A combined denoising method of empirical mode decomposition and singular spectrum analysis applied to Jason altimeter waveforms: A case of the Caspian Sea

During the satellite pulse propagation and reception, the altimeter waveform is inevitably affected by noise. To reduce the noise level in Jason altimeter waveforms, we used singular spectrum analysis(SSA),empirical mode decomposition(EMD), and the combination of SSA and EMD to obtain the denoised waveforms. The advantages of the combined method were verified and the accuracy of the mean sea surface height(MSSH) model was improved. Comparing the denoising effect of the three methods, the results show that the signal-to-noise ratio(SNR), correlation coefficient and root-mean-square error are effectively improved by the combination of SSA and EMD. The sea surface heights(SSHs) were remeasured with a 50% threshold retracker of denoised waveforms, and the MSSH model of the Caspian Sea with a grid of 1’× 1’was established from the retracked SSHs of Jason-1/2/3. Taking the mean value of the four models as a control, it is found that the model calculated by the combined denoising method has the highest accuracy. This indicates that using the combined denoising method to reduce the noise level is beneficial to improve the accuracy of the MSSH model.

A multi-subwaveform parametric retracker of the radar satellite altimetric waveform and recovery of gravity anomalies over coastal oceans

The quality of satellite radar altimetric data is very important in studies of geodesy,geophysics,and oceanography.Over coastal oceans,altimeter waveforms are contaminated by the terrain and physical environments so that the accuracy of altimeter data is lower than that over open oceans.Here we develop a new multi-subwaveform parametric retracker(MSPR) to improve the quality of altimeter data for the recovery of gravity anomaly in coastal oceans.The least squares collocation method is used to recover the residual gravity anomaly over the coastal water from altimetric data.The waveform data records from Geosat/GM around Taiwan Island are practically retracked with MSPR.When compared with the Taiwan geoid height,the results retracked by MSPR are more accurate than those retracked by the well-known β-5-parmeter method and from the geophysical data records(GDRs).The gravity anomalies over Taiwan coastal waters are calculated from the retracked altimeter data with the least squares collocation.When we compared gravity anomalies computed using altimeter GDRs with the ship-borne gravity data over Taiwan coastal ocean,we found that the results from retracked data are more accurate than those from GDRs.

Improving Gravity Anomalies Over China Marginal Sea from Retracked Geosat and ERS-1 Data

The quality of altimeter data and ocean tide model is critical to the recovery of coastal gravity anomalies. In this contribution, three retracking methods (threshold, improved threshold and Beta-5) are investigated with the aim of improving the altimeter data over a shallow water area. Comparison indicates that the improved threshold is the best retracking method over China Sea. Two ocean tide models, NAO99b and CSR4.0, are analyzed. Results show that different tide models used in the processing of altimeter data may result in differences more than 10 mGal in recovered coastal gravity anomalies. Also, NAO99b is more suitable than CSR4.0 over the shallow water area of China Sea. Finally, gravity anomalies over China Sea are calculated from retracked Geosat/GM and ERS-1/GM data by least squares collocation. Comparison with shipborne gravimetry data demonstrates that gravity anomalies from retracked data are significantly superior to those from non-retracked data. Our results have the same order as the other two altimeter-derived gravity models: Sandwell&Smith(V16) and DNSC08.