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The integration of physical and social science data can enable novel frameworks, methodologies, and innovative solutions important for addressing complex socio-environmental problems. Unfortunately, many technical, procedural, and institutional challenges hamper effective data integration—detracting from interdisciplinary socio-environmental research and broader public impact. This paper reports on the experiences and challenges of social and physical data integration, as experienced by diverse Early Career Researchers (ECRs), and offers strategies for coping with and addressing these challenges. Through a workshop convened by the National Center for Atmospheric Research (NCAR) Innovator Program, 33 participants from different disciplines, career stages, and institutions across the United States identified four thematic data integration challenges related to complexity and uncertainty, communication, scale, and institutional barriers. They further recommended individual, departmental, and institutional scale responses to cope with and address these integration challenges. These recommendations seek to inform faculty and department support for ECRs, who are often encouraged—and even expected—to engage in integrative, problem-focused, and solutions-oriented research.

 

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.