Denoising Effect of Jason-1 Altimeter Waveforms with Singular Spectrum Analysis: A Case Study of Modelling Mean Sea Surface Height over South China Sea

Abstract

Altimeter waveforms are usually contaminated due to nonmarine surfaces or inhomogeneous sea state conditions. The present work aimed to present how the singular spectrum analysis (SSA) can be used to reduce the noise level in Jason-1 altimeter waveforms to obtain SSA-denoised waveforms, improving the accuracy of a mean sea surface height (MSSH) model. Comparing the retracked sea surface heights (SSHs) by a 50% threshold retracker for the SSA-denoised waveforms with those for the raw waveforms, the results indicated that SSA allowed a noise reduction on Jason-1 waveforms, improving the accuracy of retracked SSHs. The MSSH model (called Model 1) over the South China Sea with a grid of 2′ × 2′ was established from the retracked SSHs of Jason-1 by the 50% threshold retracker for the SSA-denoised waveforms. Comparing Model 1 and Model 2 (established from the retracked SSHs by the 50% threshold retracker for the raw waveforms) with the CLS15 and DTU18 models in the South China Sea, it was found that the accuracy of Model 1 was higher than that of Model 2, which indicates that using SSA to reduce noise level in Jason-1 waveforms can effectively improve the accuracy of the MSSH model.

Keywords

• singular spectrum analysis
• altimeter waveform
• Json-1
• mean sea surface height
• threshold retracker
• waveform retracking