To improve the estimate of economic costs of future sea-level rise associated with global climate change, this report generalizes the sea-level rise cost function originally proposed by Fankhauser, and applies it to a new database on coastal vulnerability developed as part of the Dynamic Interactive Vulnerability Assessment (DIVA) tool.
      An analytic expression for the generalized sea-level rise cost function is obtained to explore the effect of various spatial distributions of capital and nonlinear sea-level rise scenarios. With its high spatial resolution, the DIVA database shows that capital is usually highly spatially concentrated along a nation's coastline, and that previous studies, which assumed linear marginal capital loss for lack of this information, probably overestimated the fraction of a nation's coastline to be protected and hence protection cost. In addition, the new function can treat a sea-level rise scenario that is nonlinear in time. As a nonlinear sea-level rise scenario causes more costs in the future than an equivalent linear sea-level rise scenario, using the new equation with a nonlinear scenario also reduces the estimated damage and protection fraction through discounting of the costs in later periods.
      Numerical calculations are performed, applying the cost function to the DIVA database and socioeconomic scenarios from the MIT Emissions Prediction and Policy Analysis (EPPA) model. The effect of capital concentration substantially decreases protection cost and capital loss compared with previous studies, but not wetland loss. The use of a nonlinear sea-level rise scenario further reduces the total cost because the cost is postponed into the future.