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The oceanic front is a narrow zone in which water properties change abruptly within a short distance. The sea surface temperature (SST) front is an important type of oceanic front, which plays a significant role in many fields including fisheries, the military, and industry. Satellite-derived SST images have been used widely for front detection, although these data are susceptible to influence by many objective factors such as clouds, which can cause missing data and a reduction in front detection accuracy. However, front detection in a single SST image cannot fully reflect its temporal variability and therefore, the long-term mean frequency of occurrence of SST fronts and their gradients are often used to analyze the variations of fronts over time. In this paper, an SST front composite algorithm is proposed that exploits the frontal average gradient and frequency more effectively. Through experiments based on MODIS Terra and Aqua data, we verified that fronts could be distinguished better by using the proposed algorithm. Additionally through its use, we analyzed the monthly variations of fronts in the Bohai, Yellow, and East China Seas, based on Terra data from 2000 to 2013.

In this paper, we introduced parameterizations of the salinity effects (on heat capacity, thermal conductivity, freezing point and saturated vapor pressure) in a lake scheme integrated in the Weather Research and Forecasting model coupled with the Community Land Model (WRF-CLM). This was done to improve temperature simulation over and in a saline lake and to test the contributions of salinity effects on various water properties via sensitivity experiments. The modified lake scheme consists of the lake module in the CLM model, which is the land component of the WRF-CLM model. The Great Salt Lake (GSL) in the USA was selected as the study area. The simulation was performed from September 3, 2001 to September 30, 2002. Our results show that the modified WRF-CLM model that includes the lake scheme considering salinity effects can reasonably simulate temperature over and in the GSL. This model had much greater accuracy than neglecting salinity effects, particularly in a very cold event when that effect alters the freezing point. The salinity effect on saturated vapor pressure can reduce latent heat flux over the lake and make it slightly warmer. The salinity effect on heat capacity can also make lake temperature prone to changes. However, the salinity effect on thermal conductivity was found insignificant in our simulations.