Calibration Experiments of CFOSAT Wavelength in the Southern South China Sea by Artificial Neural Networks

Abstract

The wave data measured by CFOSAT (China France Oceanography Satellite) have been validated mainly based on numerical model outputs and altimetry products on a global scale. It is still necessary to further calibrate the data for specific regions, e.g., the southern South China Sea. This study analyses the practicability of calibrating the dominant wavelength by using artificial neural networks and mean impact value analysis based on two sets of buoy data with a 2-year observation period and contemporaneous ERA5 reanalysis data. The artificial neural network modeling experiments are repeated 1000 times randomly by Monte Carlo methods to avoid sampling uncertainty. Both experimental results based on the random sampling method and chronological sampling method are performed. Independent buoy observations are used to validate the calibration model. The results show that although there are obvious differences between the CFOSAT wavelength data and the field observations, the parameters observed by the satellite itself can effectively calibrate the data. In addition to the wavelength, nadir significant wave height, nadir wind speed, and the distance between the calibration point and satellite observation point are the most important parameters for the calibration. Accurate data from other sources, such as ERA5, would be helpful to further improve the calibration results. The variable contributing the most to the calibration effect is the mean wave period, which virtually provides relatively accurate wavelength information for the calibration network. These results verify the possibility of synchronous self-calibration for the CFOSAT wavelength data and provide a reference for the further calibration of the satellite products in other regions.

Evaluation of CFOSAT Wave Height Data with In Situ Observations in the South China Sea

“…They suggested the SWHn shows a smaller error in the wave height within 2-3 m. Especially for the relatively open sea areas where the WS, NS1, and NS2 sites are located, when SWH is larger than 2 m, the relative error of the SWH data of CFOSAT, whether SWHs or SWHn, is lower than that when SWH is less than 2 m (Figure 5). It has also been shown by previous studies that the accuracy of remote sensing wave observation is generally better in high sea states than that in low sea states, which is due to the higher homogeneity of wave propagation compared to high sea states [7]. The analysis results in this paper are consistent with the existing results.…”

“…The products of SWIM spectra in its early version of data were quite noisy. Therefore, many authors have made great efforts to improve the quality of wave data [3][4][5][6][7][8]. For example, Wang et al [5] developed a method for retrieving the SWH over an extended swath based on the synchronous observations of SWIM and the scatterometer onboard CFOSAT, and achieved significantly increased spatial coverage and promising accuracy.…”

“…Due to the relatively low swell energy proportion in the SCS, the performance of the CFOSAT wave data may not be as good as that from open oceans. For example, previous studies have shown that there may be obvious errors in the wavelength data derived from the initial products of CFOSAT under certain sea conditions in the local regions of the southern SCS [7]. By comparing the data of southern deep regions and northern coasts of the SCS, it is further found that the bias of data in shallow water areas is significantly higher than that in deep waters, and it is necessary to eliminate the data with large errors for shallow water area [20].…”

Statistical Comparison of Ocean Wave Directional Spectra Derived From SWIM/CFOSAT Satellite Observations and From Buoy Observations

“…More recently, [7], find from a combined analysis of wave partitions from SWIM and buoys that the rms difference in the spectral peaks between both sources of information are of 0.9 s for the peak period and 20° for the direction. However, [8] in a study limited to the South China Sea find important biases on the peak wavelength from SWIM compared to buoy measurements in low sea state conditions.…”

Meteo-Climatic Conditions of Wind and Wave in the Perspective of Joint Energy Exploitation: Case Study of Dongluo Island, Hainan

“…Westward swells induced by the gales that occur in the northeast of the South China Sea result in the variations in Hs in the study area. Furthermore, the topography of the island may also affect the relationship between local wind and waves [15,24].…”