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Sea surface temperature (SST) is an important parameter used to describe the air-sea interaction and the state of marine structures. Atmospheric water vapor has a significant attenuation effect on thermal infrared information, which will reduce the accuracy of SST inversion. However, the effect of atmospheric water vapor on the inversion accuracy is not considered carefully in the existing SST inversion algorithm. In this study, a new method is proposed for retrieving SST from Landsat 8 Thermal Infrared Remote Sensing (TIRS) data based on the variation of atmospheric water vapor content (wvc). First, simulating atmospheric conditions by using moderate resolution atmospheric transmission (MODTRAN) based on atmospheric profiles data (air temperature and pressure). Second, calculating the bright temperature based on the radiation transfer equation and Planck's law. Then, constructing the SST retrieval model of thermal infrared remote sensing based on wvc. Finally, evaluating the accuracy of the proposed model by using simulation data. The root mean square errors (RMSEs) are within 0.5 K, indicating that the accuracy of the model is good in theory. In addition, taking the Zhoushan sea area as the research area, SST is retrieved by Landsat 8 TIRS data. The accuracy of inversion results is evaluated by advanced very high-resolution radiometer (AVHRR) SST products. The bias and RMSE based on the AVHRR SST products are within 1 K and 2 K, respectively. The results show that the accurate SST with high spatial resolution was successfully obtained by using the method. The study is of great significance to the acquisition of marine structural parameters, the exploitation of marine resources, and the monitoring of marine disasters.

As an important fishery in China, the changes of SSH have seriously affected the development of Zhoushan. The spatio-temporal pattern evolution of sea surface height (SSH) and response of SSH and El-Nino in Zhoushan sea area are analyzed in this paper. The results are as follows: (1) SSH trends to decrease gradually from south to north, generally distributes between 0.2-0.4 m; (2) From 1995 to 2016, SSH shows a downward trend at a rate of 0.14 cm per year; (3) The impact of El-Nino event on SSH in Zhoushan sea area is mainly performed as follows: decreased in the generation stage, increased in the development stage and decreased in the decay stage.

As an important fishery in China, the changes of marine hydrological elements have seriously affected the development of Zhoushan. The spatio-temporal pattern evolution of marine hydrological elements and the response of marine hydrological elements and El-Nino in Zhoushan sea area are analyzed in this paper. The results are as follows: (1) Marine hydrological elements have obviously seasonal variation and spatial distribution; (2) In 1995-2016, sea surface salinity (SSS) and sea surface temperature (SST) have a yearly upward trend, chlorophyll concentration (Chl) has a yearly downward trend; (3) The response of marine hydrological elements at different El-Nino stages shows a difference.

Since the launch of landsat8, high-quality surface observation data have been acquired. But the corresponding sea surface temperature (SST) products have not been seen. Moreover, the existing SST inversion algorithm do not carefully consider the effect of water vapor on the accuracy. In this study, a new method is proposed for the retrieve of SST from Landsat 8 Thermal Infrared Remote Sensing (TIRS) data based on the variation of atmospheric water vapor content. The steps are briefly described as follows: 1) constructing the SST retrieval model of thermal infrared remote sensing by using the radiation transfer equation with atmospheric profile data (air temperature and pressure); 2) retrieving SST of Zhoushan sea area, China from Landsat 8 TIRS Data; 3) evaluating the accuracy of proposed model by simulation data and AVHRR SST product. The bias and RMSE based on the simulation data are within 0.4 K. The bias and RMSE based on AVHRR SST product are 1.6063 K and 1.8507 K, respectively. The results show that the accurate SST with high spatial resolution could be obtained by using the method.

The study of the variation and development trend of regional oceanographic parameters is of great significance to the prevention and mitigation of disasters, the development and utilization of oceans, the guidance of human activities at sea, and the monitoring of the El Nino phenomenon. As an important fishery in China, the changes in oceanographic parameters have severely affected the development of the Zhoushan Islands. The spatial–temporal pattern evolution of oceanographic parameters and the response of oceanographic parameters and El Nino in the Zhoushan sea area are analyzed in this study. The remote sensing datasets of sea surface salinity (SSS), sea surface temperature (SST), sea surface height (SSH), and chlorophyll concentration (Chl) in the Zhoushan sea area were collected and averaged spatially, temporally, and yearly, in order to analyze the variability monthly and yearly, and during El Nino. The results are as follows: (1) SSS is smallest near the shore and increases with distance offshore; SST has obvious seasonal variation; the maximum variation of SSH occurred in the coastal area; and a high-value zone of Chl arises during spring and summer. (2) In the recent twenty years, SSS increased at a rate of 0.1241 PSU per year. SST, SSH, and Chl decrease at 0.0294 °C per year, 0.14 cm per year, and 0.0853 mg/m3 per year, respectively. (3) Different types of El Ninos have different effects on oceanographic parameters.