Key drivers and economic consequences of high-end climate scenarios: uncertainties and risks

The consequences of high-end climate scenarios and the risks of extreme events involve a number of critical assumptions and methodological challenges related to key uncertain- ties in climate scenarios and modelling, impact analysis, and economics. A methodological frame- work for integrated analysis of extreme events and damage costs is developed and applied to a case study of urban flooding for the medium sized Danish city of Odense. Moving from our current climate to higher atmospheric greenhouse gas (GHG) concentrations including a 2°, 4°, and a high-end 6°C scenario implies that the frequency of extreme events increase beyond scaling, and in combination with economic assumptions we find a very wide range of risk estimates for urban precipitation events. A sensitivity analysis addresses 32 combinations of climate scenarios, dam- age cost curve approaches, and economic assumptions, including risk aversion and equity repre- sented by discount rates. Major impacts of alternative assumptions are investigated. As a result, this study demonstrates that in terms of decision making the actual expectations concerning future climate scenarios and the economic assumptions applied are very important in determining the risks of extreme climate events and, thereby, of the level of cost-effective adaptation seen from the society's point of view.

[1]  J. Christensen,et al.  Climate modelling: Severe summertime flooding in Europe , 2003, Nature.

[2]  J. Christensen,et al.  Scalability of regional climate change in Europe for high-end scenarios. , 2015 .

[3]  L L Skaggs,et al.  Catalog of Residential Depth-Damage Functions Used by the Army Corps of Engineers in Flood Damage Estimation , 1992 .

[4]  R. Lind,et al.  Intertemporal Equity, Discounting, and Economic Efficiency in Water Policy Evaluation , 1997 .

[5]  K. Calvin,et al.  The RCP greenhouse gas concentrations and their extensions from 1765 to 2300 , 2011 .

[6]  H. Madsen,et al.  Evaluating adaptation options for urban flooding based on new high-end emission scenario regional climate model simulations , 2015 .

[7]  P. Cox,et al.  Quantifying future climate change , 2012 .

[8]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[9]  Suraje Dessai,et al.  Robust adaptation to climate change , 2010 .

[10]  Martin L. Weitzman,et al.  Fat-Tailed Uncertainty in the Economics of Catastrophic Climate Change , 2011, Review of Environmental Economics and Policy.

[11]  D. L. Hanson,et al.  ON THE THEORY OF RISK AVERSION , 1970 .

[12]  Bengt Kriström,et al.  Uncertainty and Climate Change , 2002 .

[13]  Jeroen C. J. H. Aerts,et al.  Comparative flood damage model assessment: towards a European approach , 2012 .

[14]  G. Bürger,et al.  Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe , 2014 .

[15]  J. C. Refsgaard,et al.  The role of uncertainty in climate change adaptation strategies—A Danish water management example , 2013, Mitigation and Adaptation Strategies for Global Change.

[16]  P. Linden,et al.  ENSEMBLES: Climate Change and its Impacts - Summary of research and results from the ENSEMBLES project , 2009 .

[17]  E. Hawkins,et al.  The Potential to Narrow Uncertainty in Regional Climate Predictions , 2009 .

[18]  Karsten Arnbjerg-Nielsen,et al.  Feasible adaptation strategies for increased risk of flooding in cities due to climate change. , 2009, Water science and technology : a journal of the International Association on Water Pollution Research.

[19]  T. Stocker,et al.  Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of IPCC Intergovernmental Panel on Climate Change , 2012 .

[20]  C. Field Managing the risks of extreme events and disasters to advance climate change adaption , 2012 .

[21]  Lukas H. Meyer,et al.  Social, Economic, and Ethical Concepts and Methods , 2014 .

[22]  P. Mikkelsen,et al.  Framework for economic pluvial flood risk assessment considering climate change effects and adaptation benefits , 2012 .

[23]  E. Hawkins,et al.  The potential to narrow uncertainty in projections of regional precipitation change , 2011 .