This study is led by Dr. Mengyuan Wang (School of Marine Sciences, Sun Yat-sen University) and her collaborators Dr. Haixian Xiong (School of Marine Sciences, Sun Yat-sen University), Prof. Shouye Yang (State Key Laboratory of Marine Geology, Tongji University), Dr. Fengling Yu (State Key Laboratory of Marine Environmental Science, Xiamen University), Dr. Deming Kong (Key Laboratory for Coastal Ocean Variation and Disaster Prediction, Guangdong Ocean University), Prof. Yongqiang Zong and Prof. Zhonghui Liu (Department of Earth Sciences, the University of Hong Kong). They proposed a non-linear regression of UK'37–SST for samples collected from the specific environment of Chinese marginal sea shallow waters.
The coastal-continental shelf environment is more complex than the open ocean. The relationship between UK'37 and SST has not been fully explored in this environment, which limits the accuracy of the reconstruction results of this indicator in marginal seas. To investigate the relationship between the alkenone unsaturation index (UK'37)and sea surface temperature (SST) in coastal and continental shelf waters, 58 surface sediment samples were collected from the South China Sea (SCS), Taiwan Strait, and East China Sea (ECS). We combined the new results with the previously published 71 data points from the SCS, the shallow water areas of the Yellow Sea (YS) and northern ECS, to form a dataset with sample sites spanning across 6 °N and 37 °N (including annual SST calibration between 14.3 °C and 28.6°C). With this dataset, we examined the UK'37 -SST relationship based on 129 samples from the Western North Pacific (WNP) margin as well as using 85 samples from specific WNP shallow water. Based on this dataset, we proposed a non-linear regression of UK'37-SST: UK'37=-1.2488+0.1740xSST-0.0035x(SST)2, R2=0.93, n=85, specifically for the environments with SST below 24 °C.
See the article:
Wang M, Xiong H, Yang S, Yu F, Kong D, Zong Y, Liu Z. 2023. Assessing the UK'37–sea surface temperature relationship in shallow marine waters. Science China Earth Sciences, https://doi.org/10.1007/s11430-021-1041-6
