Relevant bibliographies by topics / Severe Thunderstorm Warnings

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  2. Dissertations / Theses

Academic literature on the topic 'Severe Thunderstorm Warnings'

Author: Grafiati
Published: 4 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Severe Thunderstorm Warnings"

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White, Megan L., and J. Anthony Stallins. "Nonmeteorological Influences on Severe Thunderstorm Warning Issuance: A Geographically Weighted Regression-Based Analysis of County Warning Area Boundaries, Land Cover, and Demographic Variables." Weather, Climate, and Society 9, no. 3 (May 10, 2017): 421–39. http://dx.doi.org/10.1175/wcas-d-15-0070.1.

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Abstract Studies have shown that the spatial distribution of severe thunderstorm warnings demonstrates variation beyond what can be attributed to weather and climate alone. Investigating spatial patterns of these variations can provide insight into nonmeteorological factors that might lead forecasters to issue warnings. Geographically weighted regression was performed on a set of demographic and land cover descriptors to ascertain their relationships with National Weather Service (NWS) severe thunderstorm warning polygons issued by 36 NWS forecast offices in the central and southeastern United States from 2008 to 2015. County warning area (CWA) boundaries and cities were predominant sources of variability in warning counts. Global explained variance in verified and unverified severe thunderstorm warnings ranged from 67% to 81% for population, median income, and percent imperviousness across the study area, which supports the spatial influence of these variables on warning issuance. Local regression coefficients indicated that verified and unverified warning counts increased disproportionately in larger cities relative to the global trend, particularly for NWS weather forecast office locations. However, local explained variance tended to be lower in cities, possibly due to greater complexity of social and economic factors shaping warning issuance. Impacts of thunderstorm type and anthropogenic modification of existing storms should also be considered when interpreting the results of this study.
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Black, Alan W., and Walker S. Ashley. "The Relationship between Tornadic and Nontornadic Convective Wind Fatalities and Warnings." Weather, Climate, and Society 3, no. 1 (January 1, 2011): 31–47. http://dx.doi.org/10.1175/2010wcas1094.1.

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Abstract A database of tornado fatalities, nontornadic convective wind fatalities, severe thunderstorm warnings, and tornado warnings was compiled for the period 1986–2007 to assess the spatial and temporal distribution of warned and unwarned fatalities. The time of fatality and location as reported in Storm Data was compared to tornado and severe thunderstorm warnings to determine if a warning was in effect when the fatality occurred. Overall, 23.7% of tornado fatalities were unwarned, while 53.2% of nontornadic convective wind fatalities were unwarned. Most unwarned tornado fatalities occurred prior to the mid-1990s—coinciding with modernization of the National Weather Service—while unwarned nontornadic convective wind fatalities remained at a relatively elevated frequency throughout the study period. Geographic locations with high numbers of unwarned tornado and nontornadic convective wind fatalities were associated with one high-magnitude event that was unwarned rather than a series of smaller unwarned events over the period. There are many factors that contribute to warning response by the public, and the issuance of a severe thunderstorm or tornado warning is an important initial step in the warning process. A better understanding of the characteristics of warned and unwarned fatalities is important to future reduction of unwarned fatalities.
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Rauhala, Jenni, and David M. Schultz. "Severe thunderstorm and tornado warnings in Europe." Atmospheric Research 93, no. 1-3 (July 2009): 369–80. http://dx.doi.org/10.1016/j.atmosres.2008.09.026.

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Stumpf, Gregory J., and Alan E. Gerard. "National Weather Service Severe Weather Warnings as Threats-in-Motion." Weather and Forecasting 36, no. 2 (April 2021): 627–43. http://dx.doi.org/10.1175/waf-d-20-0159.1.

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AbstractThreats-in-Motion (TIM) is a warning generation approach that would enable the NWS to advance severe thunderstorm and tornado warnings from the current static polygon system to continuously updating polygons that move forward with a storm. This concept is proposed as a first stage for implementation of the Forecasting a Continuum of Environmental Threats (FACETs) paradigm, which eventually aims to deliver rapidly updating probabilistic hazard information alongside NWS warnings, watches, and other products. With TIM, a warning polygon is attached to the threat and moves forward along with it. This provides more uniform, or equitable, lead time for all locations downstream of the event. When forecaster workload is high, storms remain continually tracked and warned. TIM mitigates gaps in warning coverage and improves the handling of storm motion changes. In addition, warnings are automatically cleared from locations where the threat has passed. This all results in greater average lead times and lower average departure times than current NWS warnings, with little to no impact to average false alarm time. This is particularly noteworthy for storms expected to live longer than the average warning duration (30 or 45 min) such as long-tracked supercells that are more prevalent during significant tornado outbreaks.
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Bally, John. "The Thunderstorm Interactive Forecast System: Turning Automated Thunderstorm Tracks into Severe Weather Warnings." Weather and Forecasting 19, no. 1 (February 2004): 64–72. http://dx.doi.org/10.1175/1520-0434(2004)019<0064:ttifst>2.0.co;2.

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Hoium, Debra K., Allen J. Riordan, John Monahan, and Kermit K. Keeter. "Severe Thunderstorm and Tornado Warnings at Raleigh, North Carolina." Bulletin of the American Meteorological Society 78, no. 11 (November 1997): 2559–75. http://dx.doi.org/10.1175/1520-0477(1997)078<2559:statwa>2.0.co;2.

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James, Paul M., Bernhard K. Reichert, and Dirk Heizenreder. "NowCastMIX: Automatic Integrated Warnings for Severe Convection on Nowcasting Time Scales at the German Weather Service." Weather and Forecasting 33, no. 5 (October 1, 2018): 1413–33. http://dx.doi.org/10.1175/waf-d-18-0038.1.

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Abstract NowCastMIX is the core nowcasting guidance system at the German Weather Service. It automatically monitors several systems to capture rapidly developing high-impact mesoscale convective events, including 3D radar volume scanning, radar-based cell tracking and extrapolation, lightning detection, calibrated precipitation extrapolations, NWP, and live surface station reports. Within the context of the larger warning decision support process AutoWARN, NowCastMIX integrates the input data into a high-resolution analysis, based on a fuzzy logic approach for thunderstorm categorization and extrapolation, to provide an optimized warning solution with a 5-min update cycle for lead times of up to 1 h. Feature tracking is undertaken to optimize the direction of warning polygons, allowing individual, tangentially moving cells or cell clusters to be tracked explicitly. An adaptive ensemble clustering is deployed to reduce the spatial complexity of the resulting warning fields and smooth noisy temporal variations to a manageable level for duty forecasters. Further specialized outputs for civil aviation and for a public mobile phone warning app are generated. Now in its eighth year of operation, a comprehensive and complete set of thunderstorm analyses and nowcasts over Germany has been created, which is of unique value for ongoing research and development efforts for improving the system, as well as for addressing climatological aspects of severe convection. Verification has shown that NowCastMIX has helped to significantly improve the quality of the official warnings for severe convective weather events when used within the AutoWARN process.
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Ishihara, Masahito. "Radar Echo Population of Air-Mass Thunderstorms and Nowcasting of Thunderstorm-Induced Local Heavy Rainfalls Part II: A Feasibility Study on Nowcasting." Journal of Disaster Research 8, no. 1 (February 1, 2013): 69–80. http://dx.doi.org/10.20965/jdr.2013.p0069.

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Many air-mass thunderstorms were generated in the Tokyo metropolitan area on August 5, 2008, when a severe local rainstorm caused a flash flood in the center of Tokyo. Using three-dimensional radar reflectivity data from the Japan Meteorological Agency (JMA), nowcasting was examined concerning the peak time and peak rainfall intensity of thunderstorms. Four qualitative forecastmethods – precipitation cores aloft, time changes in vertically integrated liquid water, time changes in echo-top height, lightning activity – and three quantitative forecast methods using three parameters were adopted in eight thunderstorms related to heavy-rainfall warnings issued by the JMA on August 5, 2008. While there is much worth further examination in the method using precipitation core aloft, the other methods are not in the stage of operational use in order to forecast time and rainfall intensity at the rainfall peak of each thunderstorm.
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Cintineo, John L., Michael J. Pavolonis, Justin M. Sieglaff, Daniel T. Lindsey, Lee Cronce, Jordan Gerth, Benjamin Rodenkirch, Jason Brunner, and Chad Gravelle. "The NOAA/CIMSS ProbSevere Model: Incorporation of Total Lightning and Validation." Weather and Forecasting 33, no. 1 (February 1, 2018): 331–45. http://dx.doi.org/10.1175/waf-d-17-0099.1.

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Abstract The empirical Probability of Severe (ProbSevere) model, developed by the National Oceanic and Atmospheric Administration (NOAA) and the Cooperative Institute for Meteorological Satellite Studies (CIMSS), automatically extracts information related to thunderstorm development from several data sources to produce timely, short-term, statistical forecasts of thunderstorm intensity. More specifically, ProbSevere utilizes short-term numerical weather prediction guidance (NWP), geostationary satellite, ground-based radar, and ground-based lightning data to determine the probability that convective storm cells will produce severe weather up to 90 min in the future. ProbSevere guidance, which updates approximately every 2 min, is available to National Weather Service (NWS) Weather Forecast Offices with very short latency. This paper focuses on the integration of ground-based lightning detection data into ProbSevere. In addition, a thorough validation analysis is presented. The validation analysis demonstrates that ProbSevere has slightly less skill compared to NWS severe weather warnings, but can offer greater lead time to initial hazards. Feedback from NWS users has been highly favorable, with most forecasters responding that ProbSevere increases confidence and lead time in numerous warning situations.
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Kennedy, Patrick C., Steven A. Rutledge, Brenda Dolan, and Eric Thaler. "Observations of the 14 July 2011 Fort Collins Hailstorm: Implications for WSR-88D-Based Hail Detection and Warnings." Weather and Forecasting 29, no. 3 (June 1, 2014): 623–38. http://dx.doi.org/10.1175/waf-d-13-00075.1.

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Abstract The issuance of timely warnings for the occurrence of severe-class hail (hailstone diameters of 2.5 cm or larger) remains an ongoing challenge for operational forecasters. This study examines the application of two remotely sensed data sources between 0100 and 0400 UTC 14 July 2011 when pulse-type severe thunderstorms occurred in the jurisdiction of the Denver/Boulder National Weather Service (NWS) Forecast Office in Colorado. First, a developing hailstorm was jointly observed by the dual-polarization Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) research radar and by the operational, single-polarization NWS radar at Denver/Front Range (KFTG). During the time period leading up to the issuance of the initial severe thunderstorm warning, the dual-polarization radar data near the 0 °C altitude contained a positive differential reflectivity ZDR column (indicating a strong updraft lofting supercooled raindrops above the freezing level). Correlation coefficient ρHV reductions to ~0.93, probably due to the presence of growing hailstones, were observed above the freezing level in portions of the developing &gt;55-dBZ echo core. Second, data from the National Lightning Detection Network (NLDN), including the locations and polarity of cloud-to-ground (CG) discharges produced by several of the evening’s storms, were processed. Some association was found between the prevalence of positive CGs and storms that produced severe hail. The analyses indicate that the use of the dual-polarization data provided by the upgraded Weather Surveillance Radar-1988 Doppler (WSR-88D), in combination with the NLDN data stream, can assist operational forecasters in the real-time identification of thunderstorms that pose a severe hail threat.
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Dissertations / Theses on the topic "Severe Thunderstorm Warnings"

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Barrett, Kevin M. Greene Donald Miller. "The county bias of severe thunderstorm warnings and severe thunderstorm weather reports for the Central Texas region." Waco, Tex. : Baylor University, 2008. http://hdl.handle.net/2104/5161.

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White, Megan L. "ASSOCIATING SEVERE THUNDERSTORM WARNINGS WITH DEMOGRAPHIC AND LANDSCAPE VARIABLES: A GEOGRAPHICALLY WEIGHTED REGRESSION-BASED MAPPING OF FORECAST BIAS." UKnowledge, 2014. http://uknowledge.uky.edu/geography_etds/20.

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Severe thunderstorm warnings (SVTs) are released by meteorologists in the local forecast offices of the National Weather Service (NWS). These warnings are issued with the intent of alerting areas in the path of severe thunderstorms that human and property risk are elevated, and that appropriate precautionary measures should be taken. However, studies have shown that the spatial distribution of severe storm warnings demonstrates bias. Greater numbers of severe thunderstorm warnings sometimes are issued where population is denser. By contrast, less populated areas may be underwarned. To investigate the spatial patterns of these biases for the central and southeastern United States, geographically weighted regression was implemented on a set of demographic and land cover descriptors to ascertain their patterns of spatial association with counts of National Weather Service severe thunderstorm warnings. GWR was performed for each our independent variables (total population, median income, and percent impervious land cover) and for all three of these variables as a group. Global R2 values indicate that each individual variable as well as all three collectively explain approximately 60% of the geographical variation in severe thunderstorm warning counts. Local R2 increased in the vicinity of several urban regions, notably Atlanta, Washington, D.C., St. Louis, and Nashville. However, the independent variables did not exhibit the same spatial patterning of R2. Some cities had high local R2 for all variables. Other cities exhibited high local R2 for only one or two of these independent variables. Median income had the highest local R2 values overall. Standardized residuals confirmed significant differences among several NWS forecast offices in the number and pattern of severe thunderstorm warnings. Overall, approximately half of the influences on the distribution of severe thunderstorm warnings across the study area are related to underlying land cover and demographics. Future studies may find it productive to investigate the extent to which the spatial bias mapped in this study is an artifact of forecast culture, background thunderstorm regime, or a product of urban anthropogenic weather modification.
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"A Spatial Analysis of “Most Weather Warned” Counties by Severe Weather Phenomena in the Contiguous United States." Master's thesis, 2019. http://hdl.handle.net/2286/R.I.53568.

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abstract: Severe weather affects many regions of the United States, and has potential to greatly impact many facets of society. This study provides a climatological spatial analysis by county of severe weather warnings issued by the National Weather Service (NWS) between January 1st, 1986 to December 31st, 2017 for the contiguous United States. The severe weather warnings were issued for county-based flash flood, severe thunderstorm, and tornado phenomena issued through the study period and region. Post 2002 severe weather warnings issued by storm warning area were included in this study in the form of county-based warnings simultaneously issued for each affected county. Past studies have researched severe weather warnings issued by the NWS, however these studies are limited in geographic representation, study period, and focused on population bias. A spatial analysis of severe weather warning occurrences by county identify that (a) highest occurrences of flash flood warnings are located in the desert Southwest and Texas, (b) severe thunderstorm warning occurrence is more frequent in Arizona, portions of the Midwest, the South, and the Mid and South Atlantic states, (c) the tornado activity regions of Tornado Alley and Dixie Alley (i.e. Colorado, Kansas, Oklahoma, Arkansas, Texas, Louisiana, Mississippi, Alabama, Tennessee, and Illinois) contained the highest occurrences of tornado warnings, and (d) the highest instances of aggregate warning occurrences are found in the desert Southwest, the Midwest, and the Southern regions of the United States. Generally, severe weather warning “hot spots” tend to be located in those same regions, with greater coverage. This study concludes with a comparison of local maxima and general hot spot regions to expected regions for each phenomenon. Implications of this study are far reaching, including emergency management, and has potential to reduce risk of life.
Dissertation/Thesis
Masters Thesis Geography 2019
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