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The harmonic analysis method based on high and low water levels is discussed in this paper. In order to make full use of the information of high and low water observations (the time derivative of water level at the observation time is zero), the weight coefficient, w, is introduced to control the importance of the part related to this information in the error formula. The major diurnal constituents, O 1 and K 1, and semi diurnal constituents, N 2, M 2 and S 2 are selected directly from the monthly data analysis, and some other important constituents, P 1, ν 2 and K 2, are included as the inferred constituents. The obtained harmonic constants of the major constituents are very close to those obtained from the analysis of hourly data, and this shows that high and low water data can be used to extract tidal constants with high accuracy. The analysis result also shows that the inference and the weighting coefficient are important in the high and low water data analysis, and it is suggested that w ≥1 should be taken in monthly high and low water data analysis. This analysis method can be used directly to analyze altimetric data with w =0.
The harmonic analysis method based on high and low water levels is discussed in this paper. In order to make full use of the information of high and low water observations (the time derivative of water level at the observation time is zero), the weight coefficient , w, is introduced to control the importance of the part related to this information in the error formula. The major diurnal constituents, O 1 and K 1, and semi diurnal constituents, N 2, M 2 and S 2 are selected directly from the monthly data analysis, and some other important constituents, P 1, ν 2 and K 2, are included as the inferred constituents. The obtained harmonic constants of the major constituents are very close to those obtained from the analysis of hourly data, and this shows that high and low water data can be used to extract tidal constants with high accuracy. The analysis result also shows that the inference and the weighting coefficient are important in the high and low water data analysis, and i t is suggested that w ≥1 should be taken in monthly high and low water data analysis. This analysis method can be used directly to analyze altimetric data with w = 0.