Editorial: Climate Science Advances to Address 21st Century Weather and Climate Extremes
- 1Climate Hazards Center, Department of Geography, University of California Santa Barbara, United States
- 2Physical Sciences Division, Earth System Research Laboratory (NOAA), United States
- 3Cabot Institute for the Environment, University of Bristol, United Kingdom
As discussed in Sarah Harrison's excellent article in WIRED, studies like "trends in nearshore domoic acid" can help motivate and inform effective early warning systems, fostering unique partnerships between scientists and community members.Climate attribution and climate diagnostic studies highlight the mechanisms driving extreme events, and elucidate their potential to increase in intensity and frequency as the Earth warms. This research can, and should, inform the development of 21 st century climate services.To be truly successful, however, these services need to combine accurate and representative models "of" the world with appropriate and localized models "for" intervention.Stepping back from the science, this editorial briefly discusses the important aspect of how these pieces can fit together when disparate "communities of practice"like the oceanographers, health experts and local tribal leaders discussed in Sarah's story, work together.The provision of freely available climate services is a very exciting prospect, a force for good that can help counter two growing threats-climate change and increasing economic disparity. While climate services will not reverse inequality, they can help the communities most vulnerable to extremes. Enhanced early warning systems are one of the most cost-effective approaches to increasing resilience. Climate information can leap across continents, improving decision-making, early warning systems, and outcomes almost anywhere. As these systems evolve, we will be better together, faster and more effectively, if we pay attention to the conceptual models that undergird our shared activities.Climate Services are unique, challenging, exciting, and empowering, precisely because they connect and span many intellectual domains ( Figure 1). These connections can transform data into wise actions. While the origins of the Data-Information-Knowledge-Wisdom hierarchy 3 is uncertain, it may have originated (Wallace 2007) in T.S. Eliot's poem "Choruses from the Rock" (Eliot 1934):
Where is the wisdom we have lost in knowledge?Where is the knowledge we have lost in information? Effective climate services typically involve contributions from overlapping "communities of practice." These collaborations connect technical engineering and science efforts (on the far left of Figure 1) with on-the-ground actions and interventions on the far right. Going from left to right, we also tend to transition from the general to the specific. On the left, we might find an atmospheric model based on universal physical laws or "rocket scientists" who use highly generalized algorithms to translate satellite imagery into precipitation estimates (Kummerow et al. 2015, Skofronick-Jackson et al. 2017, Huffman et al. 2020. But, as one moves to the far right in Figure 1, we find tailored effective interventions guided by local expertise.In between the left and the right, we find the sequential contributions of "climate intermediaries." To be actionable, information typically needs to be transformed into impact assessments, answering questions like: "how might the expected or observed weather or climate conditions affect our crops, water supply, or fire fuels." This translation can add great value. For example, a recent study of drought warning activities in Malawi, found that what farmers really wanted and needed was agricultural advice, not weather data (Calvel et al. 2020), i.e., knowledgeable actionable guidance, not just data or information.Shared conceptual frameworks can facilitate effective collaboration and communication across these communities of practice, guiding the translation of data and information into knowledge and appropriate action. For example, the Famine Early Warning Systems Network identifies severely food insecure populations by developing scenarios that analyze household level food economies, but these scenarios use a rigorous multi-agency 'food security outlook' process to translate climate information into likely impacts on incomes, food access and food availability.Yes-we need to translate climate data into information that drives impact models that provide accessible outputs that can support effective actions, and each of those verbs typically manifests as thousands of lines of code and often-massive computations, but no, computation alone does not suffice. Figure 1 describe a series of coherent social interactions, emergent collaborative complex behavior, and when thinking about such structures the climate services community can learn from experts who study how cultures evolve. For example, in his book "The Interpretation of Cultures," Clifford Geertz (1973) introduces the idea that cultures behave coherently through the combination of "models of the world" and "models for the world." Models "of" the world resemble our numerical models; they attempt to imitate or simulate the world-as-it-is. Models "for" the world, however, imply specific and coherent actions, actions informed by our models "of" the world. So, according to Geertz, the study of hydraulics might help us design a dam. Because human behavior is driven by extrinsic symbolic structures (not just our genes), that it is precisely the interaction of these two distinct types of models that makes human culture possible.
Seen from this perspective, successful early warning communities are subcultures that evolve to address specific threats, such as drought or food insecurity, and their success depends on translating data into wise action (Figure 1) using shared models "for" reality supported by accurate models "of" reality. Hence, such systems spend considerable effort on describing how hazards are detected and defined (Pulwarty and Sivakumar, 2014;Wilhite and Pulwarty 2017;Funk and Shukla 2020). Crisp definitions of drought (Wilhite and Glantz, 1985;Svoboda and Fuchs 2016), and food insecurity (FEWS NET 2021), can form a shared basis for collaboration and coherent climate services development. But these definitions, and the associated impact assessments and risk management responses, will be highly location specific -thereby requiring local knowledge.But climate change is accelerating the need for climate services, and demanding that we have the best possible models "for" early warning. Surveys of extreme events, such as the forthcoming book "Drought Fire Flood" can help guide climate service development. Analyses focusing on the new science of climate change attribution evaluate how climate change may or may not contribute to extreme events. Such studies can also provide search patterns, or models "for" hazards that can guide prediction and monitoring (i.e. a, b, c, d, e). For example, many studies have suggested that climate change will produce more frequent extreme El Niño and La Niña events. For La Niñas, it turns out that numerical models "of" the climate can predict these conditions very early, in June, providing a very valuable opportunity for early warning, predicated on a conceptual model "for" climate change impacts built around the assumption that extreme sea surface temperatures will provide a solid foundation for forecasting. Given that ENSO is the leading component of seasonal forecasting skill, linking our successful model "of" the climate to models "for" early action can help us move effectively from data to information to wise interventions (Figure 1).
Keywords: climate, Climate Change, Climate Extremes, Climate service, early warning, Weather extremes
Received: 14 Mar 2021;
Accepted: 14 May 2021.
Copyright: © 2021 Funk, Hoell and Mitchell. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mx. Chris C. Funk, Climate Hazards Center, Department of Geography, University of California Santa Barbara, Santa Barbara, United States, firstname.lastname@example.org