Probabilistic Sea Level Rise Flood Projections Using a Localized Ocean Reference Surface

Projecting sea level rise (SLR) impacts requires defining ocean surface variability as a source of uncertainty. We analyze data from a Regional Ocean Modeling System (ROMS) reanalysis for the region surrounding the main Hawaiian Islands to incorporate the ocean surface uncertainty in mapping SLR flood probabilities. By analyzing the ocean surface height component of the ROMS reanalysis, we create an ocean surface reference (ORS) as a proxy for MHHW. We model the NOAA Intermediate, Intermediate-high and High regional SLR scenarios for the years 2050 and 2100 at three field sites around Oʻahu; Waikīkī, Hauʻula, Haleʻiwa. We calculate a probability density function (PDF) by convolving the PDF of water level derived from the ROMS reanalysis data with the PDF of error associated with a digital elevation model of the study sites. The resulting joint-PDF of flood depth allows us to create two types of probability-based flood projections: (1) Maps illustrating varying flood depths for a given probability threshold and, (2) maps illustrating varying probability for a specific flood depth. We compare 80% probability flood projections using our ORS approach to projections using the TCARI grid, the standard NOAA method. We highlight the importance of uncertainty and user-defined probability in identifying pixels that function as tipping points distinguishing flooding styles.