Abstract
With improved altimeter data near the coast, it is possible to use them in analysis of coastal sea level trends. In this study, we assess the sea level trends over January 2002-April 2022 with the SCMR-reprocessed altimeter dataset in the coastal zone of the northern South China Sea (SCS). The reliability of this dataset is confirmed by the inter-comparison with the CMEMS (Copernicus Marine Environment Monitoring Service) Level-3 along-track data product and the ESA CCI (European Space Agency Climate Change Initiative) v2.2 virtual station product, along with the validation against tide gauge records. Compared to two altimeter products, the SCMR has a higher number of data points for the analysis of sea level trends in the study region (28439 vs 1408 for CMEMS and 868 for ESA CCI). The monthly SLA time series from the SCMR dataset are more consistent with those from tide gauge records in terms of higher correlation coefficients (0.37–0.83) and lower root mean square of the differences (RMSD, 33.98–92.19 mm) between altimeter and tide gauge. The along-track sea level trends within the 0–20 km coastal strip range between 2–5 mm yr−1, and the degradation of sea level trends occurs when the along-track trends show significant fluctuations at the spatial scales of ∼ 300 m. Therefore, a further data editing strategy is recommended in this regard. We also find that the ENSO-related signals mainly impact on sea levels in the west of Luzon Strait and of the Philippine coast, but are dampened along the Chinese coast over 2002–2022. The regional mean sea level trend is reduced from 3.54 ± 0.85 mm yr−1 to 3.00 ± 0.84 mm yr−1 after removing the ENSO-related low-frequency variability. Finally, the variation of sea level trends from offshore oceans to coasts is found to be nonlinear, indicating the complexity of sea level changes in the study area. The blending of tide gauge records and the SCMR dataset has been successfully conducted in four tide gauges over a longer period of January 1993-April 2022, which would contribute to the analysis of long-term sea level trends at the local scales.
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