Articles | Volume 16, issue 9
https://doi.org/10.5194/essd-16-4189-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-4189-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
13 Sep 2024
Data description paper |
| 13 Sep 2024
| 13 Sep 2024
Weekly green tide mapping in the Yellow Sea with deep learning: integrating optical and synthetic aperture radar ocean imagery
Key Laboratory of Ocean Observation and Forecasting and Key Laboratory of Ocean Circulation and Waves, Institute of Oceanography, Chinese Academy of Sciences, Qingdao, 266071, China
Yuan Guo
Key Laboratory of Ocean Observation and Forecasting and Key Laboratory of Ocean Circulation and Waves, Institute of Oceanography, Chinese Academy of Sciences, Qingdao, 266071, China
Xiaofeng Li
CORRESPONDING AUTHOR
Key Laboratory of Ocean Observation and Forecasting and Key Laboratory of Ocean Circulation and Waves, Institute of Oceanography, Chinese Academy of Sciences, Qingdao, 266071, China
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Yibin Ren, Xiaofeng Li, and Yunhe Wang
Geosci. Model Dev., 18, 2665–2678, https://doi.org/10.5194/gmd-18-2665-2025, https://doi.org/10.5194/gmd-18-2665-2025, 2025
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This study developed a transformer-based deep learning model to predict the Arctic sea ice seasonally. By integrating the sea ice thickness data into the model, the spring prediction barrier of Arctic sea ice is optimized significantly. The model achieves better skills than the typical numerical model in predicting September’s sea ice extent seasonally. The sea ice thickness data play a key role in reducing the prediction errors of the Beaufort Sea, the East Siberian Sea and the Laptev Sea.
Xudong Zhang and Xiaofeng Li
Earth Syst. Sci. Data, 16, 5131–5144, https://doi.org/10.5194/essd-16-5131-2024, https://doi.org/10.5194/essd-16-5131-2024, 2024
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Internal wave (IW) is an important ocean process and is frequently observed in the South China Sea (SCS). This study presents a detailed IW dataset for the northern SCS spanning from 2000 to 2022, with a spatial resolution of 250 m, comprising 3085 IW MODIS images. This dataset can enhance understanding of IW dynamics and serve as a valuable resource for studying ocean dynamics, validating numerical models, and advancing AI-driven model building, fostering further exploration into IW phenomena.
Qian Liu, Yingjie Liu, and Xiaofeng Li
Biogeosciences, 20, 4857–4874, https://doi.org/10.5194/bg-20-4857-2023, https://doi.org/10.5194/bg-20-4857-2023, 2023
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In the Southern Ocean, abundant eddies behave opposite to our expectations. That is, anticyclonic (cyclonic) eddies are cold (warm). By investigating the variations of physical and biochemical parameters in eddies, we find that abnormal eddies have unique and significant effects on modulating the parameters. This study fills a gap in understanding the effects of abnormal eddies on physical and biochemical parameters in the Southern Ocean.
Yingjie Liu and Xiaofeng Li
Ocean Sci., 19, 1579–1593, https://doi.org/10.5194/os-19-1579-2023, https://doi.org/10.5194/os-19-1579-2023, 2023
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The study developed a deep learning model that effectively distinguishes between surface- and subsurface-intensified eddies in the northern Indian Ocean by integrating sea surface height and temperature data. The accurate distinction between these types of eddies provides valuable insights into their dynamics and their impact on marine ecosystems in the northern Indian Ocean and contributes to understanding the complex interactions between eddy dynamics and biogeochemical processes in the ocean.
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Domain: ESSD – Ocean | Subject: Physical oceanography
Gap-filled sub-surface mooring dataset off Western Australia during 2010–2023
The International Altimetry Service 2024 (IAS2024) coastal sea level dataset and first evaluations
Global ocean surface heat fluxes derived from the maximum entropy production framework accounting for ocean heat storage and Bowen ratio adjustments
A European database of resources on coastal storm impacts
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Surface current variability in the East Australian Current from long-term high-frequency radar observations
SDUST2023VGGA: a global ocean vertical gradient of gravity anomaly model determined from multidirectional data from mean sea surface
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A global daily mesoscale front dataset from satellite observations: In situ validation and cross-dataset comparison
A new multi-grid bathymetric dataset of the Gulf of Naples (Italy) from complementary multi-beam echo sounders
A New-Generation Internal Tide Model Based on 30 Years of Satellite Sea Surface Height Measurements
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MASCS 1.0: synchronous atmospheric and oceanic data from a cross-shaped moored array in the northern South China Sea during 2014–2015
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ISASO2: recent trends and regional patterns of ocean dissolved oxygen change
Constructing a 22-year internal wave dataset for the northern South China Sea: spatiotemporal analysis using MODIS imagery and deep learning
Near-real-time atmospheric and oceanic science products of Himawari-8 and Himawari-9 geostationary satellites over the South China Sea
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XBT data collected along the Southern Ocean “chokepoint” between New Zealand and Antarctica, 1994–2024
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Toan Bui, Ming Feng, and Christopher C. Chapman
Earth Syst. Sci. Data, 17, 1693–1705, https://doi.org/10.5194/essd-17-1693-2025, https://doi.org/10.5194/essd-17-1693-2025, 2025
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Moored time series data are crucial for detecting changes in the ocean. However, mooring losses or instrument failures often result in data gaps. A gap-filled time series dataset of a shelf mooring array off the Western Australian coast is created using a machine learning tool to fill the data gaps. The gap-filled data show consistency with observations and can be used to characterize marine heat waves and cold spells influenced by ocean boundary currents.
Fukai Peng, Xiaoli Deng, Yunzhong Shen, and Xiao Cheng
Earth Syst. Sci. Data, 17, 1441–1460, https://doi.org/10.5194/essd-17-1441-2025, https://doi.org/10.5194/essd-17-1441-2025, 2025
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A new reprocessed altimeter coastal sea level dataset, International Altimetry Service 2024 (IAS2024), for monitoring sea level changes along the world’s coastlines is presented. The evaluation and validation results confirm the reliability of this dataset. The altimeter-based virtual stations along the world’s coastlines can be built using this dataset to monitor the coastal sea level changes where tide gauges are unavailable. Therefore, it is beneficial for both oceanographic communities and policymakers.
Yong Yang, Huaiwei Sun, Jingfeng Wang, Wenxin Zhang, Gang Zhao, Weiguang Wang, Lei Cheng, Lu Chen, Hui Qin, and Zhanzhang Cai
Earth Syst. Sci. Data, 17, 1191–1216, https://doi.org/10.5194/essd-17-1191-2025, https://doi.org/10.5194/essd-17-1191-2025, 2025
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Earth Syst. Sci. Data, 17, 1041–1054, https://doi.org/10.5194/essd-17-1041-2025, https://doi.org/10.5194/essd-17-1041-2025, 2025
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Zaiyang Zhou, Jianzhong Ge, Dirk Sebastiaan van Maren, Hualong Luan, Wenyun Guo, Jianfei Ma, Yingjia Tao, Peng Xu, Fuhai Dao, Wanlun Yang, Keteng Ke, Shenyang Shi, Jingting Zhang, Yu Kuai, Cheng Li, Jinghua Gu, and Pingxing Ding
Earth Syst. Sci. Data, 17, 917–935, https://doi.org/10.5194/essd-17-917-2025, https://doi.org/10.5194/essd-17-917-2025, 2025
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Manh Cuong Tran, Moninya Roughan, and Amandine Schaeffer
Earth Syst. Sci. Data, 17, 937–963, https://doi.org/10.5194/essd-17-937-2025, https://doi.org/10.5194/essd-17-937-2025, 2025
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Ruichen Zhou, Jinyun Guo, Shaoshuai Ya, Heping Sun, and Xin Liu
Earth Syst. Sci. Data, 17, 817–836, https://doi.org/10.5194/essd-17-817-2025, https://doi.org/10.5194/essd-17-817-2025, 2025
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SDUST2023VGGA is a high-resolution (1' × 1') model developed to map the ocean's vertical gradient of gravity anomaly. By using multidirectional mean sea surface data, it reduces the impact of ocean dynamics and provides detailed global gravity anomaly change rates. This model provides critical insights into seafloor structures and ocean mass distribution, contributing to research in marine geophysics and oceanography. The dataset is freely available on Zenodo.
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-53, https://doi.org/10.5194/essd-2025-53, 2025
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The Histoire Physique de la Mer, written by L.F. Marsili in 1725, was one of the first treatises to analyse the science of the sea. However, it is difficult to understand Marsili's original data. This paper has undertaken a major effort to re-evaluate Marsili's observations, converting historical measurements into modern units: water weight in water density, bathymetric profiles mapping the locations where these measurements were made, and sea level variations, considering the associated error.
Qinwang Xing, Haiqing Yu, Wei Yu, Xinjun Chen, and Hui Wang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-592, https://doi.org/10.5194/essd-2024-592, 2025
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Ocean fronts play a key role in marine ecosystems and often implicitly exist in satellite observations. This work presents the first publicly available daily global front dataset spanning from 1982 to 2023, with comprehensive validations using in-situ global observations. Our validations enhance confidence in the application of satellite-based front detection and provide independent support for global front occurrence patterns. The dataset is expected to be widely used in front-related studies.
Federica Foglini, Marzia Rovere, Renato Tonielli, Giorgio Castellan, Mariacristina Prampolini, Francesca Budillon, Marco Cuffaro, Gabriella Di Martino, Valentina Grande, Sara Innangi, Maria Filomena Loreto, Leonardo Langone, Fantina Madricardo, Alessandra Mercorella, Paolo Montagna, Camilla Palmiotto, Claudio Pellegrini, Antonio Petrizzo, Lorenzo Petracchini, Alessandro Remia, Marco Sacchi, Daphnie Sanchez Galvez, Anna Nora Tassetti, and Fabio Trincardi
Earth Syst. Sci. Data, 17, 181–203, https://doi.org/10.5194/essd-17-181-2025, https://doi.org/10.5194/essd-17-181-2025, 2025
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In 2022, the new CNR research vessel Gaia Blu explored the seabed of the Naples and Pozzuoli gulfs and the Amalfi coastal area (Tyrrhenian Sea, Italy) from 50–2000 m water depth, covering 5000 m2 of seafloor. This paper describes data acquisition and processing and provides maps in unprecedented detail of this area affected by geological changes and human impacts. The findings support future geological and geomorphological investigations and mapping and monitoring of the seafloor and habitats.
Zhongxiang Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-611, https://doi.org/10.5194/essd-2024-611, 2025
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Internal tides are generated by barotropic tidal currents flowing over variable topography. They play an important role in a variety of ocean processes such as diapycnal mixing and tracer transport. A global internal tide model is developed using 30 years of satellite altimetry data and a new mapping technique. It decomposes the internal tide field into 60 plane waves at each point, giving numerous long-range beams that contain key information on their generation, propagation, and dissipation.
Yan Wang, Ge Chen, Jie Yang, Zhipeng Gui, and Dehua Peng
Earth Syst. Sci. Data, 16, 5737–5752, https://doi.org/10.5194/essd-16-5737-2024, https://doi.org/10.5194/essd-16-5737-2024, 2024
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Mesoscale eddies are ubiquitous in the ocean and account for 90 % of its kinetic energy, but their generation and dissipation are difficult to observe using current remote sensing technology. Our submesoscale eddy dataset, formed by suppressing large-scale circulation signals and enhancing small-scale chlorophyll structures, has important implications for understanding marine environments and ecosystems, as well as improving climate model predictions.
Han Zhang, Dake Chen, Tongya Liu, Di Tian, Min He, Qi Li, Guofei Wei, and Jian Liu
Earth Syst. Sci. Data, 16, 5665–5679, https://doi.org/10.5194/essd-16-5665-2024, https://doi.org/10.5194/essd-16-5665-2024, 2024
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This paper provides a cross-shaped moored array dataset (MASCS 1.0) of observations that consist of five buoys and four moorings in the northern South China Sea from 2014 to 2015. The moored array is influenced by atmospheric forcings such as tropical cyclones and monsoon as well as oceanic tides and flows. The data reveal variations of the air–sea interface and the ocean itself, which are valuable for studies of air–sea interactions and ocean dynamics in the northern South China Sea.
Simona Simoncelli, Franco Reseghetti, Claudia Fratianni, Lijing Cheng, and Giancarlo Raiteri
Earth Syst. Sci. Data, 16, 5531–5561, https://doi.org/10.5194/essd-16-5531-2024, https://doi.org/10.5194/essd-16-5531-2024, 2024
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This data review is about the reprocessing of historical eXpendable BathyThermograp (XBT) profiles from the Ligurian and Tyrrhenian seas over the time period 1999–2019. A new automated quality control analysis has been performed starting from the original raw data and operational log sheets. The data have been formatted and standardized according to the latest community best practices, and all available metadata have been inserted, including calibration information and uncertainty specification.
Giuseppe Zibordi and Jean-François Berthon
Earth Syst. Sci. Data, 16, 5477–5502, https://doi.org/10.5194/essd-16-5477-2024, https://doi.org/10.5194/essd-16-5477-2024, 2024
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The Coastal Atmosphere and Sea Time Series (CoASTS) and Bio-Optical mapping of Marine Properties (BiOMaP) programs produced bio-optical data supporting satellite ocean color applications across European seas for almost 2 decades. CoASTS and BiOMaP applied equal standardized instruments, measurement methods, quality control schemes and processing codes to ensure temporal and spatial consistency with data products.
Gang Yang, Ke Huang, Lin Zhu, Weiwei Sun, Chao Chen, Xiangchao Meng, Lihua Wang, and Yong Ge
Earth Syst. Sci. Data, 16, 5311–5331, https://doi.org/10.5194/essd-16-5311-2024, https://doi.org/10.5194/essd-16-5311-2024, 2024
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Continuous monitoring of shoreline dynamics is critical to understanding the drivers of shoreline change and evolution. This study uses long-term sequences of Landsat Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager (OLI) images to analyze the spatio-temporal evolution characteristics of the coastlines of Hainan, mainland China, Taiwan, and other countries from 1990 to 2019.
Nicolas Kolodziejczyk, Esther Portela, Virginie Thierry, and Annaig Prigent
Earth Syst. Sci. Data, 16, 5191–5206, https://doi.org/10.5194/essd-16-5191-2024, https://doi.org/10.5194/essd-16-5191-2024, 2024
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Oceanic dissolved oxygen (DO) is fundamental for ocean biogeochemical cycles and marine life. To ease the computation of the ocean oxygen budget from in situ DO data, mapping of data on a regular 3D grid is useful. Here, we present a new DO gridded product from the Argo database. We compare it with existing DO mapping from a historical dataset. We suggest that the ocean has generally been losing oxygen since the 1980s, but large interannual and regional variabilities should be considered.
Xudong Zhang and Xiaofeng Li
Earth Syst. Sci. Data, 16, 5131–5144, https://doi.org/10.5194/essd-16-5131-2024, https://doi.org/10.5194/essd-16-5131-2024, 2024
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Internal wave (IW) is an important ocean process and is frequently observed in the South China Sea (SCS). This study presents a detailed IW dataset for the northern SCS spanning from 2000 to 2022, with a spatial resolution of 250 m, comprising 3085 IW MODIS images. This dataset can enhance understanding of IW dynamics and serve as a valuable resource for studying ocean dynamics, validating numerical models, and advancing AI-driven model building, fostering further exploration into IW phenomena.
Jian Liu, Jingjing Yu, Chuyong Lin, Min He, Haiyan Liu, Wei Wang, and Min Min
Earth Syst. Sci. Data, 16, 4949–4969, https://doi.org/10.5194/essd-16-4949-2024, https://doi.org/10.5194/essd-16-4949-2024, 2024
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The Japanese Himawari-8 and Himawari-9 (H8/9) geostationary (GEO) satellites are strategically positioned over the South China Sea (SCS), spanning from 3 November 2022 to the present. They mainly provide cloud mask, fraction, height, phase, optical, and microphysical property; layered precipitable water; and sea surface temperature products within a temporal resolution of 10 min and a gridded resolution of 0.05° × 0.05°.
Yihao Wu, Hongkai Shi, Dongzhen Jia, Ole Baltazar Andersen, Xiufeng He, Zhicai Luo, Yu Li, Shiyuan Chen, Xiaohuan Si, Sisu Diao, Yihuang Shi, and Yanglin Chen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-443, https://doi.org/10.5194/essd-2024-443, 2024
Revised manuscript accepted for ESSD
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We developed a high-quality and cost-effective shallow-water depth model for >120 islands in the South China Sea, using ICESat-2 and Sentinel-2 satellite data. This model accurately maps water depths with an accuracy of ~1 m. Our findings highlight the limitations of existing global bathymetry models in shallow regions. Our model exhibited superior performance in capturing fine-scale bathymetric features with unprecedented spatial resolution, providing essential data for marine applications.
Giuseppe Aulicino, Antonino Ian Ferola, Laura Fortunato, Giorgio Budillon, Pasquale Castagno, Pierpaolo Falco, Giannetta Fusco, Naomi Krauzig, Giancarlo Spezie, Enrico Zambianchi, and Yuri Cotroneo
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-417, https://doi.org/10.5194/essd-2024-417, 2024
Revised manuscript accepted for ESSD
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This study gathered water temperature data in the last 30 years from several research cruises using XBT probes between New Zealand and the Ross Sea (Antarctica). These observations, collected in the framework of Italian National Antarctic Research Program, were rigorously checked for accuracy and corrected for depth and temperature bias. The public dataset offers valuable information to get insights into the Southern Ocean's climate and improve satellite observations and oceanographic models.
Sarah A. Rautenbach, Carlos Mendes de Sousa, Mafalda Carapuço, and Paulo Relvas
Earth Syst. Sci. Data, 16, 4641–4654, https://doi.org/10.5194/essd-16-4641-2024, https://doi.org/10.5194/essd-16-4641-2024, 2024
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This article presents the data of a 4-month observation of the Iberian Margin Cape St. Vincent ocean observatory, in Portugal (2022), a European Multidisciplinary Seafloor and water column Observatory node. Three instruments at depths between 150 and 200 m collected physical/biogeochemical parameters at different spatial and temporal scales. EMSO-ERIC aims at developing strategies to enable sustainable ocean observation with regards to costs, time, and resolution.
Owein Thuillier, Nicolas Le Josse, Alexandru-Liviu Olteanu, Marc Sevaux, and Hervé Tanguy
Earth Syst. Sci. Data, 16, 4529–4556, https://doi.org/10.5194/essd-16-4529-2024, https://doi.org/10.5194/essd-16-4529-2024, 2024
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Our study unveils a comprehensive catalogue of 17 700 unique coastal digital elevation models (DEMs) derived from the General Bathymetric Chart of the Oceans (GEBCO) as of 2022. These DEMs are designed to support a variety of scientific and educational purposes. Organised into three libraries, they cover a wide range of coastal geometries and different sizes. Data and custom colour palettes for visualisation are made freely available online, promoting open science and collaboration.
Meri Korhonen, Mateusz Moskalik, Oskar Głowacki, and Vineet Jain
Earth Syst. Sci. Data, 16, 4511–4527, https://doi.org/10.5194/essd-16-4511-2024, https://doi.org/10.5194/essd-16-4511-2024, 2024
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Since 2015, temperature and salinity have been monitored in Hornsund fjord (Svalbard), where retreating glaciers add meltwater and terrestrial matter to coastal waters. Therefore, turbidity and water sampling for suspended sediment concentration and sediment deposition are measured. The monitoring spans from May to October, enabling studies on seasonality and its variability over the years, and the dataset covers the whole fjord, including the inner basins in close proximity to the glaciers.
Kyla Drushka, Elizabeth Westbrook, Frederick M. Bingham, Peter Gaube, Suzanne Dickinson, Severine Fournier, Viviane Menezes, Sidharth Misra, Jaynice Pérez Valentín, Edwin J. Rainville, Julian J. Schanze, Carlyn Schmidgall, Andrey Shcherbina, Michael Steele, Jim Thomson, and Seth Zippel
Earth Syst. Sci. Data, 16, 4209–4242, https://doi.org/10.5194/essd-16-4209-2024, https://doi.org/10.5194/essd-16-4209-2024, 2024
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The NASA SASSIE mission aims to understand the role of salinity in modifying sea ice formation in early autumn. The 2022 SASSIE campaign collected measurements of upper-ocean properties, including stratification (layering of the ocean) and air–sea fluxes in the Beaufort Sea. These data are presented here and made publicly available on the NASA Physical Oceanography Distributed Active Archive Center (PO.DAAC), along with code to manipulate the data and generate the figures presented herein.
Chunhua Qiu, Zhenyang Du, Jiancheng Yu, Huabin Mao, Haibo Tang, Zhenhui Yi, Jiawei Qiao, Dongxiao Wang, Xiaoming Zhai, and Yeqiang Shu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-338, https://doi.org/10.5194/essd-2024-338, 2024
Revised manuscript accepted for ESSD
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The high dense AUVs’ dataset in SCS provides 24498 temperature and salinity profiles and covers 463 days’ experiments, including 83 AUGs’ and 2 AUVs’ experiments. To our knowledge, the resolution and length of this dataset is enough in detecting the asymmetry, vertical tilt, temporal evolution of MEs, and the submesoscale processes. The dataset is expected to improve the accuracy of current and biogeochemistry numerical model. More projects gathering AUVs network will be promoted in future.
Lianjun Yang, Taoyong Jin, and Weiping Jiang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-350, https://doi.org/10.5194/essd-2024-350, 2024
Revised manuscript accepted for ESSD
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Storm surges (SSs) cause massive loss of life and property in coastal areas each year. High spatial resolution and long-term SS records are the basis for assessing such events. However, tide gauges can provide limited SS information due to sparse and uneven distributions. Based on artificial intelligence technology and tide gauges, a high spatial coverage SS dataset was generated for period from 1940 to 2020, which can provide possible alternative support for deepening our understanding of SSs.
Lijing Cheng, Yuying Pan, Zhetao Tan, Huayi Zheng, Yujing Zhu, Wangxu Wei, Juan Du, Huifeng Yuan, Guancheng Li, Hanlin Ye, Viktor Gouretski, Yuanlong Li, Kevin E. Trenberth, John Abraham, Yuchun Jin, Franco Reseghetti, Xiaopei Lin, Bin Zhang, Gengxin Chen, Michael E. Mann, and Jiang Zhu
Earth Syst. Sci. Data, 16, 3517–3546, https://doi.org/10.5194/essd-16-3517-2024, https://doi.org/10.5194/essd-16-3517-2024, 2024
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Observational gridded products are essential for understanding the ocean, the atmosphere, and climate change; they support policy decisions and socioeconomic developments. This study provides an update of an ocean subsurface temperature and ocean heat content gridded product, named the IAPv4 data product, which is available for the upper 6000 m (119 levels) since 1940 (more reliable after ~1955) for monthly and 1° × 1° temporal and spatial resolutions.
Sönke Dangendorf, Qiang Sun, Thomas Wahl, Philip Thompson, Jerry X. Mitrovica, and Ben Hamlington
Earth Syst. Sci. Data, 16, 3471–3494, https://doi.org/10.5194/essd-16-3471-2024, https://doi.org/10.5194/essd-16-3471-2024, 2024
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Sea-level information from the global ocean is sparse in time and space, with comprehensive data being limited to the period since 2005. Here we provide a novel reconstruction of sea level and its contributing causes, as determined by a Kalman smoother approach applied to tide gauge records over the period 1900–2021. The new reconstruction shows a continuing acceleration in global mean sea-level rise since 1970 that is dominated by melting land ice. Contributors vary significantly by region.
Panagiotis Athanasiou, Ap van Dongeren, Maarten Pronk, Alessio Giardino, Michalis Vousdoukas, and Roshanka Ranasinghe
Earth Syst. Sci. Data, 16, 3433–3452, https://doi.org/10.5194/essd-16-3433-2024, https://doi.org/10.5194/essd-16-3433-2024, 2024
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The shape of the coast, the intensity of waves, the height of the water levels, the presence of people or critical infrastructure, and the land use are important information to assess the vulnerability of the coast to coastal hazards. Here, we provide 80 indicators of this kind at consistent locations along the global ice-free coastline using open-access global datasets. These can be valuable for quick assessments of the vulnerability of the coast and at data-poor locations.
Léo Seyfried, Laurie Biscara, Héloïse Michaud, Fabien Leckler, Audrey Pasquet, Marc Pezerat, and Clément Gicquel
Earth Syst. Sci. Data, 16, 3345–3367, https://doi.org/10.5194/essd-16-3345-2024, https://doi.org/10.5194/essd-16-3345-2024, 2024
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In Saint-Malo, France, an initiative to enhance marine submersion prevention began in 2018. Shom conducted an extensive sea campaign, mapping the bay's topography and exploring coastal processes. High-resolution data improve knowledge of the interactions between waves, tide and surge and determine processes responsible for submersion. Beyond science, these findings contribute crucially to a local warning system, providing a tangible solution to protect the community from coastal threats.
Jisun Shin, Dae-Won Kim, So-Hyun Kim, Gi Seop Lee, Boo-Keun Khim, and Young-Heon Jo
Earth Syst. Sci. Data, 16, 3193–3211, https://doi.org/10.5194/essd-16-3193-2024, https://doi.org/10.5194/essd-16-3193-2024, 2024
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We overcame the limitations of satellite and reanalysis sea surface salinity (SSS) datasets and produced a gap-free gridded SSS product with reasonable accuracy and a spatial resolution of 1 km using a machine learning model. Our data enabled the recognition of SSS distribution and movement patterns of the Changjiang diluted water (CDW) front in the East China Sea (ECS) during summer. These results will further advance our understanding and monitoring of long-term SSS variations in the ECS.
Haibin Ye, Chaoyu Yang, Yuan Dong, Shilin Tang, and Chuqun Chen
Earth Syst. Sci. Data, 16, 3125–3147, https://doi.org/10.5194/essd-16-3125-2024, https://doi.org/10.5194/essd-16-3125-2024, 2024
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A deep-learning model for gap-filling based on expected variance was developed. OI-SwinUnet achieves good performance reconstructing chlorophyll-a concentration data on the South China Sea. The reconstructed dataset depicts both the spatiotemporal patterns at the seasonal scale and a fast-change process at the weather scale. Reconstructed data show chlorophyll perturbations of individual eddies at different life stages, giving academics a unique and complete perspective on eddy studies.
Robert W. Schlegel, Rakesh Kumar Singh, Bernard Gentili, Simon Bélanger, Laura Castro de la Guardia, Dorte Krause-Jensen, Cale A. Miller, Mikael Sejr, and Jean-Pierre Gattuso
Earth Syst. Sci. Data, 16, 2773–2788, https://doi.org/10.5194/essd-16-2773-2024, https://doi.org/10.5194/essd-16-2773-2024, 2024
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Fjords play a vital role in the Arctic ecosystems and human communities. It is therefore important to have as clear of an understanding of the processes within these systems as possible. While temperature and salinity tend to be well measured, light is usually not. The dataset described in this paper uses remotely sensed data from 2003 to 2022 to address this problem by providing high-spatial-resolution surface, water column, and seafloor light data for several well-studied Arctic fjords.
Nir Haim, Vika Grigorieva, Rotem Soffer, Boaz Mayzel, Timor Katz, Ronen Alkalay, Eli Biton, Ayah Lazar, Hezi Gildor, Ilana Berman-Frank, Yishai Weinstein, Barak Herut, and Yaron Toledo
Earth Syst. Sci. Data, 16, 2659–2668, https://doi.org/10.5194/essd-16-2659-2024, https://doi.org/10.5194/essd-16-2659-2024, 2024
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This paper outlines the process of creating an open-access surface wave dataset, drawing from deep-sea research station observations located 50 km off the coast of Israel. The discussion covers the wave monitoring procedure, from instrument configuration to wave field retrieval, and aspects of quality assurance. The dataset presented spans over 5 years, offering uncommon in situ wave measurements in the deep sea, and addresses the existing gap in wave information within the region.
Fengshun Zhu, Jinyun Guo, Huiying Zhang, Lingyong Huang, Heping Sun, and Xin Liu
Earth Syst. Sci. Data, 16, 2281–2296, https://doi.org/10.5194/essd-16-2281-2024, https://doi.org/10.5194/essd-16-2281-2024, 2024
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We used multi-satellite altimeter data to construct a high-resolution marine gravity change rate (MGCR) model on 5′×5′ grids, named SDUST2020MGCR. The spatial distribution of SDUST2020MGCR and GRACE MGCR are similar, such as in the eastern seas of Japan (dipole), western seas of the Nicobar Islands (rising), and southern seas of Greenland (falling). The SDUST2020MGCR can provide a detailed view of long-term marine gravity change, which will help to study the seawater mass migration.
Lisa Deyle, Thomas H. Badewien, Oliver Wurl, and Jens Meyerjürgens
Earth Syst. Sci. Data, 16, 2099–2112, https://doi.org/10.5194/essd-16-2099-2024, https://doi.org/10.5194/essd-16-2099-2024, 2024
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A dataset from the North Sea of 85 surface drifters from 2017–2021 is presented. Surface drifters enable the analysis of ocean currents by determining the velocities of surface currents and tidal effects. The entire North Sea has not been studied using drifters before, but the analysis of ocean currents is essential, e.g., to understand the pathways of plastic. The results show that there are strong tidal effects in the shallow North Sea area and strong surface currents in the deep areas.
Yasser O. Abualnaja, Alexandra Pavlidou, James H. Churchill, Ioannis Hatzianestis, Dimitris Velaoras, Harilaos Kontoyiannis, Vassilis P. Papadopoulos, Aristomenis P. Karageorgis, Georgia Assimakopoulou, Helen Kaberi, Theodoros Kannelopoulos, Constantine Parinos, Christina Zeri, Dionysios Ballas, Elli Pitta, Vassiliki Paraskevopoulou, Afroditi Androni, Styliani Chourdaki, Vassileia Fioraki, Stylianos Iliakis, Georgia Kabouri, Angeliki Konstantinopoulou, Georgios Krokos, Dimitra Papageorgiou, Alkiviadis Papageorgiou, Georgios Pappas, Elvira Plakidi, Eleni Rousselaki, Ioanna Stavrakaki, Eleni Tzempelikou, Panagiota Zachioti, Anthi Yfanti, Theodore Zoulias, Abdulah Al Amoudi, Yasser Alshehri, Ahmad Alharbi, Hammad Al Sulami, Taha Boksmati, Rayan Mutwalli, and Ibrahim Hoteit
Earth Syst. Sci. Data, 16, 1703–1731, https://doi.org/10.5194/essd-16-1703-2024, https://doi.org/10.5194/essd-16-1703-2024, 2024
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We present oceanographic measurements obtained during two surveillance cruises conducted in June and September 2021 in the Red Sea and the Arabian Gulf. It is the first multidisciplinary survey within the Saudi Arabian coastal zone, extending from near the Saudi–Jordanian border in the north of the Red Sea to the south close to the Saudi--Yemen border and in the Arabian Gulf. The objective was to record the pollution status along the coastal zone of the kingdom related to specific pressures.
Alexandra E. Jones-Kellett and Michael J. Follows
Earth Syst. Sci. Data, 16, 1475–1501, https://doi.org/10.5194/essd-16-1475-2024, https://doi.org/10.5194/essd-16-1475-2024, 2024
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Ocean eddies can limit horizontal mixing, potentially isolating phytoplankton populations and affecting their concentration. We used two decades of satellite data and computer simulations to identify and track eddy-trapping boundaries in the Pacific Ocean for application in phytoplankton research. Although some eddies trap water masses for months, many continuously mix with surrounding waters. A case study shows how eddy trapping can enhance the signature of a phytoplankton bloom.
Richard Fiifi Annan, Xiaoyun Wan, Ruijie Hao, and Fei Wang
Earth Syst. Sci. Data, 16, 1167–1176, https://doi.org/10.5194/essd-16-1167-2024, https://doi.org/10.5194/essd-16-1167-2024, 2024
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Gravity gradient tensor, a set of six unique gravity signals, is suitable for detecting undersea features. However, due to poor spatial resolution in past years, it has received less research interest and investment. However, current datasets have better accuracy and resolutions, thereby necessitating a revisit. Our analysis shows comparable results with reference models. We conclude that current-generation altimetry datasets can precisely resolve all six gravity gradients.
Simon Treu, Sanne Muis, Sönke Dangendorf, Thomas Wahl, Julius Oelsmann, Stefanie Heinicke, Katja Frieler, and Matthias Mengel
Earth Syst. Sci. Data, 16, 1121–1136, https://doi.org/10.5194/essd-16-1121-2024, https://doi.org/10.5194/essd-16-1121-2024, 2024
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This article describes a reconstruction of monthly coastal water levels from 1900–2015 and hourly data from 1979–2015, both with and without long-term sea level rise. The dataset is based on a combination of three datasets that are focused on different aspects of coastal water levels. Comparison with tide gauge records shows that this combination brings reconstructions closer to the observations compared to the individual datasets.
Sarah Asdar, Daniele Ciani, and Bruno Buongiorno Nardelli
Earth Syst. Sci. Data, 16, 1029–1046, https://doi.org/10.5194/essd-16-1029-2024, https://doi.org/10.5194/essd-16-1029-2024, 2024
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Estimating 3D currents is crucial for the understanding of ocean dynamics, and a precise knowledge of ocean circulation is essential to ensure a sustainable ocean. In this context, a new high-resolution (1 / 10°) data-driven dataset of 3D ocean currents has been developed within the European Space Agency World Ocean Circulation project, providing 10 years (2010–2019) of horizontal and vertical quasi-geostrophic currents at daily resolution over the North Atlantic Ocean, down to 1500 m depth.
Xiaoxia Zhang and Heidi Nepf
Earth Syst. Sci. Data, 16, 1047–1062, https://doi.org/10.5194/essd-16-1047-2024, https://doi.org/10.5194/essd-16-1047-2024, 2024
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This study measured the wave-induced plant drag, flow structure, turbulent intensity, and wave energy attenuation in the presence of a salt marsh. We showed that leaves contribute to most of the total plant drag and wave dissipation. Plant resistance significantly reshapes the velocity profile and enhances turbulence intensity. Adding current obviously impact the plants' wave decay capacity. The dataset can be reused to develop and calibrate marsh-flow theoretical and numerical models.
Michael Hemming, Moninya Roughan, and Amandine Schaeffer
Earth Syst. Sci. Data, 16, 887–901, https://doi.org/10.5194/essd-16-887-2024, https://doi.org/10.5194/essd-16-887-2024, 2024
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We present new datasets that are useful for exploring extreme ocean temperature events in Australian coastal waters. These datasets span multiple decades, starting from the 1940s and 1950s, and include observations from the surface to the bottom at four coastal sites. The datasets provide valuable insights into the intensity, frequency and timing of extreme warm and cold temperature events and include event characteristics such as duration, onset and decline rates and their categorisation.
Marlies A. van der Lugt, Jorn W. Bosma, Matthieu A. de Schipper, Timothy D. Price, Marcel C. G. van Maarseveen, Pieter van der Gaag, Gerben Ruessink, Ad J. H. M. Reniers, and Stefan G. J. Aarninkhof
Earth Syst. Sci. Data, 16, 903–918, https://doi.org/10.5194/essd-16-903-2024, https://doi.org/10.5194/essd-16-903-2024, 2024
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A 6-week field campaign was carried out at a sheltered sandy beach on Texel along the Dutch Wadden Sea with the aim of gaining new insights into the driving processes behind sheltered beach morphodynamics. Detailed measurements of the local hydrodynamics, bed-level changes and sediment composition were collected. The morphological evolution on this sheltered site is the result of the subtle interplay between waves, currents and bed composition.
Oriane Bruyère, Romain Le Gendre, Vetea Liao, and Serge Andréfouët
Earth Syst. Sci. Data, 16, 667–679, https://doi.org/10.5194/essd-16-667-2024, https://doi.org/10.5194/essd-16-667-2024, 2024
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During 2019–2020, the lagoon and forereefs of Gambier Island (French Polynesia) were monitored with oceanographic instruments to measure lagoon hydrodynamics and ocean–lagoon water exchanges. Gambier Island is a key black pearl producer and the study goal was to understand the processes influencing spat collection of pearl oyster Pinctada margaritifera, the species used to produce black pearls. The data set is provided to address local pearl farming questions and other investigations as well.
Tahiana Ratsimbazafy, Thibaud Dezutter, Amélie Desmarais, Daniel Amirault, Pascal Guillot, and Simon Morisset
Earth Syst. Sci. Data, 16, 471–499, https://doi.org/10.5194/essd-16-471-2024, https://doi.org/10.5194/essd-16-471-2024, 2024
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The Canadian Coast Guard Ship has collected oceanographic data across the Canadian Arctic annually since 2003. Such activity aims to support Canadian and international researchers. The ship has several instruments with cutting-edge technology available for research each year during the summer. The data presented here include measurements of physical, chemical and biological variables during the year 2021. Datasets collected from each expedition are available free of charge for the public.
Md Jamal Uddin Khan, Inge Van Den Beld, Guy Wöppelmann, Laurent Testut, Alexa Latapy, and Nicolas Pouvreau
Earth Syst. Sci. Data, 15, 5739–5753, https://doi.org/10.5194/essd-15-5739-2023, https://doi.org/10.5194/essd-15-5739-2023, 2023
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Established in the southwest of France in 1875, the Socoa tide gauge is part of the national sea level monitoring network in France. Through a data archaeology exercise, a large part of the records of this gauge in paper format have been rescued and digitized. The digitized data were processed and quality controlled to produce a uniform hourly sea level time series covering 1875 to the present day. This new dataset is important for climate research on sea level rise, tides, and storm surges.
Robin V. F. de Vries, Shungudzemwoyo P. Garaba, and Sarah-Jeanne Royer
Earth Syst. Sci. Data, 15, 5575–5596, https://doi.org/10.5194/essd-15-5575-2023, https://doi.org/10.5194/essd-15-5575-2023, 2023
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We present a high-quality dataset of hyperspectral point and multipixel reflectance observations of virgin, ocean-harvested, and biofouled multipurpose plastics. Biofouling and a submerged scenario of the dataset further extend the variability in open-access spectral reference libraries that are important in algorithm development with relevance to remote sensing use cases.
Oriane Bruyère, Romain Le Gendre, Mathilde Chauveau, Bertrand Bourgeois, David Varillon, John Butscher, Thomas Trophime, Yann Follin, Jérôme Aucan, Vetea Liao, and Serge Andréfouët
Earth Syst. Sci. Data, 15, 5553–5573, https://doi.org/10.5194/essd-15-5553-2023, https://doi.org/10.5194/essd-15-5553-2023, 2023
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During 2018–2022, four pearl farming Tuamotu atolls (French Polynesia) were studied with oceanographic instruments to measure lagoon hydrodynamics and ocean-lagoon water exchanges. The goal was to gain knowledge on the processes influencing the spat collection of the pearl oyster Pinctada margaritifera, the species used to produce black pearls. A worldwide unique oceanographic atoll data set is provided to address local pearl farming questions and other fundamental and applied investigations.
Cited articles
Cao, H. and Han, L.: Drift path of green tide and the impact of typhoon “Chan-hom” in the Chinese Yellow Sea based on GOCI images in 2015, Ecol. Inform., 60, 101156, https://doi.org/10.1016/j.ecoinf.2020.101156, 2020.
Cao, M., Li, X., Cui, T., Pan, X., Li, Y., Chen, Y., Wang, N., Xiao, Y., Song, X., and Xu, Y.: Unprecedent green macroalgae bloom: mechanism and implication to disaster prediction and prevention, Int. J. Digit. Earth, 16, 3772–3793, https://doi.org/10.1080/17538947.2023.2257658, 2023.
Chen, G., Huang, B. X., Yang, J., Radenkovic, M., Ge, L. Y., Cao, C. C., Chen, X. Y., Xia, L. H., Han, G. Y., and Ma, Y.: Deep blue artificial intelligence for knowledge discovery of the intermediate ocean, Frontiers in Marine Science, 9, 1034188, https://doi.org/10.3389/fmars.2022.1034188, 2023.
Cui, T., Li, F., Wei, Y., Yang, X., Xiao, Y., Chen, X., Liu, R., Ma, Y., and Zhang, J.: Super-resolution optical mapping of floating macroalgae from geostationary orbit, Appl. Optics, 59, C70–C77, https://doi.org/10.1364/AO.382081, 2020.
Cui, T. W., Liang, X. J., Gong, J. L., Tong, C., Xiao, Y. F., Liu, R. J., Zhang, X., and Zhang, J.: Assessing and refining the satellite-derived massive green macro-algal coverage in the Yellow Sea with high resolution images, ISPRS J. Photogramm., 144, 315–324, https://doi.org/10.1016/j.isprsjprs.2018.08.001, 2018.
Ding, L. and Luan, R.: The taxonomy, habit, and distribution of a green alga enteromorpha prolifera (ulvales, chlorophyta), Oceanologia et Limnologia Sinica, 40, 68–71, 2009.
Dong, C., Xu, G., Han, G., Bethel, B. J., Xie, W., and Zhou, S.: Recent developments in artificial intelligence in oceanography, Ocean-Land-Atmosphere Research, 2022, 9870950, https://doi.org/10.34133/2022/9870950, 2022.
Fang, C., Song, K. S., Shang, Y. X., Ma, J. H., Wen, Z. D., and Du, J.: Remote sensing of harmful algal blooms variability for Lake Hulun using adjusted FAI (AFAI) algorithm, J. Environ. Inform., 34, 108–122, https://doi.org/10.3808/jei.201700385, 2019.
Feng, L., Zhang, H., Sun, Y., Li, X., Su, R., and Shi, X.: On nutrient releases from the decomposition of Ulva prolifera green tide and their impacts on nearshore seawaters in the southern Yellow Sea, Acta Oceanol. Sin., 42, 59–68, https://doi.org/10.3969/j.issn.0253-4193.2020.08.007, 2020.
Gao, L., Li, X., Kong, F., Yu, R., Guo, Y., and Ren, Y.: AlgaeNet: A deep-learning framework to detect floating green algae from optical and SAR imagery, IEEE J. Sel. Top. Appl., 15, 2782–2796, https://doi.org/10.1109/JSTARS.2022.3162387, 2022.
Gao, L., Guo, Y., and Li, X.: The green tide coverage product in the Yellow Sea during 2008–2022, Oceanographic Data Center, Chinese Academy of Sciences (CASODC), https://doi.org/10.12157/IOCAS.20240410.002, 2024.
Guo, W., Zhao, L., and Li, X.: The interannual variation of Green Tide in the Yellow Sea, Acta Oceanol. Sin., 38, 36–45, https://doi.org/10.3969/j.issn.0253-4193.2016.12.004, 2016.
Guo, Y., Gao, L., and Li, X.: A deep learning model for green algae detection on SAR images, IEEE T. Geosci. Remote, 60, 4210914, https://doi.org/10.1109/TGRS.2022.3215895, 2022.
Hall-Beyer, M.: Practical guidelines for choosing GLCM textures to use in landscape classification tasks over a range of moderate spatial scales, Int. J. Remote Sens., 38, 1312–1338, https://doi.org/10.1080/01431161.2016.1278314, 2017.
Hao, Y., Qu, T., Guan, C., Zhao, X., Hou, C., Tang, X., and Wang, Y.: Competitive advantages of Ulva prolifera from Pyropia aquaculture rafts in Subei Shoal and its implication for the green tide in the Yellow Sea, Mar. Pollut. Bull., 157, 111353, https://doi.org/10.1016/j.marpolbul.2020.111353, 2020.
Hu, C.: A novel ocean color index to detect floating algae in the global oceans, Remote Sens. Environ., 113, 2118–2129, https://doi.org/10.1016/j.rse.2009.05.012, 2009.
Hu, C., Feng, L., Hardy, R. F., and Eric, J.: Hochberg, Spectral and spatial requirements of remote measurements of pelagic Sargassum macroalgae, Remote Sens. Environ., 167, 229–246, https://doi.org/10.1016/j.rse.2015.05.022, 2015.
Hu, C., Qi, L., Hu, L., Cui, T., Xing, Q., He, M., Wang, N., Xiao, Y., Sun, D., and Lu, Y.: Mapping Ulva prolifera green tides from space: A revisit on algorithm design and data products, Int. J. Appl. Earth Obs., 116, 103173, https://doi.org/10.1016/j.jag.2022.103173, 2023.
Hu, L., Zeng, K., Hu, C., and He, M.-X.: On the remote estimation of Ulva prolifera areal coverage and biomass, Remote. Sens. Environ., 223, 194–207, https://doi.org/10.1016/j.rse.2019.01.014, 2019.
Jordan, M. I. and Mitchell, T. M.: Machine learning: Trends, perspectives, and prospects, Science, 349, 255–260, https://doi.org/10.1126/science.aaa8415, 2015.
LeCun, Y., Bengio, Y., and Hinton, G.: Deep learning, Nature, 521, 436–444, 2015.
Li, D., Gao, Z., and Xu, F.: Research on the dissipation of green tide and its influencing factors in the Yellow Sea based on Google Earth Engine, Mar. Pollut. Bull., 172, 112801, https://doi.org/10.1016/j.marpolbul.2021.112801, 2021.
Li, X., Liu, B., Zheng, G., Ren, Y., Zhang, S., Liu, Y., Gao, L., Liu, Y., Zhang, B., and Wang, F.: Deep-learning-based information mining from ocean remote-sensing imagery, Natl. Sci. Rev., 7, 1584–1605, 2020.
Li, X., Zhou, Y., and Wang, F.: Advanced information mining from ocean remote sensing imagery with deep learning, Journal of Remote Sensing, 2022, 9849645, https://doi.org/10.34133/2022/9849645, 2022.
Liu, D., Keesing, J. K., He, P., Wang, Z., Shi, Y., and Wang, Y.: The world's largest macroalgal bloom in the Yellow Sea, China: formation and implications, Estuar. Coast. Shelf S., 129, 2–10, 2013.
Liu, H., Guo, H., and Zhang, L.: SVM-based sea ice classification using textural features and concentration from RADARSAT-2 dual-pol ScanSAR data, IEEE J. Sel. Top. Appl., 8, 1601–1613, 2015.
Qi, L., Hu, C., Wang, M., Shang, S., and Wilson, C.: Floating algae blooms in the East China Sea, Geophys. Res. Lett., 44, 11501–11509, 2017.
Qi, L., Hu, C., Barnes, B. B., Lapointe, B. E., Chen, Y., Xie, Y., and Wang, M.: Climate and anthropogenic controls of seaweed expansions in the East China Sea and Yellow Sea, Geophys. Res. Lett., 49, e2022GL098185, https://doi.org/10.1029/2022GL098185, 2022a.
Qi, L., Wang, M., Hu, C., and Holt, B.: On the capacity of Sentinel-1 synthetic aperture radar in detecting floating macroalgae and other floating matters, Remote Sens. Environ., 280, 113188, https://doi.org/10.1016/j.rse.2022.113188, 2022b.
Russell, B. C., Torralba, A., Murphy, K. P., and Freeman, W. T.: LabelMe: a database and web-based tool for image annotation, Int. J. Comput. Vision, 77, 157–173, 2008.
Son, Y. B., Min, J.-E., and Ryu, J.-H.: Detecting massive green algae (Ulva prolifera) blooms in the Yellow Sea and East China Sea using geostationary ocean color imager (GOCI) data, Ocean Sci. J., 47, 359–375, 2012.
Sun, Y., Yao, L., Liu, J., Tong, Y., Xia, J., Zhao, X., Zhao, S., Fu, M., Zhuang, M., and He, P.: Prevention strategies for green tides at source in the Southern Yellow Sea, Mar. Pollut. Bull., 178, 113646, https://doi.org/10.1016/j.marpolbul.2022.113646, 2022.
Valiela, I., Liu, D., Lloret, J., Chenoweth, K., and Hanacek, D.: Stable isotopic evidence of nitrogen sources and C4 metabolism driving the world's largest macroalgal green tides in the Yellow Sea, Sci. Rep.-UK, 8, 17437, https://doi.org/10.1038/s41598-018-35309-3, 2018.
Wang, H. and Li, X.: DeepBlue: Advanced convolutional neural network applications for ocean remote sensing, IEEE Geosci. Remote Sens. Mag., 12, 138–161, https://doi.org/10.1109/MGRS.2023.3343623, 2024.
Wang, Z., Xiao, J., Fan, S., Li, Y., Liu, X., and Liu, D.: Who made the world's largest green tide in China? – an integrated study on the initiation and early development of the green tide in Yellow Sea, Limnol. Oceanogr., 60, 1105–1117, 2015.
Wang, Z., Fang, Z., Liang, J., and Song, X.: Estimating Ulva prolifera green tides of the Yellow Sea through ConvLSTM data fusion, Environ. Pollut., 324, 121350, https://doi.org/10.1016/j.envpol.2023.121350, 2023.
Winsor, C. P.: The Gompertz curve as a growth curve, P. Natl. Acad. Sci. USA, 18, 1–8, https://doi.org/10.1073/pnas.18.1.1, 1932.
Xing, Q. and Hu, C.: Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and Landsat data: Application of a virtual baseline reflectance height technique, Remote Sens. Environ., 178, 113–126, 2016.
Xing, Q., Wu, L., Tian, L., Cui, T., Li, L., Kong, F., Gao, X., and Wu, M.: Remote sensing of early-stage green tide in the Yellow Sea for floating-macroalgae collecting campaign, Mar. Pollut. Bull., 133, 150–156, 2018.
Xing, Q., An, D., Zheng, X., Wei, Z., Wang, X., Li, L., Tian, L., and Chen, J.: Monitoring seaweed aquaculture in the Yellow Sea with multiple sensors for managing the disaster of macroalgal blooms, Remote Sens. Environ., 231, 111279, https://doi.org/10.1016/j.rse.2019.111279, 2019.
Xu, S., Yu, T., Xu, J., Pan, X., Shao, W., Zuo, J., and Yu, Y.: Monitoring and Forecasting Green Tide in the Yellow Sea Using Satellite Imagery, Remote Sens.-Basel, 15, 2196, https://doi.org/10.3390/rs15082196, 2023.
Yu, H., Wang, C., Sui, Y., Li, J., and Chu, J.: Automatic Extraction of Green Tide Using Dual Polarization Chinese GF-3 SAR Images, J. Coastal Res., 102, 318–325, https://doi.org/10.2112/SI102-038.1, 2020.
Yuan, C., Xiao, J., Zhang, X., Zhou, J., Wang, Z.: A new assessment of the algal biomass of green tide in the Yellow Sea, Mar. Pollut. Bull., 174, 113253, https://doi.org/10.1016/j.marpolbul.2021.113253, 2022.
Zhou, F., Ge, J., Liu, D., Ding, P., Chen, C., and Wei, X.: The Lagrangian-based Floating Macroalgal Growth and Drift Model (FMGDM v1.0): application to the Yellow Sea green tide, Geosci. Model Dev., 14, 6049–6070, https://doi.org/10.5194/gmd-14-6049-2021, 2021.
Short summary
Since 2008, the Yellow Sea has faced a significant ecological issue, the green tide, which has become one of the world's largest marine disasters. Satellite remote sensing plays a pivotal role in detecting this phenomenon. This study uses AI-based models to extract the daily green tide from MODIS and SAR images and integrates these daily data to introduce a continuous weekly dataset, which aids research in disaster simulation, forecasting, and prevention.
Since 2008, the Yellow Sea has faced a significant ecological issue, the green tide, which has...
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