MODELING CLIMATE CHANGE-DRIVEN FLOOD HAZARDS ALONG PACIFIC BASIN COASTS USING THE COASTAL STORM MODELING SYSTEM (COSMOS)

Much attention is directed toward sea-level rise (SLR) in projections of 21^st century coastal flooding. This notwithstanding, the impacts of storms and changes in atmospheric forcing brought about by climate change are also of vital importance. SLR occurs gradually over many years, allowing for planning and mitigation, but episodic events associated with storms and climate cycles will continue to be a major cause of costly and hazardous flood events. Thus, it is imperative to not only determine inundation potentials due to SLR but also to include flooding from extreme water levels super-imposed on expected future sea levels.

On the open coast, flooding and inundation is largely driven by tides, storm surge, and waves. Because of the vastness of the Pacific Ocean and strong persistent winds, open coasts within the Pacific Basin are particularly vulnerable to large long-period waves that, in shallow water near the shore, cause a super-elevation of the mean water level and fluctuations about that mean (wave runup).

Many studies have estimated wave runup for coastal flooding predictions, but when considering large geographic areas, most rely on empirical models and offshore wave conditions, neglecting changes in wave energy across the continental shelf and non-linear effects such as wave-current interactions in tidally-dominated regions. In this study, a numerical modeling system (CoSMoS) scales down global climate projections to the local level across large geographic areas while accounting for non-linear effects of depth changes on waves and wave-current interactions. CoSMoS has been applied to more than 700 km along the California coast. Spatial coastal flooding extents are available via a user-friendly web tool that includes several GIS attributes. Results show that, with the exception of high SLR conditions, wave runup is the largest contributor to flooding along this high-energy coast. Inclusion of storms can increase local flood extents by > 20%. Results also indicate that flood levels are non-linearly related to sea-level rise and that the discrepancy increases with sea-level rise. Thus, linear superposition of static flood levels with SLR will result in under- or over-estimation of flood hazard. The modeling system is dynamic and transferable, with discussions underway to apply it in the Central Pacific.