A model （Bayesian oceanic front detection, BOFD） of sea surface temperature （SST） front detection in satel- lite-derived SST images based on a threshold interval is presented, to be used in different applications ...A model （Bayesian oceanic front detection, BOFD） of sea surface temperature （SST） front detection in satel- lite-derived SST images based on a threshold interval is presented, to be used in different applications such as climatic and environmental studies or fisheries. The model first computes the SST gradient by using a Sobel algorithm template. On the basis of the gradient value, the threshold interval is determined by a gradi- ent cumulative histogram. According to this threshold interval, front candidates can be acquired and prior probability and likelihood can be calculated. Whether or not the candidates are front points can be deter- mined by using the Bayesian decision theory. The model is evaluated on the Advanced Very High-Resolution Radiometer images of part of the Kuroshio front region. Results are compared with those obtained by using several SST front detection methods proposed in the literature. This comparison shows that the BOFD not only suppresses noise and small-scale fronts, but also retains continuous fronts.展开更多
Oceanic front plays a significant role in the ocean vertical mixing and the regulation of air-sea interaction,among others.The western branch of the subarctic front(WSAF)located in the Northwest Pacific has attained l...Oceanic front plays a significant role in the ocean vertical mixing and the regulation of air-sea interaction,among others.The western branch of the subarctic front(WSAF)located in the Northwest Pacific has attained lots of attention given its strong intensity and widespread influence on this region.In this study,we take advantage of the merged sea surface temperature(SST)at a high spatial resolution of 0.05°to investigate the characteristics of WSAF.The front detection algorithm that combines the Sobel operator and histogram analysis is adopted.It is advantageous in both preserving the front intensity represented by the SST gradient as well as reducing the detection noise level.We systematically applied this algorithm to the daily SST products for front detection,based on which the WSAF characteristics including its intensity,occurrence of frequency,latitudinal position and coverage area are then extracted.WSAF is mostly located within a small latitude range between 40°N and 41°N with a clear seasonal trend in its intensity that peaks in the winter and troughs in the summer.The seasonal variation of WSAF intensity is almost consistent throughout the temporal period of interest from 2010 to 2018.Similar seasonality is observed for its occurrence of frequency with the winter-summer contrast reaching up to5%.The findings presented here shall help better interpret the WSAF characteristics in the long-term run as well as their impact on the regional weather and climate patterns at high spatial resolution.展开更多
基金The National Key Technology R&D Program of China under contract No.2011BAH23B04the National High Technology Research and Development Program(863 Program)of China under contract No.2007AA092202
文摘A model （Bayesian oceanic front detection, BOFD） of sea surface temperature （SST） front detection in satel- lite-derived SST images based on a threshold interval is presented, to be used in different applications such as climatic and environmental studies or fisheries. The model first computes the SST gradient by using a Sobel algorithm template. On the basis of the gradient value, the threshold interval is determined by a gradi- ent cumulative histogram. According to this threshold interval, front candidates can be acquired and prior probability and likelihood can be calculated. Whether or not the candidates are front points can be deter- mined by using the Bayesian decision theory. The model is evaluated on the Advanced Very High-Resolution Radiometer images of part of the Kuroshio front region. Results are compared with those obtained by using several SST front detection methods proposed in the literature. This comparison shows that the BOFD not only suppresses noise and small-scale fronts, but also retains continuous fronts.
基金The Natural Science Foundation of Jiangsu Province under contract No.BK20210666the National Natural Science Foundation of China under contract Nos 41620104003 and 42006163+2 种基金the Startup Foundation for Introducing Talent of Nanjing University of Information Science&Technologythe National Key Research and Development Program of China under contract No.2021YFB3901004the Graduate Innovation Project of Jiangsu Province under contract No.KYCX21_0980。
文摘Oceanic front plays a significant role in the ocean vertical mixing and the regulation of air-sea interaction,among others.The western branch of the subarctic front(WSAF)located in the Northwest Pacific has attained lots of attention given its strong intensity and widespread influence on this region.In this study,we take advantage of the merged sea surface temperature(SST)at a high spatial resolution of 0.05°to investigate the characteristics of WSAF.The front detection algorithm that combines the Sobel operator and histogram analysis is adopted.It is advantageous in both preserving the front intensity represented by the SST gradient as well as reducing the detection noise level.We systematically applied this algorithm to the daily SST products for front detection,based on which the WSAF characteristics including its intensity,occurrence of frequency,latitudinal position and coverage area are then extracted.WSAF is mostly located within a small latitude range between 40°N and 41°N with a clear seasonal trend in its intensity that peaks in the winter and troughs in the summer.The seasonal variation of WSAF intensity is almost consistent throughout the temporal period of interest from 2010 to 2018.Similar seasonality is observed for its occurrence of frequency with the winter-summer contrast reaching up to5%.The findings presented here shall help better interpret the WSAF characteristics in the long-term run as well as their impact on the regional weather and climate patterns at high spatial resolution.
