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Experience from downscaling IPCC-SRES scenarios to specific national-level focus scenarios for ecosystem service management

Author

Listed:
  • Walz, A.
  • Braendle, J.M.
  • Lang, D.J.
  • Brand, F.
  • Briner, S.
  • Elkin, C.
  • Hirschi, C.
  • Huber, R.
  • Lischke, H.
  • Schmatz, D.R.

Abstract

Scenario analysis is a widely used approach to incorporate uncertainties in global change research. In the context of regional ecosystem service and landscape management where global IPCC climate simulations and their downscaled derivates are applied, it can be useful to work with regional socio-economic scenarios that are coherent with the global IPCC scenarios. The consistency with the original source scenarios, transparency and reproducibility of the methods used as well as the internal consistency of the derived scenarios are important methodological prerequisites for coherently downscaling pre-existing source scenarios. In contrast to well-established systematic-qualitative scenario techniques, we employ here a formal technique of scenario construction which combines expert judgement with a quantitative, indicator-based selection algorithm in order to deduce a formally consistent set of focus scenario. In our case study, these focus scenarios reflect the potential development pathways of major national-level drivers for ecosystem service management in Swiss mountain regions. The integration of an extra impact factor (“Global Trends”) directly referring to the four principle SRES scenario families, helped us to formally internalise base assumptions of IPCC SRES scenarios to regional scenarios that address a different thematic focus (ecosystem service management), spatial level (national) and time horizon (2050). Compared to the well-established systematic-qualitative approach, we find strong similarities between the two methods, including the susceptibility to personal judgement which is only partly reduced by the formal method. However, the formalised scenario approach conveys four clear advantages, (1) the better documentation of the process, (2) its reproducibility, (3) the openness in terms of the number and directions of the finally selected set of scenarios, and (4) its analytical power.

Suggested Citation

  • Walz, A. & Braendle, J.M. & Lang, D.J. & Brand, F. & Briner, S. & Elkin, C. & Hirschi, C. & Huber, R. & Lischke, H. & Schmatz, D.R., 2014. "Experience from downscaling IPCC-SRES scenarios to specific national-level focus scenarios for ecosystem service management," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 21-32.
    • Handle: RePEc:eee:tefoso:v:86:y:2014:i:c:p:21-32
    DOI: 10.1016/j.techfore.2013.08.014
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    References listed on IDEAS

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    1. Marco Moriondo & Marco Bindi & Zbigniew Kundzewicz & M. Szwed & A. Chorynski & P. Matczak & M. Radziejewski & D. McEvoy & Anita Wreford, 2010. "Impact and adaptation opportunities for European agriculture in response to climatic change and variability," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 15(7), pages 657-679, October.
    2. Tietje, Olaf, 2005. "Identification of a small reliable and efficient set of consistent scenarios," European Journal of Operational Research, Elsevier, vol. 162(2), pages 418-432, April.
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    1. Ahn, Young-Hwan & Woo, Jung-Hun & Wagner, Fabian & Yoo, Seung Jick, 2019. "Downscaled energy demand projection at the local level using the Iterative Proportional Fitting procedure," Applied Energy, Elsevier, vol. 238(C), pages 384-400.

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