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1

Drost, Robert, Mark Casteel, Julie Libarkin, Stephen Thomas, and Matt Meister. "Severe Weather Warning Communication: Factors Impacting Audience Attention and Retention of Information during Tornado Warnings." Weather, Climate, and Society 8, no. 4 (2016): 361–72. http://dx.doi.org/10.1175/wcas-d-15-0035.1.

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Abstract Weather hazards in the United States inflict both personal and economic tolls on the public. Communicating warnings about weather hazards is an important duty of TV weathercasters. Televised weather warnings are typically conveyed through live radar, live coverage, and warning scrolls. However, these traditional approaches may not be entirely effective given the limited attention some members of the public pay to these warnings. A study comparing individual responses to a traditional warning, an animated warning, and an audio warning was undertaken to evaluate the impact of delivery methods on viewer attention, retention, and preferences during viewing of severe weather warnings. A Tobii T60 eye tracker was used to document visual interactions with on-screen warnings and surveys were used to collect evidence of warning retention and preference. Demographic variables were also collected to describe the study population. Results indicate that viewers of the animated warning retained more pertinent information about the tornado warning than viewers of the traditional warning, and retention during the traditional warning was equivalent to that of the audio warning. In addition, gaze patterns for the traditional warning were much more diffuse than for the animated warning, suggesting that attention was more focused on the animation than the live video. In addition, modifications to reduce visual complexity of traditional warnings may positively impact viewer attention to individual warning elements. Future studies will consider the effectiveness of a hybrid warning containing both traditional and animated components. The current research study can be used to advance current severe weather warning communication techniques and increase public awareness during severe weather events.
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Schroeter, Serena, Harald Richter, Craig Arthur, et al. "Forecasting the impacts of severe weather." January 2021 10.47389/36, No 1 (2021): 76–83. http://dx.doi.org/10.47389/36.1.76.

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National meteorological and hydrological services provide severe weather warning information to inform decision-making by emergency management organisations. Such information also helps communities to take defensive and mitigating actions prior to and during severe weather events. Globally, warning information issued by meteorological and hydrological services varies widely. This can range from solely hazard-based to impact-based forecasting encompassing the exposure and vulnerability of communities to severe weather. The most advanced of these systems explicitly and quantitatively model the impacts of hazards on affected assets or infrastructure such as vehicle traffic or housing. Incorporating impact information into severe weather warnings contextualises and personalises the warning information, increasing the likelihood that individuals and communities will take preparatory action. However, providing useful and detailed impact information remains a challenge. This paper reviews a selection of current severe weather warnings and impact forecasting capabilities globally and highlights uncertainties that limit the forecasting and modelling of multi-hazard events.
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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 (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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Ash, Kevin D., Ronald L. Schumann, and Gregg C. Bowser. "Tornado Warning Trade-Offs: Evaluating Choices for Visually Communicating Risk." Weather, Climate, and Society 6, no. 1 (2014): 104–18. http://dx.doi.org/10.1175/wcas-d-13-00021.1.

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Abstract Recent improvements in weather observation and monitoring have increased the precision of tornado warnings. The National Weather Service currently issues storm-based tornado warnings, and even more geographically specific warnings that include probability information are under development. At the same time, the widespread proliferation of smartphone and mobile computing technology supports the rapid dissemination of graphical weather warning information. Some broadcasters and private companies have already begun using probabilistic-style tornado warning graphics. However, the development of these new types of warnings has occurred with limited research on how users interpret probabilistic visualizations. This study begins filling this void by examining responses to color scheme and relative position using probabilistic tornado warning designs. A survey of university students is used to measure the level of perceived fear and likelihood of protective action for a series of hypothetical warning scenarios. Central research questions investigate 1) differences in responses across warning designs, 2) clustering of extreme responses in each design, 3) trends in responses with respect to probability levels, 4) differences in responses inside versus outside the warnings, and 5) differences in responses near the edges of the warning designs. Results suggest a variety of trade-offs in viewer responses to tornado warnings based on visual design choices. These findings underscore the need for more comprehensive research on visualizations in weather hazard communication that can aid meteorologists in effectively warning the public and spur appropriate tornado protection behaviors in a timely manner.
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Zhang, Fang, Jin Ding, Yu Chen, et al. "Analysis of the Multi-Dimensional Characteristics of City Weather Forecast Page Views and the Spatiotemporal Characteristics of Meteorological Disaster Warnings in China." Atmosphere 15, no. 5 (2024): 615. http://dx.doi.org/10.3390/atmos15050615.

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In order to provide insights into how various page views are influenced by public engagement with weather information and to shed light on the patterns of warning issuance across different seasons and regions, this study analyzes the multi-dimensional characteristics of city weather forecast page views and the spatiotemporal characteristics of early warning information in China, from 1 March 2020 to 31 August 2023. This is achieved by utilizing the daily page views of city weather forecasts and meteorological warning data, comparing the public’s attention to weather during holidays versus regular days, assessing the public’s attention to weather under different meteorological warning levels, and performing statistical analysis of the spatiotemporal scale of meteorological disasters. Our analysis shows that compared to weekends and holidays, the public pays more attention to the weather on weekdays, and the difference between weekdays and national statutory holidays is more significant. Due to the widespread impact of heat waves, typhoons, severe convective weather, and geological disasters caused by heavy rainfall, public awareness and participation in flood season weather forecasting have significantly increased. Under red alerts, flash floods, typhoons, and geological risks are the primary concerns. Orange alerts predominantly feature flash floods, rainstorms, typhoons, snowstorms, and cold waves, while sandstorms attract the most attention during yellow alerts. Droughts, however, receive relatively less attention regardless of the warning level. Seasonal patterns in the issuance of meteorological warnings reveal a peak in summer, particularly with typhoons and rainstorms being the main concerns in July, followed by high temperatures and additional typhoon warnings in August. Heavy sea surface wind warnings exhibit a strong seasonal trend, with the majority issued during the winter months. Regionally, southern China experiences the highest frequency of severe convection weather warnings, with provinces such as Jiangxi, Guangxi, and Hunan being the most affected.
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6

Weyrich, Philippe, Anna Scolobig, David N. Bresch, and Anthony Patt. "Effects of Impact-Based Warnings and Behavioral Recommendations for Extreme Weather Events." Weather, Climate, and Society 10, no. 4 (2018): 781–96. http://dx.doi.org/10.1175/wcas-d-18-0038.1.

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Abstract Bad weather continues not only to inflict damage on property but also to kill and injure people, despite significant advances in the predictive power of meteorological warnings. There is evidence that people tend to underreact to weather warning information, to a large extent because of insufficient understanding of the impacts that severe weather events can have, as well as to demonstrate the appropriate response behavior. A growing number of experts are suggesting that standard warning information should be augmented with additional information about these factors, but this has so far largely failed to take place. Past research studies have shown possible advantages of including impact-based warnings (IBWs) and behavioral recommendations (BRs) into the warning information, but the results are in part ambiguous, due to a failure to have tested for effects of the two kinds of information separately and in combination. Based on quantitative results from a survey experiment in Switzerland, this knowledge gap is addressed. Results of the research reported here indicate significant benefits from providing both sets of information together, in terms of improving both perception and understanding of warning and intended behavioral responses. When only one piece of information is given, BRs have a significant effect on both perception and intended response, whereas IBWs have a significant effect only on intended response. These findings offer empirical justification for the added expense and time associated with the more detailed hazard warnings.
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7

Vrotsou, Katerina, Carlo Navarra, Kostiantyn Kucher, et al. "Towards a Volunteered Geographic Information-Facilitated Visual Analytics Pipeline to Improve Impact-Based Weather Warning Systems." Atmosphere 14, no. 7 (2023): 1141. http://dx.doi.org/10.3390/atmos14071141.

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Extreme weather events, such as flooding, are expected to increase in frequency and intensity. Therefore, the prediction of extreme weather events, assessment of their local impacts in urban environments, and implementation of adaptation measures are becoming high-priority challenges for local, regional, and national agencies and authorities. To manage these challenges, access to accurate weather warnings and information about the occurrence, extent, and impacts of extreme weather events are crucial. As a result, in addition to official sources of information for prediction and monitoring, citizen volunteered geographic information (VGI) has emerged as a complementary source of valuable information. In this work, we propose the formulation of an approach to complement the impact-based weather warning system that has been introduced in Sweden in 2021 by making use of such alternative sources of data. We present and discuss design considerations and opportunities towards the creation of a visual analytics (VA) pipeline for the identification and exploration of extreme weather events and their impacts from VGI texts and images retrieved from social media. The envisioned VA pipeline incorporates three main steps: (1) data collection, (2) image/text classification and analysis, and (3) visualization and exploration through an interactive visual interface. We envision that our work has the potential to support three processes that involve multiple stakeholders of the weather warning system: (1) the validation of previously issued warnings, (2) local and regional assessment-support documentation, and (3) the monitoring of ongoing events. The results of this work could thus generate information that is relevant to climate adaptation decision making and provide potential support for the future development of national weather warning systems.
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8

Bostrom, Ann, Rebecca E. Morss, Jeffrey K. Lazo, Julie L. Demuth, Heather Lazrus, and Rebecca Hudson. "A Mental Models Study of Hurricane Forecast and Warning Production, Communication, and Decision-Making*." Weather, Climate, and Society 8, no. 2 (2016): 111–29. http://dx.doi.org/10.1175/wcas-d-15-0033.1.

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Abstract The study reported here explores how to enhance the public value of hurricane forecast and warning information by examining the entire warning process. A mental models research approach is applied to address three risk management tasks critical to warnings for extreme weather events: 1) understanding the risk decision and action context for hurricane warnings, 2) understanding the commonalities and conflicts in interpretations of that context and associated risks, and 3) exploring the practical implications of these insights for hurricane risk communication and management. To understand the risk decision and action context, the study develops a decision-focused model of the hurricane forecast and warning system on the basis of results from individual mental models interviews with forecasters from the National Hurricane Center (n = 4) and the Miami–South Florida Weather Forecast Office (n = 4), media broadcasters (n = 5), and public officials (n = 6), as well as a group decision-modeling session with a subset of the forecasters. Comparisons across professionals reveal numerous shared perceptions, as well as some critical differences. Implications for improving extreme weather event forecast and warning systems and risk communication are threefold: 1) promote thinking about forecast and warning decisions as a system, with informal as well as formal elements; 2) evaluate, coordinate, and consider controlling the proliferation of forecast and warning information products; and 3) further examine the interpretation and representation of uncertainty within the hurricane forecast and warning system as well as for users.
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9

Sanders, Shadya, Terri Adams, and Everette Joseph. "Severe Weather Forecasts and Public Perceptions: An Analysis of the 2011 Super Outbreak in Tuscaloosa, Alabama." Weather, Climate, and Society 12, no. 3 (2020): 473–85. http://dx.doi.org/10.1175/wcas-d-18-0090.1.

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AbstractThis paper uses the “Super Outbreak” of 2011 as a case study to examine the potential gaps between the dissemination of severe weather warnings and the public’s behavioral response to this information. This study focuses on a single tornado track that passed through Tuscaloosa, Alabama. The tornado caused massive damage and destruction and led to a total of 62 fatalities. The threat of severe storms was known days in advance, and forecasts were disseminated to the public. Questions were raised about the forecasts, warning lead times, and the perception of the warnings among residents. This paper examines the potential gaps that exist between the dissemination of tornadic warning information and citizen response. The analysis of data collected through a mixed-method approach suggests that, regardless of weather forecast accuracy, a significant chasm exists between the dissemination of warnings and the personalizing of risks, which results in limited use of protective measures in the face of severe weather threats.
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10

Golding, Brian, Elizabeth Ebert, David Hoffmann, and Sally Potter. "Preparing for the unprecedented." Advances in Science and Research 20 (July 31, 2023): 85–90. http://dx.doi.org/10.5194/asr-20-85-2023.

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Abstract. In 2021, several weather disasters occurred in which conditions surpassed recorded extremes. Analysis of the performance of warning systems in these disasters by the WWRP HIWeather project shows that in most, but not all cases, there was adequate forewarning of the magnitude of the event, but that lack of preparedness and/or communication failures led to loss of life in particularly vulnerable groups. Using information from the HIWeather value chain database, we present an overview of key aspects of each event – the weather and its impact, the forecasts, the warnings, and the responses – followed by some results of a comparative analysis of warning performance and some conclusions about critical components of a successful warning system. In the light of this analysis we conclude with a checklist of key components in the design of an effective warning system for unprecedented weather events.
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11

Schumacher, Russ S., Daniel T. Lindsey, Andrea B. Schumacher, Jeff Braun, Steven D. Miller, and Julie L. Demuth. "Multidisciplinary Analysis of an Unusual Tornado: Meteorology, Climatology, and the Communication and Interpretation of Warnings*." Weather and Forecasting 25, no. 5 (2010): 1412–29. http://dx.doi.org/10.1175/2010waf2222396.1.

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Abstract On 22 May 2008, a strong tornado—rated EF3 on the enhanced Fujita scale, with winds estimated between 136 and 165 mi h−1 (61 and 74 m s−1)—caused extensive damage along a 55-km track through northern Colorado. The worst devastation occurred in and around the town of Windsor, and in total there was one fatality, numerous injuries, and hundreds of homes significantly damaged or destroyed. Several characteristics of this tornado were unusual for the region from a climatological perspective, including its intensity, its long track, its direction of motion, and the time of day when it formed. These unusual aspects and the high impact of this tornado also raised a number of questions about the communication and interpretation of information from National Weather Service watches and warnings by decision makers and the public. First, the study examines the meteorological circumstances responsible for producing such an outlier to the regional severe weather climatology. An analysis of the synoptic and mesoscale environmental conditions that were favorable for significant tornadoes on 22 May 2008 is presented. Then, a climatology of significant tornadoes (defined as those rated F2 or higher on the Fujita scale, or EF2 or higher on the Enhanced Fujita scale) near the Front Range is shown to put the 22 May 2008 event into climatological context. This study also examines the communication and interpretation of severe weather information in an area that experiences tornadoes regularly but is relatively unaccustomed to significant tornadoes. By conducting interviews with local decision makers, the authors have compiled and chronicled the flow of information as the event unfolded. The results of these interviews demonstrate that the initial sources of warning information varied widely. Decision makers’ interpretations of the warnings also varied, which led to different perceptions on the timeliness and clarity of the warning information. The decision makers’ previous knowledge of the typical local characteristics of tornadoes also affected their interpretations of the tornado threat. The interview results highlight the complex series of processes by which severe weather information is communicated after a warning is issued by the National Weather Service. The results of this study support the growing recognition that societal factors are just as important to the effectiveness of weather warnings as the timeliness of and information provided in those warnings, and that these factors should be considered in future research in addition to the investments and attention given to improving detection and warning capabilities.
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12

Howard, Seth P., Kim E. Klockow-McClain, Alison P. Boehmer, and Kevin M. Simmons. "Firm Behavior in the Face of Severe Weather: Economic Analysis between Probabilistic and Deterministic Warnings." Weather and Forecasting 36, no. 3 (2021): 757–67. http://dx.doi.org/10.1175/waf-d-20-0107.1.

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AbstractTornadoes cause billions of dollars in damage and over 100 fatalities on average annually. Yet, an indirect cost to these storms is found in lost sales and/or lost productivity from responding to over 2000 warnings per year. This project responds to the Weather Research and Forecasting Innovation Act of 2017, H.R. 353, which calls for the use of social and behavioral science to study and improve storm warning systems. Our goal is to provide an analysis of cost avoidance that could accrue from a change to the warning paradigm, particularly to include probabilistic hazard information at storm scales. A survey of nearly 500 firms was conducted in and near the Dallas–Fort Worth metropolitan area asking questions about experience with tornadoes, sources of information for severe weather, expected cost of responding to tornado warnings, and how the firm would respond to either deterministic or probabilistic warnings. We find a dramatic change from deterministic warnings compared to the proposed probabilistic and that a probabilistic information system produces annual cost avoidance in a range of $2.3–$7.6 billion (U.S. dollars) compared to the current deterministic warning paradigm.
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13

Casteel, Mark A., and Joe R. Downing. "How Individuals Process NWS Weather Warning Messages on Their Cell Phones." Weather, Climate, and Society 5, no. 3 (2013): 254–65. http://dx.doi.org/10.1175/wcas-d-12-00031.1.

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Abstract U.S. government officials are focusing their attention on how to deliver timely and effective warning information to the public, especially given the devastating weather-related events that have occurred in recent years. With the increase of cell phones (and in particular, web-capable smartphones), weather warnings sent through various cellular technologies represent one way for officials to quickly notify an increasingly mobile public. Cellular technology innovations also make it possible for officials to broadcast information-rich media like graphics to cell phones. Whether warning messages must include such “rich” media to be effective remains an open question. The current study investigates the effectiveness of National Weather Service (NWS) warning messages sent either in plain text or in text that includes a radar image of the storm. The research protocol was modeled after the interactive National Weather Service (iNWS) messaging service currently available to NWS core partners. In the study, participants read full-text NWS warnings of tornadoes or flash floods that either did or did not include a radar image of the storm. The researchers timed participants' ability to decide if a critical town was in the warning area, and then probed their understanding of the message content. Results show that participants' decision times to the town question did not differ between the graphic and no-graphic conditions. None of the other message content measures differed as a function of message condition. The results have potential implications for the federal government's new Wireless Emergency Alert (WEA) system, which, as yet, is limited to text-only warnings.
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Grasso, Valentina, Alfonso Crisci, Marco Morabito, et al. "Italian codified hashtags for weather warning on Twitter – who is really using them?" Advances in Science and Research 14 (April 4, 2017): 63–69. http://dx.doi.org/10.5194/asr-14-63-2017.

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Abstract. During emergencies, an increasing number of messages are shared through social media platforms, becoming a primary source of information for lay people and emergency managers. Weather services and institutions have started to employ social media to deliver weather warnings even if sometimes this communication lacks in strategy. In Twitter, for example, hashtagging is very important to associate messages with certain topics; in recent years, codified hashtagging is emerging as a practical way to coordinate Twitter conversations during emergencies and quickly retrieve relevant information. In 2014, a syntax for codified hashtags for weather warning was proposed in Italy: a list of 20 hashtags, realized by combining #allertameteo (weather warning) + XXX, where final letters code the regional identification. This contribution presents a monitoring of Twitter usage of weather warning codified hashtags in Italy (since July 2015) and an analysis of different contexts. Twitter messages were retrieved using TwitterVigilance, a multi-users platform to crawl Twitter data, collect and store messages and perform quantitative analytics, about users, hashtags, tweets/retweets volumes. The Codified Hashtags data set is presented and discussed with main analytics and evaluation of regional contexts where it was successfully employed.
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15

Tran, Martin, Samuel Kreinberg, Eric Specking, et al. "Smart Installation Weather Warning Decision Support." Systems 12, no. 1 (2024): 14. http://dx.doi.org/10.3390/systems12010014.

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Army installation commanders need timely weather information to make installation closure decisions before or during adverse weather events (e.g., hail, thunderstorms, snow, and floods). We worked with the military installation in Fort Carson, CO, and used their Weather Warning, Watch, and Advisory (WWA) criteria list to establish the foundation for our algorithm. We divided the Colorado Springs area into 2300 grids (2.5 square kilometers areas) and grouped the grids into ten microclimates, geographically and meteorologically unique regions, per pre-defined microclimate regions provided by the Fort Carson Air Force Staff Weather Officers (SWOs). Our algorithm classifies each weather event in the WWA list using the National Weather Service’s and National Digital Forecast Database’s data. Our algorithm assigns each event a criticality level: none, advisory, watch, or warning. The traffic network data highlight the importance of each road segment for travel to and from Fort Carson. The algorithm also uses traffic network data to assign weight to each grid, which enables the aggregation to the region and installation levels. We developed a weather dashboard in ArcGIS Pro to verify our algorithm and visualize the forecasted warnings for the grids and regions that are or may be affected by weather events.
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Weyrich, Philippe, Anna Scolobig, Florian Walther, and Anthony Patt. "Responses to severe weather warnings and affective decision-making." Natural Hazards and Earth System Sciences 20, no. 10 (2020): 2811–21. http://dx.doi.org/10.5194/nhess-20-2811-2020.

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Abstract. When public agencies provide information provision to help people make better decisions, they often face the choice between economy and completeness. For weather services warning people of high-impact weather events, this choice is between offering standard warnings (SWs) only of the weather event itself, such as wind-speed, or also describing the likely impacts (so-called impact-based warnings, IBWs). Previous studies have shown IBWs to lead to a greater behavioral response. These studies, however, have relied on surveys describing hypothetical weather events; given that participants did not feel threatened, they may have been more likely to process the warning slowly and analytically, which could bias the results towards finding a greater response to the IBWs. In this study, we conducted a field experiment involving actual and potentially threatening weather events for which there was variance with respect to the time interval between the warning and the forecasted event and for which we randomly assigned participants to receive SWs or IBWs. We observe that shorter time intervals led to a greater behavioral response, suggesting that fear of an imminent threat is an important factor motivating behavior. We observe that IBWs did not lead to greater rates of behavioral change than SWs, suggesting that when fear is a driving factor, the additional information in IBWs may be of little importance. We note that our findings are highly contextualized, but we call into question the prevailing belief that IBWs are necessarily more helpful than SWs.
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Shilenje, Zablon W., and Bob A. Ogwang. "The Role of Kenya Meteorological Service in Weather Early Warning in Kenya." International Journal of Atmospheric Sciences 2015 (March 12, 2015): 1–8. http://dx.doi.org/10.1155/2015/302076.

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Early warning in weather forecasting entails provision of timely and effective weather information that allows individuals, organisations, or communities exposed to likely weather hazards to take action that avoids or reduces their exposure to risks. Various sectors have developed different ways to mitigate the effects of climate anomalies. The study reviews the existing monitoring and response structures, and communications flow channels of weather data at different levels, focusing on the role of Kenya Meteorological Service (KMS). The methodology employed was literature review of various documents. The study argues that early warning and weather information communication are essential elements for effective governance of weather risks through a well-developed warning system. At the end, the study recommends strengthening the existing structures with respect to weather monitoring, processing, and dissemination of weather products to end users.
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Lakshmanan, Valliappa, Travis Smith, Gregory Stumpf, and Kurt Hondl. "The Warning Decision Support System–Integrated Information." Weather and Forecasting 22, no. 3 (2007): 596–612. http://dx.doi.org/10.1175/waf1009.1.

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Abstract The Warning Decision Support System–Integrated Information (WDSS-II) is the second generation of a system of tools for the analysis, diagnosis, and visualization of remotely sensed weather data. WDSS-II provides a number of automated algorithms that operate on data from multiple radars to provide information with a greater temporal resolution and better spatial coverage than their currently operational counterparts. The individual automated algorithms that have been developed using the WDSS-II infrastructure together yield a forecasting and analysis system providing real-time products useful in severe weather nowcasting. The purposes of the individual algorithms and their relationships to each other are described, as is the method of dissemination of the created products.
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Hoffmann, David, Elizabeth E. Ebert, Carla Mooney, Brian Golding, and Sally Potter. "Using value chain approaches to evaluate the end-to-end warning chain." Advances in Science and Research 20 (July 11, 2023): 73–79. http://dx.doi.org/10.5194/asr-20-73-2023.

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Abstract. The weather information value chain provides a framework for characterising the production, communication, and use of information by all stakeholders in an end-to-end warning system covering weather and hazard monitoring, modelling and forecasting, risk assessment, communication and preparedness activities. Warning services are typically developed and provided through a multitude of complex and malleable value chains (networks), often established through co-design, co-creation and co-provision. In November 2020, a 4-year international project under the World Meteorological Organization (WMO) World Weather Research Programme was instigated to explore value chain approaches to describe and evaluate warning systems for high impact weather by integrating physical and social science. It aims to create a framework with guidance and tools for using value chain approaches, and to develop a database of high impact weather warning case studies for scientists and practitioners to review, analyse and learn from previous experience using value chain approaches. Here we describe a template for high-impact weather event case study collection that provides a tool for scientists and practitioners involved in researching, designing and evaluating weather-related warning systems to review previous experience of high impact weather events and assess their efficacy.
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Kamaya, Noriko, Mitsuyuki Hoshiba, Akio Katsumata, and Keiji Doi. "Continuity of Earthquake and Tsunami Monitoring by Japan Meteorological Agency under Critical Conditions." Seismological Research Letters 92, no. 1 (2020): 17–25. http://dx.doi.org/10.1785/0220200259.

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Abstract The Japan Meteorological Agency (JMA) is a governmental organization that has responsibilities for mitigation of natural disasters. JMA issues warnings and information about natural disasters, in addition to daily weather forecasts. When an earthquake occurs, JMA analyzes seismic data to issue an earthquake early warning and to warn of possible tsunamis when a tsunami is expected to strike coastal areas of Japan. During tsunami warning in effect, JMA monitors tsunami meters and updates the warning. JMA also provides several types of macroseismic information. To fulfill these responsibilities, JMA collects data from 4400 seismic intensity meters, 1800 seismometers, 400 tsunami meters, and 39 strainmeters. Monitoring must be continued even under difficult situations such as times following great earthquakes, volcanic eruptions, severe weather conditions, and pandemics. JMA has dual operations centers located in Tokyo and Osaka. When one loses functionality due to a disaster or infection, the other continues 24/7 operations including warnings and issuing other information. Disastrous situations often cause power and communication failures and insufficient numbers of technical specialists. Following the 2011 Tohoku-oki earthquake, JMA enhanced power and communication capabilities by adding large capacity batteries at each station and satellite communication links. During the coronavirus disease 2019 (COVID-19) pandemic, JMA has taken several measures to prevent technical specialists’ infection to continue the full range of functions for issuing of warnings and conveying needed information.
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Schultz, David M., Eve C. Gruntfest, Mary H. Hayden, Charles C. Benight, Sheldon Drobot, and Lindsey R. Barnes. "Decision Making by Austin, Texas, Residents in Hypothetical Tornado Scenarios*." Weather, Climate, and Society 2, no. 3 (2010): 249–54. http://dx.doi.org/10.1175/2010wcas1067.1.

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Abstract One of the goals of the Warning Project is to understand how people receive warnings of hazardous weather and subsequently use this information to make decisions. As part of the project, 519 surveys from Austin, Texas, floodplain residents were collected and analyzed. About 90% of respondents understood that a tornado warning represented a more serious and more likely threat than a tornado watch. Most respondents (86%) were not concerned about a limited number of false alarms or close calls reducing their confidence in future warnings, suggesting no cry-wolf effect. Most respondents reported safe decisions in two hypothetical scenarios: a tornado warning issued while the respondent was home and a tornado visible by the respondent while driving. However, nearly half the respondents indicated that they would seek shelter from a tornado under a highway overpass if they were driving. Despite the limitations of this study, these results suggest that more education is needed on the dangers of highway overpasses as shelter from severe weather.
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Losee, Joy E., Karen Z. Naufel, Lawrence Locker, and Gregory D. Webster. "Weather Warning Uncertainty: High Severity Influences Judgment Bias." Weather, Climate, and Society 9, no. 3 (2017): 441–54. http://dx.doi.org/10.1175/wcas-d-16-0071.1.

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Abstract Information about hurricanes changes as the storm approaches land. Additionally, people tend to think that severe events are more likely to occur even if the probability of that event occurring is the same as a less severe event. Thus, holding probability constant, this research tested the influence of severity on storm judgments in the context of updates about the approaching storm’s severity. In two studies, participants watched one of four (experiment 1) or one of five (experiment 2) sequences of updating hurricane warnings. The position of category 1 and category 5 hurricane warnings in the sequences varied (e.g., category 1 first and category 5 last, or category 5 first and category 1 last). After the videos, participants made judgments about the approaching storm. In experiment 1, participants generally overestimated the threat of the storm if they saw a category 5 hurricane warning in any position. Experiment 2, designed to test whether experiment 1 results were due to a contrast effect, revealed a similar pattern to experiment 1. Overall, when participants saw a category 5 hurricane warning, they anchored to severity regardless of updates that the storm had decreased in severity. Importantly, however, the extent of anchoring to severity depended on the type of judgment participants made. In terms of policy, the study proposes that weather warning agencies focus on message content at least as much as they focus on message accuracy.
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Lusambili, Adelaide, Veronique Filippi, Britt Nakstad, et al. "Community perspectives of heat and weather warnings for pregnant and postpartum women in Kilifi, Kenya." PLOS ONE 19, no. 11 (2024): e0313781. http://dx.doi.org/10.1371/journal.pone.0313781.

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Background Extreme weather is a recognised risk factor for stillbirth and preterm birth, disrupts women’s access to healthcare during pregnancy and childbirth, and negatively affects the care of newborns. Reliable and accessible heat and weather warning systems are key in alerting individuals to undertake protective measures. There is a notable gap in understanding how women and caregivers in rural East Africa perceive and utilize weather information. We investigated community members’ heat and weather warning information-seeking behaviour, identified available sources, assessed their reliability and utility, and examined their influence on behaviour. Settings Our research was conducted in rural Kilifi County in Kenya’s coastal region. The area experiences temperatures exceeding 23°C throughout the year, with extended periods of extreme temperatures [> 40°C] and long and severe droughts. Methods We conducted in-depth interviews [IDI] with pregnant and postpartum women [n = 21] and held six focus group discussions [FGDs] involving mothers-in-law and community health volunteers [CHVs]. The data were analysed in NVivo 12 using both inductive and deductive approaches. Results We found significant gaps concerning pregnant and post-partum women, and their caregivers, having timely access to weather forecasts and heat information from health or meteorological authorities. Information on heat and weather warnings is disseminated through various channels, including television, radio, mobile phones, and word of mouth, which are facilitated by community influencers such as CHVs and local chiefs. Indigenous methods of weather forecasting, such as cloud observation, consulting local “rainmakers”, and studying the behavioural patterns of amphibians, are employed in conjunction with warnings from the Kenyan Meteorological Department (KMD). Barriers to accessing weather information include the cost of television and smartphones and a lack of segmented information in local languages. Conclusions National and county meteorological services need to enhance public participation, communication, and the delivery of heat and weather information to guide community-level response measures and individual behaviour change. They should also collaborate with health professionals to address heat risks for vulnerable groups. Further research is needed to empower indigenous weather predictors with modern weather information and revise national policies to deliver tailored messages to vulnerable populations like pregnant and postpartum women.
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Gao, Jidong, Travis M. Smith, David J. Stensrud, et al. "A Real-Time Weather-Adaptive 3DVAR Analysis System for Severe Weather Detections and Warnings." Weather and Forecasting 28, no. 3 (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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Eachus, Joshua D., and Barry D. Keim. "A Survey for Weather Communicators: Twitter and Information Channel Preferences." Weather, Climate, and Society 11, no. 3 (2019): 595–607. http://dx.doi.org/10.1175/wcas-d-18-0091.1.

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Abstract It has been almost a decade since researchers assessed user preferences in gathering weather information. Maturing channels and increasingly mobile audiences necessitate the need for understanding what channels people use for weather information, what information people want, and how they react to specific content—especially potentially life-saving warnings. Furthermore, geographically compartmentalizing this information will allow communication strategies to be tailored to a more localized audience. As an initiative to this effort, a survey of digitally connected Louisianians found different channel preferences than were found in previous studies. Beyond this study, future research should seek to identify regional preferences since the last broad study on this topic nearly 10 years ago. In the survey, information preferences are collected with Twitter as the focal point, but other channels are included as choices to assess overall user preference. As older channels such as television decline in preference, mobile telephone applications are disrupting previous literature by quickly gaining popularity while studies on their utility remain in short supply. Results show that user channel preferences do not necessarily align with those that best serve weather communication efforts. Facebook, a channel notoriously problematic from a chronology standpoint, is favored by many respondents. On Twitter, there is a disconnect in the type of information respondents report wanting and what type of information generates a response. Interest in warning messages was not coincident with the threat posed by that specific type of weather. The format—wording and construction—of warning messages that generated the most response on Twitter does not align with extensive literature on proper risk communication.
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Kolawole, Oluwatoyin Dare, Moseki Ronald Motsholapheko, Barbara Ntombi Ngwenya, Ananias Moses, Melda Nonhle Makebea, and Matshidiso Tshidi Kaisara. "Smallholder Farmers’ Responses to Scientific Early Warning on Weather in the Okavango Delta, Botswana." Journal of Sustainable Development 11, no. 6 (2018): 82. http://dx.doi.org/10.5539/jsd.v11n6p82.

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Although formal channels of communication exist for conveying early warning scientific weather messages, it is widely believed that small-scale farmers continue to utilize traditional practices in obtaining weather information. This study identifies and assesses the factors which influence the uptake of scientific early warning weather information by small farmers in the Okavango Delta, Botswana. A descriptive-analytical design was used to study 90 farmers in Kareng and Bodibeng communities situated within the delta basin. A multi-stage sampling procedure was used to select the sample from an existing household listing. A semi-structured interview and focus group discussion (FGD) were used to elicit information from the respondents. Findings show that most farmers (68.9%) moderately utilize scientific weather information, while 16.7% had a low uptake of the messages. Nonetheless, 14.4% of farmers had a high uptake of weather information. There was significant positive correlation, at p≤0.01 confidence level, between uptake of early warning scientific weather information and educational level, age, traditionalism and fatalism. The uptake of scientific weather information or messages had a strong association with information sources such as Kgotla meetings, TV, print media, agricultural extension agents and the radio. The uptake of modern scientific weather information needs to be promoted through these modes of communication, coupled with well-resourced extension services, and in ways that may not be perceived to denigrate indigenous knowledge. Sectoral departments should collaborate in addressing existing challenges for appropriate climate response action.
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Tomczyk, Samuel, Maxi Rahn, Henriette Markwart, and Silke Schmidt. "A Walk in the Park? Examining the Impact of App-Based Weather Warnings on Affective Reactions and the Search for Information in a Virtual City." International Journal of Environmental Research and Public Health 18, no. 16 (2021): 8353. http://dx.doi.org/10.3390/ijerph18168353.

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Background: Warning apps can provide personalized public warnings, but research on their appraisal and impact on compliance is scarce. This study introduces a virtual city framework to examine affective reactions when receiving an app-based warning, and subsequent behavioral intentions. Methods: In an online experiment, 276 participants (M = 41.07, SD = 16.44, 62.0% female) were randomly allocated to one of eight groups (warning vs. no warning, thunderstorm vs. no thunderstorm, video vs. vignette). Participants were guided through a virtual city by a mock-up touristic app (t1). Then, the app issued a warning about an impending thunderstorm (t2), followed by a virtual thunderstorm (t3). The virtual city tour was presented via vignettes or videos. ANCOVAs were used to investigate trajectories of momentary anxiety, hierarchical regressions analyzed the impact of momentary anxiety on information seeking. Results: Participants who received a warning message and were confronted with a thunderstorm showed the highest increase in momentary anxiety, which predicted information seeking intentions. Conclusions: The findings underscore the importance of affective appraisal in processing warning messages. The virtual city framework is able to differentiate the impact of warning versus event in an online context, and thus promising for future warning research in virtual settings.
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Bi, HuiJing, HongYan Zhang, YueMei Jiang, and XiLan Zhao. "A New Security Warning Model about Power Grid." MATEC Web of Conferences 160 (2018): 04005. http://dx.doi.org/10.1051/matecconf/201816004005.

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In recent years, lots of power grid blackouts at home and abroad indicates that the meteorological disasters caused by external meteorological conditions has gradually rose to major contradiction of power grid security. Basing on release information of meteorology, lightning monitoring information and power transmission equipment monitoring information, it established a weather warning model about power grid security, combined with real-time security analysis. Firstly, mathematical models of various types of weather conditions and weather risk assessment model grid were built, then actual operating conditions of a certain regional power grid and model results were compared, the comparison result prove the accuracy of the warning model, and provides a strong recommendation for decision-making.
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Prianti, Ni Putu Nonik, Roddialek Pollo, Judi K. Nasjoro, and Sulton Kharisma. "Perbandingan Estimasi Radar Cuaca Dopler Baron Terhadap Data Observasi Kejadian Hujan Di Kota Kupang." Bumi Lestari Journal of Environment 20, no. 2 (2020): 1. http://dx.doi.org/10.24843/blje.2020.v20.i02.p01.

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Radar is able to provide information about extreme weather observations in the form of heavy rain, so it is important to find the level of accuracy of the radar in providing extreme weather information. So that with accurate data disaster mitigation can be done by creating an early warning system using radar data in order to minimize the impact that will occur. Comparative analysis of the estimated rainfall events on the radar with surface observation data shows a good level of accuracy, but the blankness of the data on the radar due to damage thus influences the decision making of the forecasters when providing extreme weather information quickly to the public. By knowing the radar accuracy level is quite good in estimating rain events, BMKG can provide weather information in the form of appropriate early warning so that people can anticipate extreme weather events
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Mohsen, S. Alsaadi, and D. Alotaibi Naif. "5G Network Slicing for Improved Meteorological Warning Dissemination." Journal of Intelligent Systems and Applied Data Science (JISADS) 1, no. 2 (2024): 35–40. https://doi.org/10.5281/zenodo.15477254.

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This study addresses challenges in meteorological warning dissemination by examining the limitations of traditional communication methods that have been used. Leveraging 5G technologies such as mobile communications, IoT, and advanced satellites, the research focuses on integrating 5G network slicing to enhance the transmission speed and accuracy of meteorological disaster warnings. The paper proposes a concise design reference scheme, defining key indices and requirements for 5G network slicing tailored to meteorological information transmission. The three-tiered end-to-end architecture of 5G network slicing, involving the management, control, and user planes, is outlined. Key components like CSMF, NSMF, and NSSMF contribute to the comprehensive life cycle management of end-to-end slicing. The study classifies Service Level Agreement (SLA) indicators for 5G network slicing, aligning them with industry standards, and establishes a foundational understanding for implementation. This framework aims to revolutionize information transmission, providing a scalable and adaptive solution for meteorological warning systems in dynamic environments.
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Ali, Abdullah, Iddam Hairully Umam, Hesti Heningtyas, et al. "Pengembangan Sistem Peringatan Dini Cuaca Ekstrem Terintegrasi Berbasis Y-Model Webgis Development Methodology (Y-WDM)." Jurnal Geografi, Edukasi dan Lingkungan (JGEL) 6, no. 2 (2022): 87–100. http://dx.doi.org/10.22236/jgel.v6i2.8222.

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The incidence of hydrometeorological disasters in Indonesia is in the largest percentage for the last 10 years. The development of an integrated extreme weather early warning system is one of the initial processes in a series of hydrometeorological disaster mitigation efforts. Data models, observation and remote sensing become the database in early warning of extreme weather, the officers who carry out early detection of hazards so that they have sufficient waiting time to prepare an effective emergency response plan. In this study, an early warning system was built by implementing the Y-Model WebGIS Development Methodology (YWDM) which is a combination of geographic information systems and web-based application development context. Spatial data processing is carried out using the python programming language, including radar and weather satellite data, surface observation, lightning detection, storm detection and identification, and nowcasting models. Web GIS visualization is built by using JavaScript and php programming language, database management managed using PostgreSQL. The results of the implementation are in the form of a SPACE (Spatial Based Extreme Weather Warning System) framework which Sidarma-Nowcast is a system within the framework. The development of this system shows an increase and the level of improvement in the process of producing and disseminating early warning information.
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Yoder-Bontrager, Daryl, Joseph E. Trainor, and Madison Swenson. "Giving Attention: Reflections on Severe Weather Warnings and Alerts on Mobile Devices." International Journal of Mass Emergencies & Disasters 35, no. 3 (2017): 169–90. http://dx.doi.org/10.1177/028072701703500304.

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Smartphones are an increasingly important channel through which to issue weather alerts and warnings. Yet it is important to consider the nature of these devices and the implications for alerts and warnings. Alerts have traditionally been designed to get the attention of recipients while warnings provide the information needed to decide if it is necessary to take protective action. Smartphones are distinct from traditional channels in that they do both. They can be incredibly effective at delivering alerts and are also able to deliver multiple streams of warning information simultaneously to a single person. Our work suggests that this reality can result in information flow fatigue if these message systems are not properly designed. In a process which we describe as setting up jigs, smartphone users report the importance of restricting or prioritizing information using their phone settings or even turning off notifications or shutting down their phones at specific times and places. Our analysis of focus group discussions concludes that storm alerts and warnings delivered through smartphones must prioritize personalized settings and messages that help recipients filter the information they want to give their attention to rather than designing them to forcibly get people's attention.
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Piciullo, Luca, Mads-Peter Dahl, Graziella Devoli, Hervé Colleuille, and Michele Calvello. "Adapting the EDuMaP method to test the performance of the Norwegian early warning system for weather-induced landslides." Natural Hazards and Earth System Sciences 17, no. 6 (2017): 817–31. http://dx.doi.org/10.5194/nhess-17-817-2017.

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Abstract. The Norwegian national landslide early warning system (LEWS), operational since 2013, is managed by the Norwegian Water Resources and Energy Directorate and was designed for monitoring and forecasting the hydrometeorological conditions potentially triggering slope failures. Decision-making in the LEWS is based upon rainfall thresholds, hydrometeorological and real-time landslide observations as well as on landslide inventory and susceptibility maps. Daily alerts are issued throughout the country considering variable size warning zones. Warnings are issued once per day for the following 3 days and can be updated according to weather forecasts and information gathered by the monitoring network. The performance of the LEWS operational in Norway has been evaluated applying the EDuMaP method, which is based on the computation of a duration matrix relating number of landslides and warning levels issued in a warning zone. In the past, this method has been exclusively employed to analyse the performance of regional early warning models considering fixed warning zones. Herein, an original approach is proposed for the computation of the elements of the duration matrix in the case of early warning models issuing alerts on variable size areas. The approach has been used to evaluate the warnings issued in Western Norway, in the period 2013–2014, considering two datasets of landslides. The results indicate that the landslide datasets do not significantly influence the performance evaluation, although a slightly better performance is registered for the smallest dataset. Different performance results are observed as a function of the values adopted for one of the most important input parameters of EDuMaP, the landslide density criterion (i.e. setting the thresholds to differentiate among classes of landslide events). To investigate this issue, a parametric analysis has been conducted; the results of the analysis show significant differences among computed performances when absolute or relative landslide density criteria are considered.
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Trinh Thu Phuong, Nguyen Tien Kien, Luong Huu Dung, and Luong Phuong Linh. "BUILDING A REAL-TIME INFORMATION AND FLASH FLOODS, LANDSLIDES EARLY WARNING SYSTEM IN MOUNTAINOUS AND MIDLAND AREAS OF VIET NAM." Tạp chí Khoa học Biến đổi khí hậu, no. 27 (September 30, 2023): 44–55. http://dx.doi.org/10.55659/2525-2496/27.85960.

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Flash flood is a natural disaster occurring shortly on small scale albeit with great devastation. In fact, the current flash flood events, landslide investigations and surveys from research agencies and local authorities play an important role in creating diverse data sources for researching and exploring the signs as well as modeling adjustment for detecting the risks. This article presents the results of making a Web portal used for the reception and integration of early warnings from citizens, local authorities and governing bodies against flash floods and landslides. This system collects real time rainfall data from the CDH of Meteorology and Hydrology Administration, integrates the numerical weather prediction WRF (the Weather Research and Forescast) model with 6 h, 24 h, 48 h forecast lead time and SEAFFGS product results. Also, it would elaborate on the system providing tools for aiding, analysing, producing and disseminating warning bulletins against flash floods and landslides for mountainous and midland areas, sending warning message about high risk flash flood and landslide with the total observed rainfall or rainfall forecast over the threshold via email or Zalo automatically. This information which can be accessed everywhere via the internet, will effectively support the forecasters in mornitoring and publishing the flash flood and landslide warning bulletins; help the authorities and citizens become aware of natural disasters early and mitigate damage caused by flash floods and landslides.
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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 (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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Krennert, Thomas, Georg Pistotnik, Rainer Kaltenberger, and Christian Csekits. "Crowdsourcing of weather observations at national meteorological and hydrological services in Europe." Advances in Science and Research 15 (May 18, 2018): 71–76. http://dx.doi.org/10.5194/asr-15-71-2018.

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Abstract. National Meteorological and Hydrological Services (NMHSs) increase their efforts to deliver impact-based weather forecasts and warnings. At the same time, a desired increase in cost-efficiency prompts these services to automatize their weather station networks and to reduce the number of human observers, which leads to a lack of “ground truth” information about weather phenomena and their impact. A possible alternative is to encourage the general public to submit weather observations, which may include crucial information especially in high-impact situations. We wish to provide an overview of the state and properties of existing collaborations between NMHSs and voluntary weather observers or storm spotters across Europe. For that purpose, we performed a survey among 30 European NMHSs, from which 22 NMHSs returned our questionnaire. This study summarizes the most important findings and evaluates the use of “crowdsourced” information. 86 % of the surveyed NMHSs utilize information provided by the general public, 50 % have established official collaborations with spotter groups, and 18 % have formalized them. The observations are most commonly used for a real-time improvement of severe weather warnings, their verification, and an establishment of a climatology of severe weather events. The importance of these volunteered weather and impact observations has strongly risen over the past decade. We expect that this trend will continue and that storm spotters will become an essential part in severe weather warning, like they have been for decades in the United States of America. A rising number of incoming reports implies that quality management will become an increasing issue, and we finally discuss an idea how to handle this challenge.
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Karstens, Christopher D., James Correia, Daphne S. LaDue, et al. "Development of a Human–Machine Mix for Forecasting Severe Convective Events." Weather and Forecasting 33, no. 3 (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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Shapovalov, Vitaliy A. "System of Warning about Dangerous Atmospheric Phenomena in the North Caucasus for Objects of Economic Activity." Materials Science Forum 931 (September 2018): 1019–24. http://dx.doi.org/10.4028/www.scientific.net/msf.931.1019.

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This paper presents the developed program-mathematical software for receiving, archiving, analysis and display of radar, lightning and satellite data on clouds and precipitation, interfacing of meteorological information. The program of processing of meteorological information "GIMET-2010" is established on a network of weather radars DMRL-C of the Russian Federation. An automated system combining radar and lightning detection system information applies to the command posts of the uniformed services on the fight against hail and centers of severe storm warning. Following items are provided: a receiving and transmitting to consumers the operational radar data on the actual weather; the detection, identification, and warning of hazardous weather phenomena for airports and populated areas; measurement of the intensity and amount of precipitation for agriculture, hydrological forecasts and land reclamation; obtaining precipitation map for agriculture and insurance companies.
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USHIYAMA, Motoyuki. "AN ANALYSIS OF UNDERSTANDING OF USERS FOR GRADED WEATHER WARNING INFORMATION." Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering) 70, no. 4 (2014): I_1513—I_1518. http://dx.doi.org/10.2208/jscejhe.70.i_1513.

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Tamamadin, M., A. Susandi, A. F. Pratama, et al. "Automation Process to Support an Information System on Extreme Weather Warning." IOP Conference Series: Materials Science and Engineering 803 (May 28, 2020): 012044. http://dx.doi.org/10.1088/1757-899x/803/1/012044.

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Wallace, Zebulon C. "Forecasters, emergency managers, and residents: Building better risk communication." Journal of Emergency Management 22, no. 3 (2024): 235–48. http://dx.doi.org/10.5055/jem.0745.

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The US National Weather Service (NWS) and emergency managers (EMs) around the country are tasked with communicating severe weather information to the public. Frequent interaction between professionals and residents is essential to building effective partnerships. This paper investigates these interactions and also explores the perspectives of NWS forecasters, EMs, and rural residents related to the efficacy of warning communication, message understanding, preferred platforms, and engagement in protective actions. Data for this study were collected through three original survey instruments that were directed to NWS forecasters and EMs across the country, and residents in four rural communities. Findings reveal that residents generally understand warning messages and generally feel tornado risk communication is effective in their communities. However, residents do not appear to have a plan of action formulated prior to a warning and are, therefore, making, rather than implementing, a plan when warning is issued. This study gives rural residents a voice in the warning communication process and a chance for forecasters and EMs to gain valuable information as they better plan to serve these communities.
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Krennert, Thomas, Rainer Kaltenberger, Georg Pistotnik, Alois M. Holzer, Franz Zeiler, and Mathias Stampfl. "Trusted Spotter Network Austria – a new standard to utilize crowdsourced weather and impact observations." Advances in Science and Research 15 (May 18, 2018): 77–80. http://dx.doi.org/10.5194/asr-15-77-2018.

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Abstract. Information from voluntary storm spotters has been an increasingly important part for the severe weather warning process at the Zentralanstalt für Meteorologie and Geodynamik (ZAMG), Austria's National Weather Service, for almost 15 years. In 2010 a collaboration was formalized and an annual training was established to educate voluntary observers into “Trusted Spotters”. The return of this investment is a higher credibility of their observations after these spotters have undergone a basic meteorological training and have become aware of their responsibility. The European Severe Storms Laboratory (ESSL) was included to this collaboration to adopt their successful quality control system of severe weather reports, which is employed in the European Severe Weather Database ESWD. That way, reports from Trusted Spotters automatically obtain a higher quality flag, which enables a faster processing by forecasters on duty for severe weather warnings, when time is a critical issue. The concept of combining training for voluntary storm spotters and a thorough quality management was recognized as a “Best Practice Model” by the European Meteorological Society. We propose to apply this concept also in other European countries and present its advancement into an even broader, pan-European approach. The European Weather Observer app EWOB, recently released by ESSL, provides a novel and easy-to-handle tool to submit weather and respective impact observations. We promote its use to provide better data and information for a further real-time improvement of severe weather warnings.
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de Baar, Jouke H. S., Irene Garcia-Marti, and Gerard van der Schrier. "Spatial regression of multi-fidelity meteorological observations using a proxy-based measurement error model." Advances in Science and Research 20 (June 6, 2023): 49–53. http://dx.doi.org/10.5194/asr-20-49-2023.

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Abstract. High-resolution weather maps are fundamental components of early warning systems, since they enable the (near) real-time tracking of extreme weather events. In this context, crowd-sourced weather networks producing low-fidelity observations are often the only type of data available at local (e.g. neighborhood) scales. In this work, we demonstrate that we can provide such maps by combining high-fidelity official weather data with low-fidelity crowd-sourced weather data and high-resolution covariate information. Because the crowd-sourced data contains significant bias and noise, we develop an approach to include a bias budget and noise budget in the multi-fidelity Bayesian spatial data analysis. The weights of the different components of these bias and noise budgets are tuned to the data set. We apply this approach to 24 hours of weather data in the Netherlands, for a day that had a “code orange” (i.e. “be prepared for extreme weather with high risk of impact”) weather warning for heavy precipitation. From our analysis, we see a significant – qualitative and quantitative – synergy effect when introducing low-fidelity data and high-resolution covariate information.
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De la Luz, V., J. A. González-Esparza, M. Sergeeva, P. Corona-Romero, J. Mejía-Ambriz, and L. X. González. "The Mexican Early Warning System for Space Weather." Proceedings of the International Astronomical Union 13, S335 (2017): 236–39. http://dx.doi.org/10.1017/s1743921317010158.

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AbstractEarly Warning of Space Weather phenomena is one of the most important products produced by Mexican Space Weather Service (SCiESMEX). The aim is to deliver a verified warning to Mexican National Center for Disaster Prevention (CENAPRED) as well as to general public in near-real time automatically. First, the international pubic warning (or alert) is produced by Space Weather Prediction Center of National Oceanic and Atmospheric Administration, U.S.A. Further, the alert is received by SCiESMEX system, decodified, translated in Spanish and put in the context of local current conditions. The alerts are transformed and validated in agreement to Mexican policies of civil protection and CENAPRED protocols. The automatic system segments the information and delivers the corresponding web- page-alerts, emails, twits, facebook messages and SMS. The latency of the alert is 5 minutes. The code is running since January of 2015 without major interruptions.
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Raddaoui, Omar, and Mohamed M. Ahmed. "Evaluating the Effects of Connected Vehicle Weather and Work Zone Warnings on Truck Drivers’ Workload and Distraction using Eye Glance Behavior." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 3 (2020): 293–304. http://dx.doi.org/10.1177/0361198120910743.

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This study acts in support of the Wyoming Department of Transport (WYDOT) connected vehicle pilot efforts in the deployment of effective, safe, and user-centered connected vehicle (CV) applications and human machine interface (HMI) displays. This study sought to quantify the workload demands and distraction introduced by the pilot’s spot weather impact warning (SWIW) and work zone warning (WZW) applications on professional truck drivers. Using driving simulator experimentation and eye-tracking technology, the effects of exposure to the CV warnings on the participants’ glance behavior were quantified. The study revealed that the weather notifications did not invoke any notable workload or distraction to the participants. Conversely, the WZWs deteriorated the participants’ roadway scanning behavior and brought about prolonged off-road glances, and therefore could carry adverse safety impacts to drivers in real-life conditions. This was largely attributed to the fact that, unlike the weather notifications, the WZW application appeared to have over-communicated information to the participants during a short time window and under difficult driving conditions and resulted in a relatively cluttered HMI. In light of these findings, WYDOT, the leading pilot stakeholder, is amending the design of the WZW application in such a way that message flow rate is reduced and only necessary information is displayed. All in all, the methodology applied in this study was effective in uncovering the overall effects of exposure to CV warnings and therefore could be useful for evaluating workload and distraction in the context of emergent advanced driver assistance systems.
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Ou, Tsung-Hua, Tsun-Hua Yang, and Pei-Zen Chang. "Combination of Large Language Models and Portable Flood Sensors for Community Flood Response: A Preliminary Study." Water 17, no. 7 (2025): 1055. https://doi.org/10.3390/w17071055.

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The effectiveness of early warning systems can help people take action to mitigate the impact of extreme weather events once warnings are issued. The early warning systems developed by public agencies usually issue standard messages that, in many situations, may not affect all the people who receive the messages. In the long run, this can lead to behaviors in people who may not respond to relevant warnings, resulting in inefficiency. Users demand faster and more customized information that matches their needs, such as “How does this affect me right now?” or “What can I do to mitigate the impact?” This study proposes a decentralized framework at the community level that includes custom Internet of Things (IoT) sensors for timely information monitoring and large language models (LLMs) for the generation of user-defined warning messages. The sensors have the advantages of easy installation, low cost, and affordable maintenance fees. The trained LLMs expedite information processing given specific prompts and generate customized response messages to the users. In addition, the framework is established within a serverless environment, enabling rapid deployment and scalability. This integration of IoT sensors and LLMs demonstrates how the system performs once sensors detect flooding and how LLMs can deliver real-time, efficient, and localized action-ready information in different scenarios. This combination significantly enhances the responsiveness during flood events.
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Kim, Dae-Jun, Jin-Hee Kim, Eun-Jeong Yun, Dae Gyoon Kang, and Eunhye Ban. "Farmstead-Specific Weather Risk Prediction Technique Based on High-Resolution Weather Grid Distribution." Atmosphere 15, no. 1 (2024): 116. http://dx.doi.org/10.3390/atmos15010116.

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In recent years, the importance and severity of weather-related disasters have escalated, attributed to rising temperatures and the occurrence of extreme weather events due to global warming. The focus of disaster management has shifted from crisis management (e.g., repairing and recovering from damage caused by natural disasters) to risk management (e.g., prediction and preparation) while concentrating on early warning, thanks to the development of media and communication conditions. The Rural Development Administration (Korea) has developed the “early warning service for weather risk management in the agricultural sector” that detects weather risks for crops from high-resolution weather information in advance and provides customized information to respond to possible disaster risks in advance in response to the increasing number of extreme weather events. The core technology of this service is damage prediction technology that determines the overall agricultural weather risk level by quantifying the current growth stage of cultivated crops and the probability of possible weather disasters according to the weather conditions of the farm. Agrometeorological disasters are damages caused by weather conditions that can affect crops and can be predicted by estimating the probability of damage that may occur from the interaction between hazardous weather and crop characteristics. This review introduces the classification of possible weather risks by their occurrence mechanisms, based on the developmental stage of crops and prediction techniques that have been developed or applied to date. The accumulated crop growth and weather risk information is expected to be utilized as support material for farming decision-making, which helps farmers proactively respond to crop damage due to extreme weather events by providing highly reliable disaster forecasts through the advancement of prediction technology.
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Lee, Ghangshin, Sooncheon Hwang, and Dongmin Lee. "Improvements of Warning Signs for Black Ice Based on Driving Simulator Experiments." International Journal of Environmental Research and Public Health 19, no. 12 (2022): 7549. http://dx.doi.org/10.3390/ijerph19127549.

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Black ice is one of the main causes of traffic accidents in winter, and warning signs for black ice are generally ineffective because of the lack of credible information. To overcome this limitation, new warning signs for black ice were developed using materials that change color in response to different temperatures. The performance and effects of the new signs were investigated by conducting driver behavior analysis. To this end, driving simulator experiments were conducted with 37 participants for two different rural highway sections, i.e., a curve and a tangent. The analysis results of the driving behavior and visual behavior experiments showed that the conventional signs had insufficient performance in terms of inducing changes in driving behavior for safety. Meanwhile, the new signs actuated by weather conditions offered a statistically significant performance improvement. Typically, driver showed two times higher speed deceleration when they fixed eyes on the new weather-actuated warning sign (12.80 km/h) compared to the conventional old warning sign (6.84 km/h) in the curve segment. Accordingly, this study concluded that the new weather-actuated warning signs for black ice are more effective than the conventional ones for accident reduction during winters.
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Karavaev, D. M., Yu V. Kuleshov, and G. G. Shchukin. "Study of Ultra-High Frequency Radiometric Humidity Sounding of the Atmosphere for the Early Warning of Hazardous Weather Phenomena." Радиотехника и электроника 68, no. 6 (2023): 615–20. http://dx.doi.org/10.31857/s0033849423060050.

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Ground-based microwave radiometry was used to study the characteristics of the moisture content of the atmosphere during the development of cloud-related hazardous weather phenomena, precipitation, and thunderstorms. On the basis of complex radiophysical studies of the atmosphere, carried out in the Leningrad oblast, the possibility of improving the methods of early warning of dangerous weather phenomena and diagnostics Ground-based microwave radiometry was used to study the characteristics of the moisture content of the atmosphere during the development of cloud-related hazardous weather phenomena, precipitation, and thunderstorms. On the basis of complex radiophysical studies of the atmosphere, carried out in the Leningrad oblast, the possibility of improving the methods of early warning of dangerous weather phenomena and diagnostics of atmospheric fronts with the involvement of operational microwave radiometric information is shown.
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Blair, Scott F., and Jared W. Leighton. "Assessing Real-Time Tornado Information Disseminated through NWS Products." Weather and Forecasting 29, no. 3 (2014): 591–600. http://dx.doi.org/10.1175/waf-d-13-00126.1.

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Abstract Real-time confirmation of a tornado specified in National Weather Service (NWS) warnings and statements is believed to increase the credibility and urgency of these critical warning messages for the end user, because it represents the greatest degree of certainty that the hazard exists. This timely tornado information disseminated in official NWS products and relayed through multiple sources by private and public partners may help the public believe, personalize, confirm, and respond to the warning message. This is the first study to explicitly assess the frequency of real-time confirmation of ongoing tornadoes within NWS products and explore what unique conditions may facilitate or hinder this process. Tornado reports and their respective NWS warnings and statements during a 5-yr period from 2007 to 2011 across the central contiguous United States were compiled and examined. Overall, 40% of tornadoes were confirmed in NWS products in real time. Increasing tornado pathlength, duration, and intensity subsequently resulted in an increasing likelihood of real-time confirmation prior to the tornado dissipating. The time of day was a factor; nighttime tornadoes were 20% less likely to receive real-time confirmation than daytime events. Additionally, increasing tornado forecast risk in products issued by the Storm Prediction Center corresponded to an increasing likelihood of real-time confirmation. Analysis of these data reveals specific scenarios when tornadoes are more or less likely to be reported in real time, providing some guidance for when timely ground-truth information may or may not be available.
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