Deep learning reveals hotspots of global oceanic oxygen changes in the 21st century

This is a global ocean-scale dissolved oxygen dataset derived from a deep learning method using hydrometeorological and biogeocheical driver factors. The dataset provides yearly estimates of dissolved oxygen concentration during 2003 to 2020 throughout the whole water column, with a spatial resolution of 0.25° × 0.25°. The unprecedented high-resolution dataset provides information on dissolved oxygen spatial distribution and temporal trend, making it a significant contribution to understanding global warming and anthropogenic stressors.