The accuracy of sea surface parameters retrieved from altimeter missions is predominantly governed by the choice of the so-called “retracking” algorithm, i.e., the model and inversion method implemented to obtain the surface parameters from the backscattered waveform. For continuity reasons, the choice of space agencies is usually to apply the same retracker from one satellite mission to the other to ensure long-time homogeneous series. In this article, taking the opportunity of a new configuration of the nadir pointing measurements onboard the recently launched China France Oceanography Satellite (CFOSAT) with the Surface Waves Investigation and Monitoring (SWIM) instrument (Hauser et al., 2020), the retracking method was upgraded, by implementing a novel algorithm, called “Adaptive” retracker. It combines the improvements brought by Poisson et al., (2018) for the estimation of surface parameters from peaked waveforms over sea ice, improvements in the way the instrumental characteristics are considered in the model (mispointing, point target response) and a more accurate consideration of speckle statistics. In this article, we first show from simulations carried out in the instrumental configuration of SWIM that the Adaptive algorithm has better accuracy and performance than the classical MLE4 algorithm. Then, the geophysical parameters obtained with real data from SWIM are analyzed with comparisons to reference data sets (model and products from altimeters). We show that this new algorithm has several benefits with respect to the classical MLE4 method: no need of lookup tables to correct biases, significant noise reduction on all geophysical variables especially the significant wave height, and performance of inversion over a large set of echo shapes, resulting from standard oceanic scenes as well as highly specular conditions such as over bloom or sea ice.

中文翻译：

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自适应算法用于重新跟踪高度计天底回波的优势：模拟和 CFOSAT/SWIM 观测结果

从高度计任务中获取的海面参数的准确性主要取决于所谓的“重新跟踪”算法的选择，即为从反向散射波形中获取海面参数而实施的模型和反演方法。出于连续性原因，航天机构的选择通常是从一个卫星任务到另一个卫星任务应用相同的重新跟踪器，以确保长时间的同质系列。在本文中，利用最近发射的中法海洋卫星 (CFOSAT) 和表面波调查和监测 (SWIM) 仪器 (Hauseret al., 2020)，通过实施一种称为“自适应”重新跟踪器的新算法，重新跟踪方法得到了升级。它结合了 Poisson 带来的改进et al., (2018) 用于从海冰上的峰值波形估计表面参数，改进模型中考虑仪器特性的方式（错误指向、点目标响应）以及更准确地考虑散斑统计。在本文中，我们首先通过在 SWIM 仪器配置中进行的模拟表明自适应算法比经典的 MLE4 算法具有更好的准确性和性能。然后，通过与参考数据集（高度计的模型和产品）进行比较，分析从 SWIM 获得的实际数据获得的地球物理参数。我们展示了这种新算法相对于经典的 MLE4 方法有几个好处：不需要查找表来纠正偏差，