Considering the interaction of different tidal waves, an adjoint numerical model is developed to simulate M2, S2, K1 and O1 tidal waves in the Bohai Sea, the Yellow Sea and the East China Sea （B-Y-E） simultaneously....Considering the interaction of different tidal waves, an adjoint numerical model is developed to simulate M2, S2, K1 and O1 tidal waves in the Bohai Sea, the Yellow Sea and the East China Sea （B-Y-E） simultaneously. Compared with previous researches, by using the adjoint assimilation technique to inverse open boundary conditions and bottom friction coefficients based on altimetric data from TOPEX/Poseidon （T/P） and tidal gauges data, the precision of the numerical simulation is significantly improved. Selecting 14 days of simulated results after the initial wanning run to conduct harmonic analysis, the results can show the characteristics of M2, S2, K1 and O1 tidal wave systems perfectly in B-Y-E. Compared with 9 current stations, the calculated harmonic constants of tidal currents for M2 and K1 are in good agreement with the observed ones.展开更多
The distribution of the suspended sediment concentration （SSC） in the Bohai Sea, Yellow Sea and East China Sea （BYECS） is studied based on the observed turbidity data and model simulation results. The observed tur...The distribution of the suspended sediment concentration （SSC） in the Bohai Sea, Yellow Sea and East China Sea （BYECS） is studied based on the observed turbidity data and model simulation results. The observed turbidity results show that （i） the highest SSC is found in the coastal areas while in the outer shelf sea areas turbid water is much more difficult to observe, （ii） the surface layer SSC is much lower than the bottom layer SSC and （iii） the winter SSC is higher than the summer SSC. The Regional Ocean Modeling System （ROMS） is used to simulate the SSC distribution in the BYECS. A comparison between the modeled SSC and the observed SSC in the BYECS shows that the modeled SSC can reproduce the principal features of tlte SSC distribution in the BYECS. The dynamic mechanisms of the sediment erosion and transport processes are studied based on the modeled results. The horizontal distribution of the SSC in the BYECS is mainly determined by the current-wave induced bottom stress and the fine-grain sediment distribution. The current-induced bottom stress is much higher than the wave-induced bottom stress, which means the tidal currents play a more significant role in the sediment resuspension than the wind waves. The vertical mixing strength is studied based on the mixed layer depth and the turbulent kinetic energy distribution in the BYECS. The strong winter time vertical mixing, which is mainly caused by the strong wind stress and surface cooling, leads to high surface layer SSC in winter. High surface layer SSC in summer is restricted in the coastal areas.展开更多
Two typical satellite sea surface temperature (SST) datasets, from the Multi-functional Transport Satellite (MTSAT) and Tropical Rainfall Measuring Mission Microwave Imager (TMI), were evaluated for the East China Sea...Two typical satellite sea surface temperature (SST) datasets, from the Multi-functional Transport Satellite (MTSAT) and Tropical Rainfall Measuring Mission Microwave Imager (TMI), were evaluated for the East China Sea, Yellow Sea, and Bohai Sea throughout 2008. Most monthly-mean availabilities of MTSAT are higher than those of TMI, whereas the seasonal variation of the latter is less than that of the former. The analysis on the one-year data shows that the annual mean availability of MTSAT (61%) is greater than that of TMI (56%). This is mainly because MTSAT is a geostationary satellite, which achieves longer observation than the sun-synchronous TMI. The daily availability of TMI (28%-75%) is more constant than that of MTSAT (9%-93%). The signal of infrared sensors on MTSAT is easily disturbed on cloudy days. In contrast, the TMI microwave sensor can obtain information through clouds. Based on in-situ SSTs, the SST accuracy of TMI is superior to that of MTSAT. In 2008, the root mean square (RMS) error of TMI and MTSAT were 0.77 K and 0.84 K, respectively. The annual mean biases were 0.14 K (TMI) and -0.31 K (MTSAT). To attain a high availability of SSTs, we propose a fusion method to merge both SSTs. The annual mean availability of fusion SSTs increases 17% compared to MTSAT. In addition, the availabilities of the fusion SSTs become more constant. The annual mean RMS and bias of fusion SSTs (0.78 K and -0.06 K, respectively) are better than those of MTSAT (0.84 K and -0.31 K).展开更多
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 ...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.展开更多
文摘Considering the interaction of different tidal waves, an adjoint numerical model is developed to simulate M2, S2, K1 and O1 tidal waves in the Bohai Sea, the Yellow Sea and the East China Sea （B-Y-E） simultaneously. Compared with previous researches, by using the adjoint assimilation technique to inverse open boundary conditions and bottom friction coefficients based on altimetric data from TOPEX/Poseidon （T/P） and tidal gauges data, the precision of the numerical simulation is significantly improved. Selecting 14 days of simulated results after the initial wanning run to conduct harmonic analysis, the results can show the characteristics of M2, S2, K1 and O1 tidal wave systems perfectly in B-Y-E. Compared with 9 current stations, the calculated harmonic constants of tidal currents for M2 and K1 are in good agreement with the observed ones.
基金supported by the China Scholarship Council and the National Basic Research Program of China(973 Program 2010CB428904 and 2005CB422300)
文摘The distribution of the suspended sediment concentration （SSC） in the Bohai Sea, Yellow Sea and East China Sea （BYECS） is studied based on the observed turbidity data and model simulation results. The observed turbidity results show that （i） the highest SSC is found in the coastal areas while in the outer shelf sea areas turbid water is much more difficult to observe, （ii） the surface layer SSC is much lower than the bottom layer SSC and （iii） the winter SSC is higher than the summer SSC. The Regional Ocean Modeling System （ROMS） is used to simulate the SSC distribution in the BYECS. A comparison between the modeled SSC and the observed SSC in the BYECS shows that the modeled SSC can reproduce the principal features of tlte SSC distribution in the BYECS. The dynamic mechanisms of the sediment erosion and transport processes are studied based on the modeled results. The horizontal distribution of the SSC in the BYECS is mainly determined by the current-wave induced bottom stress and the fine-grain sediment distribution. The current-induced bottom stress is much higher than the wave-induced bottom stress, which means the tidal currents play a more significant role in the sediment resuspension than the wind waves. The vertical mixing strength is studied based on the mixed layer depth and the turbulent kinetic energy distribution in the BYECS. The strong winter time vertical mixing, which is mainly caused by the strong wind stress and surface cooling, leads to high surface layer SSC in winter. High surface layer SSC in summer is restricted in the coastal areas.
基金Supported by the Open Fund of the Key Laboratory of Ocean Circulationand Waves,Chinese Academy of Sciences(No.KLOCAW1010)the Knowledge Innovation Program of Chinese Academy of Sciences(No.KZCX1-YW-12-04)the National High Technology Research and Development Program of China(863Program)(Nos.2007AA092202,2008AA121701)
文摘Two typical satellite sea surface temperature (SST) datasets, from the Multi-functional Transport Satellite (MTSAT) and Tropical Rainfall Measuring Mission Microwave Imager (TMI), were evaluated for the East China Sea, Yellow Sea, and Bohai Sea throughout 2008. Most monthly-mean availabilities of MTSAT are higher than those of TMI, whereas the seasonal variation of the latter is less than that of the former. The analysis on the one-year data shows that the annual mean availability of MTSAT (61%) is greater than that of TMI (56%). This is mainly because MTSAT is a geostationary satellite, which achieves longer observation than the sun-synchronous TMI. The daily availability of TMI (28%-75%) is more constant than that of MTSAT (9%-93%). The signal of infrared sensors on MTSAT is easily disturbed on cloudy days. In contrast, the TMI microwave sensor can obtain information through clouds. Based on in-situ SSTs, the SST accuracy of TMI is superior to that of MTSAT. In 2008, the root mean square (RMS) error of TMI and MTSAT were 0.77 K and 0.84 K, respectively. The annual mean biases were 0.14 K (TMI) and -0.31 K (MTSAT). To attain a high availability of SSTs, we propose a fusion method to merge both SSTs. The annual mean availability of fusion SSTs increases 17% compared to MTSAT. In addition, the availabilities of the fusion SSTs become more constant. The annual mean RMS and bias of fusion SSTs (0.78 K and -0.06 K, respectively) are better than those of MTSAT (0.84 K and -0.31 K).
基金Supported by the National Natural Science Foundation of China(No.41271409)
文摘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.
