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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 >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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Cintineo, John L., Michael J. Pavolonis, Justin M. Sieglaff, and Daniel T. Lindsey. "An Empirical Model for Assessing the Severe Weather Potential of Developing Convection." Weather and Forecasting 29, no. 3 (June 1, 2014): 639–53. http://dx.doi.org/10.1175/waf-d-13-00113.1.
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Abstract The formation and maintenance of thunderstorms that produce large hail, strong winds, and tornadoes are often difficult to forecast due to their rapid evolution and complex interactions with environmental features that are challenging to observe. Given inherent uncertainties in storm development, it is intuitive to predict severe storms in a probabilistic manner. This paper presents such an approach to forecasting severe thunderstorms and their associated hazards, fusing together data from several sources as input into a statistical model. Mesoscale numerical weather prediction (NWP) models have been developed in part to forecast environments favorable to severe storm development. Geostationary satellites, such as the Geostationary Operational Environmental Satellite (GOES) series, maintain a frequently updating view of growing cumulus clouds over the contiguous United States to provide temporal trends in developing convection to forecasters. The Next Generation Weather Radar (NEXRAD) network delivers repeated scans of hydrometeors inside storms, monitoring the intensification of hydrometeor size and extent, as well as hydrometeor motion. Forecasters utilize NWP models, and GOES and NEXRAD data, at different stages of the forecast of severe storms, and the model described in this paper exploits data from each in an attempt to predict severe hazards in a more accurate and timely manner while providing uncertainty information to the forecaster. A preliminary evaluation of the model demonstrates good skill in the forecast of storms, and also displays the potential to increase lead time on severe hazards, as measured relative to the issuance times of National Weather Service (NWS) severe thunderstorm and tornado warnings and occurrence times of severe events in local storm reports.
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Karstens, Christopher D., Greg Stumpf, Chen Ling, Lesheng Hua, Darrel Kingfield, Travis M. Smith, James Correia, et al. "Evaluation of a Probabilistic Forecasting Methodology for Severe Convective Weather in the 2014 Hazardous Weather Testbed." Weather and Forecasting 30, no. 6 (November 19, 2015): 1551–70. http://dx.doi.org/10.1175/waf-d-14-00163.1.
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Abstract A proposed new method for hazard identification and prediction was evaluated with forecasters in the National Oceanic and Atmospheric Administration Hazardous Weather Testbed during 2014. This method combines hazard-following objects with forecaster-issued trends of exceedance probabilities to produce probabilistic hazard information, as opposed to the static, deterministic polygon and attendant text product methodology presently employed by the National Weather Service to issue severe thunderstorm and tornado warnings. Three components of the test bed activities are discussed: usage of the new tools, verification of storm-based warnings and probabilistic forecasts from a control–test experiment, and subjective feedback on the proposed paradigm change. Forecasters were able to quickly adapt to the new tools and concepts and ultimately produced probabilistic hazard information in a timely manner. The probabilistic forecasts from two severe hail events tested in a control–test experiment were more skillful than storm-based warnings and were found to have reliability in the low-probability spectrum. False alarm area decreased while the traditional verification metrics degraded with increasing probability thresholds. The latter finding is attributable to a limitation in applying the current verification methodology to probabilistic forecasts. Relaxation of on-the-fence decisions exposed a need to provide information for hazard areas below the decision-point thresholds of current warnings. Automated guidance information was helpful in combating potential workload issues, and forecasters raised a need for improved guidance and training to inform consistent and reliable forecasts.
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Gutter, Barrett F., Kathleen Sherman-Morris, and Michael E. Brown. "Severe Weather Watches and Risk Perception in a Hypothetical Decision Experiment." Weather, Climate, and Society 10, no. 4 (July 25, 2018): 613–23. http://dx.doi.org/10.1175/wcas-d-18-0001.1.
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Abstract A great deal of research has been conducted regarding tornado warnings and protective actions taken, including some studies in which respondents were presented with hypothetical tornado warning scenarios. Much less research has been conducted in which respondents were presented with tornado watch scenarios, even though they cover a larger area and longer time period, thus potentially disrupting a far greater number of people. To address this lack of research, surveys were used to determine the influence of severe weather watches on planned Saturday afternoon and evening activities away from the immediate vicinity of the respondent’s home. Respondents were presented a hypothetical watch scenario, in which they had some activity planned for later that afternoon or evening. Each respondent rated his or her likelihood to continue an activity depending on the severity of the watch and the length of the activity. Respondents were provided information about each hypothetical watch including duration and primary threats. Responses from the survey indicated that as the severity of the watch or the length of the activity increased, the likelihood of the respondent continuing the activity decreased. For a severe thunderstorm watch, a tornado watch, and a particularly dangerous situation (PDS) tornado watch, 36.1%, 51.2%, and 80.2% of the respondents, respectively, would not continue an activity lasting 30 min or longer.
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Karstens, Christopher D., James Correia, Daphne S. LaDue, Jonathan Wolfe, Tiffany C. Meyer, David R. Harrison, John L. Cintineo, et al. "Development of a Human–Machine Mix for Forecasting Severe Convective Events." Weather and Forecasting 33, no. 3 (May 17, 2018): 715–37. http://dx.doi.org/10.1175/waf-d-17-0188.1.
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Abstract Providing advance warning for impending severe convective weather events (i.e., tornadoes, hail, wind) fundamentally requires an ability to predict and/or detect these hazards and subsequently communicate their potential threat in real time. The National Weather Service (NWS) provides advance warning for severe convective weather through the issuance of tornado and severe thunderstorm warnings, a system that has remained relatively unchanged for approximately the past 65 years. Forecasting a Continuum of Environmental Threats (FACETs) proposes a reinvention of this system, transitioning from a deterministic product-centric paradigm to one based on probabilistic hazard information (PHI) for hazardous weather events. Four years of iterative development and rapid prototyping in the National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Testbed (HWT) with NWS forecasters and partners has yielded insights into this new paradigm by discovering efficient ways to generate, inform, and utilize a continuous flow of information through the development of a human–machine mix. Forecasters conditionally used automated object-based guidance within four levels of automation to issue deterministic products containing PHI. Forecasters accomplished this task in a timely manner while focusing on communication and conveying forecast confidence, elements considered necessary by emergency managers. Observed annual increases in the usage of first-guess probabilistic guidance by forecasters were related to improvements made to the prototyped software, guidance, and techniques. However, increasing usage of automation requires improvements in guidance, data integration, and data visualization to garner trust more effectively. Additional opportunities exist to address limitations in procedures for motion derivation and geospatial mapping of subjective probability.
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Ramis, C., R. Romero, and V. Homar. "The severe thunderstorm of 4 October 2007 in Mallorca: an observational study." Natural Hazards and Earth System Sciences 9, no. 4 (July 24, 2009): 1237–45. http://dx.doi.org/10.5194/nhess-9-1237-2009.
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Abstract. During the afternoon of 4 October 2007, a thunderstorm swept across the Island of Mallorca from southwest to northeast. Strong straight-line winds (up to 30 m/s) and heavy rain (rates up to 100 mm/h) were registered accompanying the storm. Tornadoes with an estimated intensity of F2–F3 developed nearby the city of Palma, severely affecting industrial installations. One person was killed by the impact of heavy debris while more than 10 million € in damages were attributed to the event in the industrial area only. The observed evolution of temperature, humidity, wind and pressure, as well as the sequence of radar images, reveal that a squall line was initially organized over the sea and then moved north-eastwards at an estimated speed of around 80 km/h. This paper presents an analysis of the event from an observational point of view. The aim of the study is to contribute to the characterization of these rare events in the Western Mediterranean by analyzing the observational information available for this particular extreme event. The diagnosis is aimed at helping forecasters to identify this kind of organized deep convective events and being able to issue timely warnings. The synoptic scenario shows warm and moist advection at low levels over Balearics and an upper-level trough over mainland Spain. This situation is known to be prone to deep convection in Mediterranean Spain in autumn. Radiosonde ascents from Murcia and Palma show convective instability at mid levels that can conduce to develop convection if appropriate ascents occur. A plausible lifting mechanism to trigger convection is attributed to large amplitude gravity waves, registered as short-period pressure oscillations by surface barographs.
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Soderholm, Joshua S., Kathryn I. Turner, Jordan P. Brook, Tony Wedd, and Jeffery Callaghan. "High-impact thunderstorms of the Brisbane metropolitan area." Journal of Southern Hemisphere Earth Systems Science 69, no. 1 (2019): 239. http://dx.doi.org/10.1071/es19017.
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Accurate thunderstorm warnings in the hours-to-minutes preceding impact are often limited by the complex evolution of the mesoscale atmospheric environment. To accurately capture these complexities, analysis of observations remained central to operational short-term nowcasting predictions of thunderstorms. Over the past 40 years, multiple highimpact thunderstorm events have impacted the Brisbane Metropolitan Area (BMA) of South East Queensland resulting in significant insured losses. Four of these high-impact events were the focus of the following work. These cases included three events that resulted in the greatest insured losses for the BMA, exceeding AU$4 billion (2017) (18 January 1985, 16 November 2008 and 27 November 2014) and a fourth significant event (24 December 1989). Synthesis of previous work indicates that the four high-impact cases occurred during a south-easterly change with strengthening winds ahead of the change, suggesting commonalities may exist that can be exploited for forecasting. This paper provides a detailed observational analysis of the environment and convective storms from the four BMA events to explore discriminating characteristics that may improve the skill of nowcasting. For the four BMA events, significant deep convection was observed along the change for the hours prior to the change’s arrival at the Brisbane Airport, potentially acting as an early indicator of favourable conditions for high-impact thunderstorms. It was found that the timing of the south-easterly change through Brisbane was also highly correlated for all events, occurring within a 90-min window during the mid-afternoon convective heating maximum. Despite the destructive severe weather, upper air conditions were marginal for supporting organised thunderstorms, highlighting the importance of capturing mesoscale processes, such as the south-easterly change. To further understand possible discriminators of the four high-impact BMA cases, a 10-year climatology of the mesoscale and synoptic environment associated with south-easterly change events was developed for the warm season months of November to January. It is shown that although only a small number of events are associated with high-impact BMA thunderstorms, these events share a set of conditions relating to the prechange wind shift, timing of the south-easterly change and radar signatures.
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Ripberger, Joseph T., Carol L. Silva, Hank C. Jenkins-Smith, and Mark James. "The Influence of Consequence-Based Messages on Public Responses to Tornado Warnings." Bulletin of the American Meteorological Society 96, no. 4 (April 1, 2015): 577–90. http://dx.doi.org/10.1175/bams-d-13-00213.1.
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Abstract The Central Region Headquarters of the National Weather Service (NWS) recently launched an experimental product that supplements traditional tornado and severe thunderstorm warning products with information about the potential impact of warned storms. As yet, however, we know relatively little about the influence of consequence-based messages on warning responsiveness. To address this gap, we fielded two surveys of U.S. residents that live in tornado-prone regions of the country. Both surveys contained an experiment wherein participants were randomly assigned a consequence-based tornado warning message and asked to indicate how they would respond if they were to receive such a warning. Respondents that were assigned to higher-impact categories were more likely choose protective action than respondents assigned to lower-impact categories. There was, however, a threshold beyond which escalating the projected consequences of the storm no longer increased the probability of protective action. To account for this, we show that the relationship between consequence-based messages and protective action depends on the type of action being considered. At lower levels of projected impact, increasing the expected consequences of the storm simultaneously increased the probability that respondents selected a “shelter in place” or “leave residence” option. At higher levels of projected impact, this relationship changed—increasing the projected consequences of the storm decreased the probability that respondents would shelter in place and increased the probability that they would leave their residence for what they perceived to be a safer location. In some severe storm situations, this behavior may increase rather than decrease the risks.
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Gravelle, Chad M., John R. Mecikalski, William E. Line, Kristopher M. Bedka, Ralph A. Petersen, Justin M. Sieglaff, Geoffrey T. Stano, and Steven J. Goodman. "Demonstration of a GOES-R Satellite Convective Toolkit to “Bridge the Gap” between Severe Weather Watches and Warnings: An Example from the 20 May 2013 Moore, Oklahoma, Tornado Outbreak." Bulletin of the American Meteorological Society 97, no. 1 (January 1, 2016): 69–84. http://dx.doi.org/10.1175/bams-d-14-00054.1.
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Abstract With the launch of the Geostationary Operational Environmental Satellite–R (GOES-R) series in 2016, there will be continuity of observations for the current GOES system operating over the Western Hemisphere. The GOES-R Proving Ground was established in 2008 to help prepare satellite user communities for the enhanced capabilities of GOES-R, including new instruments, imagery, and products that will have increased spectral, spatial, and temporal resolution. This is accomplished through demonstration and evaluation of proxy products that use current GOES data, higher-resolution data provided by polar-orbiting satellites, and model-derived synthetic satellite imagery. The GOES-R demonstration products presented here, made available to forecasters in near–real time (within 20 min) via the GOES-R Proving Ground, include the 0–9-h NearCast model, 0–1-h convective initiation probabilities, convective cloud-top cooling, overshooting top detection, and a pseudo–Geostationary Lightning Mapper total lightning tendency diagnostic. These products are designed to assist in identifying areas of increasing convective instability, pre-radar echo cumulus cloud growth preceding thunderstorm formation, storm updraft intensity, and potential storm severity derived from lightning trends. In turn, they provide the warning forecaster with improved situational awareness and short-term predictive information that enhance their ability to monitor atmospheric conditions preceding and associated with the development of deep convection, a time period that typically occurs between the issuance of National Weather Service (NWS) Storm Prediction Center convective watches and convective storm warnings issued by NWS forecast offices. This paper will focus on how this GOES-R satellite convective toolkit could have been used by warning forecasters to enhance near-storm environment analysis and the warning-decision-making process prior to and during the 20 May 2013 Moore, Oklahoma, tornado event.
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Lawson, John R., John S. Kain, Nusrat Yussouf, David C. Dowell, Dustan M. Wheatley, Kent H. Knopfmeier, and Thomas A. Jones. "Advancing from Convection-Allowing NWP to Warn-on-Forecast: Evidence of Progress." Weather and Forecasting 33, no. 2 (April 1, 2018): 599–607. http://dx.doi.org/10.1175/waf-d-17-0145.1.
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Abstract The Warn-on-Forecast (WoF) program, driven by advanced data assimilation and ensemble design of numerical weather prediction (NWP) systems, seeks to advance 0–3-h NWP to aid National Weather Service warnings for thunderstorm-induced hazards. An early prototype of the WoF prediction system is the National Severe Storms Laboratory (NSSL) Experimental WoF System for ensembles (NEWSe), which comprises 36 ensemble members with varied initial conditions and parameterization suites. In the present study, real-time 3-h quantitative precipitation forecasts (QPFs) during spring 2016 from NEWSe members are compared against those from two real-time deterministic systems: the operational High Resolution Rapid Refresh (HRRR, version 1) and an upgraded, experimental configuration of the HRRR. All three model systems were run at 3-km horizontal grid spacing and differ in initialization, particularly in the radar data assimilation methods. It is the impact of this difference that is evaluated herein using both traditional and scale-aware verification schemes. NEWSe, evaluated deterministically for each member, shows marked improvement over the two HRRR versions for 0–3-h QPFs, especially at higher thresholds and smaller spatial scales. This improvement diminishes with forecast lead time. The experimental HRRR model, which became operational as HRRR version 2 in August 2016, also provides added skill over HRRR version 1.
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Donavon, Rodney A., and Karl A. Jungbluth. "Evaluation of a Technique for Radar Identification of Large Hail across the Upper Midwest and Central Plains of the United States." Weather and Forecasting 22, no. 2 (April 1, 2007): 244–54. http://dx.doi.org/10.1175/waf1008.1.
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Abstract Radar data were analyzed for severe thunderstorms that produced severe hail (>19 mm diameter) across the central and northern plains of the United States during the 2001–04 convective seasons. Results showed a strongly linear relationship between the 50-dBZ echo height and the height of the melting level—so strong that a severe hail warning methodology was successfully deployed at the National Weather Service Warning and Forecast Offices in North Dakota and Iowa. Specifically, for each of 183 severe hailstorms, the 50-dBZ echo height near the hail event time was plotted against the depth of the environmental melting level. Linear regression revealed a coefficient of determination of 0.86, which suggested a strong linear relationship between the 50-dBZ echo height and the melting-level depth for the severe hail producing storms. As the height of the melting level increased, the expected 50-dBZ echo height increased. A severe warning criterion for large hail was based on the 10th percentile from the linear regression, producing a probability of detection of 90% and a false alarm rate of 22%. Additional analysis found that the 50-dBZ echo-height technique performs very well for weakly to moderately sheared thunderstorm environments. However, for strongly sheared, supercell-type environments, signatures such as weak-echo regions and three-body scatter spikes led to more rapid severe thunderstorm detection in many cases.
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Schultz, Christopher J., Walter A. Petersen, and Lawrence D. Carey. "Preliminary Development and Evaluation of Lightning Jump Algorithms for the Real-Time Detection of Severe Weather." Journal of Applied Meteorology and Climatology 48, no. 12 (December 1, 2009): 2543–63. http://dx.doi.org/10.1175/2009jamc2237.1.
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Abstract Previous studies have demonstrated that rapid increases in total lightning activity (intracloud + cloud-to-ground) are often observed tens of minutes in advance of the occurrence of severe weather at the ground. These rapid increases in lightning activity have been termed “lightning jumps.” Herein, the authors document a positive correlation between lightning jumps and the manifestation of severe weather in thunderstorms occurring across the Tennessee Valley and Washington D.C. A total of 107 thunderstorms from the Tennessee Valley; Washington, D.C.; Dallas, Texas; and Houston, Texas, were examined in this study. Of the 107 thunderstorms, 69 thunderstorms fall into the category of nonsevere and 38 into the category of severe. From the dataset of 69 isolated nonsevere thunderstorms, an average, peak, 1-min flash rate of 10 flashes per minute was determined. A variety of severe thunderstorm types were examined for this study, including a mesoscale convective system, mesoscale convective vortex, tornadic outer rainbands of tropical remnants, supercells, and pulse severe thunderstorms. Of the 107 thunderstorms, 85 thunderstorms (47 nonsevere, 38 severe) were from the Tennessee Valley and Washington, D.C., and these 85 thunderstorms tested six lightning jump algorithm configurations (Gatlin, Gatlin 45, 2σ, 3σ, Threshold 10, and Threshold 8). Performance metrics for each algorithm were then calculated, yielding encouraging results from the limited sample of 85 thunderstorms. The 2σ lightning jump algorithm had a high probability of detection (POD; 87%), a modest false-alarm rate (FAR; 33%), and a solid Heidke skill score (0.75). These statistics exceed current NWS warning statistics with this dataset; however, this algorithm needs further testing because there is a large difference in sample sizes. A second and more simplistic lightning jump algorithm named the Threshold 8 lightning jump algorithm also shows promise, with a POD of 81% and a FAR of 41%. Average lead times to severe weather occurrence for these two algorithms were 23 min. The overall goal of this study is to advance the development of an operationally applicable jump algorithm that can be used with either total lightning observations made from the ground, or in the near future from space using the Geostationary Operational Environmental Satellite Series R (GOES-R) Geostationary Lightning Mapper.
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Cintineo, John L., Michael J. Pavolonis, Justin M. Sieglaff, and Andrew K. Heidinger. "Evolution of Severe and Nonsevere Convection Inferred from GOES-Derived Cloud Properties." Journal of Applied Meteorology and Climatology 52, no. 9 (September 2013): 2009–23. http://dx.doi.org/10.1175/jamc-d-12-0330.1.
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AbstractGeostationary satellites [e.g., the Geostationary Operational Environmental Satellite (GOES)] provide high temporal resolution of cloud development and motion, which is essential to the study of many mesoscale phenomena, including thunderstorms. Initial research on thunderstorm growth with geostationary imagery focused on the mature stages of storm evolution, whereas more recent research on satellite-observed storm growth has concentrated on convective initiation, often defined arbitrarily as the presence of a given radar echo threshold. This paper seeks to link the temporal trends in robust GOES-derived cloud properties with the future occurrence of severe-weather radar signatures during the development phase of thunderstorm evolution, which includes convective initiation. Two classes of storms (severe and nonsevere) are identified and tracked over time in satellite imagery, providing distributions of satellite growth rates for each class. The relationship between the temporal trends in satellite-derived cloud properties and Next Generation Weather Radar (NEXRAD)-derived storm attributes is used to show that this satellite-based approach can potentially be used to extend severe-weather-warning lead times (with respect to radar-derived signatures), without a substantial increase in false alarms. In addition, the effect of varying temporal sampling is investigated on several storms during a period of GOES super-rapid-scan operations (SRSOR). It is found that, from a satellite perspective, storms evolve significantly on time scales shorter than the current GOES operational scan strategies.
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Pettegrew, Brian P., Patrick S. Market, Raymond A. Wolf, Ronald L. Holle, and Nicholas W. S. Demetriades. "A Case Study of Severe Winter Convection in the Midwest." Weather and Forecasting 24, no. 1 (February 1, 2009): 121–39. http://dx.doi.org/10.1175/2008waf2007103.1.
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Abstract Between 2100 UTC 11 February 2003 and 0200 UTC 12 February 2003, a line of thunderstorms passed swiftly through parts of eastern Iowa and into north-central Illinois. Although this storm somewhat resembled a warm season, line-type mesoscale convective system, it was unique in that the thunderstorm winds exceeded the severe criterion (50 kt; 25.7 m s−1) during a snowburst. While the parent snowband deposited only 4 cm of snow, it did so in a short period and created a treacherous driving situation because of the ensuing near-whiteout conditions caused by strong winds that reached the National Weather Service severe criteria, as the line moved across central Illinois. Such storms in the cold season rarely occur and are largely undocumented; the present work seeks to fill this void in the existing literature. While this system superficially resembled a more traditional warm season squall line, deeper inspection revealed a precipitation band that failed to conform to that paradigm. Radar analysis failed to resolve any of the necessary warm season signatures, as maximum reflectivities of only 40–45 dBZ reached no higher than 3.7 km above ground level. The result was low-topped convection in a highly sheared environment. Moreover, winds in excess of 50 kt (25.7 m s−1) occurred earlier in the day without thunderstorm activity, upstream of the eventual severe thundersnow location. Perhaps of greatest importance is the fact that the winds in excess of the severe criterion were more the result of boundary layer mixing, and largely coincident with the parent convective line. This event was a case of forced convection, dynamically linked to its parent cold front via persistent frontogenesis and the convective instability associated with it; winds sufficient for a severe thunderstorm warning, while influenced by convection, resulted from high momentum mixing downward through a dry-adiabatic layer.
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Naglic, MS, Steven J. "National Weather Service Storm-based (polygon) Warnings." Journal of Emergency Management 5, no. 5 (September 1, 2007): 14. http://dx.doi.org/10.5055/jem.2007.0019.
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On October 1, 2007 NOAA’s National Weather Service began a major service change. Short-term warnings for tornadoes, severe thunderstorms, flash floods, areal floods, and marine hazards have migrated from being issued for entire counties, parishes, or zones to those that are more geographically specific. The stormbased polygon system will make possible the warning of small portions of individual counties or adjoining counties, and as a result only warn that portion of the population that will be impacted by the storm.
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Bonelli, P., and P. Marcacci. "Thunderstorm nowcasting by means of lightning and radar data: algorithms and applications in northern Italy." Natural Hazards and Earth System Sciences 8, no. 5 (October 28, 2008): 1187–98. http://dx.doi.org/10.5194/nhess-8-1187-2008.
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Abstract. Thunderstorms and their ground effects, such as flash floods, hail, lightning, strong winds, and tornadoes, are responsible for most weather damages in northern Italy, especially in the warm season from May to September. A nowcasting and warning system focused on severe thunderstorm events would be useful to reduce risks for people involved in outside activities and for electric, telecommunication, and sensitive industrial business. C-band radar and Lighting Location Systems provide useful, fast and high resolution data for the detection of convective systems and for following their dynamics. The whole of northern Italy is covered by radar with a resolution of 1 km and by a lightning network with a mean accuracy of 0.5 km on the single point of impact. The authors present an algorithm developed for tracking high intensity storm cells by means of radar and lightning data. Application to northern Italy reveals that tracking thunderstorm cells can be used as an alert system that may help prevent damages from extreme weather, as well as allowing for studying the correlation among lightning, rainfall and tornado occurrence. Assessing the algorithm skill is also discussed, and a forecast verification method is described and applied for the duration of a thunderstorm season.
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Roberts, Rita D., Donald Burgess, and Matthew Meister. "Developing Tools for Nowcasting Storm Severity." Weather and Forecasting 21, no. 4 (August 1, 2006): 540–58. http://dx.doi.org/10.1175/waf930.1.
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Abstract A conceptual model is presented for developing a new tool for nowcasting severe thunderstorms using existing operational data. Selected output from two operational, automated, weather detection and forecasting systems have been combined together within a fuzzy logic–based, data fusion system to test the concept and produce 15-min nowcasts of severe weather. The NCAR Auto-Nowcast System provides information and nowcasts on the evolving boundary layer and storm initiation, growth, and decay. The National Severe Storms Laboratory Warning Decision Support System (WDSS) identifies severe weather attributes within storms and provides storm-centric and specific detections of strong winds, mesocyclones, tornadoes, and probabilities of hail and severe hail. A modified version of the Auto-Nowcast System is employed as the engine for combining the Auto-Nowcast gridded output with the object-based WDSS output. Severe thunderstorm nowcasts are compared with available spotter reports for a multicellular, hail-producing squall-line event and a tornadic supercell event. Proof of concept is demonstrated and the results are encouraging as some skill is observed with the 15-min nowcasts. Many challenges still exist in producing a robust tool and these challenges are discussed.
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del Moral, Anna, Tammy M. Weckwerth, Tomeu Rigo, Michael M. Bell, and María Carmen Llasat. "C-Band Dual-Doppler Retrievals in Complex Terrain: Improving the Knowledge of Severe Storm Dynamics in Catalonia." Remote Sensing 12, no. 18 (September 10, 2020): 2930. http://dx.doi.org/10.3390/rs12182930.
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Convective activity in Catalonia (northeastern Spain) mainly occurs during summer and autumn, with severe weather occurring 33 days per year on average. In some cases, the storms have unexpected propagation characteristics, likely due to a combination of the complex topography and the thunderstorms’ propagation mechanisms. Partly due to the local nature of the events, numerical weather prediction models are not able to accurately nowcast the complex mesoscale mechanisms (i.e., local influence of topography). This directly impacts the retrieved position and motion of the storms, and consequently, the likely associated storm severity. Although a successful warning system based on lightning and radar observations has been developed, there remains a lack of knowledge of storm dynamics that could lead to forecast improvements. The present study explores the capabilities of the radar network at the Meteorological Service of Catalonia to retrieve dual-Doppler wind fields to study the dynamics of Catalan thunderstorms. A severe thunderstorm that splits and a tornado-producing supercell that is channeled through a valley are used to demonstrate the capabilities of an advanced open source technique that retrieves dynamical variables from C-band operational radars in complex terrain. For the first time in the Iberian Peninsula, complete 3D storm-relative winds are obtained, providing information about the internal dynamics of the storms. This aids in the analyses of the interaction between different storm cells within a system and/or the interaction of the cells with the local topography.
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Gao, Jidong, Travis M. Smith, David J. Stensrud, Chenghao Fu, Kristin Calhoun, Kevin L. Manross, Jeffrey Brogden, et al. "A Real-Time Weather-Adaptive 3DVAR Analysis System for Severe Weather Detections and Warnings." Weather and Forecasting 28, no. 3 (June 1, 2013): 727–45. http://dx.doi.org/10.1175/waf-d-12-00093.1.
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Abstract A real-time, weather-adaptive three-dimensional variational data assimilation (3DVAR) system has been adapted for the NOAA Warn-on-Forecast (WoF) project to incorporate all available radar observations within a moveable analysis domain. The key features of the system include 1) incorporating radar observations from multiple Weather Surveillance Radars-1988 Doppler (WSR-88Ds) with NCEP forecast products as a background state, 2) the ability to automatically detect and analyze severe local hazardous weather events at 1-km horizontal resolution every 5 min in real time based on the current weather situation, and 3) the identification of strong circulation patterns embedded in thunderstorms. Although still in the early development stage, the system performed very well within the NOAA's Hazardous Weather Testbed (HWT) Experimental Warning Program during preliminary testing in spring 2010 when many severe weather events were successfully detected and analyzed. This study represents a first step in the assessment of this type of 3DVAR analysis for use in severe weather warnings. The eventual goal of this real-time 3DVAR system is to help meteorologists better track severe weather events and eventually provide better warning information to the public, ultimately saving lives and reducing property damage.
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Cho, John Y. N., and James M. Kurdzo. "Weather Radar Network Benefit Model for Nontornadic Thunderstorm Wind Casualty Cost Reduction." Weather, Climate, and Society 12, no. 4 (October 2020): 789–804. http://dx.doi.org/10.1175/wcas-d-20-0063.1.
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AbstractAn 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.
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Waniha, Pascal F., Rita D. Roberts, James W. Wilson, Agnes Kijazi, and Benedicto Katole. "Dual-Polarization Radar Observations of Deep Convection over Lake Victoria Basin in East Africa." Atmosphere 10, no. 11 (November 13, 2019): 706. http://dx.doi.org/10.3390/atmos10110706.
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Lake Victoria in East Africa supports the livelihood of thousands of fishermen and it is estimated that 3000–5000 human deaths occur per year over the lake. It is hypothesized that most of these fatalities are due to localized, severe winds produced by intense thunderstorms over the lake during the rainy season and larger scale, intense winds over the lake during the dry season. The intense winds produce a rough state of the lake (big wave heights) that cause fishing boats to capsize. In this region, weather radars have never been a primary tool for monitoring and nowcasting high impact weather. The Tanzania Meteorological Agency operates an S-band polarimetric radar in Mwanza, Tanzania, along the south shore of Lake Victoria. This radar collects high temporal and spatial resolution data that is now being used to detect and monitor the formation of deep convection over the lake and improve scientific understanding of storm dynamics and intensification. Nocturnal thunderstorms and convection initiation over the lake are well observed by the Mwanza radar and are strongly forced by lake and land breezes and gust fronts. Unexpected is the detection of clear air echo to ranges ≥100 km over the lake that makes it possible to observe low-level winds, gust fronts, and other convergence lines near the surface of the lake. The frequent observation of extensive clear air and low-level convergence lines opens up the opportunity to nowcast strong winds, convection initiation, and subsequent thunderstorm development and incorporate this information into a regional early warning system proposed for Lake Victoria Basin (LVB). Two weather events are presented illustrating distinctly different nocturnal convection initiation over the lake that evolve into intense morning thunderstorms. The evolution of these severe weather events was possible because of the Mwanza radar observations; satellite imagery alone was insufficient to provide prediction of storm initiation, growth, movement, and decay.
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Doswell, Charles A., Harold E. Brooks, and Michael P. Kay. "Climatological Estimates of Daily Local Nontornadic Severe Thunderstorm Probability for the United States." Weather and Forecasting 20, no. 4 (August 1, 2005): 577–95. http://dx.doi.org/10.1175/waf866.1.
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Abstract The probability of nontornadic severe weather event reports near any location in the United States for any day of the year has been estimated. Gaussian smoothers in space and time have been applied to the observed record of severe thunderstorm occurrence from 1980 to 1994 to produce daily maps and annual cycles at any point. Many aspects of this climatology have been identified in previous work, but the method allows for the consideration of the record in several new ways. A review of the raw data, broken down in various ways, reveals that numerous nonmeteorological artifacts are present in the raw data. These are predominantly associated with the marginal nontornadic severe thunderstorm events, including an enormous growth in the number of severe weather reports since the mid-1950s. Much of this growth may be associated with a drive to improve warning verification scores. The smoothed spatial and temporal distributions of the probability of nontornadic severe thunderstorm events are presented in several ways. The distribution of significant nontornadic severe thunderstorm reports (wind speeds ≥ 65 kt and/or hailstone diameters ≥ 2 in.) is consistent with the hypothesis that supercells are responsible for the majority of such reports.
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Rasuly, A. A., K. K. W. Cheung, and B. McBurney. "Hail events across the Greater Metropolitan Severe Thunderstorm Warning Area." Natural Hazards and Earth System Sciences 15, no. 5 (May 13, 2015): 973–84. http://dx.doi.org/10.5194/nhess-15-973-2015.
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Abstract. This study addresses the recent climatology of hail occurrence in the Greater Metropolitan Severe Thunderstorm Warning Area (GMSTWA) of New South Wales (NSW). The study area is a sprawling suburban area with a population of nearly 4.7 million and one of Australia's largest metropoles. The main objective is to highlight the recent temporal–spatial fluctuations of hail event frequencies and magnitudes (sizes) for each of recognized and vastly inhabited local government areas (LGAs). The relevant hail event data from 1989 to 2013 were initially derived from the severe storm archive of the Australian Bureau of Meteorology. A climatologically oriented GIS technique was then applied in the examining and mapping procedure of all hail events and hail days reported throughout the study area. By applying a specific criterion, severe hail (defined as 2 cm or more in diameter) was cautiously selected for relevant analysis. The database includes 357 hail events with sizes 2–11 cm which occurred in 169 hail days (a day in which a hail event at least more than 2 cm reported) across the region during the past 25 years. The hail distribution patterns are neither temporally nor spatially uniform in magnitude throughout the study area. Temporal analysis indicated that most of hail events occur predominately in the afternoons with peak time of 1–5 p.m. Australian eastern standard time (EST). They are particularly common in spring and summer, reaching maximum frequency in November and December. There is an average of 14.3 events per year, but a significant decreasing trend in hail frequency and associated magnitude in the recent years has been identified. In turn, spatial analyses also established three main distribution patterns over the study area which include the Sydney metropolitan, the coastal and the most pronounced topographic effects. Based on the understanding of the favorable factors for thunderstorm development in the GMSTWA, the potential impacts from climate variability and future climate change have been briefly discussed.
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Schultz, Christopher J., Walter A. Petersen, and Lawrence D. Carey. "Lightning and Severe Weather: A Comparison between Total and Cloud-to-Ground Lightning Trends." Weather and Forecasting 26, no. 5 (October 1, 2011): 744–55. http://dx.doi.org/10.1175/waf-d-10-05026.1.
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Abstract Many studies over the past several decades have attempted to correlate trends in lightning (e.g., rates, polarity) to severe weather occurrence. These studies mainly used cloud-to-ground (CG) lightning information due to the ease of data availability, high detection efficiency, and broad coverage across the United States, with somewhat inconclusive results. Conversely, it has been demonstrated that trends in total lightning are more robustly correlated to severe weather occurrence, with rapid increases in total lightning observed 10s of minutes prior to the onset of severe weather. Unfortunately, total lightning observations are not as numerous, or available over the same areal coverage domain, as provided by CG networks. Relatively few studies have examined concurrent trends in both total and CG lightning within the same severe thunderstorm, or even large sets of thunderstorms using an objective lightning jump algorithm. Multiple studies have shown that the total flash rate rapidly increases prior to the onset of severe weather. What is untested within the same framework is the use of CG information to perform the same task. Herein, total and CG lightning trends for 711 thunderstorms occurring in four regions of the country were examined to demonstrate the increased utility that total lightning provides over CG lightning, specifically within the framework of developing a useful lightning-based severe weather warning decision support tool. Results indicate that while both lightning datasets demonstrate the presence of increased lightning activity prior to the onset of severe weather, the use of total lightning trends was more effective than CG trends [probability of detection (POD), 79% versus 66%; false alarm rate (FAR), 36% versus 53%; critical success index (CSI), 55% versus 38%; Heidke skill score (HSS), 0.71 versus 0.55]. Moreover, 40% of false alarms associated with total lightning, and 16% of false alarms with CG lightning trends, occurred when a lightning jump associated with a severe weather “warning” was already in effect. If these false alarms are removed, the FAR drops from 36% to 22% for total lightning and from 53% to 44% for CG lightning. Importantly, average lead times prior to severe weather occurrence were higher using total lightning as compared with CG lightning (20.65 versus 13.54 min). The ultimate goal of this study was to demonstrate the increased utility of total lightning information that the Geostationary Lightning Mapper (GLM) will provide to operational meteorology in anticipation of severe convective weather on a hemispheric scale once Geostationary Operational Environmental Satellite-R (GOES-R) is deployed in the next decade.
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Zhang, Yunji, David J. Stensrud, and Fuqing Zhang. "Simultaneous Assimilation of Radar and All-Sky Satellite Infrared Radiance Observations for Convection-Allowing Ensemble Analysis and Prediction of Severe Thunderstorms." Monthly Weather Review 147, no. 12 (November 11, 2019): 4389–409. http://dx.doi.org/10.1175/mwr-d-19-0163.1.
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Abstract This study explores the benefits of assimilating infrared (IR) brightness temperature (BT) observations from geostationary satellites jointly with radial velocity (Vr) and reflectivity (Z) observations from Doppler weather radars within an ensemble Kalman filter (EnKF) data assimilation system to the convection-allowing ensemble analysis and prediction of a tornadic supercell thunderstorm event on 12 June 2017 across Wyoming and Nebraska. While radar observations sample the three-dimensional storm structures with high fidelity, BT observations provide information about clouds prior to the formation of precipitation particles when in-storm radar observations are not yet available and also provide information on the environment outside the thunderstorms. To better understand the strengths and limitations of each observation type, the satellite and Doppler radar observations are assimilated separately and jointly, and the ensemble analyses and forecasts are compared with available observations. Results show that assimilating BT observations has the potential to increase the forecast and warning lead times of severe weather events compared with radar observations and may also potentially complement the sparse surface observations in some regions as revealed by the probabilistic prediction of mesocyclone tracks initialized from EnKF analyses as various times. Additionally, the assimilation of both BT and Vr observations yields the best ensemble forecasts, providing higher confidence, improved accuracy, and longer lead times on the probabilistic prediction of midlevel mesocyclones.
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Blair, Scott F., Jennifer M. Laflin, Dennis E. Cavanaugh, Kristopher J. Sanders, Scott R. Currens, Justin I. Pullin, Dylan T. Cooper, et al. "High-Resolution Hail Observations: Implications for NWS Warning Operations." Weather and Forecasting 32, no. 3 (May 11, 2017): 1101–19. http://dx.doi.org/10.1175/waf-d-16-0203.1.
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Abstract A field research campaign, the Hail Spatial and Temporal Observing Network Effort (HailSTONE), was designed to obtain physical high-resolution hail measurements at the ground associated with convective storms to help address several operational challenges that remain unsatisfied through public storm reports. Field phases occurred over a 5-yr period, yielding hail measurements from 73 severe thunderstorms [hail diameter ≥ 1.00 in. (2.54 cm)]. These data provide unprecedented insight into the hailfall character of each storm and afford a baseline to explore the representativeness of the climatological hail database and hail forecasts in NWS warning products. Based upon the full analysis of HailSTONE observations, hail sizes recorded in Storm Data as well as hail size forecasts in NWS warnings frequently underestimated the maximum diameter hailfall occurring at the surface. NWS hail forecasts were generally conservative in size and at least partially calibrated to incoming hail reports. Storm mode played a notable role in determining the potential range of maximum hail size during the life span of each storm. Supercells overwhelmingly produced the largest hail diameters, with smaller maximum hail sizes observed as convection became progressively less organized. Warning forecasters may employ a storm-mode hail size forecast philosophy, in conjunction with other radar-based hail detection techniques, to better anticipate and forecast hail sizes during convective warning episodes.
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Scharfenberg, Kevin A., Daniel J. Miller, Terry J. Schuur, Paul T. Schlatter, Scott E. Giangrande, Valery M. Melnikov, Donald W. Burgess, David L. Andra, Michael P. Foster, and John M. Krause. "The Joint Polarization Experiment: Polarimetric Radar in Forecasting and Warning Decision Making." Weather and Forecasting 20, no. 5 (October 1, 2005): 775–88. http://dx.doi.org/10.1175/waf881.1.
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Abstract To test the utility and added value of polarimetric radar products in an operational environment, data from the Norman, Oklahoma (KOUN), polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) were delivered to the National Weather Service Weather Forecast Office (WFO) in Norman as part of the Joint Polarization Experiment (JPOLE). KOUN polarimetric base data and algorithms were used at the WFO during the decision-making and forecasting processes for severe convection, flash floods, and winter storms. The delivery included conventional WSR-88D radar products, base polarimetric radar variables, a polarimetric hydrometeor classification algorithm, and experimental polarimetric quantitative precipitation estimation algorithms. The JPOLE data collection, delivery, and operational demonstration are described, with examples of several forecast and warning decision-making successes. Polarimetric data aided WFO forecasters during several periods of heavy rain, numerous large-hail-producing thunderstorms, tornadic and nontornadic supercell thunderstorms, and a major winter storm. Upcoming opportunities and challenges associated with the emergence of polarimetric radar data in the operational community are also described.
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Demuth, Julie L., Rebecca E. Morss, Jeffrey K. Lazo, and Douglas C. Hilderbrand. "Improving Effectiveness of Weather Risk Communication on the NWS Point-and-Click Web Page." Weather and Forecasting 28, no. 3 (June 1, 2013): 711–26. http://dx.doi.org/10.1175/waf-d-12-00118.1.
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Abstract The National Weather Service's (NWS) point-and-click (PnC) web page is a primary channel through which NWS directly provides routine and hazardous weather information to its users. The research presented here aims to improve risk communication of hazardous weather information on the PnC web page. The focus is on improving communication of threat existence and threat timing because this important information influences how individuals perceive and respond to a weather risk. Experimental presentations of PnC forecast information were designed for two weather scenarios: a severe thunderstorm warning and a flood watch. The experimental presentations were created by adding new textual and graphical pieces of information that were intended to better convey threat existence and timing, and they were evaluated through two rounds of nationwide surveys of PnC web page users. The survey results show that the default presentation of forecast information on the PnC web page was the least effective at conveying hazardous weather threat existence and timing. Adding start-time text and end-time text, when these information pieces were coupled, helped respondents understand the precise time that weather threats were in effect for the rapid-onset, short-duration severe thunderstorm warning and for the delayed-start, longer-duration flood watch. Adding a box graphic placed around the forecast icons further enhanced communication effectiveness by drawing respondents' attention to the weather threat. Other experimental forecast presentations were designed but were less effective at communicating hazardous weather threat existence and timing, illustrating the importance of empirically evaluating weather risk communication prior to providing it operationally.
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Bowden, Katie A., and Pamela L. Heinselman. "A Qualitative Analysis of NWS Forecasters’ Use of Phased-Array Radar Data during Severe Hail and Wind Events." Weather and Forecasting 31, no. 1 (January 28, 2016): 43–55. http://dx.doi.org/10.1175/waf-d-15-0089.1.
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Abstract The 2013 Phased Array Radar Innovative Sensing Experiment (PARISE) investigated the impacts of higher-temporal-resolution radar data on National Weather Service forecasters’ warning decision processes during severe hail and wind events. In total, 12 forecasters participated in the 2013 PARISE over a 6-week period during the summer of 2013. Participants were assigned to either a control [5-min phased-array radar (PAR) updates] or experimental (1-min PAR updates) group, and worked two cases in simulated real time. This paper focuses on the qualitative retrospective reports of participants’ warning decision processes that were collected using the recent case walk-through method. Timelines of participants’ warning decision process were created for both cases, which were then thematically coded according to a situational awareness framework. Coded themes included perception, comprehension, and projection. It was found that the experimental group perceived significantly more information during both cases than the control group (case 1 p = 0.045 and case 2 p = 0.041), which may have improved the quality of their comprehensions and projections. Analysis of timelines reveals that 1-min PAR updates were important to the experimental group’s more timely and accurate warning decisions. Not only did the 1-min PAR updates enable experimental participants to perceive precursor signatures earlier than control participants, but through monitoring trends in radar data, the experimental group was able to better detect storm motion, more accurately identify expected weather threats from severe thunderstorms, more easily observe strengthening and diminishing trends in storms, and make more correct tornado-related warning decisions.
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Spyrou, Christos, George Varlas, Aikaterini Pappa, Angeliki Mentzafou, Petros Katsafados, Anastasios Papadopoulos, Marios N. Anagnostou, and John Kalogiros. "Implementation of a Nowcasting Hydrometeorological System for Studying Flash Flood Events: The Case of Mandra, Greece." Remote Sensing 12, no. 17 (August 27, 2020): 2784. http://dx.doi.org/10.3390/rs12172784.
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Severe hydrometeorological hazards such as floods, droughts, and thunderstorms are expected to increase in the future due to climate change. Due to the significant impacts of these phenomena, it is essential to develop new and advanced early warning systems for advance preparation of the population and local authorities (civil protection, government agencies, etc.). Therefore, reliable forecasts of extreme events, with high spatial and temporal resolution and a very short time horizon are needed, due to the very fast development and localized nature of these events. In very short time-periods (up to 6 h), small-scale phenomena can be described accurately by adopting a “nowcasting” approach, providing reliable short-term forecasts and warnings. To this end, a novel nowcasting system was developed and presented in this study, combining a data assimilation system (LAPS), a large amount of observed data, including XPOL radar precipitation measurements, the Chemical Hydrological Atmospheric Ocean wave System (CHAOS), and the WRF-Hydro model. The system was evaluated on the catastrophic flash flood event that occurred in the sub-urban area of Mandra in Western Attica, Greece, on 15 November 2017. The event was one of the most catastrophic flash floods with human fatalities (24 people died) and extensive infrastructure damage. The update of the simulations with assimilated radar data improved the initial precipitation description and led to an improved simulation of the evolution of the phenomenon. Statistical evaluation and comparison with flood data from the FloodHub showed that the nowcasting system could have provided reliable early warning of the flood event 1, 2, and even to 3 h in advance, giving vital time to the local authorities to mobilize and even prevent fatalities and injuries to the local population.
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Calhoun, Kristin M., Travis M. Smith, Darrel M. Kingfield, Jidong Gao, and David J. Stensrud. "Forecaster Use and Evaluation of Real-Time 3DVAR Analyses during Severe Thunderstorm and Tornado Warning Operations in the Hazardous Weather Testbed." Weather and Forecasting 29, no. 3 (June 1, 2014): 601–13. http://dx.doi.org/10.1175/waf-d-13-00107.1.
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Abstract A weather-adaptive three-dimensional variational data assimilation (3DVAR) system was included in the NOAA Hazardous Weather Testbed as a first step toward introducing warn-on-forecast initiatives into operations. NWS forecasters were asked to incorporate the data in conjunction with single-radar and multisensor products in the Advanced Weather Interactive Processing System (AWIPS) as part of their warning-decision process for real-time events across the United States. During the 2011 and 2012 experiments, forecasters examined more than 36 events, including tornadic supercells, severe squall lines, and multicell storms. Products from the 3DVAR analyses were available to forecasters at 1-km horizontal resolution every 5 min, with a 4–6-min latency, incorporating data from the national Weather Surveillance Radar-1988 Doppler (WSR-88D) network and the North American Mesoscale model. Forecasters found the updraft, vertical vorticity, and storm-top divergence products the most useful for storm interrogation and quickly visualizing storm trends, often using these tools to increase the confidence in a warning decision and/or issue the warning slightly earlier. The 3DVAR analyses were most consistent and reliable when the storm of interest was in close proximity to one of the assimilated WSR-88D, or data from multiple radars were incorporated into the analysis. The latter was extremely useful to forecasters in blending data rather than having to analyze multiple radars separately, especially when range folding obscured the data from one or more radars. The largest hurdle for the real-time use of 3DVAR or similar data assimilation products by forecasters is the data latency, as even 4–6 min reduces the utility of the products when new radar scans are available.
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Li, Ling, Zhengwei He, Sheng Chen, Xiongfa Mai, Asi Zhang, Baoqing Hu, Zhi Li, and Xinhua Tong. "Subpixel-Based Precipitation Nowcasting with the Pyramid Lucas–Kanade Optical Flow Technique." Atmosphere 9, no. 7 (July 12, 2018): 260. http://dx.doi.org/10.3390/atmos9070260.
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Short-term high-resolution quantitative precipitation forecasting (QPF) is very important for flash-flood warning, navigation safety, and other hydrological applications. This paper proposes a subpixel-based QPF algorithm using a pyramid Lucas–Kanade optical flow technique (SPLK) for short-time rainfall forecast. The SPLK tracks the storm on the subpixel level by using the optical flow technique and then extrapolates the precipitation using a linear method through redistribution and interpolation. The SPLK compares with object-based and pixel-based nowcasting algorithms using eight thunderstorm events to assess its performance. The results suggest that the SPLK can perform better nowcasting of precipitation than the object-based and pixel-based algorithms with higher adequacy in tracking and predicting severe storms in 0–2 h lead-time forecasting.
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Wang, Hao, Gangyi Chen, Huanhuan Lei, Yongqian Wang, and Shunxian Tang. "Improving the Predictability of Severe Convective Weather Processes by Using Wind Vectors and Potential Temperature Changes: A Case Study of a Severe Thunderstorm." Advances in Meteorology 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/8320189.
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Strong, local convective weather events are capable of causing extensive damage, but weather observation systems with limited resolution and radar monitoring can typically provide only a few minutes to hours of prior warning time. This paper presents a comprehensive case study of the cumulative evolution of several characteristic quantities during one extremely severe convective weather process. The research results indicate that the main feature of strong convective weather is the uneven distribution of thermal energy in the atmosphere, and the structure of this heat distribution determines the level of instability in the atmosphere. A vertical “clockwise rolling current” occurs in the wind field structure at the beginning of the process, and this is accompanied by a rapid drop in temperature at the top of the troposphere. When these signs occurred in the case study, radar technology was used to refine the precipitation region and spatial characteristics of the approaching storm. The height and vertical evolution of radar echoes were indicative of the characteristics of the system’s movement through space. Such findings may be useful for improving the forecasting times for strong convective weather.
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Vasiloff, Steven V., Kenneth W. Howard, and Jian Zhang. "Difficulties with Correcting Radar Rainfall Estimates Based on Rain Gauge Data: A Case Study of Severe Weather in Montana on 16–17 June 2007." Weather and Forecasting 24, no. 5 (October 1, 2009): 1334–44. http://dx.doi.org/10.1175/2009waf2222154.1.
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Abstract The principal source of information for operational flash flood monitoring and warning issuance is weather radar–based quantitative estimates of precipitation. Rain gauges are considered truth for the purposes of validating and calibrating real-time radar-derived precipitation data, both in a real-time sense and climatologically. This paper examines various uncertainties and challenges involved with using radar and rain gauge data in a severe local storm environment. A series of severe thunderstorm systems that occurred across northeastern Montana illustrates various problems with comparing radar precipitation estimates and real-time gauge data, including extreme wind effects, hail, missing gauge data, and radar quality control. Ten radar–gauge time series pairs were analyzed with most found to be not useful for real-time radar calibration. These issues must be carefully considered within the context of ongoing efforts to develop robust real-time tools for evaluating radar–gauge uncertainties. Recommendations are made for radar and gauge data quality control efforts that would benefit the operational use of gauge data.
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Rasuly, A. A., K. K. W. Cheung, and B. McBurney. "Hailstones across the Greater Sydney Metropolitan Area." Natural Hazards and Earth System Sciences Discussions 2, no. 11 (November 18, 2014): 6973–7016. http://dx.doi.org/10.5194/nhessd-2-6973-2014.
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Abstract. This study addresses the recent climatology of hail occurrence in the Greater Metropolitan Severe Thunderstorm Warning Area (GMSTWA) of New South Wales, Australia, which is a sprawling suburban area, with a population of nearly 4.7 million and one of Australia's largest metropolis. The main objective is to highlight the recent temporal-spatial fluctuations of hailstone frequencies and magnitudes for each of recognized and vastly inhabited Local Government Areas (LGAs). The relevant hail event data from 1989 to 2013 were initially derived from the severe storm archive of Australian Bureau of Meteorology. A climatologically oriented GIS technique was applied in the examining and mapping procedure of all hail events and hail days reported throughout the study area. By applying a specific criterion, all severe hails (defined as 2 cm or more in diameter) were cautiously selected and then imported into the ArcGIS software for relevant analysis. Appropriate data layers were stored in a unique database to allow logical integration of the data directly into some geoprocessing functions, mainly for querying, analyzing and mapping purposes in a model-builder setting. The database includes 357 hailstones with sizes 2–11 cm and occurred in 169 hail days across the region during the past 25 years. The models have established that hailstones are neither temporally nor spatially uniform in magnitude throughout the study area. Temporal analysis indicated that most of hail events occurred predominately in the afternoons with peak time of 1–5 p.m. EST. They were particularly common in spring and summer, and reached maximum frequency in November and December. There was an average of 14.3 events each year, but a significant decreasing trend in terms of hail frequency and associated magnitude in the recent years has been identified. In turn, spatial models also established three main distribution patterns over the study area, which include the Sydney Metropolitan, coastal and pronounced topographic effects. Based on the understanding of the favorable factors for thunderstorm development in the GMSTWA, the potential impacts from climate variability and future climate change have been briefly discussed.
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Li, Jun, Chian-Yi Liu, Peng Zhang, and Timothy J. Schmit. "Applications of Full Spatial Resolution Space-Based Advanced Infrared Soundings in the Preconvection Environment." Weather and Forecasting 27, no. 2 (April 1, 2012): 515–24. http://dx.doi.org/10.1175/waf-d-10-05057.1.
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Abstract Advanced infrared (IR) sounders such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) provide atmospheric temperature and moisture profiles with high vertical resolution and high accuracy in preconvection environments. The derived atmospheric stability indices such as convective available potential energy (CAPE) and lifted index (LI) from advanced IR soundings can provide critical information 1 ~ 6 h before the development of severe convective storms. Three convective storms are selected for the evaluation of applying AIRS full spatial resolution soundings and the derived products on providing warning information in the preconvection environments. In the first case, the AIRS full spatial resolution soundings revealed local extremely high atmospheric instability 3 h ahead of the convection on the leading edge of a frontal system, while the second case demonstrates that the extremely high atmospheric instability is associated with the local development of severe thunderstorm in the following hours. The third case is a local severe storm that occurred on 7–8 August 2010 in Zhou Qu, China, which caused more than 1400 deaths and left another 300 or more people missing. The AIRS full spatial resolution LI product shows the atmospheric instability 3.5 h before the storm genesis. The CAPE and LI from AIRS full spatial resolution and operational AIRS/AMSU soundings along with Geostationary Operational Environmental Satellite (GOES) Sounder derived product image (DPI) products were analyzed and compared. Case studies show that full spatial resolution AIRS retrievals provide more useful warning information in the preconvection environments for determining favorable locations for convective initiation (CI) than do the coarser spatial resolution operational soundings and lower spectral resolution GOES Sounder retrievals.
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Smith, Travis M., Jidong Gao, Kristin M. Calhoun, David J. Stensrud, Kevin L. Manross, Kiel L. Ortega, Chenghao Fu, et al. "Examination of a Real-Time 3DVAR Analysis System in the Hazardous Weather Testbed." Weather and Forecasting 29, no. 1 (February 1, 2014): 63–77. http://dx.doi.org/10.1175/waf-d-13-00044.1.
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Abstract Forecasters and research meteorologists tested a real-time three-dimensional variational data assimilation (3DVAR) system in the Hazardous Weather Testbed during the springs of 2010–12 to determine its capabilities to assist in the warning process for severe storms. This storm-scale system updates a dynamically consistent three-dimensional wind field every 5 min, with horizontal and average vertical grid spacings of 1 km and 400 m, respectively. The system analyzed the life cycles of 218 supercell thunderstorms on 27 event days during these experiments, producing multiple products such as vertical velocity, vertical vorticity, and updraft helicity. These data are compared to multiradar–multisensor data from the Warning Decision Support System–Integrated Information to document the performance characteristics of the system, such as how vertical vorticity values compare to azimuthal shear fields calculated directly from Doppler radial velocity. Data are stratified by range from the nearest radar, as well as by the number of radars entering into the analysis of a particular storm. The 3DVAR system shows physically realistic trends of updraft speed and vertical vorticity for a majority of cases. Improvements are needed to better estimate the near-surface winds when no radar is nearby and to improve the timeliness of the input data. However, the 3DVAR wind field information provides an integrated look at storm structure that may be of more use to forecasters than traditional radar-based proxies used to infer severe weather potential.
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Brown, Rodger A., Bradley A. Flickinger, Eddie Forren, David M. Schultz, Dale Sirmans, Phillip L. Spencer, Vincent T. Wood, and Conrad L. Ziegler. "Improved Detection of Severe Storms Using Experimental Fine-Resolution WSR-88D Measurements." Weather and Forecasting 20, no. 1 (February 1, 2005): 3–14. http://dx.doi.org/10.1175/waf-832.1.
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Abstract Doppler velocity and reflectivity measurements from Weather Surveillance Radar-1988 Doppler (WSR-88D) radars provide important input to forecasters as they prepare to issue short-term severe storm and tornado warnings. Current-resolution data collected by the radars have an azimuthal spacing of 1.0° and range spacing of 1.0 km for reflectivity and 0.25 km for Doppler velocity and spectrum width. To test the feasibility of improving data resolution, National Severe Storms Laboratory’s test bed WSR-88D (KOUN) collected data in severe thunderstorms using 0.5°-azimuthal spacing and 0.25-km-range spacing, resulting in eight times the resolution for reflectivity and twice the resolution for Doppler velocity and spectrum width. Displays of current-resolution WSR-88D Doppler velocity and reflectivity signatures in severe storms were compared with displays showing finer-resolution signatures. At all ranges, fine-resolution data provided better depiction of severe storm characteristics. Eighty-five percent of mean rotational velocities derived from fine-resolution mesocyclone signatures were stronger than velocities derived from current-resolution signatures. Likewise, about 85% of Doppler velocity differences across tornado and tornadic vortex signatures were stronger than values derived from current-resolution data. In addition, low-altitude boundaries were more readily detected using fine-resolution reflectivity data. At ranges greater than 100 km, fine-resolution reflectivity displays revealed severe storm signatures, such as bounded weak echo regions and hook echoes, which were not readily apparent on current-resolution displays. Thus, the primary advantage of fine-resolution measurements over current-resolution measurements is the ability to detect stronger reflectivity and Doppler velocity signatures at greater ranges from a WSR-88D.
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Bartzokas, A., J. Azzopardi, L. Bertotti, A. Buzzi, L. Cavaleri, D. Conte, S. Davolio, et al. "The RISKMED project: philosophy, methods and products." Natural Hazards and Earth System Sciences 10, no. 7 (July 1, 2010): 1393–401. http://dx.doi.org/10.5194/nhess-10-1393-2010.
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Abstract. This paper presents RISKMED, a project targeted to create an Early Warning System (EWS) in case of severe or extreme weather events in the central and eastern Mediterranean and specifically in southern Italy, northwestern Greece, Malta and Cyprus. As severe or extreme weather events are considered, cases when the values of some meteorological parameters (temperature, wind, precipitation) exceed certain thresholds, and/or a severe weather phenomenon (thunderstorm, snowfall) occurs. For an accurate weather forecast, selected meteorological models have been operated daily, based on a nesting strategy using two or three domains, providing detailed forecasts over the above mentioned areas. The forecast results are further exploited for the evaluation and prediction of human discomfort and fire weather indices. Finally, sea wave models have also been operating daily over the central and eastern Mediterranean Sea. In case a severe or extreme weather event is forecasted within the next 48 or 72 h for selected target areas (sub-regions defined by their morphological and population characteristics), the local authorities and the public are informed via a user-friendly graphic system, the so-called RISK MAP. On the web page of the Project ( http://www.riskmed.net ), additional information is provided about the real-time values of some meteorological parameters, the latest satellite picture and the time and space distribution of lightning during the last 24 h. The RISKMED project was financed by the EU and th Ministries of National Economy of Greece, Italy, Malta and Cyprus, in the frame of INTERREG IIIB/ARCHIMED programme.
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Stewart, Alan E. "Affective Normative Data for English Weather Words." Atmosphere 11, no. 8 (August 14, 2020): 860. http://dx.doi.org/10.3390/atmos11080860.
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The research in this article examines the emotional associations people have to common weather words and to selected terms that appear in weather communications (e.g., severe thunderstorm warning). A sample of 420 university students provided ratings for each term along four dimensions: 1. Valence (unhappy vs. happy), 2. Arousal (calm vs. excited), 3. Dominance (in control/dominant vs. controlled/passive), and 4. Surprise (unsurprising/predictable vs. surprising/unpredictable). The results of this research provide descriptive statistical data for the 141 weather words along the four dimensions. The author also examined the correlations of the four dimensions across the terms and observed a high degree of association between the rated arousal and surprise characteristics of terms. In addition, the results revealed the clustering of weather words according to shared similarities across the four affective dimensions (illustrating affective-based synonymy). The results of the research are significant because they reveal a deeper understanding of the subjective and emotional experiences of the atmosphere that people may have when describing the weather of a place. Similarly, the normative data from this research may be used in the analysis of weather- or climate-based communications to characterize the emotional significance or impact of a message.
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Moore, Angelyn W., Ivory J. Small, Seth I. Gutman, Yehuda Bock, John L. Dumas, Peng Fang, Jennifer S. Haase, Mark E. Jackson, and Jayme L. Laber. "National Weather Service Forecasters Use GPS Precipitable Water Vapor for Enhanced Situational Awareness during the Southern California Summer Monsoon." Bulletin of the American Meteorological Society 96, no. 11 (November 1, 2015): 1867–77. http://dx.doi.org/10.1175/bams-d-14-00095.1.
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Abstract During the North American Monsoon, low-to-midlevel moisture is transported in surges from the Gulf of California and Eastern Pacific Ocean into Mexico and the American Southwest. As rising levels of precipitable water interact with the mountainous terrain, severe thunderstorms can develop, resulting in flash floods that threaten life and property. The rapid evolution of these storms, coupled with the relative lack of upper-air and surface weather observations in the region, make them difficult to predict and monitor, and guidance from numerical weather prediction models can vary greatly under these conditions. Precipitable water vapor (PW) estimates derived from continuously operating ground-based GPS receivers have been available for some time from NOAA’s GPS-Met program, but these observations have been of limited utility to operational forecasters in part due to poor spatial resolution. Under a NASA Advanced Information Systems Technology project, 37 real-time stations were added to NOAA’s GPS-Met analysis providing 30-min PW estimates, reducing station spacing from approximately 150 km to 30 km in Southern California. An 18–22 July 2013 North American Monsoon event provided an opportunity to evaluate the utility of the additional upper-air moisture observations to enhance National Weather Service (NWS) forecaster situational awareness during the rapidly developing event. NWS forecasters used these additional data to detect rapid moisture increases at intervals between the available 1–6-h model updates and approximately twice-daily radiosonde observations, and these contributed tangibly to the issuance of timely flood watches and warnings in advance of flash floods, debris flows, and related road closures.