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Interannual variability of cyclones that are generated over the eastern Asian continent and passed over the Yellow, Bohai, and East China seas (YBE cyclones) in spring is analyzed using reanalysis datasets for the period of 1979–2017. Possible causes for the variability are also discussed. Results show that the number of YBE cyclones exhibits significant interannual variability with a period of 4–5 years. Developing cyclones are further classified into two types: rapidly developing cyclones and slowly developing cyclones. The number of rapidly developing cyclones is highly related to the underlying sea surface temperature (SST) anomalies (SSTA) and the atmospheric baroclinicity from Lake Baikal to the Japan Sea. The number of slowly developing cyclones, however, is mainly affected by the North Atlantic Oscillation (NAO) in the preceding winter (DJF); it works through the upper-level jet stream over Japan and the memory of ocean responses to the atmosphere. Positive NAO phase in winter is associated with the meridional tripole pattern of SSTA in the North Atlantic Ocean, which persists from winter to the following spring (MAM) due to the thermal inertia of the ocean. The SSTA in the critical mid-latitude Atlantic region in turn act to affect the overlying atmosphere via sensible and latent heat fluxes, leading to an increased frequency of slowly developing cyclones via exciting an anomalous eastward-propagating Rossby wave train. These results are confirmed by several numerical simulations using an atmospheric general circulation model. [ABSTRACT FROM AUTHOR]

Using hourly sea level data from four tide gauges, the changes of the extreme sea level in the Bohai Sea were analyzed in this work. Three components (i.e., mean sea level, tide and surge) as well as the tide–surge interaction were studied to find which component was important in the changes of extreme sea levels. Significant increasing trends exist in the mean sea level at four tide gauges from 1980 to 2016, and the increase rate ranges from 0.2 to 0.5 cm/year. The mean high tide levels show positive trends at four tide gauges, and the increasing rate (0.1 to 0.3 cm/year) is not small compared with the long-term trends of the mean sea levels. However, the mean tidal ranges show negative trends at Longkou, Qinhuangdao and Tanggu, with the rate from about −0.7 to −0.2 cm/year. At Qinhuangdao and Tanggu, the annual surge intensity shows explicit long-term decreasing trend. At all four tide gauges, the storm surge intensity shows distinct inter-annual variability and decadal variability. All four tide gauges show significant tide–surge interaction, the characteristics of the tide–surge interaction differ due to their locations, and no clear long-term change was found. Convincing evidence implies that the extreme sea levels increase during the past decades from 1980 to 2016 at all tide gauges, with the increasing rate differing at different percentile levels. The extreme sea level changes in the Bohai Sea are highly affected by the changes of mean sea level and high tide level, especially the latter. The surge variation contributes to the changes of extreme sea level at locations where the tide–surge interaction is relatively weak. [ABSTRACT FROM AUTHOR]

The coastline detection is one of the main applications of the Gaofen-3 satellite in the ocean field. However, the capability of Gaofen-3 SAR image in coastline detection has not yet been validated. In this paper, two Gaofen-3 SAR images, acquired in 2016, were used to extract the coastlines of the regions of Bohai and Taihu in China, respectively. The classical Fuzzy C-means (FCM) method was used in the coastline detection, but had been improved by combining the Wavelet decomposition algorithm to better suppress the inherent speckle noises of SAR image. Coastline detection results obtained from two Sentinel-1 SAR images acquired on the same regions were compared with those of the Gaofen-3 images. By using the manually delineated coastlines as the standards in the qualitative evaluations, improvements of about 12.0%, 8.3%, 23.8%, and 9.4% can be achieved by the improved FCM method with respect to the indicators of mean, RMSE, PGSD, and P90%, respectively; demonstrating that the Gaofen-3 data is superior to the Sentinel-1 data in the detection of coastline. [ABSTRACT FROM AUTHOR]