Jen Henderson

Hurricanes threaten communities in complex and evolving ways due to storm characteristics and geography, as well as demographic and cultural factors. Risks to people in the path of these storms are compounded when wind and water hazards co-occur, such as tornadoes and flash floods, a hazard often referred to as TORFFs. For National Weather Service (NWS) forecasters, messaging these co-occurring threats poses many challenges, including the ongoing assessment and prioritization of which threat is likely to have the greatest impacts and the communication of risks to different publics. In this research, we focus on Hurricane Florence, a category 1 hurricane that produced historic flooding and some wind-related threats, including tornadoes, across the mid-Atlantic coast in September 2018. Through inductive, qualitative analysis of 33 semi-structured interviews with NWS forecasters responsible for issuing alerts during Florence, we examine the intricacies of messaging flood and wind threats as they evolved over the hurricane’s life cycle. Our results show that forecasters aimed to amplify messaging for flood threats over wind threats during Florence. Along with forecast details and expected impacts, motivations for this messaging choice included the potential for flood fatalities and concerns that the public would not understand the severity of compounding hurricane threats. One reason for this disconnect may be the emphasis placed by experts in weather prediction on the Saffir–Simpson hurricane wind scale (SSHWS) as a metric of hurricane severity. Forecaster messaging strategies were informed by these concerns, which may also have implications for how messaging should be shaped in the future.

"Expanding the Concept of Knowledge Transition through Social Science Research" published on 10 Jan 2024 by American Meteorological Society.

Confidence is a concept important to weather prediction, shaping how risk information is created, shared, understood, and acted upon. For forecasters in the National Weather Service (NWS) and their partners in public safety, confidence is central to their work, appearing frequently during their decision support services. While confidence has been examined in a variety of literatures, it is often addressed simplistically or as one of many variables in a study. It is rarely the object of study in and of itself, even less so in a naturalistic setting like an operational environment. To build a more robust knowledge of confidence and its many dimensions, we conducted a multisited ethnography of three interrelated sites central to tornado prediction and information dissemination, leading up to and during a cool-season tornado event. In partnership with collaborators from the NWS and emergency management, we simultaneously deployed to a National Center, a local Weather Forecast Office, and an emergency management office. This article explicates confidence from multiple social science theories, considering the scientific, data-based roots of confidence, as well as its affective, relational, and procedural origins. Our results show that confidence emerges in varied and complex ways and at different scales. Confidence can indicate one’s assessment of evidence and agreement (or lack) of it, beliefs about partners’ future behavior based on past experiences, and ritual interactions between offices that create patterned expectations. We argue for a more robust interdisciplinary analysis of confidence given how it shapes weather-related policies and practices, technologies, and communication strategies.

Disaster events – which can arise from meteorologic, geologic, technologic, or biologic hazards – have long served as sites to investigate socio-behavioral phenomena. Their disruption to and suspen...

Unintended consequences from decisions made in one part of a social-ecological system (SES) in response to climate hazards can magnify vulnerabilities for others in the same system. Yet anticipating or identifying these cascades and spillovers in real time is difficult. Social learning is an important component of adaptation that has the ability to facilitate adaptive capacity by mobilizing multiple actors around a common resource to manage collectively in ways that build local knowledge, reflective practices, and a broader understanding of contexts for decisions. While the foundations of social learning in resource management have been theorized in the literature, empirical examples of unintended consequences that trigger social learning are few. This article analyzes two cases of drought decisions made along the Arkansas River Basin in Colorado; in each, social learning occurred after actors experienced unanticipated impacts from others’ decisions. Methods include interviews with actors, both individual and institutional representatives of different sectors (e.g. recreation, agriculture, etc.), and a review of relevant historical and policy documents. The study identifies four features of social learning that aided actors’ responses to unanticipated consequences: first, governance structures that facilitated more holistic river management; second, relationship boundaries that expanded beyond small scale decisions to capture interactions and emergent problems; third, knowledge of others’ previous experience, whether direct or indirect; and fourth, creation of spaces for safer experimentation with adaptation changes. Results identify empirical examples of actors who successfully learned to adapt together to unexpected consequences and thus may provide insight for others collectively managing drought extremes. Unintended consequences from decisions made in one part of a social-ecological system (SES) in response to climate hazards can magnify vulnerabilities for others in the same system. Yet anticipating or identifying these cascades and spillovers in real time is difficult. Social learning is an important component of adaptation that has the ability to facilitate adaptive capacity by mobilizing multiple actors around a common resource to manage collectively in ways that build local knowledge, reflective practices, and a broader understanding of contexts for decisions. While the foundations of social learning in resource management have been theorized in the literature, empirical examples of unintended consequences that trigger social learning are few. This article analyzes two cases of drought decisions made along the Arkansas River Basin in Colorado; in each, social learning occurred after actors experienced unanticipated impacts from others’ decisions. Methods include interviews with actors, both individual and institutional representatives of different sectors (e.g. recreation, agriculture, etc.), and a review of relevant historical and policy documents. The study identifies four features of social learning that aided actors’ responses to unanticipated consequences: first, governance structures that facilitated more holistic river management; second, relationship boundaries that expanded beyond small scale decisions to capture interactions and emergent problems; third, knowledge of others’ previous experience, whether direct or indirect; and fourth, creation of spaces for safer experimentation with adaptation changes. Results identify empirical examples of actors who successfully learned to adapt together to unexpected consequences and thus may provide insight for others collectively managing drought extremes.