In California, sea-level rise during the 21st century threatens to accelerate coastal cliff recession rates. To forecast such changes for managers and policymakers, models must play a key role. In this paper, we extend a ～70-year long dataset of measured historic sea cliff retreat rates in Southern California into the 21st century using a suite of simple analytical and empirical models. Ensemble results suggest that coastal cliff recession rates could increase on average by 0.09- 0.22 m yr~(-1) for a 0.5-1.0 m rise in sea level by 2100, 27- 67% faster than historical rates. The basic models used herein will serve as a baseline against which more complex, process-based and statistical (Bayesian) forecasts will be compared. The application of different models, with varying levels of detail, to the same geomorphic problem will provide a comprehensive forecast and address the question of how to reduce model complexity while minimizing uncertainty.
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