Abstract. This paper presents an observational dataset on submesoscale eddies obtained from high–resolution chlorophyll–a data captured by GOCI I. Our methodology involves a combination of digital image processing, filtering, and object detection techniques, along with specific chlorophyll–a image enhancement procedure to extract essential information about submesoscale eddies. This information includes their time, polarity, geographical coordinates of the eddy center, eddy radius, coordinates of the upper left and lower right corners of the prediction box, area of the eddy's inner ellipse, and confidence score. The dataset spans eight time intervals, ranging from 00:00 to 08:00 (UTC) daily, covering the period from April 1, 2011, to March 31, 2021. A total of 19,136 anticyclonic eddies and 93,897 cyclonic eddies were identified with a confidence minimum of 0.2. The mean radius of anticyclonic eddies is 24.44 km (range 2.5 km to 44.25 km), while that of cyclonic eddies is 12.34 km (range 1.75 km to 44 km). This unprecedented hourly resolution dataset on submesoscale eddies offers valuable insights into their distribution, morphology, and energy dissipation. It significantly contributes to our understanding of marine environments, ecosystems and the improvement of climate model predictions. The dataset is available at https://doi.org/10.5281/zenodo.7694115 (Wang and Yang, 2023).

中文翻译：

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基于GOCI I叶绿素的西北太平洋亚尺度涡旋识别数据集——基于深度学习的数据


摘要。本文介绍了从高分辨率叶绿素（GOCI I 捕获的数据）获得的亚中尺度涡流的观测数据集。我们的方法涉及数字图像处理、过滤和目标检测技术的组合，以及特定叶绿素（一种图像增强程序）提取有关亚尺度涡流的基本信息。这些信息包括它们的时间、极性、涡流中心的地理坐标、涡流半径、预测框的左上角和右下角的坐标、涡流内椭圆的面积和置信度得分。该数据集跨越8个时间间隔，范围为每天00:00至08:00（UTC），涵盖2011年4月1日至2021年3月31日期间。共识别出19,136个反气旋涡流和93,897个气旋涡旋。置信度最小值为 0.2。反气旋涡流的平均半径为24.44公里（范围2.5公里至44.25公里），而气旋涡流的平均半径为12.34公里（范围1.75公里至44公里）。这个前所未有的亚尺度涡流每小时分辨率数据集为了解涡流的分布、形态和能量耗散提供了宝贵的见解。它极大地有助于我们了解海洋环境、生态系统和改进气候模型预测。该数据集可在 https://doi.org/10.5281/zenodo.7694115 上获取（Wang 和 Yang，2023）。