Sea ice can attenuate wave energy significantly when waves propagate through ice covers.In this study,a third-generation wave model called simulating wave nearshore(SWAN)was advanced to include damping of wave energy due to friction in the boundary layer below the ice.With the addition of an eddy viscosity wave-ice model,the resulting new SWAN model was applied to simulate wave height in the Bohai Sea during the freezing winter.Its performance was validated with available buoy data near the ice edge,and the new model showed an improvement in accuracy because it considered the ice effect on waves.We then performed a wave hindcast for the Bohai Sea during a freezing period in the winter of 2016 that had the severest ice conditions in recent years and found that the mean significant wave height changed by approximately 16.52%.In the Liaodong Bay,where sea ice concentration is highest,the change reached 32.57%,compared with the most recent SWAN model version.The average influence of sea ice on wave height simulation was also evaluated over a five-year(2013-2017)hindcast during January and February.We found that the wave height decrease was more significant in storm conditions even the eddy viscosity wave-ice model itself showed no advantage on damping stronger waves. 相似文献
High concentrations of PM2.5 are universally considered as a main cause for haze formation. Therefore, it is important to identify the spatial heterogeneity and influencing factors of PM2.5 concentrations for regional air quality control and management. In this study, PM2.5 data from 2000 to 2015 was determined from an inversion of NASA atmospheric remote sensing images. Using geo-statistics, geographic detectors, and geo-spatial analysis methods, the spatio-temporal evolution patterns and driving factors of PM2.5 concentration in China were evaluated. The main results are as follows. (1) In general, the average concentration of PM2.5 in China increased quickly and reached its peak value in 2006; subsequently, concentrations remained between 21.84 and 35.08 μg/m3. (2) PM2.5 is strikingly heterogeneous in China, with higher concentrations in the north and east than in the south and west. In particular, areas with relatively high PM2.5 concentrations are primarily in four regions, the Huang-Huai-Hai Plain, Lower Yangtze River Delta Plain, Sichuan Basin, and Taklimakan Desert. Among them, Beijing-Tianjin-Hebei Region has the highest concentration of PM2.5. (3) The center of gravity of PM2.5 has generally moved northeastward, which indicates an increasingly serious haze in eastern China. High-value PM2.5 concentrations have moved eastward, while low-value PM2.5 has moved westward. (4) Spatial autocorrelation analysis indicates a significantly positive spatial correlation. The “High-High” PM2.5 agglomeration areas are distributed in the Huang-Huai-Hai Plain, Fenhe-Weihe River Basin, Sichuan Basin, and Jianghan Plain regions. The “Low-Low” PM2.5 agglomeration areas include Inner Mongolia and Heilongjiang, north of the Great Wall, Qinghai-Tibet Plateau, and Taiwan, Hainan, and Fujian and other southeast coastal cities and islands. (5) Geographic detection analysis indicates that both natural and anthropogenic factors account for spatial variations in PM2.5 concentration. Geographical location, population density, automobile quantity, industrial discharge, and straw burning are the main driving forces of PM2.5 concentration in China.
In order to archive,quality control and disseminate a large variety of marine data in a marine data exchange platform,a marine XML has been developed to encapsulate marine data,which provides an efficient means to store,transfer and display marine data.This paper first presents the details of the main marine XML elements and then gives an example showing how to transform CTD-observed data into Marine XML format,which illustrates the XML encapsulation process of marine observed data. 相似文献