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Collaborating Authors
Results
Automatic Quality Check Method On In-Situ Data From the Coastal Ocean Monitoring Net Around Taiwan
Kao, Chia Chuen (Dept. of Hydraulic & Ocean Engineering, National Cheng Kung University) | Doong, Dong Jiing (Dept. of Hydraulic & Ocean Engineering, National Cheng Kung University) | Hsin Chuang, Laurence Zsu (Coastal Ocean Monitoring Center, National Cheng Kung University) | Lee, Beng Chun (Dept. of Environment Design, Huafan University)
ABSTRACT The Coastal Ocean Monitoring Center (COMC) was established to assist the government to develop and operate the hydrological monitoring network around Taiwan coast. Currently, the network consists of eight data buoys, one pile station, twelve coastal meteorological stations and seven tidal stations. Real time observation data are provided for coastal hazard warning system and coastal zone management applications. To assure the data correctness, a data quality-check (QC) program is developed to provide the systematical and timely examination on the measurements. This paper presents the automatic data quality check method for checking the wave statistical parameters. INTRODUCTION Taiwan Island locates in the subtropical region, where severe seas triggered by typhoons in summer seasons often result into terrible losses of the human life and property in the coastal areas. The Coastal Ocean Monitoring Center (COMC) was established within the National Cheng Kung University in 1997 to assist the government to develop and operate a hydrological monitoring network around Taiwan coast. Currently, the network consists of eight buoys stations, one pile station, twelve coastal meteorological stations and seven tidal stations. The location map of the stations is shown in Figure 1. The buoy station, a 2.5-meter wave-following discus buoy is deployed as shown in Figure 2. The buoy is equipped with a tri-axial accelerometer to measure surface wave particle movements for the estimation of directional wave spectrum. At shallow-water pile stations located in areas of mild slope and sandy seabed, an ultrasonic wave gauge array is installed to provide measurements of sea surface displacements. The in-situ meteorological and oceanographic observations from the network provide the government with critical information to prepare severe weather warnings. Long-term data from the network are used to calibrate and validate marine weather forecasting models and to develop design criteria for coastal structures.
- Government (0.88)
- Energy (0.68)
Wavelet Spectrum Extracted From Coastal Marine Radar Images
Doong, Dong Jiing (Department of Hydraulic and Ocean Engineering, National Cheng Kung University) | Wu, Li Chung (Department of Hydraulic and Ocean Engineering, National Cheng Kung University) | Kao, Chia Chuen (Department of Hydraulic and Ocean Engineering, National Cheng Kung University) | Hsin Chuang, Laurence Zsu (Coastal Ocean Monitoring Center, National Cheng Kung University)
ABSTRACT Ocean waves are extremely random and are directly and indirectly dependent on meteorological, hydrological, oceanographic and topographical factors. Field measurements must be performed to increase the knowledge of ocean waves. Remote sensing techniques have become quite popular for ocean wave measurement applications. Microwave RADAR that can provide all weather monitoring during day and night and is less affected by cloud and rain is now the most popular sensor of remote sensing techniques among others. The spectrum represents the distribution of wave energy. The wave parameters such as wave height, period, direction and wavelength are derived from wave spectrum. It is therefore important to derive the spectral information from remote sensing images. However, the nearshore images feature non-homogeneity. It is therefore the purpose of this study to develop a non-homogeneous image spectrum analysis method in order to extract the spectral information. This method is developed based on two-dimensional Wavelet transform which has space-frequency representation. The derived image spectrum is called the Wavelet Spectrum. This paper presents the derivation and validation of this method. INTRODUCTION Ocean wave information is required for various purposes, such as coastal engineering, environment protection, port operations, disaster prevention and rescue. Wave data are obtained from many methods, such as theoretic analysis, laboratory experiment, numerical simulation and field measurement. Because the ocean waves, which feature extremely random, are directly and indirectly dependent to meteorological, hydrological, oceanographic and topographical factors, they cannot be fully understood only by theoretical or numerical approaches. Field measurement must be performed to increase the knowledge of waves. Diverse ways of wave measurement have been investigated since last few decades. They may be categorized as in-situ measurements and remote sensing techniques. At present, various in-situ measurements have significantly developed and improved to better quality, however it is not easy to collect space information.