Volume 39, Issue 9
VALUE SPECIAL ISSUE ARTICLE

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

O. Rössler

Corresponding Author

E-mail address: ole.roessler@giub.unibe.ch

Institute for Geography, Oeschger Centre of Climate Change Research, University of Bern, Bern, Switzerland

Correspondence

O. Rössler, Institute of Geography, Oeschger Centre for Climate Change Research, University of Bern, Hallerstrasse 12, 3012 Bern, Switzerland.

Email: ole.roessler@giub.unibe.ch

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A. M. Fischer

Federal Office of Meteorology and Climatology MeteoSwiss, Zurich, Switzerland

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H. Huebener

Hessian Agency for Nature Conservation, Environment and Geology, Germany

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D. Maraun

Wegener Center for Climate and Global Change, University of Graz, Austria

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R. E. Benestad

The Norwegian Meteorological Institute, Oslo, Norway

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P. Christodoulides

Faculty of Engineering and Technology, Cyprus University of Technology, Limassol, Cyprus

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P. M. M. Soares

Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Portugal

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R. M. Cardoso

Instituto Dom Luiz, Faculdade de Ciências, Universidade de Lisboa, Portugal

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C. Pagé

UMR CNRS 5318 CECI – CERFACS, Toulouse, France

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H. Kanamaru

Food and Agriculture Organization of the United Nations (FAO), Rome, Italy

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F. Kreienkamp

Deutscher Wetterdienst, Potsdam, Germany

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D. Vlachogiannis

Environmental Research Laboratory, NCSR Demokritos, Athens, Greece

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First published: 18 April 2017
Citations: 11
Funding information EU COST Action ES1102, Grant/Award Number: EU FP7, EU COST Action ES1102

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.

Number of times cited according to CrossRef: 11

  • Compilation of a guideline providing comprehensive information on freely available climate change data and facilitating their efficient retrieval, Climate Services, 10.1016/j.cliser.2020.100179, 19, (100179), (2020).
  • Statistical downscaling with the downscaleR package (v3.1.0): contribution to the VALUE intercomparison experiment, Geoscientific Model Development, 10.5194/gmd-13-1711-2020, 13, 3, (1711-1735), (2020).
  • Fighting big data and ensemble fatigue in climate change impact studies: Can we turn the ensemble cascade upside down?, International Journal of Climatology, 10.1002/joc.6696, 0, 0, (2020).
  • Evaluation of downscaling methods over Europe: Results of the EU‐COST action VALUE, International Journal of Climatology, 10.1002/joc.6184, 39, 9, (3689-3691), (2019).
  • Assessing the degree of hydrologic stress due to climate change, Climatic Change, 10.1007/s10584-019-02497-4, (2019).
  • Comparison of statistical downscaling methods with respect to extreme events over Europe: Validation results from the perfect predictor experiment of the COST Action VALUE, International Journal of Climatology, 10.1002/joc.5469, 39, 9, (3846-3867), (2018).
  • Statistical downscaling skill under present climate conditions: A synthesis of the VALUE perfect predictor experiment, International Journal of Climatology, 10.1002/joc.5877, 39, 9, (3692-3703), (2018).
  • Estimating daily meteorological data and downscaling climate models over landscapes, Environmental Modelling & Software, 10.1016/j.envsoft.2018.08.003, 108, (186-196), (2018).
  • Consistency of climate change projections from multiple global and regional model intercomparison projects, Climate Dynamics, 10.1007/s00382-018-4181-8, (2018).
  • Climate projections and downscaling techniques: a discussion for impact studies in urban systems, International Journal of Urban Sciences, 10.1080/12265934.2017.1409132, (1-31), (2017).
  • Deriving user-informed climate information from climate model ensemble results, Advances in Science and Research, 10.5194/asr-14-261-2017, 14, (261-269), (2017).