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As the chart datum of China, the lowest normal low water (LNLW) was calculated using three tidal constituents, major (Q1, O1, P1, K1, N2, M2, S2 and K2), shallow water (M4, MS4 and M6) and long-period tidal (Sa and Ssa). The construction of a tidal datum is mainly concerned with improvements in the major tidal constituents, and the contribution of the long-period tidal component has been generally neglected. In this study, long-term tide gauge observations and multi-mission satellite altimetry data were used to investigate the spatial distribution of the long-period tidal contribution in Chinese seas and analyze the relative long-period tidal contribution rate into four regions. The results showed that the mean contribution in Chinese seas is 7.63 %, with the largest contribution in the Bohai Sea (11.33 %) and smallest in the East China Sea (5.27 %). Differences between tide gauge and satellite-derived results were compared in detail. The Sa and M2 tidal amplitudes are the main factors affecting the long-period tidal contribution to the LNLW. The relative long-period tidal contribution can be up to 34.18 % when tide gauge observations record small M2 and large Sa amplitudes. These results indicate that the long-period tidal constituent cannot be neglected in the establishment of the LNLW datum. Therefore, to improve tidal datum precision, precise extraction and accuracy assessments of long-period tidal constituents should be a research focus. [ABSTRACT FROM AUTHOR]

In this study, to meet the need for the accurate prediction of sea level anomaly (SLA), a hybrid model is proposed. In this model, empirical mode decomposition is combined with singular spectrum analysis and least-squares extrapolation to predict satellite-derived SLA. Each intrinsic mode function series of an empirical mode decomposition is decomposed and reconstructed using singular spectrum analysis. The reconstructed components and the residual series are predicted using least-squares extrapolation. This hybrid model was used for satellite-derived SLAs that were obtained using multi-mission along-track satellite altimetry data from September 1992 to January 2018, and the prediction errors for 3 years lead times were analysed. The observations and predictions of the principal components for annual or interannual periods correlated well, and the proposed hybrid model effectively predicted the SLAs. For the 3 years lead time predictions, the mean absolute error and root-mean-square error were 1.03 and 1.32 cm, respectively, which were less than those reported for existing methods. [ABSTRACT FROM AUTHOR]