With the development of satellite observation technology, higher resolution and shorter return cycle have also placed higher demands on satellite data processing. The non-tide high-frequency barotropic oscillation in the marginal sea produces large aliasing errors in satellite altimeter observations. In previous studies, the satellite altimeter aliasing correction generally relied on a few bottom pressure data or the model data. Here, we employed the high-frequency tide gauge data to extract the altimeter non-tide aliasing correction in the west Mediterranean Sea. The spatial average method and EOF analysis method were adopted to track the high-frequency oscillation signals from 15 tide gauge records (TGs), and then were used to correct the aliasing errors in the Jason-1 and Envisat observations. The results showed that the EOF analysis method is better than the spatial average method in the altimeter data correction. After EOF correction, 90% of correlation (COR) between TG and sea level of Jason-1 has increased ~5%, and ~3% increase for the Envisat sea level; for the spatial average correction method, only ~70% of Jason-1 and Envisat data at the TGs location has about 2% increase in correlation. The EOF correction reduced the average percentage of error variance (PEL) by ~30%, while the spatial average correction increased the average percentage of PEL by ~20%. After correction by the EOF method, the altimeter observations are more consistent with the distribution of strong currents and eddies in the west Mediterranean Sea. The results prove that the proposed EOF method is more effective and accurate for the non-tide aliasing correction.

中文翻译：

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地中海大型高频正压信号去混叠的新方法

随着卫星观测技术的发展，更高的分辨率和更短的返回周期也对卫星数据处理提出了更高的要求。边缘海中的非潮汐高频正压振荡在卫星高度计观测中产生较大的混叠误差。在先前的研究中，卫星高度计混叠校正通常依赖于一些底部压力数据或模型数据。在这里，我们使用了高频潮汐仪数据来提取西地中海的高度计非潮汐混叠校正。采用空间平均法和EOF分析法对15个潮汐记录记录（TGs）的高频振荡信号进行跟踪，然后对Jason-1和Envisat观测值中的混叠误差进行校正。结果表明，在高度计数据校正中，EOF分析方法优于空间平均方法。经过EOF校正后，TG与Jason-1海平面之间的相关性（COR）的90％增加了约5％，Envisat海平面增加了约3％。对于空间平均校正方法，TG位置处只有〜70％的Jason-1和Envisat数据的相关性增加了约2％。EOF校正使平均误差百分比（PEL）降低了约30％，而空间平均校正使PEL的平均百分比提高了约20％。经EOF方法校正后，高度计观测结果与西地中海强流和涡流的分布更加一致。结果表明，所提出的EOF方法对于非潮汐混叠校正更为有效和准确。