面向中尺度涡提取的SLA去噪方法研究

噪声去除一直是基于卫星高度计资料的海洋中尺度涡提取研究的难点和热点,然而无论是卷积滤波器还是信息滤波器都存在对海面高度异常（SLA）数据的局部过处理现象。鉴于此,本文提出一种基于包络面去噪的海洋中尺度涡提取方法。该算法可利用分离层内的信息稳定性和层间的信息完备性,很好地改进了卷积运算没有考虑局部噪声的不足,进而有效地提高去噪能力。其具体流程为：首先,对初始化的原始数据场进行上下包络面构造,形成原始数据子场;然后,根据子场内部和子场间的稳健性,把原始数据场转换为子场集合;其次,利用子场极差和标准差,对子场集合进行信息重组,形成噪声去除后的信息场;最后,利用去噪后的信息场数据,采用Winding-Angle（WA）和泛克立金中尺度涡提取算法在西北太平洋进行对比验证实验。实验结果表明,本文提出的方法较前人的方法有较大的提升,准确率为91.23%,取得了较好的应用效果。

Denoising Algorithm of Sea Level Anomalies for Mesoscale Eddy Extraction

The noise removal of sea level anomaly (SLA) data set is crucial and important for extracting the mesoscale eddies. There are many filtering methods that have been developed for eliminating the noises in the sea level anomaly data set before extracting the mesoscale eddies. Nowadays, there are two mainstream approaches of noise removal, which are the convolution filtering and the information filtering. However, these filtering methods have some disadvantages that they could not recognize the right signal from the wrong signals. Therefore, some of the wrong or negligible signals are also taken into account by these noises removal methods. For solving this problem, an envelope surface-based denoising algorithm of sea level anomaly data is proposed before extracting the mesoscale eddies. The envelope surface-based denoising algorithm could improve the effect of noise removal by using the information stability and completeness in the separated layers. This algorithm overcomes the insufficiency of the convolution filtering method that it could not distinguish the wrong signal from the right ones. The detailed process of the envelope surface-based denoising algorithm includes three steps. First of all, the upper and lower envelope structures are used on the original data sets which have been initialized for extracting the subfields of sea level anomaly. Secondly, according to the robustness inside and among several subfields, the envelope surface-based denoising algorithm decomposes the original sea level anomaly fields into several subfields. The subfields could represent the information of the original sea level anomaly from different layers. Then the ranges and standard deviations of these subfields are adopted to recombine the information of several subfields set for shaping an information field after the noise removal. In the end, based on the information field after noise removal, the mesoscale eddies in the northwestern Pacific (22°N-50°N, 130°E-150°W) are extracted by applying the Winding-Angle (WA) algorithm. The results are compared with the mesoscale eddies extracted by the universal Kriging algorithm. From the results of this case study in the northwestern Pacific, we proved the veracity and efficiency of the envelope surface-based denoising algorithm. The veracity of the extracted mesoscale eddies could reach 91.23% in total. In contrary to the universal Kriging algorithm, the veracity of the extracted mesoscale eddies is greatly enhanced.