Three stages in the variation of the depth of hypoxia in the California Current System 2003-2020 by satellite estimation.

The depth of hypoxia (DOH) is the shallowest depth at which the waters become hypoxic (oxygen concentration < 60 μmol kg-1), is a crucial indicator of the formation and expansion of oxygen minimum zones (OMZs). In this study, a nonlinear polynomial regression inversion model was developed to estimate the DOH in the California Current System (CCS), based on the dissolved oxygen profile detected by the Biogeochemical-Argo (BGC-Argo) float and remote sensing data. Satellite-derived net community production was used in the algorithm development, to denote the combined effect of phytoplankton photosynthesis and O2 consumption. Our model performs well, with a coefficient of determination of 0.82 and a root mean square error of 37.69 m (n = 80) from November 2012 to August 2016. Then, it was used to reconstruct the variation in satellite-derived DOH in the CCS from 2003 to 2020, and three stages of the DOH variation trend were identified. From 2003 to 2013, the DOH showed a significant shallowing trend due to the intense subsurface O2 consumption caused by strong phytoplankton production in the CCS coastal region. The trend was interrupted by two successive strong climate oscillation events from 2014 to 2016, which led to a significant deepening of the DOH and a slowing, or even reversal, of the variations in other environmental parameters. After 2017, the effects of climate oscillation events gradually disappeared, and the shallowing pattern in the DOH recovered slightly. However, by 2020, the DOH had not returned to the pre-2014 shallowing characteristic, which would lead to continuing complex ecosystem responses in the context of global warming. Based on the satellite inversion model of DOH in the CCS, we provide a new insight on the high-resolution spatiotemporal OMZ variations during an 18-year period in the CCS, which will aid in the evaluation and prediction of local ecosystems variation.