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

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 fusion with along-track, jointly calibrated altimeter observations from the Climate Change Initiative Sea State dataset. As a retrospective reconstruction, the offline fusion allows observations acquired both before and after a target time to contribute to the estimate, with their influence explicitly constrained by temporal separation. Validation against buoy measurements and withheld 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 is designed to reduce sampling-related temporal inhomogeneity by maintaining a relatively stable number of observations and broadly consistent orbital sampling characteristics throughout the record. (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).