◽  
Author(s):  
Harold E. Brooks ◽  
James Correia
Keyword(s):  
False Alarm ◽  
Lead Time ◽  
Performance Metrics ◽  
Warning System ◽  
Probability Of Detection ◽  
False Alarms ◽  
National Weather Service ◽  
False Alarm Ratio ◽  
Tornado Warnings ◽  
Weather Service

Abstract Tornado warnings are one of the flagship products of the National Weather Service. We update the time series of various metrics of performance in order to provide baselines over the 1986–2016 period for lead time, probability of detection, false alarm ratio, and warning duration. We have used metrics (mean lead time for tornadoes warned in advance, fraction of tornadoes warned in advance) that work in a consistent way across the official changes in policy for warning issuance, as well as across points in time when unofficial changes took place. The mean lead time for tornadoes warned in advance was relatively constant from 1986 to 2011, while the fraction of tornadoes warned in advance increased through about 2006, and the false alarm ratio slowly decreased. The largest changes in performance take place in 2012 when the default warning duration decreased, and there is an apparent increased emphasis on reducing false alarms. As a result, the lead time, probability of detection, and false alarm ratio all decrease in 2012. Our analysis is based, in large part, on signal detection theory, which separates the quality of the warning system from the threshold for issuing warnings. Threshold changes lead to trade-offs between false alarms and missed detections. Such changes provide further evidence for changes in what the warning system as a whole considers important, as well as highlighting the limitations of measuring performance by looking at metrics independently.

The Influence of Weather Watch Type on the Quality of Tornado Warnings and its Implications for Future Forecasting Systems

2021 ◽  
Author(s):  
Makenzie J. Krocak ◽  
Harold E. Brooks
Keyword(s):  
False Alarm ◽  
Lead Time ◽  
Severe Weather ◽  
Probability Of Detection ◽  
False Alarm Ratio ◽  
Tornado Warnings ◽  
General Improvement ◽  
The Difference ◽  
Tornado Warning

AbstractWhile many studies have looked at the quality of forecast products, few have attempted to understand the relationship between them. We begin to consider whether or not such an influence exists by analyzing storm-based tornado warning product metrics with respect to whether they occurred within a severe weather watch and, if so, what type of watch they occurred within.The probability of detection, false alarm ratio, and lead time all show a general improvement with increasing watch severity. In fact, the probability of detection increased more as a function of watch-type severity than the change in probability of detection during the time period of analysis. False alarm ratio decreased as watch type increased in severity, but with a much smaller magnitude than the difference in probability of detection. Lead time also improved with an increase in watch-type severity. Warnings outside of any watch had a mean lead time of 5.5 minutes, while those inside of a particularly dangerous situation tornado watch had a mean lead time of 15.1 minutes. These results indicate that the existence and type of severe weather watch may have an influence on the quality of tornado warnings. However, it is impossible to separate the influence of weather watches from possible differences in warning strategy or differences in environmental characteristics that make it more or less challenging to warn for tornadoes. Future studies should attempt to disentangle these numerous influences to assess how much influence intermediate products have on downstream products.

scholarly journals Characteristics of Tornado Events and Warnings in the Southeastern United States

2019 ◽  
Vol 34 (4) ◽  
pp. 1017-1034 ◽  
Author(s):  
Alexandra K. Anderson-Frey ◽  
Yvette P. Richardson ◽  
Andrew R. Dean ◽  
Richard L. Thompson ◽  
Bryan T. Smith
Keyword(s):  
United States ◽  
False Alarm ◽  
Southeastern United States ◽  
Probability Of Detection ◽  
High Shear ◽  
Related Literature ◽  
False Alarm Ratio ◽  
Tornado Warnings ◽  
Tornado Warning

Abstract The southeastern United States has become a prime area of focus in tornado-related literature due, in part, to the abundance of tornadoes occurring in high-shear low-CAPE (HSLC) environments. Through this analysis of 4133 tornado events and 16 429 tornado warnings in the southeastern United States, we find that tornadoes in the Southeast do indeed have, on average, higher shear and lower CAPE than tornadoes elsewhere in the contiguous United States (CONUS). We also examine tornado warning skill in the form of probability of detection (POD; percent of tornadoes receiving warning prior to tornado occurrence) and false alarm ratio (FAR; percent of tornado warnings for which no corresponding tornado is detected), and find that, on average, POD is better and FAR is worse for tornadoes in the Southeast than for the CONUS as a whole. These measures of warning skill remain consistent even when we consider only HSLC tornadoes. The Southeast also has nearly double the CONUS percentage of deadly tornadoes, with the highest percentage of these deadly tornadoes occurring during the spring, the winter, and around local sunset. On average, however, the tornadoes with the lowest POD also tend to be those that are weakest and least likely to be deadly; for the most part, the most dangerous storms are indeed being successfully warned.

False Alarms, Tornado Warnings, and Tornado Casualties

2009 ◽  
Vol 1 (1) ◽  
pp. 38-53 ◽  
Author(s):  
Kevin M. Simmons ◽  
Daniel Sutter
Keyword(s):  
False Alarm ◽  
The United States ◽  
Probability Of Detection ◽  
False Alarms ◽  
Lead Times ◽  
Time Intervals ◽  
Standard Deviation Increase ◽  
False Alarm Ratio ◽  
Tornado Warnings ◽  
The Impact

Abstract This paper extends prior research on the societal value of tornado warnings to the impact of false alarms. Intuition and theory suggest that false alarms will reduce the response to warnings, yet little evidence of a “false alarm effect” has been unearthed. This paper exploits differences in the false-alarm ratio across the United States to test for a false-alarm effect in a regression model of tornado casualties from 1986 to 2004. A statistically significant and large false-alarm effect is found: tornadoes that occur in an area with a higher false-alarm ratio kill and injure more people, everything else being constant. The effect is consistent across false-alarm ratios defined over different geographies and time intervals. A one-standard-deviation increase in the false-alarm ratio increases expected fatalities by between 12% and 29% and increases expected injuries by between 14% and 32%. The reduction in the national tornado false-alarm ratio over the period reduced fatalities by 4%–11% and injuries by 4%–13%. The casualty effects of false alarms and warning lead times are approximately equal in magnitude, suggesting that the National Weather Service could not reduce casualties by trading off a higher probability of detection for a higher false-alarm ratio, or vice versa.

scholarly journals Radar Observations of Tornado-Warned Convection Associated with Tropical Cyclones over Florida

2017 ◽  
Vol 32 (1) ◽  
pp. 165-186 ◽  
Author(s):  
Steven M. Martinaitis
Keyword(s):  
False Alarm ◽  
Tropical Cyclones ◽  
Rotational Velocity ◽  
Elevation Angle ◽  
Probability Of Detection ◽  
Polarization Data ◽  
False Alarm Ratio ◽  
Tornado Warnings ◽  
Tornado Warning ◽  
Velocity Enhancement

Abstract Statistical evaluations of tornado warnings issued during recent tropical cyclone events yielded an above-average false alarm ratio. This study analyzed tornado-warned convection associated with Tropical Storms Debby (2012) and Andrea (2013) using superresolution and dual-polarization data from Weather Surveillance Radar-1988 Doppler radars located throughout the Florida peninsula to identify precursor characteristics and signatures that would distinguish tornadic events prior to tornadogenesis. A series of radar-based interrogation guidance at varying ranges from radar is presented to help facilitate the reduction of the tornado-warning false alarm ratio without compromising the probability of detection. For convection within 74.1 km from the nearest radar, low-level velocity characteristics include a rotational velocity ≥ 10.3 m s−1 (20 kt), shear across the rotation ≥ 0.010 s−1, and a contracting rotation diameter. The convection should also exhibit supercell reflectivity signatures and at least a mesocyclone velocity enhancement signature or horizontal separation of greater ZDR and KDP values. Guidance at a range from 74.1 to 129.6 km is similar except for not requiring the presence of a supercell reflectivity signature and the change of the rotational velocity guidance to ≥7.7 m s−1 (15 kt) at the 0.5°-elevation angle. Convection at a range beyond 129.6 km only requires a rotational velocity ≥ 7.7 m s−1 (15 kt) at the 0.5°-elevation angle. Evaluation of the radar interrogation guidance for tornadic events and tornado-warned convection for six tropical cyclones reduced the number of false alarm events by 28.9% and reduced the false alarm ratio from 0.740 to 0.669.

An Analysis of 2016-2018 Tornadoes and National Weather Service Tornado Warnings across the contiguous United States

2021 ◽  
Author(s):  
Evan S. Bentley ◽  
Richard L. Thompson ◽  
Barry R. Bowers ◽  
Justin G. Gibbs ◽  
Steven E. Nelson
Keyword(s):  
United States ◽  
Rotational Velocity ◽  
Radar Data ◽  
Probability Of Detection ◽  
False Alarms ◽  
National Weather Service ◽  
Low Level ◽  
Tornado Warnings ◽  
Tornado Warning ◽  
Weather Service

AbstractPrevious work has considered tornado occurrence with respect to radar data, both WSR-88D and mobile research radars, and a few studies have examined techniques to potentially improve tornado warning performance. To date, though, there has been little work focusing on systematic, large-sample evaluation of National Weather Service (NWS) tornado warnings with respect to radar-observable quantities and the near-storm environment. In this work, three full years (2016–2018) of NWS tornado warnings across the contiguous United States were examined, in conjunction with supporting data in the few minutes preceding warning issuance, or tornado formation in the case of missed events. The investigation herein examines WSR-88D and Storm Prediction Center (SPC) mesoanalysis data associated with these tornado warnings with comparisons made to the current Warning Decision Training Division (WDTD) guidance.Combining low-level rotational velocity and the significant tornado parameter (STP), as used in prior work, shows promise as a means to estimate tornado warning performance, as well as relative changes in performance as criteria thresholds vary. For example, low-level rotational velocity peaking in excess of 30 kt (15 m s−1), in a near-storm environment which is not prohibitive for tornadoes (STP > 0), results in an increased probability of detection and reduced false alarms compared to observed NWS tornado warning metrics. Tornado warning false alarms can also be reduced through limiting warnings with weak (<30 kt), broad (>1nm) circulations in a poor (STP=0) environment, careful elimination of velocity data artifacts like sidelobe contamination, and through greater scrutiny of human-based tornado reports in otherwise questionable scenarios.

scholarly journals An approach of constant false alarm ratio for improved target tracking

2020 ◽  
Vol 70 (3) ◽  
pp. 17-23
Author(s):  
Zvonko Radosavljević ◽  
Dejan Ivković
Keyword(s):  
False Alarm ◽  
Tracking Error ◽  
Probability Of Detection ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Moving Targets ◽  
False Alarm Ratio ◽  
Motion Models ◽  
Areas Of Interest

Each radar has the function of surveillance of certain areas of interest. In particular, the radar also has the function of tracking moving targets in that territory with some probability of detection, which depends on the type of detector. Constant false alarm ratio (CFAR) is a very commonly used detector. Changing the probability of target detection can directly affect the quality of tracking the moving targets. The paper presents the theoretical basis of the influence of CFAR detectors on the quality of tracking, as well as an approach to the selection of CFAR detectors, CATM CFAR, which enables better monitoring by the Interacting Multiple Model (IMM) algorithm with two motion models. Comparative analysis of CA and CATM algorithm realized by numerical simulations has shown that CATM CFAR gives less tracking error with proportionally the same computer resources.

scholarly journals Verification of Tropical Cyclone Genesis Forecasts from Global Numerical Models: Comparisons between the North Atlantic and Eastern North Pacific Basins

2016 ◽  
Vol 31 (3) ◽  
pp. 947-955 ◽  
Author(s):  
Daniel J. Halperin ◽  
Henry E. Fuelberg ◽  
Robert E. Hart ◽  
Joshua H. Cossuth
Keyword(s):  
Tropical Cyclone ◽  
False Alarm ◽  
North Atlantic ◽  
North Pacific ◽  
Probability Of Detection ◽  
Early Years ◽  
Global Models ◽  
False Alarm Ratio ◽  
The North ◽  
The North Atlantic

Abstract Accurately forecasting tropical cyclone (TC) genesis is an important operational need, especially since the National Hurricane Center’s Tropical Weather Outlook product has been extended from 2 to 5 days. A previous study by the coauthors verified North Atlantic TC genesis forecasts from five global models out to 4 days during 2004–11. This study expands on the previous research by 1) verifying TC genesis forecasts over both the Atlantic and eastern North Pacific basins, 2) extending the forecast window to 5 days, and 3) updating the analysis period through 2014. Verification statistics are presented and compared between the two basins. Probability of detection and critical success indices generally are greater over the eastern North Pacific basin compared to the North Atlantic. There is a trade-off between models that exhibit a greater probability of detection and a greater false alarm ratio, and models that exhibit a smaller false alarm ratio and a smaller probability of detection. Results also reveal that the models preferentially miss TCs over the North Atlantic (eastern North Pacific) that have a relatively small radius of the outer closed isobar (radius of maximum wind) at the forecast genesis time. Overall, global models have become a more reliable source of TC genesis guidance during the past few years compared to the early years in the dataset.

scholarly journals Evaluation of Global Flood Detection Using Satellite-Based Rainfall and a Hydrologic Model

2012 ◽  
Vol 13 (4) ◽  
pp. 1268-1284 ◽  
Author(s):  
Huan Wu ◽  
Robert F. Adler ◽  
Yang Hong ◽  
Yudong Tian ◽  
Fritz Policelli
Keyword(s):  
False Alarm ◽  
Event Detection ◽  
Global Scale ◽  
Hydrologic Model ◽  
Flood Frequency ◽  
Probability Of Detection ◽  
Flood Event ◽  
False Alarms ◽  
Pearson Type ◽  
The Impact

Abstract A new version of a real-time global flood monitoring system (GFMS) driven by Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) rainfall has been developed and implemented using a physically based hydrologic model. The purpose of this paper is to evaluate the performance of this new version of the GFMS in terms of flood event detection against flood event archives to establish a baseline of performance and directions for improvement. This new GFMS is quantitatively evaluated in terms of flood event detection during the TRMM era (1998–2010) using a global retrospective simulation (3-hourly and ⅛° spatial resolution) with the TMPA 3B42V6 rainfall. Four methods were explored to define flood thresholds from the model results, including three percentile-based statistical methods and a Log Pearson type-III flood frequency curve method. The evaluation showed the GFMS detection performance improves [increasing probability of detection (POD)] with longer flood durations and larger affected areas. The impact of dams was detected in the validation statistics, with the presence of dams tending to result in more false alarms and greater false-alarm duration. The GFMS validation statistics for flood durations &gt;3 days and for areas without dams vary across the four methods, but center around a POD of ~0.70 and a false-alarm rate (FAR) of ~0.65. The generally positive results indicate the value of this approach for monitoring and researching floods on a global scale, but also indicate limitations and directions for improvement of such approaches. These directions include improving the rainfall estimates, utilizing higher resolution in the runoff-routing model, taking into account the presence of dams, and improving the method for flood identification.

scholarly journals PERBANDINGAN TEKNIK WARM DAN COLD START PADA MODEL WRF-3DVAR ASIMILASI DATA RADAR PADA PREDIKSI HUJAN LEBAT DI WILAYAH SURABAYA DAN SEKITARNYA

2020 ◽  
Vol 21 (1) ◽  
pp. 13-21
Author(s):  
Nayla Alvina Rahma ◽  
Jaka Anugrah Ivanda Paski
Keyword(s):  
False Alarm ◽  
Cold Start ◽  
Probability Of Detection ◽  
False Alarm Ratio ◽  
Warm Start ◽  
Constant Altitude ◽  
Position Indicator

Penelitian ini bertujuan untuk mengetahui perbedaan hasil prediksi hujan WRF-3DVAR asimilasi data radar dengan menggunakan teknik warm start (spin-up 12 jam) dan cold start (tanpa spin-up). Kejadian hujan yang dianalisis adalah kejadian hujan lebat tanggal 19-20 Januari 2019 di wilayah Surabaya dan sekitarnya. Data yang digunakan untuk simulasi adalah data Global Forescast System (GFS) dan data reflektivitas radar cuaca BMKG Surabaya produk Constant Altitude Plan Position Indicator (CAPPI). Analisis dilakukan dengan membandingan kondisi awal model pada parameter suhu dan kelembaban udara untuk mengetahui efek dari metode asimilasi data. Uji keandalan model dilakukan dengan melakukan verifikasi dikotomi (hujan/tidak hujan) hasil luaran model WRF dengan data hujan di 4 titik pengamatan, yaitu di Stasiun meteorologi Juanda, Stasiun meteorologi Perak, Stasiun Klimatologi Karangploso, dan Stasiun Geofisika Tretes. Hasil menunjukkan bahwa asimilasi data radar dengan mode cold start mempunyai hasil yang lebih baik dibandingkan dengan warm start, yang ditandai dengan lebih tingginya nilai Probability of Detection (POD) dan lebih rendahnya False Alarm Ratio (FAR). Asimilasi data dengan menggunakan mode cold start memiliki performa yang lebih baik dalam mendeteksi curah hujan per jam dengan ambang batas >1 mm dan >5 mm, sedangkan curah hujan >10 mm per jam lebih baik diprediksi menggunakan mode warm start.

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