:: Volume 7, Issue 1 (5-2019) ::
jgit 2019, 7(1): 211-224 Back to browse issues page
Tidal prediction using time series analysis of Buoy observations
Saeed Farzaneh *, Mohammad Ali Sharifi, Kamal Parvazi, Bahare Namazi
University of Tehran
Abstract:   (2061 Views)
Although tidal observations which are extracted from coastal tide gages, have higher accuracy due to their higher sampling rate, installing these types of gages can impose some spatial limitation since we cannot use every part of sea to install them. To solve this limitation, we can employ satellite altimetry observations. However, satellite altimetry observations have lower sampling rate. According to spatial limitation in installing tide gages and lower rate of satellite altimetry observations, we need observation as along with gathered information which can solve those two main margins. Buoy observations not only for its higher accuracy and sampling rate, but also because of its exclusive features can let us observe further coastal regions to record sea level observations. In this study, buoy observations are analyzed using Least Square Harmonic Estimation (LS-HE) method. According to this, important frequencies in those data can be extracted. This process is equally important in Tidal modeling as well as prediction. Tidal modeling and prediction are based on frequency which is derived from observations. In this contribution, time-series data of 57 buoy stations from 2005 to 2017 are processed and a list of important frequencies is prepared. In the following, the comparison between tidal prediction modeling extracted from buoy and tide gage observation was made by using this frequency list. Tide prediction of all the stations during a month was made according to important frequency list extracted in this study. The average RMSE for predicted data in buoy stations has been about 6 cm. Finally, to validate buoy’s data, comparison between buoy and tide gage data was made which represents about 9 cm difference in sea level prediction.
Keywords: Buoy observations, Time series analysis, Least square harmonic estimation, Tidal frequency, Tidal Prediction.
Full-Text [PDF 2354 kb]   (602 Downloads)    
Type of Study: Research | Subject: Geodesy
Received: 2018/01/27 | Accepted: 2018/09/1 | Published: 2019/06/21

XML   Persian Abstract   Print

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 7, Issue 1 (5-2019) Back to browse issues page