The problem of scale and how to link phenomena within and across scales is an important scientific question in many fields, and is particularly relevant for climate change governance (e.g. Levin, 1992, Kolbert, 2006). However, climate science still commonly applies one-dimensional and static approaches to scale, which have been criticised for being apolitical and detached from the social construct and relevance of the phenomena being studied.   

We investigated the concept of scale used by the climate change community and sought to identify what can be learned from other disciplines and practitioners that frame and use scale differently. Following Howitt (1998), we investigated three framings of scale: i) scale as size, (ii) scale as level and (iii) scale as relation. Scale as size focuses on measurement units, such as space and time and is the common framing in physical sciences. Scale as level, commonly used in physical geography, refers to the conceptual hierarchy of spaces and their interplay that reflects actual levels of organisation in the real world. Related, but less studied and applied, scale as relation emerged from ecology and now is also common in social sciences.

We found that scale as size is commonly used in climate science and services, especially related to space and time. For spatial scales, downscaling techniques and, more recently, kilometre-scale global climate models, focus on ever-finer scales that seek to align the scale of observation or model with the operational or impact scale of a (climate) phenomenon. For temporal scales, besides the commonly used long term climate projections, there has been an increased interest in (sub)seasonal and multi-annual predictions. Even more relevant are aspirations to provide seamless climate predictions and projections that directly link these different modelling approaches. 

We found less evidence of the climate science community using other interpretations of scale, but some climate services practitioners appear to engage with these other framings. Interpreting scale as level could help link processes and phenomena that operate at different levels. Equally, the relational framing of scale is perhaps the most important for sustainable, resilient and just aspects of climate change. For example, it is key to explore and communicate the relationship between global GHG emissions and large scale phenomena, on one side, and the local impacts and climate-related decision-making contexts, on the other. These types of relational framings alongside providing climate information across timescales will increasingly be required to render climate services more relevant and applicable.

With these findings in mind, we present results from a first attempt to jointly rethink the concept of scale with various climate practitioners and scientists. We conclude by arguing that shifting to a multi-level, multi-dimensional interpretation of scale would allow climate services to better support decision-making for multi-faceted climate change adaptation action. 

How to cite: Bojovic, D., Pickard, S., Baulenas, E., and Terrado, M.: Reimagining the scale in climate services , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-918, https://doi.org/10.5194/ems2024-918, 2024.

The continued development of General Circulation Models (GCMs) towards increasing resolution and complexity is a predominantly chosen strategy to advance climate science, resulting in channelling of research and funding to meet this aspiration. Yet many other modelling strategies have also been developed and can be used to understand past and present climates, to project future climates and ultimately to support decision-making. We argue that a plurality of climate modelling strategies and an equitable distribution of funding among them would be an improvement on the current predominant strategy for informing policy making. To support our claim, we use a philosophy of science approach to compare increasing resolution and complexity of General Circulation Models with three alternate examples: the use of machine learning techniques, the physical climate storyline approach, and Earth System Models of Intermediate Complexity. We show that each of these strategies prioritises a particular set of methodological aims, among which are empirical agreement, realism, comprehensiveness, diversity of process representations, inclusion of the human dimension, reduction of computational expense, and intelligibility. Thus, each strategy may provide adequate information to support different specific kinds of research and decision questions. We conclude that, because climate decision-making consists of different kinds of questions, many modelling strategies are all potentially useful, and can be used in a complementary way.  The outcomes of active diversification of climate modelling strategies would be to broaden the kinds of decision questions we are capable to answer, as well as to have more justified confidence in the robust core of projections, more potential input from those who will be affected by decisions, and thereby more effective consensus building for climate action.

How to cite: Thompson, E., Baldissera Pacchetti, M., and Jebeile, J.: For a Pluralism of Climate Modelling Strategies, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1074, https://doi.org/10.5194/ems2024-1074, 2024.

The complex and interconnected nature of climate change together and the need to adapt to such changes demands for collective efforts, expertise, and resources across a range of actors and scales of action (Bidwell et al., 2013). In this context, knowledge networks can be defined as "A set of nodes — individuals or group of individuals heterogeneously distributed that serve as agents for storing, creating and sharing knowledge on climate change adaptation — interconnected by social relationships that enable and constrain the nodes’ efforts to acquire, transfer, create and act upon such knowledge" (adapted from Phelps, 2012). Depending on their nature and scope, these knowledge networks can operate in multiple ways towards advancing and promoting climate change adaptation efforts e.g. by facilitating the exchange and creation of knowledge and ideas, mobilization of resources, fostering collaborations, social learning, and connecting different levels of governance (Pugh and Prusak, 2013). In addition, these knowledge networks can also support a range of efforts such as informing policy, raising awareness, enhancing social learning, guiding business-related advocacy and assist social activism (Bremer et al., 2022). However, current knowledge of these types of networks operating in Europe is limited. To address this gap, we conducted a systematic literature review to understand the landscape of these networks in Europe in order to gain insights into key typologies, their role in supporting adaptation across a range of (often interconnected) scales of action, their governance structures, and the use of climate information in their adaptation-related efforts. Based on the inclusion/exclusion criteria adopted, we identified approximately 40 knowledge networks covering a range of areas of intervention, scales of operation as well as different types of actors involved. This paper will present the findings from our analysis providing new insights into the current landscape of these networks and how they operate and interact to support adaptation efforts in Europe. By doing so, the paper constitutes a key contribution to ongoing discussions on how to improve and maximise adaptation efforts across scales, actors and typologies of interventions in Europe.

How to cite: Bruno Soares, M., Lamb, G., Puga-Gonzalez, I., Baulenas, E., Pickard, S., Shults, L., Kause, A., and Van Wolleghem, P.: Current landscape of knowledge networks for climate change adaptation in Europe, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1048, https://doi.org/10.5194/ems2024-1048, 2024.

User engagement for developing climate services has traditionally displayed a unilateral transaction of climate data to tackle specific needs. However, user-centred approaches with bidirectional interaction are becoming more widely accepted in the climate services field. The use of storylines of how recent extreme events could evolve in different future climates has been identified as an innovative tool for user engagement and communication. However, the meaningfulness of storylines could fall short if the climate community fails to speak to users’ day-to-day tasks and decision-making contexts. Additional effort should be taken to welcome the social aspect of storylines by including storytelling as a tool to facilitate knowledge exchange and spot where climate science can speed up sustainable decisions. Framing information as a story could provide valuable benefits and stimulate action-taking by heightening cognitive processes that rely on emotion (Toomey, 2023). Moreover, stories require causal connections to structure whatever happens makes sense and is credible, identical to how science and decision-making behave (Hertel & Reisberg, 2004).

Following a co-production framework, storylines have been applied to the development of the Digital Twin on Climate Change Adaptation under the Destination Earth (DestinE) initiative. On a case study basis (including wildfire, energy, hydrology, and urban applications), users were invited to discuss the added value storylines would bring to their local context when adapting to future climate change impacts. Preliminary results show that storylines can bring meaningful climate information to users and incentivize action. Its development in DestinE demonstrates the latest aspirations to make scientific results more relatable to non-academic audiences. However, user interactions during the project highlight the considerable differences among the various case studies, even within the same sectoral application. With the addition of storylines in DestinE, we illustrate a first and rather simple attempt to incorporate storytelling elements into user engagement to identify cross-scale cutting drivers of change. Understanding underlying issues and challenges that motivate user’s needs will play a vital role in making climate science meaningful. We recommend that the exploration of storytelling to align climate information to human needs should be recognized as a useful tool to move across both technical and social disciplines.

Hertel, P., & Reisberg, D. (Eds.). (2004). Memory and emotion. Oxford University Press.

Toomey, A. H. (2023). Why facts don't change minds: Insights from cognitive science for the improved communication of conservation research. Biological Conservation, 278, 109886.

How to cite: Versteeg, G. B. and Terrado, M.: Combining storylines and storytelling to stimulate climate action, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1080, https://doi.org/10.5194/ems2024-1080, 2024.

How to cite: Mayer, S., Li, L., Xie, K., and Sobolowski, S.: Reflections on climate and administrative scales in Western Norway, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-822, https://doi.org/10.5194/ems2024-822, 2024.

The wine industry is one of the agri-food sectors most highly influenced by climate variability and change at different timescales. In particular, integrating reliable and timely seasonal to decadal climate information in decision-making might help the wine sector better manage climate-related risks such as spring frost or water restrictions. This explains the recent interest of the wine industry in having climate information at these time scales. However, some of the challenges that prevent the users from uptake of climate information are the coarse resolution of the climate model outputs and the lack of coherence between the climate predictions from different sources (i.e., forecast systems at seasonal and decadal time scales). To produce coherent regional climate information for the wine industry, the suitability of different statistical downscaling methods to increase the resolution of user-relevant climate variables and indicators has been assessed for specific locations in Catalonia. Furthermore, a novel methodology for the temporal merging of seasonal and decadal predictions has been implemented to improve the accuracy of the relevant climate variables. This temporal merging method exploits the knowledge from the physical processes relevant to climate predictability at both seasonal and decadal time scales. The new scientific knowledge has been developed in the framework of the EU-funded project ASPECT (Adaptation-oriented Seamless Predictions of European ClimaTe). In this initiative, all the scientific methods are being co-developed in collaboration with representative stakeholders to ensure the climate information produced has actual value for the management of the vineyards and wineries, and the strategic planning for the wine market. 

How to cite: Torralba, V., Soret, A., Terrado, M., Delgado-Torres, C., Duzenli, E., Solaraju-Murali, B., and Muñoz, A. G.: Unveiling seamless climate information benefits for the wine sector: co-development of a case study, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-576, https://doi.org/10.5194/ems2024-576, 2024.