The satellite-derived aerosol optical depth (AOD) data is used to investigate the distribution of aerosol over the South China Sea (SCS). High correlation coefficients are found between in situ AERONET data and satellite AOD measurements around the SCS with the highest coefficient of 0.9 on the Dongsha Island (i.e., Pratas Island). The empirical orthogonal function (EOF) analysis of AOD over the SCS shows that high AOD is always found around offshore areas of China, Indochina, Sumatra, and Borneo. Besides, spring is the major season of occurring coarse aerosol particles (AOT_C) but fine aerosol particles (AOT_F) occur yearly. The biomass burning is found in Indochina during March and April, and so it is in Sumatra and Borneo from August to October. The results also show that the AOT_F are higher during El Niño events, but higher AOT_C are found in La Niña years.

Satellite remote sensing sea surface temperature (SST) data are lost due to cloud cover. Missing data often cause inconvenience in subsequent applications and thus need to be reconstructed. In this study, the Data Interpolating Empirical Orthogonal Function (DINEOF) method was used to reconstruct the hourly SST data missing from the Himawari-8 satellite in the waters near Taiwan. The SST characteristics in the waters around Taiwan are quite complex, with high SST at Kuroshio in the east of Taiwan and great variation in the SST west of Taiwan due to the influence of tides. Therefore, the analysis with DINEOF was conducted using 25-h data to match the tidal cycle. The influence of SST characteristics on the accuracy of SST reconstruction is also discussed. The results show that in the western sea area where the variation of SST is large, the average root-mean-square error of SST between the original SST and the reconstructed SST is the lowest and the average coefficient of determination is the highest. The accuracy of the reconstructed SST is positively correlated with the SST variation. Furthermore, the statistical results also show that the DINEOF method can effectively reconstruct the SST regardless of the missing data rate.

The present work employs a three-dimensional ocean model (MITgcm) driven by tidal and climatological forcings to assess the range of impacts of thermal wastewater discharge from the Third Nuclear Power Plant (NP_No.3) in Nan Wan Bay on the local ecosystem. Tides and daily wind forcings are incorporated into the MITgcm to examine their effects on thermal plume dispersion and water circulation in Nan Wan Bay. The model results reveal that the thermal plume is most likely to disperse to the southwest in the summer; it is unlikely to drift to the southeast or northeast because of the presence of the gentle southwesterly monsoon. In the winter, the thermal plume is most likely to be directed to the southwest and is unlikely to be directed to the northeast or southeast because of the prevailing northeasterly monsoon. Additionally, it is worth emphasizing that strong tidal currents generate a pair of counter-rotating eddies that significantly influence the dispersion of the thermal plume. However, seasonal monsoons also play an essential role in modifying the thermal plume’s direction and dispersion.

In order to assess the range of impact of thermal wastewater discharge from the third Nuclear Power Plant (NP_No.3) on the local ecosystem, a three-dimensional ocean model (MITgcm) driven by tidal and climatological forcings is employed to study the present work. Tides and daily wind forcings are incorporated into the MITgcm model to examine their effects on the thermal plume and the water circulation in Nan Wan Bay. The model results reveal that the thermal plume is most likely to disperse to the southwest in summer; it is unlikely to drift to the southeast or northeast because of the presence of gentle southwesterly monsoon. In winter, the thermal plume is most likely to be directed to the southwest but barely visible in the northeast or southeast directions because of prevailing northeasterly monsoon. Additionally, it is worth emphasizing that strong tidal currents generate a pair of counter-rotating eddies that significantly dominate the dispersal of the thermal plume. However, seasonal monsoons also play an essential role in modifying the plume’s direction and dispersion. The model results reveal that the flow field and thermal plume agree well with observational data.

Internal waves have been observed by lots of high resolution satellite images, such as Synthetic Aperture Radar (SAR) and optical images of SPOT and Landsat. These images are usually expensive. In this study, some free but lower spatial resolution satellite images are applied to observe the internal wave phenomena. The internal waves in the Sulu Sea are detected from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) onboard the Orbview-2 satellite. The SeaWiFS image has a spatial resolution of 1.1 km. It is acceptable to observe the internal wave phenomena while the soliton width is larger than the image resolution. The results show that the internal solitary in the Sulu Sea can be observed successfully with SeaWiFS chlorophyll images. The internal waves in the Sulu Sea have amplitudes of 10 to 90 m and wavelengths of 5 to 16 km. The large-amplitude internal solitary waves may significantly influence the near-surface chlorophyll concentration. The chlorophyll concentration would be lower when the depression internal waves passed through. A theoretic model is proposed and tested to estimate the amplitudes of internal waves from chlorophyll concentration images.