CoSMoS (Coastal Storm Modeling System) Southern California v3.0 Phase 2 projections of coastal cliff retreat due to 21st century sea-level rise

Summary: This dataset contains projections of coastal cliff-retreat rates and positions for future scenarios of sea-level rise (SLR). Projections were made using numerical and statistical models based on field observations such as historical cliff retreat rate, nearshore slope, coastal cliff height, and mean annual wave power.
Details: Cliff-retreat position projections and associated uncertainties are for scenarios of 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, and 5 meters of sea-level rise (SLR). Projections were made at CoSMoS cross-shore transects (CST) spaced 100 m alongshore. Projections were made using a baseline sea-cliff edge from 2010 (which is included in the dataset). There are two separate datasets (or KMZ files) available: one that ignores coastal armoring , such as seawalls and revetments, and allows the cliff to retreat unimpeded (“Do Not Hold the Line”); and another that assumes that current coastal armoring will be maintained and 100% effective at stopping future cliff erosion (“Hold the Line”).
Eight numerical models were used to make projections. The projections are therefore a robust average of all models, and the uncertainties are proportional to the differences between individual model forecasts at each CST. The models relate breaking-wave height and period to cliff rock or unconsolidated sediment erosion. As sea level rises, waves break closer to the sea cliff, and more wave energy impacts the cliffs – and accelerates cliff erosion rates. Model behavior also includes wave run-up (Stockdon and others, 2006), wave set-up that raises the water level during big-wave events, and tidal levels.
The models were run on idealized cliff profiles extending from about 10 m water depth to 1 kilometer inland from the cliff edge. Profiles were extracted by overlaying the cross-shore transects on a high-resolution digital elevation model (DEM) covering the Southern California study area. Using aerial photography, the presence of a beach was recorded (yes or no) for all transects, and the cliff toe elevation (or beach/cliff junction) was digitized from the DEM profiles. Using historic cliff edge retreat rates by Hapke and Reid (2007), unknown coefficients within the cliff-profile models were calibrated using a Monte Carlo simulation (in other words, coefficients were tuned until the modeled mean retreat rate equaled the observed mean retreat rate for a given transect).
Uncertainty was tallied using a root mean squared error (RMSE) approach. The RMSE represents cumulative uncertainty from multiple sources and assumes that different sources of error will, at times, cancel each other out. It is therefore not a 'worst-case uncertainty' (in other words, a straight sum of errors) but instead an average uncertainty. Main sources of uncertainty in the RMSE calculation are the base error of the historical retreat rates that the predictions are based on (+/- 0.15 m/yr) and the spread, or standard deviation, of the eight model predictions. Total RMSE increased with SLR rate and varied between +/- 2-3 m to a maximum of +/- 50 m for the extreme 5 m SLR scenario.
References Cited: Hackney, C., Darby, S. E., and Leyland, J. (2013). Modelling the response of soft cliffs to climate change: A statistical, process-response model using accumulated excess energy. Geomorphology, 187, 108-121.
Hapke, C.J., and Reid, D., 2007. National Assessment of Shoreline Change, Part 4: Historical Coastal Cliff Retreat along the California Coast: U.S. Geological Survey Open-file Report 2007-1133. http://pubs.usgs.gov/of/2007/1133/
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