{"title":"日本和福岛附近漂移浮标轨迹的统计聚类以确定拉格朗日环流特征","authors":"L.J. Hamilton","doi":"10.1016/j.mio.2013.09.002","DOIUrl":null,"url":null,"abstract":"<div><p><span>A simple statistical clustering method is demonstrated to aid the identification of spatially repeating or persistent Lagrangian circulation patterns inherent in ensembles of drifting buoy trajectories. The technique is applied to the regional oceanic circulation about </span>Japan<span><span> and to the mesoscale circulation off Fukushima on Japan’s east coast. The drifter trajectories form a highly irregular data set in both space and time, with very different locations, configurations, cumulative travel distances (tens of metres to thousands of km), travel times (hours to years), and start and end positions. The interpolation technique of Kim, Kim, Ho, and Chu, Journal of Climate 24 (2) (2011), is found suitable to transform the spatially complex </span>buoy data<span> into a form suitable for statistical clustering. To resolve and give context to the very different spatial scales<span> encountered in oceanic circulations the methods are applied in a hierarchical fashion to progressively smaller areas (120–180°E, 20–50°N; 140–160°E, 32–44°N; 140–145°E, 35–40°N). A winding number method is devised to identify and distinguish between clockwise and anti-clockwise sense of circulation. The analysis techniques provide what can be regarded as a spatial decomposition of Lagrangian flow fields. The methods do not require curve fitting or modelling, feature analysis, curve alignment, or spatial gridding, binning, and averaging, and are not dependent on density of observations. The methodology forms a useful data exploration technique for examination of trajectory data in general.</span></span></span></p></div>","PeriodicalId":100922,"journal":{"name":"Methods in Oceanography","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.mio.2013.09.002","citationCount":"0","resultStr":"{\"title\":\"Statistical clustering of drifting buoy trajectories to identify Lagrangian circulation features around Japan and off Fukushima\",\"authors\":\"L.J. Hamilton\",\"doi\":\"10.1016/j.mio.2013.09.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>A simple statistical clustering method is demonstrated to aid the identification of spatially repeating or persistent Lagrangian circulation patterns inherent in ensembles of drifting buoy trajectories. The technique is applied to the regional oceanic circulation about </span>Japan<span><span> and to the mesoscale circulation off Fukushima on Japan’s east coast. The drifter trajectories form a highly irregular data set in both space and time, with very different locations, configurations, cumulative travel distances (tens of metres to thousands of km), travel times (hours to years), and start and end positions. The interpolation technique of Kim, Kim, Ho, and Chu, Journal of Climate 24 (2) (2011), is found suitable to transform the spatially complex </span>buoy data<span> into a form suitable for statistical clustering. To resolve and give context to the very different spatial scales<span> encountered in oceanic circulations the methods are applied in a hierarchical fashion to progressively smaller areas (120–180°E, 20–50°N; 140–160°E, 32–44°N; 140–145°E, 35–40°N). A winding number method is devised to identify and distinguish between clockwise and anti-clockwise sense of circulation. The analysis techniques provide what can be regarded as a spatial decomposition of Lagrangian flow fields. The methods do not require curve fitting or modelling, feature analysis, curve alignment, or spatial gridding, binning, and averaging, and are not dependent on density of observations. The methodology forms a useful data exploration technique for examination of trajectory data in general.</span></span></span></p></div>\",\"PeriodicalId\":100922,\"journal\":{\"name\":\"Methods in Oceanography\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.mio.2013.09.002\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Methods in Oceanography\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2211122013000327\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methods in Oceanography","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211122013000327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
一种简单的统计聚类方法被证明有助于识别空间重复或持续的拉格朗日环流模式固有的浮标轨迹集合。该技术应用于日本附近的区域海洋环流和日本东海岸福岛附近的中尺度环流。漂流者的轨迹在空间和时间上形成了一个高度不规则的数据集,具有非常不同的位置、配置、累积旅行距离(几十米到几千公里)、旅行时间(小时到几年)以及开始和结束的位置。Kim, Kim, Ho, and Chu, Journal of Climate 24(2)(2011)的插值技术适合将空间复杂的浮标数据转换为适合统计聚类的形式。为了解决和提供海洋环流中遇到的非常不同的空间尺度的背景,这些方法以分层方式应用于逐渐变小的区域(120-180°E, 20-50°N;140 - 160°E, 32-44°N;140 - 145°E, 35 - 40°N)。设计了一种圈数法来识别和区分顺时针和逆时针循环感。分析技术提供了可以被视为拉格朗日流场的空间分解。这些方法不需要曲线拟合或建模、特征分析、曲线对齐、空间网格划分、分箱和平均,也不依赖于观测的密度。该方法为一般的轨迹数据检查提供了一种有用的数据探索技术。
Statistical clustering of drifting buoy trajectories to identify Lagrangian circulation features around Japan and off Fukushima
A simple statistical clustering method is demonstrated to aid the identification of spatially repeating or persistent Lagrangian circulation patterns inherent in ensembles of drifting buoy trajectories. The technique is applied to the regional oceanic circulation about Japan and to the mesoscale circulation off Fukushima on Japan’s east coast. The drifter trajectories form a highly irregular data set in both space and time, with very different locations, configurations, cumulative travel distances (tens of metres to thousands of km), travel times (hours to years), and start and end positions. The interpolation technique of Kim, Kim, Ho, and Chu, Journal of Climate 24 (2) (2011), is found suitable to transform the spatially complex buoy data into a form suitable for statistical clustering. To resolve and give context to the very different spatial scales encountered in oceanic circulations the methods are applied in a hierarchical fashion to progressively smaller areas (120–180°E, 20–50°N; 140–160°E, 32–44°N; 140–145°E, 35–40°N). A winding number method is devised to identify and distinguish between clockwise and anti-clockwise sense of circulation. The analysis techniques provide what can be regarded as a spatial decomposition of Lagrangian flow fields. The methods do not require curve fitting or modelling, feature analysis, curve alignment, or spatial gridding, binning, and averaging, and are not dependent on density of observations. The methodology forms a useful data exploration technique for examination of trajectory data in general.