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热带海洋学报 >

2016 , Vol. 35 >Issue 2: 30 - 39

DOI: https://doi.org/10.11978/2015052

海洋水文学

“选尺度资料同化”方法在海洋数值模拟中的应用: 对一次西沙强暖涡过程的模拟试验*

  • 王品强 ,
  • 李毅能 ,
  • 彭世球
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  • 1. 热带海洋环境国家重点实验室(中国科学院南海海洋研究所), 广东 广州 510301; 2. 中国科学院大学, 北京 100049;
王品强(1989—), 男, 湖北省潜江市人, 硕士研究生, 从事资料同化、数值模式研究。E-mail: wangpq@scsio.ac.cn

收稿日期: 2015-04-15

  修回日期: 2015-09-23

  网络出版日期: 2016-02-29

基金资助

国家重点基础研究发展计划重大科技攻关项目(2011CB403505、2014CB953904); 中国科学院战略性先导科技专项(A类, XDA11010304); 国家自然科学基金项目(41376021、41306013); 广东省突发性海洋灾害事件应急技术研究中心项目(2012A 032100004)

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Application of scale-selective data assimilation method in ocean modeling: simulation of a strong warm eddy in Xisha

  • WANG Pinqiang ,
  • LI Yineng ,
  • PENG Shiqiu
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  • 1. State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Sciences),;Guangzhou 510301, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2015-04-15

  Revised date: 2015-09-23

  Online published: 2016-02-29

Supported by

The Ministry of Science and Technology of the People’s Republic of China (MOST) (2011CB403505, 2014CB953904); The Strategic Priority Research Program of the Chinese Academy of Sciences (Grant XDA11010304); The National Natural Science Foundation of China (41176024, 41306013); Guangdong Marine’sdisaster emergency response technology research center (2012A032100004)

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摘要

“选尺度同化”(SSDA)方法是指在资料同化中考虑观测资料和模式变量的多尺度特征, 选择性地对模式变量在某一尺度上进行调整同时保持在其他尺度上不变。为检验该方法在海洋资料同化中的应用效果, 以2010年8月南海西沙群岛海域出现的强暖涡(称为西沙暖涡)为试验对象, 对比了同化卫星高度计海表高度资料及其反演的地转流对暖涡的改善效果, 其中对地转流的同化采用了两种同化方法, 即采用和未采用选尺度同化方法。各个试验结果对比表明, 同化海表高度和利用选尺度同化方法同化地转流均能改善对西沙暖涡的模拟, 两者同时同化对西沙暖涡模拟的改善最显著。其中, 同化海表高度是通过压力场调整速度场, 对西沙暖涡的范围改善更显著; 选尺度同化方法则通过速度场调整压力场, 有利于维持海水向暖涡中心的辐合, 对暖涡强度模拟效果更好。此外, 不采用SSDA方法同化地转流(即不对模式流场进行尺度分离)的试验模拟效果最差, 原因在于通过地转流直接调整整个流场会抑制小尺度流场(非地转流部分)的自由发展。

关键词： 西沙暖涡; 选尺度同化; 地转流; 卫星高度计

本文引用格式

王品强 , 李毅能 , 彭世球 . “选尺度资料同化”方法在海洋数值模拟中的应用: 对一次西沙强暖涡过程的模拟试验*[J]. 热带海洋学报, 2016 , 35(2) : 30 -39 . DOI: 10.11978/2015052

Abstract

Scale-selective data assimilation (SSDA), through considering multiscale features in both observational data and model variables during assimilation, can selectively adjust certain scales of motion while keeping other scales unchanged. To test the effectiveness of SSDA in ocean data assimilation, an exceptional anticyclonic eddy event in August 2010 over the sea area of the Xisha Islands (referred to as Xisha Warm Eddy) is chosen. In this study, we compared the effects of assimilating sea level anomaly (SLA) and its derived geostrophic currents. Geostrophic currents were assimilated in two ways, applying the SSDA or not. Results showed that assimilating SLA or geostrophic currents can both improve the simulation of Xisha Warm Eddy. On one hand, assimilating SLA improved the horizontal size of Xisha Warm Eddy since the velocity field followed the change of pressure field, permitting divergence of sea water. On the other hand, assimilating geostrophic currents improved the intensity of Xisha Warm Eddy because SSDA can adjust pressure field according to velocity field, which helped maintain the convergence of Xisha Warm Eddy. Simultaneously assimilating both geostrophic currents and SLA improved the simulation most significantly. Therefore, SSDA is necessary for assimilating geostrophic currents.

Key words： Xisha Warm Eddy; scale-selective data assimilation (SSDA); geostrophic current; satellite altimeter

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