Accelerated warming and salinification in China’s semi-enclosed shallow sea revealed by homogenized long-term observations
摘要
Long-term in situ instrumental records from marine stations are essential for understanding historical marine climate and environment change, which in turn, provides valuable insights for the evaluation of future climate change in response to sustainable coastal management. Long-term instrumental records of sea surface temperature (SST) and sea surface salinity (SSS) in semi-enclosed shallow seas are prone to inhomogeneities from non-climatic factors, such as sensor drift, station relocation. It is difficult to make accurate assessments of both anthropogenic and natural climate signals. Xiaochangshan (XCS) marine station at the northern Yellow Sea (NYS) represents a rare observation resource and opportunity, since both SST and SSS of the station are simultaneously and continuously monitored since 1960 with a long distance from land and free from urbanization influences. This study presents a detailed evaluation of the inhomogeneity of monthly SST and SSS data from XCS station (1960–2019). Multiple break points in the SST and SSS data series were identified by the penalized maximum t-test (PMT) and penalized maximum F-test (PMF). These inhomogeneous biases were then adjusted by quantile-matching (QM) method. The newly homogenized data were used to estimate the local marine climate changes. Analysis reveals a critical regime shift toward accelerated warming and salinization. The NYS exhibited a multidecadal SST rise of 0.26°C per decade (1960–2019), with a total warming of 0.66°C during 2010s, accompanied by SSS increases of 0.29 per decade over 1960–2019 and a total increase of 0.54 during 2010s, respectively. This acceleration exceeds regional surface temperature rise benchmarks, suggesting amplified thermodynamic feedbacks in semi-enclosed systems. This study provided one of the few continuous, land-independent long-term marine observational records in China. These homogenized datasets provide a solid data foundation for coastal resource management and climate adaptation strategies, supporting science-based decision-making for mariculture and ecosystem conservation.