A Refined Method for Altimetry SSH Data Fusion to Enhance the Characterization of Kuroshio Extension: A Case Study

Abstract High-quality merged altimetry sea level products have been instrumental in analyzing oceanic dynamics, spanning global and regional sea level trends, and capturing interannual signals, but effectively characterizing mesoscale features remains a persistent issue. The essence of addressing this challenge lies in the selection of highly correlated data sources for fusion, within the confines of limited discrete observations from sea surface altimeters. To tackle this challenge, we propose a refined method focused on reducing the suboptimal interpolation window size and optimizing the mapping process, particularly emphasizing the enhancement of Kuroshio Extension (KE) characterization. By scrutinizing the spatial and temporal evolution of sea surface temperature (SST) fields, we have devised a modified strategy for selecting altimetry along-track data. This strategic approach facilitates the acquisition of more precise observations on a finer time scale, thereby circumventing the inclusion of altimetry observations with low correlation. To validate the efficacy of this approach, we performed a case study of sea surface height (SSH) data fusion in the KE region. As a result, the portrayal of KE intricacies, encompassing its axis and meandering, has markedly improved in the refined SSH gridded maps. A comparative analysis against drifter observations underscores the efficacy of the refined method. Velocity biases have been substantially reduced from −0.21 to 0.05 m s −1 , while the correlation coefficient has surged from 0.64 to 0.90. Concurrently, the root-mean-square error has plummeted from 0.42 to 0.21 m s −1 . These improvements signify significant strides toward more accurate and reliable characterizations of oceanic mesoscale features, particularly evident in the nuanced depiction of the KE. Significance Statement Accurately characterizing the mesoscale dynamical features of gridded sea surface height (SSH) products remains a significant challenge in oceanographic research. Previous studies have often employed a fixed configuration of critical mapping parameters, limiting the reduction of reconstruction errors. In this study, we address this challenge by proposing a refined method aimed at enhancing the characterization of mesoscale features. Our approach involves modifying the expression of the space–time correlation function and adjusting the size of the suboptimal interpolation window. We achieve this by carefully analyzing the spatial and temporal evolution of sea surface temperature (SST) fields. Through this refined methodology, we aim to improve the portrayal of details within the Kuroshio Extension (KE) region. A comparative analysis against drifter trajectories highlights the substantial benefits of our refined approach. The refined SSH map more accurately captures the interaction between mesoscale eddies and the KE, leading to a more comprehensive depiction of oceanic dynamics in this critical region.