Identification of storm events and contiguous coastal sections for deterministic modeling of extreme coastal flood events in response to climate change

• Published in: Coastal engineering (Amsterdam) Vol. 140; pp. 316 - 330
• Main Authors: Erikson, Li H., Espejo, Antonio, Barnard, Patrick L., Serafin, Katherine A., Hegermiller, Christie A., O'Neill, Andrea, Ruggiero, Peter, Limber, Patrick W., Mendez, Fernando J.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2018
• Subjects: Coastal storm cells; Dynamical downscaling; Global climate models; K-means clustering; Southern California; Dynamical downscaling; Southern California; Coastal storm cells; Global climate models; K-means clustering
• ISSN: 0378-3839; 1872-7379
• DOI: 10.1016/j.coastaleng.2018.08.003

Deterministic dynamical modeling of future climate conditions and associated hazards, such as flooding, can be computationally-expensive if century-long time-series of waves, sea level variations, and overland flow patterns are simulated. To alleviate some of the computational costs, local impacts of individual coastal storms can be explored by first identifying particular events or scenarios of interest and dynamically modeling those events in detail. In this study, an efficient approach to selecting storm events for subsequent deterministic detailed modeling of coastal flooding is presented. The approach identifies locally relevant scenarios derived from regional datasets spanning long time-periods and covering large geographic areas. This is done by identifying storm events from global climate models using a robust, yet computationally simple approach for calculating total water level proxies at the shore, assuming a linear superposition of the important processes contributing to the overall total water level. Clustering of the total water level time-series is used to define coherent coastal cells where similar return period water level extrema occur in response to region-wide storms. Results show that the more severe but rare coastal flood events (e.g., the 100-year (yr) event) typically occur from the same storm across the region, but that a number of different storms are responsible for the less severe but more frequent local extreme water levels (e.g., the 1-yr event). This new ‘storm selection’ approach is applied to the Southern California Bight, a region of varying shoreline orientations that is subject to wave refraction across complex bathymetry, and shadowing, focusing, diffraction, and dissipation of wave energy by islands. Results indicate that wave runup dominates total water level extremes at this study site, highlighting the importance of downscaling global-scale models to nearshore waves when seeking accurate projections of local coastal hazards in response to climate change. •A computationally efficient method to downscale global scale atmospheric patterns to local total water levels is developed.•Clustering is used to identify coastal segments that respond similarly to region-wide (100s of kms) storms.•Excluding tides, extreme total water levels are dominated by wave runup in Southern California, USA.•100-year return period storm-driven coastal water levels largely occur from the same regional storm event.•Numerous different region-wide storms are responsible for the less severe but more frequent local extreme water levels.