Ocean fronts play a key role in marine ecosystems and often implicitly exist in satellite observations. This work presents the first publicly available daily global front dataset spanning 1982 to 2023, with comprehensive validations using in situ global observations. Our validations enhance confidence in the application of satellite-based front detection and provide independent support for global front occurrence patterns. The dataset is expected to be widely used in front-related studies.

Observations of the sea surface temperature in the Arabian Sea show exceptional warming before the onset of the Indian Ocean summer monsoon. The sea surface temperature change is mainly caused by sea surface heat flux forcing, horizontal advection, and vertical entrainment. Here, we quantify the contribution of those factors to the Arabian Sea warm pool using heat budget analysis and highlight how large-scale ocean modes control its change.

This study reports the existence of a relatively-low-productivity area of upwelling east of Hainan Island (UEH), which is inconsistent with previous cognition. The reason for this phenomenon is the crucial role of the Guangdong Coastal Current and precipitation. The current and precipitation would induce a high productivity, which is interrupted by the upwelling processes. Therefore, the upwelling has a relatively limited effect on the Chl a concentration in the UEH area.

SCSOFS has provided daily updated marine forecasting in the South China Sea for the next 5 d since 2013. Comprehensive updates have been conducted to the configurations of SCSOFS's physical model and data assimilation scheme in order to improve its forecasting skill. The three most sensitive updates are highlighted. Scientific comparison and accuracy assessment results indicate that remarkable improvements have been achieved in SCSOFSv2 with respect to the original version SCSOFSv1.

In order to improve forecasting skills of South China Sea Operational Forecasting System operated in NMEFC of China, comprehensive updates have been conducted to the configurations of physical model and data assimilation scheme. Scientific inter-comparison and accuracy assessment has been performed by employing GODAE IV-TT Class 4 metrics. The results indicate that remarkable improvements have been achieved in the new version of SCSOFS.