Solving Harmonic Sea-Level Model with Kalman Filter: A Macau Case Study

In this study, sea-level predictions based on harmonic tidal models with their parameters estimated by the Kalman filter algorithm are tested for Macau. It is shown that Kalman filter is able to solve harmonic sea-level models from short observation record once they are put in the state-space form. Current case study indicates that harmonic models with four to five dominant tidal constituents may give the best prediction performance in Macau giving that their harmonic parameters are estimated by Kalman filter with as little as four to twenty days record. These encouraging results indicate that Kalman filter is a strong contender for solving harmonic tidal forecaster in Macau as well as other places in the world with limited monitoring data.