Adjoint-based sensitivity analysis for a numerical storm surge model

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: This is version 1 of this Preprint.


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Simon Warder , Kevin Horsburgh, Matthew Piggott 


Numerical storm surge models are essential to forecasting coastal flood hazard and informing the design of coastal defences. However, such models rely on a variety of inputs, many of which will carry uncertainty, and an awareness and understanding of the sensitivity of the model outputs with respect to those uncertain inputs is necessary when interpreting model results. Here, we use an unstructured-mesh numerical coastal ocean model, Thetis, and its adjoint, to perform a sensitivity analysis for a hindcast of the 5th/6th December 2013 North Sea surge event, with respect to the bottom friction coefficient, bathymetry and wind stress forcing. The results reveal spatial and temporal patterns of sensitivity, providing physical insight into the mechanisms of surge generation and propagation, and can also be used to estimate the uncertainty in skew surge model predictions due to uncertainty in each model input. Our results demonstrate the power of adjoint methods to gain relevant insight into a storm surge model, providing information complementary to traditional ensemble uncertainty quantification methods.



Applied Mathematics, Numerical Analysis and Computation, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics


Unstructured mesh, Adjoint, Finite element method, Sensitivity analysis, Storm surge, Uncertainty quantification


Published: 2020-06-30 00:24


CC BY Attribution 4.0 International

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