Challenges to link climate change data provision and user needs: Perspective from the COST‐action VALUE

Abstract

The application of climate change impact assessment (CCIA) studies in general and especially the linkages between different actor groups typically involved is often not trivial and subject to many limitations and uncertainties. Disciplinary issues like competing downscaling approaches, imperfect climate and impact model data and uncertainty propagation as well as the selection of appropriate data sets are only one part of the story. Interdisciplinary and transdisciplinary challenges add to these, as climate data and impact model data provision and their usage require at least a minimum of common work and shared understanding among actors. Here, we provide the VALUE perspective on current disciplinary challenges and limitations at the downscaling interface and elaborate transdisciplinary issues that hamper a proper working downscaling interface. The perspective is partly based on a survey on user needs of downscaled data that was distributed among 62 participants across Europe involving 22 sectors. Partly, it is based on the exchanges and experiences gained during the lifetime of VALUE that brought together different actor groups of different disciplines: climate modellers, impact modellers, statisticians and stakeholders. We outline a sketch that summarizes the linkages between the main identified actor groups: climate model data providers, impact modellers and societal users. We summarize review and structure current actors groups, needs and issues. We argue that this structuring enables involved actors to tackle these issues in a more organized and hence effective way. A key solution to several difficulties at the downscaling interface is to our understanding the development of guidelines based on benchmark tests like the VALUE framework. In addition, fostering communication between actor groups—and financing this communication—is essential to obtain the best possible CCIA as a prerequisite for robust adaptation.

Deriving user-informed climate information from climate model ensemble results

“…This also corresponds to experiences gathered in other countries (Formayer et al, 2011;MeteoSwiss, 2016) andprojects (e.g., Swart andAvelar, 2011;Hewitt et al, 2013;Groot et al, 2014;Roessler et al, 2017). Thus, even though we focus on the ReKliEs-De project workshop, the questions and problems that were formulated there are shared by other users -albeit perhaps to different degrees.…”

“…Presently, a growing number of institutions, projects, and initiatives address this gap (e.g., Groot et al, 2014;Harold et al, 2016;Roessler et al, 2017). Additionally, the Global Framework for Climate Services (GFCS, www.wmo.int/gfcs/) has started a discussion towards an ethical framework for climate services, which calls for integrity, transparency, humility, and collaboration when providing climate services.…”

“…Thus, climate data providers (in the definition of Roessler et al, 2017) or climate service providers (in the definition of the GFCS, www.wmo.int/gfcs/) need to deliver easily understandable and condensed climate model information (one user at the workshop suggested the concept of "climate model fact sheets"). This information should refrain from using the discipline-specific climate modeling "lingo" and should instead try to be as simple and as short as possible.…”

A hierarchical analysis of the impact of methodological decisions on statistical downscaling of daily precipitation and air temperatures

“…The VALUE project (Maraun et al, ; Gutiérrez et al, ; Maraun et al, ) included a stakeholder/end‐user survey (62 participants) that found temperature and precipitation were the top two climate variables of interest. The required accuracy was ±10–20% for temperature and ±10–50% for precipitation and temporal and spatial resolutions of daily and point or < 1 km are desired (Rössler et al, ). Due to large fractional errors that can arise close to 0°C, we assume a mean air temperature of 15°C and equate a ± 15% uncertainty to ±2.25°C.…”

Augmented Smart Cities Integrating Sensor Web and Spatial Data Infrastructure (SmaCiSENS)

“…platform which can be open, shareable, knowledgeable, and contributable globally [7][8][9]. 3 of 15 Spatial data are dramatically increasing in volume and complexity, just as the users of these data in 95 the scientific community and the public are rapidly increasing in number [10][11].…”