@article{10902/24231,
year = {2021},
month = {7},
url = {http://hdl.handle.net/10902/24231},
abstract = {ABSTRACT: Reliable predictions and accompanying uncertainty estimates of coastal evolution on decadal to centennial time scales are increasingly sought. So far, most coastal change projections rely on a single, deterministic realization of the unknown future wave climate, often derived from a global climate model. Yet, deterministic projections do not account for the stochastic nature of future wave conditions across a variety of temporal scales (e.g., daily, weekly, seasonally, and interannually). Here, we present an ensemble Kalman filter shoreline change model to predict coastal erosion and uncertainty due to waves at a variety of time scales. We compare shoreline change projections, simulated with and without ensemble wave forcing conditions by applying ensemble wave time series produced by a computationally efficient statistical downscaling method. We demonstrate a sizable (site-dependent) increase in model uncertainty compared with the unrealistic case of model projections based on a single, deterministic realization (e.g., a single time series) of the wave forcing. We support model-derived uncertainty estimates with a novel mathematical analysis of ensembles of idealized process models. Here, the developed ensemble modeling approach is applied to a well-monitored beach in Tairua, New Zealand. However, the model and uncertainty quantification techniques derived here are generally applicable to a variety of coastal settings around the world.},
publisher = {John Wiley & Sons},
publisher = {Journal of Geophysical Research. Earth Surface 2021, 126 (7), e2019JF005506},
title = {The application of ensemble wave forcing to quantify uncertainty of shoreline change predictions.},
author = {Vitousek, Sean and Cagigal Gil, Laura and Montaño, Jennifer and Rueda Zamora, Ana Cristina and Méndez Incera, Fernando Javier and Coco, Giovanni and Barnard, Patrick L.},
}