On the need of bias correction methods for wave climate projections

Abstract

Abstract This study focuses on the assessment of systematic biases in wave climate simulations, exploring different bias correction methods commonly used for climate impact variables (e.g. precipitation, temperature), and on the analysis of bias corrected wave climate projections. Four different bias correction methods are analyzed, two of which are applied to an 8-member dynamic multi-forcing global wave climate ensemble, to mitigate the significant wave height (HS) bias. The GOW2 (Global Ocean Waves 2) global wave hindcast is used as reference data for the calibration. Assuming that the statistical properties of the present climate biases are maintained in the future, these biases can be corrected by applying a bias correction model based on the reference data. Thus, the impact of climate change in the bias corrected future HS climate, is also investigated. A bias corrected 8-member ensemble is analyzed for the 2081–2100 period, under the RCP8.5 scenario. The results indicate the relevance of bias correction in both the estimation of ensemble mean HS projected changes towards the end of the 21st century, and in the ensemble spread magnitude. Outcomes support the need for a quantile based bias correction, able to deal with extreme events, which have a disproportionate impact in coastal processes.