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Rebecca E. Morss, Jeffrey K. Lazo, Barbara G. Brown, Harold E. Brooks, Philip T. Ganderton, and Brian N. Mills

Despite the meteorological community's long-term interest in weather-society interactions, efforts to understand socioeconomic aspects of weather prediction and to incorporate this knowledge into the weather prediction system have yet to reach critical mass. This article aims to reinvigorate interest in societal and economic research and applications (SERA) activities within the meteorological and social science communities by exploring key SERA issues and proposing SERA priorities for the next decade.

The priorities were developed by the authors, building on previous work, with input from a diverse group of social scientists and meteorologists who participated in a SERA workshop in August 2006. The workshop was organized to provide input to the North American regional component of THORPEX: A Global Atmospheric Research Programme, but the priorities identified are broadly applicable to all weather forecast research and applications.

To motivate and frame SERA activities, we first discuss the concept of high-impact weather forecasts and the chain from forecast creation to value realization. Next, we present five interconnected SERA priority themes—use of forecast information in decision making, communication of forecast uncertainty, user-relevant verification, economic value of forecasts, and decision support— and propose research integrated across the themes.

SERA activities can significantly improve understanding of weather-society interactions to the benefit of the meteorological community and society. However, reaching this potential will require dedicated effort to bring together and maintain a sustainable interdisciplinary community.

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Julie L. Demuth, Rebecca E. Morss, Isidora Jankov, Trevor I. Alcott, Curtis R. Alexander, Daniel Nietfeld, Tara L. Jensen, David R. Novak, and Stanley G. Benjamin


U.S. National Weather Service (NWS) forecasters assess and communicate hazardous weather risks, including the likelihood of a threat and its impacts. Convection-allowing model (CAM) ensembles offer potential to aid forecasting by depicting atmospheric outcomes, including associated uncertainties, at the refined space and time scales at which hazardous weather often occurs. Little is known, however, about what CAM ensemble information is needed to inform forecasting decisions. To address this knowledge gap, participant observations and semistructured interviews were conducted with NWS forecasters from national centers and local weather forecast offices. Data were collected about forecasters’ roles and their forecasting processes, uses of model guidance and verification information, interpretations of prototype CAM ensemble products, and needs for information from CAM ensembles. Results revealed forecasters’ needs for specific types of CAM ensemble guidance, including a product that combines deterministic and probabilistic output from the ensemble as well as a product that provides map-based guidance about timing of hazardous weather threats. Forecasters also expressed a general need for guidance to help them provide impact-based decision support services. Finally, forecasters conveyed needs for objective model verification information to augment their subjective assessments and for training about using CAM ensemble guidance for operational forecasting. The research was conducted as part of an interdisciplinary research effort that integrated elicitation of forecasters’ CAM ensemble needs with model development efforts, with the aim of illustrating a robust approach for creating information for forecasters that is truly useful and usable.

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Julie L. Demuth, Rebecca E. Morss, Leysia Palen, Kenneth M. Anderson, Jennings Anderson, Marina Kogan, Kevin Stowe, Melissa Bica, Heather Lazrus, Olga Wilhelmi, and Jen Henderson


This article investigates the dynamic ways that people communicate, assess, and respond as a weather threat evolves. It uses social media data, which offer unique records of what people convey about their real-world risk contexts. Twitter narratives from 53 people who were in a mandatory evacuation zone in a New York City neighborhood during Hurricane Sandy in 2012 were qualitatively analyzed. The study provides rich insight into the complex, dynamic information behaviors and risk assessments of people at risk, and it illustrates how social media data can be collected, sampled, and analyzed to help provide this understanding. Results show that this sample of people at significant risk attended to forecast information and evacuation orders as well as multiple types of social and environmental cues. Although many tweeted explicitly about the mandatory evacuation order, forecast information was usually referenced only implicitly. Social and environmental cues grew more important as the threat approached and often triggered heightened risk perceptions or protective actions. The results also reveal the importance of different aspects of people’s cognitive and affective risk perceptions as well as specific emotions (e.g., fear, anger) for understanding risk assessments. People discussed a variety of preparatory and protective behavioral responses and exhibited multiple types of coping responses (e.g., humor) as the threat evolved. People’s risk assessments and responses were closely intertwined, and their risk perceptions were not continuously elevated as the hurricane approached; they exhibited different ways of interpreting, coping, and responding as they accessed and processed evolving information about the threat.

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Fuqing Zhang, Rebecca E. Morss, J. A. Sippel, T. K. Beckman, N. C. Clements, N. L. Hampshire, J. N. Harvey, J. M. Hernandez, Z. C. Morgan, R. M. Mosier, S. Wang, and S. D. Winkley


Hurricane Rita made landfall near the Texas–Louisiana border in September 2005, causing major damage and disruption. As Rita approached the Gulf Coast, uncertainties in the storm’s track and intensity forecasts, combined with the aftermath of Hurricane Katrina, led to major evacuations along the Texas coast and significant traffic jams in the broader Houston area. This study investigates the societal impacts of Hurricane Rita and its forecasts through a face-to-face survey with 120 Texas Gulf Coast residents. The survey explored respondents’ evacuation decisions prior to Hurricane Rita, their perceptions of hurricane risk, and their use of and opinions on Hurricane Rita forecasts. The vast majority of respondents evacuated from Hurricane Rita, and more than half stated that Hurricane Katrina affected their evacuation decision. Although some respondents said that their primary reason for evacuating was local officials’ evacuation order, many reported using information about the hurricane to evaluate the risk it posed to them and their families. Despite the major traffic jams and the minor damage in many evacuated regions, most evacuees interviewed do not regret their decision to evacuate. The majority of respondents stated that they intend to evacuate for a future category 3 hurricane, but the majority would stay for a category 2 hurricane. Most respondents obtained forecasts from multiple sources and reported checking forecasts frequently. Despite the forecast uncertainties, the respondents had high confidence in and satisfaction with the forecasts of Rita provided by the National Hurricane Center.

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Rebecca E. Morss, Julie L. Demuth, Heather Lazrus, Leysia Palen, C. Michael Barton, Christopher A. Davis, Chris Snyder, Olga V. Wilhelmi, Kenneth M. Anderson, David A. Ahijevych, Jennings Anderson, Melissa Bica, Kathryn R. Fossell, Jennifer Henderson, Marina Kogan, Kevin Stowe, and Joshua Watts


During the last few decades, scientific capabilities for understanding and predicting weather and climate risks have advanced rapidly. At the same time, technological advances, such as the Internet, mobile devices, and social media, are transforming how people exchange and interact with information. In this modern information environment, risk communication, interpretation, and decision-making are rapidly evolving processes that intersect across space, time, and society. Instead of a linear or iterative process in which individual members of the public assess and respond to distinct pieces of weather forecast or warning information, this article conceives of weather prediction, communication, and decision-making as an interconnected dynamic system. In this expanded framework, information and uncertainty evolve in conjunction with people’s risk perceptions, vulnerabilities, and decisions as a hazardous weather threat approaches; these processes are intertwined with evolving social interactions in the physical and digital worlds. Along with the framework, the article presents two interdisciplinary research approaches for advancing the understanding of this complex system and the processes within it: analysis of social media streams and computational natural–human system modeling. Examples from ongoing research are used to demonstrate these approaches and illustrate the types of new insights they can reveal. This expanded perspective together with research approaches, such as those introduced, can help researchers and practitioners understand and improve the creation and communication of information in atmospheric science and other fields.

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