|ABSTRACT||Nowadays, negative impacts of climate change can be observed to a greater extent on the whole planet: increasing/decreasing precipitations, rising sea levels, melting glaciers, and so on (IPCC, 2014). According to EEA, compared to average global increase of 0.8°C, European land temperature has increased by 1.3°C (2016). Moreover, some parts of Europe appear more sensitive than others, such as Mediterranean and mountain regions, where a higher temperature rise was registered (EEA, 2016).
It is in this optics that Climate Services appear as an emerging topic in CC adaptation domain. Defined by WMO as “a decision aide derived from climate information that assists individuals and organizations in society to make improved ex-ante decision-making”, or by EU as “transforming climate-related data and other information into customized products such as projections, trends, economic analysis, advice on best practices, development and evaluation of solutions, and any other climate-related service liable to benefit that may be of use for the society” (wmo.int; ec.europa.eu). Among several “actions” of “EU strategy on adaptation to climate change”, climate services are seen as “knowledge adaptation” and as a tool for better resilience (EU COM (2013) 216). Climate services can provide information for decision-making bodies and contribute to risk and adaptation mechanisms. Moreover, these tools can be largely deployed in different sectors of our economies. As this domain has registered a growing interest only recently, these tools are still being experimented and assessed. Today, climate services can offer tailored information in terms of predictions on major climate variables and this requires the ability to transform this scientific data into something useful and user-friendly for potential beneficiaries. As many scholars argue, not always scientific data meets the needs/demands of users: different institutional logics, spatial scales and timing (Dilling&Lemos, 2011; McNie, 2007; Sarewits&Pielke, 2007). As Pita Spruijt et al (2014) point out, “policy makers seek certainties and solutions, whereas scientists typically offer probabilities, uncertainty and multiple scenarios” (2014:17). Therefore, in order to close the so-called “science-policy gap”, several authors argue for production of socially robust science in terms of active involvement of public in scientific processes (Choi et al, 2016; Jasanoff, 2003). The co-construction of climate services can enable scientific community to provide useful data which will be actually used by society.
As most of the literature argues for co-production of these tools, it is interesting to discuss the ways to co-build climate services. What is an appropriate spatial or time scale? Which stakeholders to involve, when and how? What has been done so far? The aim of this contribution is to offer an overview on climate services from historic, practical and “design” perspectives and to raise questions for further debates.|