Inter-Sectoral Impact Model Intercomparison Project



The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) is a community-driven modelling effort with the goal of providing cross-sectoral global impact assessments, based on common climate (RCPs – Representative Concentration Pathways) and socio-economic (SSPs – Shared Socio-Economic Pathways) scenarios. Impacts and uncertainties for different sectors and from multiple impact models are explored and policy relevant metrics are deduced.

In this context, GCF applies the DIVA Model to assess global scale impacts of future warming and associated sea-level rise on the risk of coastal flooding. Together with the Potsdam Institute for Climate Impact Research we apply multiple climate models and RCPs to compute sea-level rise scenarios for the 21st century including the contribution of the melting of glaciers and the ice-shields of Greenland and Antarctica. Flood risk is considered in terms of expected annual number of people flooded, expected annual damage to assets, and adaptation costs for dike investment and maintenance. We thereby vary model structure and data sources along dimensions of highest expected uncertainty. These are the digital elevation model of continental topography, the population distribution, and the adaptation strategy.

Funded by:

The ISI-MIP Fast-Track project is funded by the German Federal Ministry of Education and Research (BMBF) with project funding reference number 01LS1201A.


Coastal regions may face massive increases in damages from storm surge flooding over the course of the 21st century. According our simulations, in 2100, up to 600 million people (around 5 percent of the global population) could be affected by coastal flooding if no adaptation measures are put in place (Figure 1). Global average storm surge damages could increase from about 10-40 billion USD per year today to up to 100,000 billion USD per year by the end of century, if no adaptation action is taken.

Figure 1. Global expected annual number of people flooded. The bold lines show the average across the range of DEMs, population data sets, GCMs and land-ice scenarios used. The shaded areas show the respective uncertainty ranges defined by the maximal and minimal numbers.



Hinkel, J., D. Lincke, A. T. Vafeidis, M. Perrette, R. J. Nicholls, R. S. J. Tol, B. Marzeion, X. Fettweis, C. Ionescu, and A. Levermann (2014). Coastal flood damage and adaptation cost under 21st century sea-level rise. In: Proceedings of the National Academy of Sciences. Published ahead of print February 3, 2014. Press release



Daniel Lincke



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