Comprehensive Analysis of Trends in Ocean Surface Current by Delineating Kuroshio Extent Using an Optimized Segmentation Algorithm
Most studies investigated Kuroshio on quantitative values measured at standard grid locations or along a transect. However, this research delineates Kuroshio from its surrounding waters, and surface current trends are analyzed from 1993 to 2020, extending from a single location to a basin scale. Thi...
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2024-01-01
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| author | Mohammed Abdul Athick A.S. Shih-Yu Lee Chian-Yi Liu |
| author_facet | Mohammed Abdul Athick A.S. Shih-Yu Lee Chian-Yi Liu |
| author_sort | Mohammed Abdul Athick A.S. |
| collection | DOAJ |
| description | Most studies investigated Kuroshio on quantitative values measured at standard grid locations or along a transect. However, this research delineates Kuroshio from its surrounding waters, and surface current trends are analyzed from 1993 to 2020, extending from a single location to a basin scale. This unique approach combines segmentation and image processing. When integrated with the goodness of variance fit greater than 0.8, it proves more efficacious than conventional threshold/histogram techniques in delineating patchy Kuroshio extent contributing to oceanography and climate studies. The generalized trend from delineated Kuroshio exhibited a systemwide weakening. To analyze whether the trend is uniform or varies with Latitude, delineated Kuroshio is divided into five sections based on the hydrological characteristics. The trend was analyzed using three statistical, two frequency, and one Bayesian approach on a regional mean and a pixel-by-pixel basis. Weakening in Luzon and along Taiwan is worth noting. In contrast, a strengthening in the Tokara Strait to Nagoya and Nagoya-150°E. Interestingly, the transition zone from weakening to strengthening in the Kuroshio South-II. Regarding computational efficiency, Detecting Breakpoints and Estimating Segments in Trend (DBEST) and Wavelet Transform (WT) outperformed the other methods. Ensemble Empirical Mode Decomposition (EEMD) and Seasonal Trend Loess (STL) have similar levels of efficiency. Breaks for Additive Season and Trend (BFAST) is designed for a linear trend, while EEMD is suitable for a general trend. The Bayesian Estimator of Abrupt, Seasonal Change and Trend (BEAST) combines multiple models to reduce overfitting and produces highly correlated trends from GlobCurrent and drifter data. |
| format | Article |
| id | doaj-art-88c8471c5ec04abfb37c1bcfd6b5f412 |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
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| series | IEEE Access |
| spelling | doaj-art-88c8471c5ec04abfb37c1bcfd6b5f4122025-08-20T02:30:31ZengIEEEIEEE Access2169-35362024-01-011217746817749010.1109/ACCESS.2024.350216810757402Comprehensive Analysis of Trends in Ocean Surface Current by Delineating Kuroshio Extent Using an Optimized Segmentation AlgorithmMohammed Abdul Athick A.S.0https://orcid.org/0000-0001-6381-7251Shih-Yu Lee1https://orcid.org/0000-0001-8484-3846Chian-Yi Liu2https://orcid.org/0000-0003-1725-4405Taiwan International Graduate Program (TIGP), Earth System Science (ESS), Academia Sinica, Taipei, TaiwanResearch Center for Environmental Changes, Academia Sinica, Taipei, TaiwanResearch Center for Environmental Changes, Academia Sinica, Taipei, TaiwanMost studies investigated Kuroshio on quantitative values measured at standard grid locations or along a transect. However, this research delineates Kuroshio from its surrounding waters, and surface current trends are analyzed from 1993 to 2020, extending from a single location to a basin scale. This unique approach combines segmentation and image processing. When integrated with the goodness of variance fit greater than 0.8, it proves more efficacious than conventional threshold/histogram techniques in delineating patchy Kuroshio extent contributing to oceanography and climate studies. The generalized trend from delineated Kuroshio exhibited a systemwide weakening. To analyze whether the trend is uniform or varies with Latitude, delineated Kuroshio is divided into five sections based on the hydrological characteristics. The trend was analyzed using three statistical, two frequency, and one Bayesian approach on a regional mean and a pixel-by-pixel basis. Weakening in Luzon and along Taiwan is worth noting. In contrast, a strengthening in the Tokara Strait to Nagoya and Nagoya-150°E. Interestingly, the transition zone from weakening to strengthening in the Kuroshio South-II. Regarding computational efficiency, Detecting Breakpoints and Estimating Segments in Trend (DBEST) and Wavelet Transform (WT) outperformed the other methods. Ensemble Empirical Mode Decomposition (EEMD) and Seasonal Trend Loess (STL) have similar levels of efficiency. Breaks for Additive Season and Trend (BFAST) is designed for a linear trend, while EEMD is suitable for a general trend. The Bayesian Estimator of Abrupt, Seasonal Change and Trend (BEAST) combines multiple models to reduce overfitting and produces highly correlated trends from GlobCurrent and drifter data.https://ieeexplore.ieee.org/document/10757402/Delineationimage segmentationKuroshioocean currentpixel-by-pixel trendspatio-temporal trend |
| spellingShingle | Mohammed Abdul Athick A.S. Shih-Yu Lee Chian-Yi Liu Comprehensive Analysis of Trends in Ocean Surface Current by Delineating Kuroshio Extent Using an Optimized Segmentation Algorithm IEEE Access Delineation image segmentation Kuroshio ocean current pixel-by-pixel trend spatio-temporal trend |
| title | Comprehensive Analysis of Trends in Ocean Surface Current by Delineating Kuroshio Extent Using an Optimized Segmentation Algorithm |
| title_full | Comprehensive Analysis of Trends in Ocean Surface Current by Delineating Kuroshio Extent Using an Optimized Segmentation Algorithm |
| title_fullStr | Comprehensive Analysis of Trends in Ocean Surface Current by Delineating Kuroshio Extent Using an Optimized Segmentation Algorithm |
| title_full_unstemmed | Comprehensive Analysis of Trends in Ocean Surface Current by Delineating Kuroshio Extent Using an Optimized Segmentation Algorithm |
| title_short | Comprehensive Analysis of Trends in Ocean Surface Current by Delineating Kuroshio Extent Using an Optimized Segmentation Algorithm |
| title_sort | comprehensive analysis of trends in ocean surface current by delineating kuroshio extent using an optimized segmentation algorithm |
| topic | Delineation image segmentation Kuroshio ocean current pixel-by-pixel trend spatio-temporal trend |
| url | https://ieeexplore.ieee.org/document/10757402/ |
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