A global gridded dataset of significant wave height via fusion of multi-mission altimetry and numerical hindcast

Abstract. Satellite altimeters provide long-term, high-accuracy observations of significant wave height (SWH) over the global ocean. However, their sparse spatial and temporal sampling introduces undersampling errors in wave climate analyses. Direct gridding of multi-mission altimeter data through spatiotemporal interpolation still results in low-accuracy global SWH fields due to this limitation. To overcome this challenge, we use SWH outputs from a WAVEWATCH III hindcast as a background field and apply an offline post-fusion with along-track, jointly calibrated altimeter observations from the Climate Change Initiative Sea State dataset. Unlike data assimilation within numerical wave models, this offline fusion approach allows retrospective correction of past model outputs using future observations. Validation against buoy measurements and independent satellite data demonstrates that the fused gridded product achieves high accuracy. To address different application needs, we provide two versions of the fused dataset: 1) A "two-sat" version that incorporates data from only two satellites at any given time, designed for wave climate studies. This configuration ensures temporal consistency by maintaining a stable data volume over the entire time span. 2) A "multi-sat" version that integrates data from as many altimeter missions as possible, intended to support applications such as the training of artificial intelligence-based wave models, where higher spatial and temporal accuracy is prioritized. The dataset is freely available at https://doi.org/10.57760/sciencedb.29314 (Su and Jiang, 2025).