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APPLICATION OF THE SPECTRAL NUDGING ON GLOBAL TIDES TOWARDS A GLOBAL TOTAL WATER LEVEL PREDICTION SYSTEM

机译:谱归纳法在全球潮流中对全球总水位预测系统的应用

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With the long-term goal of developing an ensemble forecast system for coastal flooding, we are developing a dynamically-based, numerical model of the global ocean. The model is based on the NEMO framework and has been used to predict global tides and surges in previous studies. This study focuses on the optimization of the joint prediction of both tides and surges, the two main components of total water level that cause coastal flooding. To improve the predictions of the tide we use a modified form of 'spectral nudging'. We show this leads to significant improvements in the prediction of the M_2 tide in the open ocean, and also in the shallow regions closer to shore where the model is not nudged. The median value of the vector difference of the tidal amplitude based on sea level observations and a data-assimilative model, and the predictions of our ocean model, is reduced from 11.2 cm to 2.66 cm by the nudging. The improvement deteriorates significantly however if additional tidal constituents are included in the model (most notably S_2). This is explained in terms of spectral leakage between tidal bands associated with the nudging methodology and a straightforward solution is proposed.
机译:为了开发沿海洪灾总体预报系统的长期目标,我们正在开发基于动态的全球海洋数值模型。该模型基于NEMO框架,在先前的研究中已用于预测全球潮汐和潮汐。这项研究的重点是优化潮汐和潮汐的联合预报,潮汐和潮汐是造成沿海洪水的总水位的两个主要组成部分。为了改进对潮汐的预测,我们使用了“频谱微调”的改进形式。我们表明,这将大大改善公海中M_2潮汐的预测,以及在未推升该模型的靠近海岸的浅水区。通过微调,基于海平面观测和数据同化模型以及我们的海洋模型的预测,潮汐振幅矢量差的中值从11.2 cm减小到2.66 cm。但是,如果模型中包含其他潮汐成分(最明显的是S_2),则改进效果会大大降低。这是根据潮汐带之间的频谱泄漏(与微调方法相关联)进行解释的,并提出了一种直接的解决方案。

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