The EU needs a demand-driven innovation policy for climate services

Climate services have climbed high on the agenda of EU research policy, yet few contributions have reflected on the actual usability of climate services from the perspectives of the intended users, let alone the implications for future EU research and innovation policy. This commentary reflects on four key lessons learnt from engagement in climate services research projects and discusses implications for future EU research policy: i) all end-users have pre-established decision-making processes and tools for their purposes, hence all new information needs to be adapted ii) one size fits none – and tailoring takes time iii) building trust between different actors, processes and confidence in new information is key in the tailoring process – and resource-demanding iv) purveyors and intermediaries can facilitate tailoring processes but need to finance their activities until end-users demonstrate willingness to pay and/or the climate service is readily implemented. The main argument is that more attention needs to be paid to the demand-side of climate services to help viable climate services make it through the innovation “valley of death” – that is, the twilight zone between technical invention and (commercially) successful innovation. EU Research and Innovation (R&I) funding streams and policies for establishing truly transdisciplinary learning loops driven by (actual) user needs can function as vehicles through the valley of death.This research was funded by the EU Horizon 2020 program under grant agreement number 776787.Peer ReviewedPostprint (published version

Formalization and separation:A systematic basis for interpreting approaches to summarizing science for climate policy

In studies of environmental issues, the question of how to establish a productive interplay between science and policy is widely debated, especially in relation to climate change. The aim of this article is to advance this discussion and contribute to a better understanding of how science is summarized for policy purposes by bringing together two academic discussions that usually take place in parallel: the question of how to deal with formalization (structuring the procedures for assessing and summarizing research, e.g. by protocols) and separation (maintaining a boundary between science and policy in processes of synthesizing science for policy). Combining the two dimensions, we draw a diagram onto which different initiatives can be mapped. A high degree of formalization and separation are key components of the canonical image of scientific practice. Influential Science and Technology Studies analysts, however, are well known for their critiques of attempts at separation and formalization. Three examples that summarize research for policy purposes are presented and mapped onto the diagram: the Intergovernmental Panel on Climate Change, the European Union’s Science for Environment Policy initiative, and the UK Committee on Climate Change. These examples bring out salient differences concerning how formalization and separation are dealt with. Discussing the space opened up by the diagram, as well as the limitations of the attraction to its endpoints, we argue that policy analyses, including much Science and Technology Studies work, are in need of a more nuanced understanding of the two crucial dimensions of formalization and separation. Accordingly, two analytical claims are presented, concerning trajectories, how organizations represented in the diagram move over time, and mismatches, how organizations fail to handle the two dimensions well in practice.</jats:p

One world or two? Science-policy interactions in the climate field

This article assesses how science–policy interactions are conceptualized in the social sciences with special reference to climate change and the IPCC. In terms of the dimension of distance (or proximity) between science and policy, we discern two ideal-type cases: a ‘two-worlds’ and a ‘one-world’ perspective. The first understands science and policy as independent spheres separated by a clear gap, while the second perceives science and policy as tightly coupled. These two perspectives, presented here in detail and in various sub-variants in order to show their complexity, appear dominant also in the discussions on how to improve, not only describe, the interaction between science and policy. We argue that this situation of opposing perspectives is not beneficial, nor properly recognized by scholars in the field. In response to this, we present a typology that may serve as a modest and judicious way for thinking about and making more nuanced choices in designing science–policy relations