Abstract
This paper presents a tailor-made scenario approach for climate change adaptation planning, which emphasises involvement of stakeholders in the development of socioeconomic scenarios and relates to the planning situation and interest of the planning entity. The method was developed and tested in case studies in three different sectors in Sweden (the health sector, the tourism sector and water resource management). The result of the case studies is that the tailor-made scenario approach facilitated the engagement of the local planning body in climate change adaptation and helped them to analyse consequences and possible solutions in a structured way. However, the scenarios that emerged mainly focused on socioeconomic drivers on which the planning body had a large impact or drivers that can be influenced through cooperation with other actors at the local or regional level. While this result underlines the need for local stakeholder involvement in scenario processes, it also indicates a local bias that could be remedied by a stronger representation of national and global perspectives in the scenario development process. Finally, we discuss how a “bottom-up” approach could be combined with a “consistency” approach, which points towards a possible way forward to a hybrid methodology that is compatible with the scenario framework currently being developed in connection to the fifth assessment report of the IPCC.
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Notes
The climate scenario was based on the climate modelling of the Swedish Meteorological and Hydrological Institute (SMHI, 2011). Starting with a global climate model (ECHAM4/OPYC3), SMHI performs calculations with finer resolution over Europe using the regional climate model RCA3. The heat wave scenario was constructed as follows. If for example the minimum temperature in Paris on a particular date during the heat wave of 2003 was 3 standard deviations above the average in Paris, then we assumed a corresponding temperature anomaly over Umeå with a minimum temperature that was 3 standard deviations above the projected climate in Umeå in the year 2030. During the projected 2-week heat wave in Umeå, July 2030 (the hottest month in Umeå), the minimum temperature peaked at 20 °C (3 days) and the maximum temperature reached 33 °C (2 days). These figures should be compared to the 30-year averages for minimum and maximum temperature in July in Umeå, which are 11 and 19.5 °C respectively. Hence, the modelled heat wave represents a substantial alternation of normal conditions.
The regional climate projection used in the study meant that the mean temperature during winter (summer) in 2030 will increase by 2.5 (1.5) °C. In the medium climate scenario for 2060 the mean temperature during winter (summer) will increase by 3.5 (2–2.5) °C, while the high climate change scenario imply increased winter (summer) temperature by 5.5 (3–3.5) °C.
References
Amara R (1981) The futures field: searching for definitions and boundaries. Futurist 15:25–29
Arnell N, Kram T, Carter T et al (2011) A framework for a new generation of socioeconomic scenarios for climate change impact, adaptation, vulnerability and mitigation research. Working Paper, August 15. http://www.isp.ucar.edu/sites/default/files/Scenario_FrameworkPaper_15aug11_0.pdf Cited 4 sep 2012
Baard P, Carlsen H, Edvardsson Björnberg K et al (2012) Scenarios and sustainability: tools for alleviating the gap between municipal means and responsibilities in adaptation planning. Local Environment 17(6–7):641–662. doi:10.1080/13549839.2011.646969
Bartholomew K (2007) Land use-transportation scenario planning: promise and reality. Transportation 34:397–412
Basu R, Samet JM (2002) Relation between elevated ambient temperature and mortality: a review of the epidemiologic evidence. Epidemiol Rev 24:190–202
Berkhout F, Hertin J, Jordan A (2002) Socio-economic futures in climate change impact assessment: using scenarios as learning machines. Glob Environ Chang 12:83–95
Bizikova L, Dickinson T, Pintér L (2009) Participatory scenario development for climatechange adaptation. In: Reid H (ed) Community-based adaptation to climate change (Participatory Learning and Action 60). IIED, London
Börjeson L, Höjer M, Dreborg KH et al (2006) Scenario types and techniques: towards a user’s guide. Futures 38:723–739
Bradfield R, Wright G, Burt G et al (2005) The Origins and Evolution of Scenario Techniques in Long Range Business Planning. Futures 37:795–812
Burch S, Sheppard SRJ, Shaw A, Flanders D (2010) Planning for climate change in a flood prone community: municipal barriers to policy action and the use of visualizations as decision-support tools. J Flood Risk Manag 3:126–139
Carter TR, Jylhä K, Perrels A et al (2005) FINADAPT scenarios for the 21st century. Alternative futures for considering adaptation to climate change in Finland, FINADAPT Working Paper no. 2, Finnish Environment Institute Mimeographs 332, Helsinki. http://www.environment.fi/download.asp?contentid=44018&lan=en Cited 4 sep 2012
Chermack TJ (2004) Improving decision-making with scenario planning. Futures 36:295–309
Emery FE, Trist EL (1965) The causal texture of organizational environments. Hum Relat 18:21–32
Fouillet A, Rey G, Laurent F et al (2006) Excess mortality related to the August 2003 heat wave in France. Int Arch Occup Environ Health 80:16–24
Gidley JM, Fien J, Smith JA, Thomsen DC, Smith TF (2009) Participatory future methods: towards adaptability and resilience in climate-vulnerable communities. Environ Pol Govern 19:427–440
Hallegatte S (2009) Strategies to adapt to an uncertain climate change. Glob Environ Chang 19:240–247
Höjer M, Dreborg KH, Engström R et al (2011) Experience of the Development and use of scenarios for evaluating Swedish national environmental objectives. Futures 43:498–512
Hughes N, Tomei J, Ekins P (2009) Critical review of the Application of the UKCIP Socioeconomic Scenarios: Lessons Learnt and Future Directions. Department of Geography, King’s College London. http://ukcip-main.clustered.net/wordpress/wp-content/PDFs/UKCIP_SRES_review.pdf Cited 4 sep 2012
IPCC (2012) Summary for Policymakers. In: Field CB, Barros V, Stocker TF (eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge
Jacques P (2006) Downscaling climate models and environmental policy: From global to regional politics. J Environ Plan Manag 49:301–307
Kok K, Biggs R, Zurek M (2007) Methods for Developing Multiscale Participatory Scenarios: Insights from Southern Africa and Europe. Ecol Soc 12:8–23
Kriegler E, O’Neill B, Hallegatte S et al (2010) Socioeconomic scenario development for climate change analysis. CIRED Working Paper. DT/WP No 2010-23, October 2010. http://www.centre-cired.fr/IMG/pdf/CIREDWP-201023.pdf Cited 4 sep 2012
Lorenzoni I, Jordan A, Hulme M et al (2000) A co-evolutionary approach to climate change impact assessment: Part 1. Integrating socio-economic and climate change scenarios. Glob Environ Chang 10:57–68
Meehl GA, Stocker TF, Collins WD et al (2007) Global Climate Projections. In: Solomon S, Qin D, Manning M et al (eds) Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge
Millennium Ecosystem Assessment (2005) Ecosystems and human well-being: synthesis. Island Press, Washington, DC
Morgan DL (1997) Focus groups as qualitative research. Sage Publications, Thousand Oaks
Moss RH, Edmonds JA, Hibbar KA et al (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756
Nakićenović N, Alcamo J, Davis G et al (2000) Emission scenarios. Special Report of Working Group III of the Intergovernmental Panel of Climate Change. Cambridge University Press, New York
O’Neill B, Pulver S, Van Deveer S et al (2008) Where next with global environmental scenarios? Environ Res Lett 3(4):045012. doi:10.1088/1748-9326/3/4/045012
Ritchey T (2011) Wicked Problems—Social Messes: Decision Support Modelling with Morphological Analysis. Springer Verlag, Berlin Heidelberg
Rocklöv J, Forsberg B (2008) The effect of temperature on mortality in Stockholm 1998–2003—a study of lag structures and heat wave effects. Scand J Public Health 36:516–523
Rounsevell MDA, Metzger MJ (2010) Developing qualitative scenario storylines for environmental change assessment. Wiley Interdiscip Rev Clim Chang 1:606–619
Schär C, Vidale PL, Luthi D et al (2004) The role of increasing temperature variability in European summer heat waves. Nature 427:332–336
Schenk NJ, Lensink M (2007) Communicating uncertainty in the IPCC’s greenhouse gas emissions scenarios. Clim Chang 82:292–308
Shaw A, Sheppard S, Burch S et al (2009) Making local futures tangible—Synthesizing, downscaling, and visualizing climate change scenarios for participatory capacity building. Glob Environ Chang 19:447–463
SMHI (2011) Sveriges klimat i framtiden. http://www.smhi.se/sgn0106/leveranser/sverigeanalysen/ Cited 4 sep 2012
Svenfelt Å, Engström R, Höjer M (2010) Use of explorative scenarios in environmental policy making—evaluation of policy instruments for management of land, water and the bulit environment. Future 42:1166–1175
Swedish Commission on Climate and Vulnerability (2007) Sweden facing climate change—threats and opportunities [in Swedish], Final report from the Swedish Commission on Climate and Vulnerability SOU 2007:60. Swedish Government Official Reports, Stockholm
Trenberth KE, Jones PD, Ambenje P et al (2007) Observations: Surface and Atmospheric Climate Change. In: Solomon S, Qin D, Manning M et al (eds) Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge
UK Government Offices for Science (2011) Blacket Review of High Impact Low Probability Risks. Department for Business, Innovation and Skills, London
UKCIP (2001) Socio-economic scenarios for climate change impact assessment: a guide to their use in the UK Climate Impacts Programme. UK Climate Impacts Programme, Oxford
UNEP (2002) Global Environment Outlook 3: Past, Present and Future Perspectives. UNEP, New York
van der Heijden K (2005) Scenarios: The Art of Strategic Conversation, 2nd edn. Wiley, Chichester
van Drunen MA, van’t Klooster SA, Berkhout F (2011) Bounding the future: The use of scenarios in assessing climate change impacts. Futures 43:488–496
van Vuuren DP, Lucas PL, Hilderink H (2007) Downscaling drivers of global environmental change: Enabling use of global SRES scenarios at the national and grid levels. Glob Environ Chang 17:114–130
van Vuuren DP, Smith SJ, Riahi K (2010) Downscaling socioeconomic and emissions scenarios for global environmental change research: a review. Wiley Interdiscip Rev Clim Chang 1:393–404
van Vuuren DP, Edmonds J, Kainuma M et al (2011) The representative concentration pathways: an overview. Clim Chang 109:5–31
van Vuuren DP, Riahi K, Moss R et al (2012) A proposal for a new scenario framework to support research and assessment in different climate research communities. Glob Environ Chang 22:21–35
Wilby RL, Troni J, Biot Y et al (2009) A review of climate risk information for adaptation and development planning. Int J Climatol 29:1193–1215
Zwicky F (1969) Discovery, Invention. Research—Through the Morphological Approach. The Macmillian Company, Toronto
Acknowledgements
The authors would like to thank all participants in the three case studies and especially the municipal civil servants that helped organise the studies. The Swedish Environmental Protection Agency is acknowledged for financial support through the research programme CLIMATOOLS. We also give a special thanks to the anonymous reviewers for many useful suggestions for improvement.
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Carlsen, H., Dreborg, K.H. & Wikman-Svahn, P. Tailor-made scenario planning for local adaptation to climate change. Mitig Adapt Strateg Glob Change 18, 1239–1255 (2013). https://doi.org/10.1007/s11027-012-9419-x
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DOI: https://doi.org/10.1007/s11027-012-9419-x