State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences , Guangzhou 510301, China ; University of Chinese Academy of Sciences , Beijing 100049, China.
State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences , Guangzhou 510301, China.
Sci Data. 2014 Dec 23;1:140052. doi: 10.1038/sdata.2014.52. eCollection 2014.
Ocean reanalysis provides a temporally continuous and spatially gridded four-dimensional estimate of the ocean state for a better understanding of the ocean dynamics and its spatial/temporal variability. Here we present a 19-year (1992-2010) high-resolution ocean reanalysis dataset of the upper ocean in the South China Sea (SCS) produced from an ocean data assimilation system. A wide variety of observations, including in-situ temperature/salinity profiles, ship-measured and satellite-derived sea surface temperatures, and sea surface height anomalies from satellite altimetry, are assimilated into the outputs of an ocean general circulation model using a multi-scale incremental three-dimensional variational data assimilation scheme, yielding a daily high-resolution reanalysis dataset of the SCS. Comparisons between the reanalysis and independent observations support the reliability of the dataset. The presented dataset provides the research community of the SCS an important data source for studying the thermodynamic processes of the ocean circulation and meso-scale features in the SCS, including their spatial and temporal variability.
海洋再分析为更好地了解海洋动力及其时空变异性提供了一个时间连续、空间网格化的四维海洋状态估计。本文介绍了一个基于海洋数据同化系统生成的南海上层海洋 19 年(1992-2010 年)高分辨率海洋再分析数据集。广泛的观测资料,包括现场温盐剖面、船舶测量和卫星反演的海面温度、以及卫星测高得到的海面高度异常,通过多尺度增量三维变分数据同化方案同化到海洋环流模型的输出中,生成了一个南海每日高分辨率再分析数据集。再分析与独立观测的比较支持了数据集的可靠性。该数据集为南海研究界提供了一个重要的数据源,用于研究海洋环流的热力学过程和南海的中尺度特征,包括它们的时空变异性。