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Abstract Heavy precipitation events and their associated flooding can have major impacts on communities and stakeholders. There is a lack of knowledge, however, about how stakeholders make decisions at the subseasonal-to-seasonal (S2S) time scales (i.e., 2 weeks to 3 months). To understand how decisions are made and S2S predictions are or can be used, the project team for “Prediction of Rainfall Extremes at Subseasonal to Seasonal Periods” (PRES 2 iP) conducted a 2-day workshop in Norman, Oklahoma, during July 2018. The workshop engaged 21 professionals from environmental management and public safety communities across the contiguous United States in activities to understand their needs for S2S predictions of potential extended heavy precipitation events. Discussions and role-playing activities aimed to identify how workshop participants manage uncertainty and define extreme precipitation, the time scales over which they make key decisions, and the types of products they use currently. This collaboration with stakeholders has been an integral part of PRES 2 iP research and has aimed to foster actionable science. The PRES 2 iP team is using the information produced from this workshop to inform the development of predictive models for extended heavy precipitation events and to collaboratively design new forecast products with our stakeholders, empowering them to make more-informed decisions about potential extreme precipitation events. 

Abstract Interdependent critical infrastructures in coastal regions, including transportation, electrical grid, and emergency services, are continually threatened by storm-induced flooding. This has been demonstrated a number of times, most recently by hurricanes such as Harvey and Maria, as well as Sandy and Katrina. The need to protect these infrastructures with robust protection mechanisms is critical for our continued existence along the world’s coastlines. Planning these protections is non-trivial given the rare-event nature of strong storms and climate change manifested through sea level rise. This article proposes a framework for a methodology that combines multiple computational models, stakeholder interviews, and optimization to find an optimal protective strategy over time for critical coastal infrastructure while being constrained by budgetary considerations. 

Abstract 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.