Salinity estimation using the T‐S relation in the context of variational data assimilation
Salinity estimation using the T‐S relation in the context of variational data assimilation
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DOI：
10.1029/2003jc001781
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发表时间：
2003-04
影响因子：
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通讯作者：
G. Han;Jiang Zhu;Guangqing Zhou
中科院分区：
文献类型：
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作者：
G. Han;Jiang Zhu;Guangqing Zhou
[1]在变分同化的框架下，提出了一种利用温盐关系统计量的盐度调整方案。该方案不仅考虑了平均T-S图，而且考虑了T-S关系的方差。为了检验该方案的性能，一个1-D的Mellor-Yamada型混合层模式和一个电导率温度深度（CTD）的数据集在热带西太平洋在两个实验中使用。CTD数据集包含密集的温度和盐度观测。在实验中，首先，平均T-S图及其方差是从同化期间的温度和盐度观测获得的;然后，通过最小化包含四项的成本函数来调整温度和盐度廓线：温度观测项，温度和盐度的背景项，一项测量盐度与通过平均T-S图从温度推断的盐度之间的距离。一个更简单的方案，首先调整同化温度数据的温度廓线，然后用平均T-S图和最新更新的温度廓线取代模式盐度廓线，也进行了比较测试。所提出的方案在重建盐度变化在大多数水平上表现出良好的技能，并表现略好于简单的方案，总体改善4- 10%。并对该方法的适用性进行了讨论。
[1] A salinity adjustment scheme using statistics of the temperature-salinity (T-S) relationship is proposed in the framework of variational data assimilation. The scheme not only considers the mean T-S diagram but also takes the variance of the T-S relations into consideration. To test performance of the scheme, a 1-D mixed layer model of the Mellor-Yamada type and a conductivity-temperature-depth (CTD) data set in the western tropical Pacific are used in two experiments. The CTD data set contains intensive temperature and salinity observations. In the experiments, first, the mean T-S diagram and its variance are obtained from temperature and salinity observations over the assimilation period; then, temperature and salinity profiles are adjusted by minimizing a cost function that contains four terms: the temperature observation term, the background terms for both temperature and salinity, and a term measuring the distance between the salinity and the inferred salinity from the temperature via the mean T-S diagram. A simpler scheme, which first adjusts the temperature profile by assimilating temperature data and then replaces the model salinity profile using the mean T-S diagram and the newly updated temperature profile, is also tested for comparison. The proposed scheme shows good skill in reconstructing salinity variations at most levels and performs slightly better than the simpler scheme with overall improvements of 4-10%. The applicability of the method is also discussed.