Abstract. This paper presents an observational dataset on submesoscale eddies, which obtains from high–resolution chlorophyll–a distribution images from GOCI I. We employed a combination of digital image processing, filtering, YOLOv7–X, and small object detection techniques, along with specific chlorophyll image enhancement processing, to extract information on submesoscale eddies, including 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, which covers eight daily periods between 00:00 and 08:00 (UTC) from April 1, 2011, to March 31, 2021. We identified a total of 19,136 anticyclonic eddies and 93,897 cyclonic eddies at a confidence threshold 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). The unprecedented hourly resolution dataset on submesoscale eddies provides information on their distribution, morphology, and energy dissipation, making it a significant contribution to understanding marine environments and ecosystems, as well as improving 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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源自 GOCI I 叶绿素的亚尺度涡流识别数据集——基于深度学习的数据

摘要。反气旋性涡旋的平均半径为 24.44 公里（范围 2.5 公里至 44.25 公里），而气旋性涡旋的平均半径为 12.34 公里（范围 1.75 公里至 44 公里）。史无前例的亚尺度涡流小时分辨率数据集提供了有关它们的分布、形态和能量耗散的信息，使其对了解海洋环境和生态系统以及改进气候模型预测做出了重大贡献。该数据集可在 https://doi.org/10.5281/zenodo.7694115（Wang 和 Yang，2023）获取。使其对了解海洋环境和生态系统以及改进气候模型预测做出重大贡献。该数据集可在 https://doi.org/10.5281/zenodo.7694115（Wang 和 Yang，2023）获取。使其对了解海洋环境和生态系统以及改进气候模型预测做出重大贡献。该数据集可在 https://doi.org/10.5281/zenodo.7694115（Wang 和 Yang，2023）获取。