# REBEC: Robust Evolutionary-based Calibration Approach for the Numerical Wind Wave Model

## TL;DR

This paper introduces REBEC, a robust evolutionary calibration method for wind wave models that balances accuracy and robustness by creating an ensemble of perturbed models, outperforming traditional algorithms in various scenarios.

## Contribution

The paper presents a novel ensemble-based evolutionary calibration approach that enhances the robustness of wind wave model calibration compared to existing methods.

## Key findings

- REBEC outperforms SPEA2 in calibration scenarios
- Ensemble approach improves model robustness
- Effective in local wind wave modeling

## Abstract

The adaptation of numerical wind wave models to the local time-spatial conditions is a problem that can be solved by using various calibration techniques. However, the obtained sets of physical parameters become over-tuned to specific events if there is a lack of observations. In this paper, we propose a robust evolutionary calibration approach that allows to build the stochastic ensemble of perturbed models and use it to achieve the trade-off between quality and robustness of the target model. The implemented robust ensemble-based evolutionary calibration (REBEC) approach was compared to the baseline SPEA2 algorithm in a set of experiments with the SWAN wind wave model configuration for the Kara Sea domain. Provided metrics for the set of scenarios confirm the effectiveness of the REBEC approach for the majority of calibration scenarios.