基于Argo剖面和SST以及SLA数据重构三维网格温度场-海洋预报

基于Argo剖面和SST以及SLA数据重构三维网格温度场

单位：浙江海洋大学, 浙江舟山 316022

分类号：P731.11

出版年·卷·期（页码）：2020·37·第四期（66-75）

摘要：

基于2004年1月—2017年4月的Argo剖面数据和SST数据，采用客观分析方法，构建出三维网格温度初始场，再采用回归分析方法统计出海面高度异常与三维网格温度初始场之间的相关关系，最后利用高分辨率的海面高度异常信息重构三维温度分析场。在西北太平洋区域构建了0.5°×0.5°的月平均三维温度分析场，垂向分辨率5 m（5~300 m）和10 m（300~700 m）。通过与BOA_Argo和EN4的逐月平均温度数据的时空分布对比分析表明：所构建的温度场能够较为真实地反映海洋温度场的垂向结构变化特征，能将SST信号的特征反映到混合层，并且能反映下层水团变化过程和特征。该分析场可以用于研究下层中小尺度温度变化特征，也可以作为模式初始场改进模式对海洋下层温盐的模拟结果。

Based on Argo profile and Sea Surface Temperature (SST) data from January 2004 to April 2017, threedimensional sea temperature field is constructed using objective analysis, and the correlation between sea Surface Level Anomaly (SLA) and the three-dimensional temperature field is calculated using regression analysis method. Thereafter, high-resolution SLA data is used to reconstruct three-dimensional temperature field. A 0.5°×0.5° monthly averaged three-dimensional temperature field is reconstructed for the northwest Pacific Ocean in this paper with the vertical resolution of 5 m and 10 m for the depth of 5~300 m and 300~700 m, respectively. By comparison with the temporal and spatial distribution of the BOA_monthly averaged Argo and EN4 temperature data, the temperature field reconstructed in this paper can reflect the characteristics of vertical sea temperature variation. In addition, the reconstructed temperature field can convey the SST signal into the mixed layer, and demonstrate the variation process and characteristics in the lower ocean. The temperature field reconstructed in this paper can be used to study the characteristics of small scale temperature variation, and can also be used as model initial condition to improve the simulation of temperature in the lower ocean.

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