Joint projections of sea level and storm surge using a flood index

Christopher M Little, Atmospheric and Environmental Research Lexington, Lexington, MA, United States, Ning Lin, Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, Radley M Horton, Columbia University, New York, NY, United States, Robert E Kopp, Rutgers University New Brunswick, Department of Earth and Planetary Sciences, New Brunswick, NJ, United States and Michael Oppenheimer, Princeton University, Woodrow Wilson School of Public and International Affairs, Princeton, NJ, United States
Abstract:
Capturing the joint influence of sea level rise (SLR) and tropical cyclones (TCs) on future coastal flood risk poses significant challenges. To address these difficulties, Little et al. (2015) use a proxy of tropical cyclone activity and a probabilistic flood index that aggregates flood height and duration over a wide area (the US East and Gulf coasts). This technique illuminates the individual impacts of TCs and SLR and their correlation across different coupled climate models. By 2080-2099, changes in the flood index relative to 1986-2005 are substantial and positively skewed: a 10th-90th percentile range of 35-350x higher for a high-end business-as-usual emissions scenario (see figure).

This aggregated flood index: 1) is a means to consistently combine TC-driven storm surges and SLR; 2) provides a more robust description of historical surge-climate relationships than is available at any one location; and 3) allows the incorporation of a larger climate model ensemble -- which is critical to uncertainty characterization. It does not provide a local view of the complete spectrum of flood severity (i.e. return curves). However, alternate techniques that provide localized return curves (e.g. Lin et al., 2012) are computationally intensive, limiting the set of large-scale climate models that can be incorporated, and require several linked statistical and dynamical models, each with structural uncertainties that are difficult to quantify.

Here, we present the results of Little et al. (2015) along with: 1) alternate formulations of the flood index; 2) strategies to localize the flood index; and 3) a comparison of flood index projections to those provided by model-based return curves. We look to this interdisciplinary audience for feedback on the advantages and disadvantages of each tool for coastal planning and decision-making.

Lin, N., K. Emanuel, M. Oppenheimer, and E. Vanmarcke, 2012: Physically based assessment of hurricane surge threat under climate change. Nature Clim. Change, 2(6), 462–467.

Little, C. M., R. M. Horton, R. E. Kopp, M. Oppenheimer, G. A. Vecchi, and G. Villarini, 2015: Joint projections of us east coast sea level and storm surge. Nature Clim. Change, advance online publication.

Back to: Coasts in Crisis: Sea Level Rise and Inundation and the Drivers for Adaptation II