Regionalized ensemble estimation of wave periods for assessing wave energy resources across Canada. Part I: Improved wave-period modelling methodology

Abstract

Large-scale estimations of wave periods are desired for wave energy assessment, ocean engineering, and wave climate research. Long-term global wave data from satellite altimeters are routinely applied to the estimations. However, this is challenged by uncertainties in wave-period models (WPMs), inaccuracies in data, and simplifications in modeling. Additionally, there exists a gap in the comprehensive examination of the variational mechanisms governing wave periods or model performances. As an effort to address them, we innovate a macroscale regionalized ensemble wave-period modeling (MREWPM) method by optimizing four wave-period models, driven by enhanced altimeter-based REWS (regionalized ensemble wave simulation) estimates of wave heights and wind speeds, within a regionalization framework in macroscale water environments. Results show that MREWPM driven by REWS dataset outperforms existing methods and performs better at larger scales (e.g., in eliminating local-scale overestimation). WPMs are more accurate over remote, deep, and windy regions in cool seasons under metrics-, scale- and data-dependent variations of performances with driving factors (mainly geographical features). This study serves as a foundational contribution towards the enhancement of wave-period simulations, the advancement of understanding wave-period dynamics, and the scientific evaluation of wave energy at macroscales.