In this study, we analysed the interannual variability of sea surface temperature (SST), sea surface wind (SSW), and sea level anomaly (SLA) in the South China Sea (SCS) during 1985–2016 using monthly reanalysis and satellite datasets. An empirical orthogonal function (EOF) analysis was performed to evaluate the interannual variability of each variable. The warming rate of SST was 0.18 ± 0.26°C decade⁻¹ in the SCS. The first EOF of SST was characterized by basin-wide warming, with the highest anomalies in the northern deep basin. The first temporal coefficient of SST was negatively correlated with the Niño 3.4 index, with a lag of 6 mo. The mean rising rate of SLA was 7.6 cm decade⁻¹, with the greatest trend in the coastal water of Vietnam, which exhibited a similar spatial pattern with the first EOF of SLA. The temporal coefficient of SLA was negatively correlated with that of SST, with a lag of 5 mo. The trend of SSW was around 0.8 m s⁻¹ decade⁻¹ over the SCS. The first EOF of SSW was characterized by an anticyclonic pattern. The temporal coefficient was correlated with that of SST, with a lead of 2 mo. Wavelet coherence was used to investigate the cross-correlation relationship between SST and other variables. SST and SLA had a strong negative correlation in the 8–16-mo (1–1.5 yr) band. The high positive wavelet coherencies between SST and SSW and Niño 3.4 were mainly in the 32–64 mo (3–5 yr) band in the SCS.

A time series of satellite data on Chlorophyll-a concentration (Chl-a) that used ocean color was studied to determine mechanisms of phytoplankton variation in recent decade in the Yellow Sea, China during 2003–2015. The variability patterns on seasonal and inter-annual oscillation periods were confirmed using the Empirical Orthogonal Function (EOF), and Morlet wavelet transform analyses, respectively. The first EOF mode for Chl-a was dominated by obvious spring and fall blooms in a spatial pattern that was related to the strong mixing of the water masses from the Yellow Sea Cold Warm Mass (YSCWM) and the Yellow Sea Warm Current (YSWC) in winter. The second EOF mode for Chl-a showed an opposite spatial pattern between the northern and southern regions. The temporal coefficient showed differences in the timing of blooms. On an inter-annual scale, Chl-a indicated variation at periods of 2–4 years during 2003–2015. Chl-a showed a significantly negative correlation with the sea surface temperature (r = -0.21, p<0.01), with time lags of 4 months (Chl-a ahead). Chl-a was coupled with El Niño Southern Oscillation (ENSO) events, with a positive correlation (r = 0.46, p<0.01) at a lag of 3–5 months (ENSO ahead). The present study demonstrated that the variation in phytoplankton biomass was controlled primarily by water mass seasonally, and it was influenced by ENSO events on an inter-annual scale.

The Yellow Sea Cold Water Mass (YSCWM) is an important component of the hydrodynamic system and it significantly impacts the primary production of the Yellow Sea. This study investigated the difference in the interannual variability and long-term trends between the northern YSCWM (NYSCWM) and southern YSCWM (SYSCWM), and explored the main physical environmental factors that led to their inconsistency using multiple wavelet coherence. On the interannual scale, the intensities of the NYSCWM and SYSCWM exhibited consistent variability, but the intensity of the SYSCWM had a larger standard deviation and longer periodic signal than that of the NYSCWM. The two-factor combination of surface air temperature (SAT)–Niño 3.4 in the NYSCWM and sea surface temperature (SST)–northward seawater velocity (Vgos) in the SYSCWM controlled the interannual variability, which meant the influencing intensity variability differed in the NYSCWM and SYSCWM. In the long-term trend, the intensities of the NYSCWM and SYSCWM both showed decreasing trends during the study period. However, the enhanced circulation provided more horizontal heat input into the SYSCWM, and the relatively higher increase in SST and decrease in the amplitude of variation in the thermocline depth promoted vertical heat exchange in the SYSCWM, thereby making the intensity of the SYSCWM decrease more quickly than that of the NYSCWM. These findings provide important references that facilitate a deeper understanding of the influence of hydrological processes on marine ecosystems in marginal seas.

The Arabian Sea has undergone significant warming since the mid-20th century, highlighting the importance of assessing how decadal climate patterns influence chlorophyll-a (Chl-a) and broader marine ecosystem dynamics. This study investigates the variability of Chl-a, sea surface temperature (SST), and sea level anomaly (SLA) over the past three decades, and their relationships with the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). The mean Chl-a concentration was 1.10 mg/m³, with peak levels exceeding 2 mg/m³ between 2009 and 2013, and the lowest value (0.6 mg/m³) was recorded in 2014. Elevated Chl-a levels were consistently observed in February and March across both coastal and offshore regions. Empirical orthogonal function (EOF) analysis revealed distinct spatial patterns in Chl-a and SST, indicating dynamic regional variability. The SST increased by 0.709 °C over the past four decades, accompanied by a steady rise in the SLA of approximately 1 cm. The monthly mean Chl-a exhibited a strong inverse relationship with both the SST and SLA and a positive correlation with SST gradients (R² > 0.5). A positive correlation (R² > 0.5) was found between the PDO and Chl-a, whereas the PDO was negatively correlated with the SST and SLA. In contrast, the AMO was negatively correlated with Chl-a but positively associated with warming and SLA rise. These findings underline the contrasting roles of the PDO and AMO in modulating productivity and ocean dynamics in the Arabian Sea. This study emphasizes the need for continued monitoring to improve predictions of ecosystem responses under future climate change scenarios.