Probabilistic sea level rise flood projections using a localized ocean reference surface

Abstract

Abstract Projecting sea level rise (SLR) impacts requires defining ocean surface variability as a source of uncertainty. We analyze ocean surface height data from a Regional Ocean Modeling System reanalysis to produce an ocean reference surface (ORS) as a proxy for the local mean higher high water. This method allows incorporation of ocean surface level uncertainty into bathtub modeling and generation of probability-based projections of SLR-induced flooding. For demonstration, we model the NOAA Intermediate, Intermediate-high and High regional SLR scenarios at three locations on the island of Oʻahu, Hawai’i. We compare 80% probability-based flood projections generated using our approach to those generated using the Tidal Constituents and Residual Interpolation (TCARI) method. TCARI is the predecessor of VDatum, the standard method used by NOAA available only for the continental U.S., Puerto Rico, and U.S. Virgin Islands. For validation, ORS pixel values representing the Honolulu tide gauge location are compared to tide gauge observations. The more realistic distribution of daily higher high water provided by ORS improves projections of SLR-induced flooding for locations where VDatum is not available. We highlight the importance of uncertainty and user-defined probability in identifying locations of flooding and pathways for additional sources of flooding.