  Satellite altimetry, which measures water level with global coverage and high
resolution, provides an unprecedented opportunity for a wide and refined
understanding of the changing tides in the coastal area, but the sampling
frequency is too low to satisfy the Nyquist frequency requirement and too few
data points per year are available to recognize a sufficient number of tidal
constituents to capture the trend of tidal changes on a yearly basis. To
address these issues, a novel Regularized Least-Square approach is developed to
relax the limitation to the range of satellite operating conditions. In this
method, the prior information of the regional tidal amplitudes is used to
support a least square analysis to obtain the amplitudes and phases of the
tidal constituents for water elevation time series of different lengths and
time intervals. Synthetic data experiments performed in Delaware Bay and
Galveston Bay showed that the proposed method can determine the tidal
amplitudes with high accuracy and the sampling interval can be extended to the
application level of major altimetry satellites. The proposed algorithm was
further validated using the data of the altimetry mission, Jason-3, to show its
applicability to irregular and noisy data. The new method could help identify
the changing tides with sea-level rise and anthropogenic activities in coastal
areas, informing coastal flooding risk assessment and ecosystem health
analysis.
