Articles | Volume 20, issue 6
https://doi.org/10.5194/os-20-1527-2024
© 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/os-20-1527-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Multiple timescale variations in fronts in the Seto Inland Sea, Japan
Menghong Dong
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, 310012, China
Center for Marine Environmental Studies, Ehime University, Matsuyama, 7908577, Japan
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Menghong Dong, Xinyu Guo, Takuya Matsuura, Taichi Tebakari, and Jing Zhang
Biogeosciences, 22, 2383–2402, https://doi.org/10.5194/bg-22-2383-2025, https://doi.org/10.5194/bg-22-2383-2025, 2025
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Submarine groundwater discharge (SGD), a common coastal hydrological process that involves submarine inflow of groundwater into the sea, is associated with a large nutrient load. To clarify the distribution of SGD-derived nutrients after release at the bottom of the sea and their contribution to phytoplankton growth in the marine ecosystem, we modeled the SGD process in Toyama Bay using a specialized computer code that can distinguish SGD-derived nutrients from nutrients from other sources.
Menghong Dong, Xinyu Guo, Takuya Matsuura, Taichi Tebakari, and Jing Zhang
Biogeosciences, 22, 2383–2402, https://doi.org/10.5194/bg-22-2383-2025, https://doi.org/10.5194/bg-22-2383-2025, 2025
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Submarine groundwater discharge (SGD), a common coastal hydrological process that involves submarine inflow of groundwater into the sea, is associated with a large nutrient load. To clarify the distribution of SGD-derived nutrients after release at the bottom of the sea and their contribution to phytoplankton growth in the marine ecosystem, we modeled the SGD process in Toyama Bay using a specialized computer code that can distinguish SGD-derived nutrients from nutrients from other sources.
Qian Leng, Xinyu Guo, Junying Zhu, and Akihiko Morimoto
Biogeosciences, 20, 4323–4338, https://doi.org/10.5194/bg-20-4323-2023, https://doi.org/10.5194/bg-20-4323-2023, 2023
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Using a numerical model, we revealed that a large proportion of nutrients in a semi-enclosed sea (Seto Inland Sea, Japan) comes from the Pacific Ocean and supports about half of the phytoplankton growth in the sea. Such results imply that the human-made management of nutrient load from land needs to consider the presence of oceanic nutrients, which act as a background concentration and are not controlled by human activities.
Lei Lin, Hao Liu, Xiaomeng Huang, Qingjun Fu, and Xinyu Guo
Hydrol. Earth Syst. Sci., 26, 5207–5225, https://doi.org/10.5194/hess-26-5207-2022, https://doi.org/10.5194/hess-26-5207-2022, 2022
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Earth system (climate) model is an important instrument for projecting the global water cycle and climate change, in which tides are commonly excluded due to the much small timescales compared to the climate. However, we found that tides significantly impact the river water transport pathways, transport timescales, and concentrations in shelf seas. Thus, the tidal effect should be carefully considered in earth system models to accurately project the global water and biogeochemical cycle.
Junying Zhu, Jie Shi, and Xinyu Guo
Ocean Sci., 18, 659–673, https://doi.org/10.5194/os-18-659-2022, https://doi.org/10.5194/os-18-659-2022, 2022
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A bottom cold water mass (BCWM) is a widespread physical oceanographic phenomenon among coastal seas. Observations reveal a prominent interannual variation in a BCWM in the Seto Inland Sea during 1994–2015. We found that air–sea heat flux change during the warming season plays an important role in its interannual variation. Comparison with other BCWMs indicates that the size is a key factor for their difference. The findings help understand the response of BCWMs to sea surface forcing change.
Toru Kobari, Taiga Honma, Daisuke Hasegawa, Naoki Yoshie, Eisuke Tsutsumi, Takeshi Matsuno, Takeyoshi Nagai, Takeru Kanayama, Fukutaro Karu, Koji Suzuki, Takahiro Tanaka, Xinyu Guo, Gen Kume, Ayako Nishina, and Hirohiko Nakamura
Biogeosciences, 17, 2441–2452, https://doi.org/10.5194/bg-17-2441-2020, https://doi.org/10.5194/bg-17-2441-2020, 2020
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We report on biological productivity under turbulent nitrate flux amplified with the Kuroshio. Oceanographic observations exhibit that the Kuroshio topographically enhances significant turbulent mixing and nitrate influx to the euphotic zone. Onboard experiments show phytoplankton and microzooplankton growths enhanced with the nitrate flux and a significant microzooplankton grazing on phytoplankton. These rapid and systematic trophodynamics enhance biological productivity in the Kuroshio.
Chao Zhang, Huiwang Gao, Xiaohong Yao, Zongbo Shi, Jinhui Shi, Yang Yu, Ling Meng, and Xinyu Guo
Biogeosciences, 15, 749–765, https://doi.org/10.5194/bg-15-749-2018, https://doi.org/10.5194/bg-15-749-2018, 2018
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This study compares the response of phytoplankton growth in the northwest Pacific to those in the Yellow Sea. In general, larger positive responses of phytoplankton induced by combined nutrients (in the subtropical gyre of the northwest Pacific) than those induced by a single nutrient (in the Kuroshio Extension and the Yellow Sea) from the dust are observed. We also emphasize the importance of an increase in bioavailable P stock for phytoplankton growth following dust addition.
X. Y. Guo, X.-H. Zhu, Y. Long, and D. J. Huang
Biogeosciences, 10, 6403–6417, https://doi.org/10.5194/bg-10-6403-2013, https://doi.org/10.5194/bg-10-6403-2013, 2013
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Approach: Remote Sensing | Properties and processes: Mesoscale to submesoscale dynamics
Enhanced resolution capability of SWOT sea surface height measurements and their application in monitoring ocean dynamics variability
Generation of super-resolution gap-free ocean colour satellite products using data-interpolating empirical orthogonal functions (DINEOF)
Sargassum accumulation and transport by mesoscale eddies
Blending 2D topography images from the Surface Water and Ocean Topography (SWOT) mission into the altimeter constellation with the Level-3 multi-mission Data Unification and Altimeter Combination System (DUACS)
Estimating ocean currents from the joint reconstruction of absolute dynamic topography and sea surface temperature through deep learning algorithms
Integrating wide-swath altimetry data into Level-4 multi-mission maps
Monitoring the coastal–offshore water interactions in the Levantine Sea using ocean color and deep supervised learning
MAESSTRO: Masked Autoencoders for Sea Surface Temperature Reconstruction under Occlusion
Advances in Surface Water and Ocean Topography for Fine-Scale Eddy Identification from Altimeter Sea Surface Height Merging Maps
Deep learning for the super resolution of Mediterranean sea surface temperature fields
Impact of surface and subsurface-intensified eddies on sea surface temperature and chlorophyll a in the northern Indian Ocean utilizing deep learning
Regional mapping of energetic short mesoscale ocean dynamics from altimetry: performances from real observations
Ocean 2D eddy energy fluxes from small mesoscale processes with SWOT
Yong Wang, Shengjun Zhang, and Yongjun Jia
Ocean Sci., 21, 931–944, https://doi.org/10.5194/os-21-931-2025, https://doi.org/10.5194/os-21-931-2025, 2025
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The distance-weighted averaging method was used to calculate the along-orbit sea surface height (SSH) wavenumber spectra of four satellites and to evaluate the along-track resolution capability of the four satellites. The results show that the resolution of Surface Water and Ocean Topography (SWOT) in the Kuroshio region is 25 km, which is twice the resolution of conventional satellites. A parameter was defined using the cross-power-spectrum approach and used to analyse the global ocean.
Aida Alvera-Azcárate, Dimitry Van der Zande, Alexander Barth, Antoine Dille, Joppe Massant, and Jean-Marie Beckers
Ocean Sci., 21, 787–805, https://doi.org/10.5194/os-21-787-2025, https://doi.org/10.5194/os-21-787-2025, 2025
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This work presents an approach for increasing the spatial resolution of satellite data and interpolating gaps due to cloud cover, using a method called DINEOF (data-interpolating empirical orthogonal functions). The method is tested on turbidity and chlorophyll-a concentration data in the Belgian coastal zone and the North Sea. The results show that we are able to improve the spatial resolution of these data in order to perform analyses of spatial and temporal variability in coastal regions.
Rosmery Sosa-Gutierrez, Julien Jouanno, and Leo Berline
EGUsphere, https://doi.org/10.5194/egusphere-2025-514, https://doi.org/10.5194/egusphere-2025-514, 2025
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Since 2010, pelagic Sargassum blooms have increased in several tropical Atlantic regions, causing socioeconomic and ecosystem impacts. Offshore the structuration of Sargassum by the mesoscale dynamics may influence transport and growth. Sargassum, stays afloat, constantly interacting with currents, waves, winds, and mesoscale eddies. We find that anticyclonic and cyclonic effectively trap Sargassum throughout their propagation, with a greater tendency for cyclones to accumulate Sargassum.
Gerald Dibarboure, Cécile Anadon, Frédéric Briol, Emeline Cadier, Robin Chevrier, Antoine Delepoulle, Yannice Faugère, Alice Laloue, Rosemary Morrow, Nicolas Picot, Pierre Prandi, Marie-Isabelle Pujol, Matthias Raynal, Anaelle Tréboutte, and Clément Ubelmann
Ocean Sci., 21, 283–323, https://doi.org/10.5194/os-21-283-2025, https://doi.org/10.5194/os-21-283-2025, 2025
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The Surface Water and Ocean Topography (SWOT) mission delivers unprecedented swath-altimetry products. In this paper, we describe how we extended the Level-3 algorithms to handle SWOT’s unique swath-altimeter data. We also illustrate and discuss the benefits, relevance, and limitations of Level-3 swath-altimeter products for various research domains.
Daniele Ciani, Claudia Fanelli, and Bruno Buongiorno Nardelli
Ocean Sci., 21, 199–216, https://doi.org/10.5194/os-21-199-2025, https://doi.org/10.5194/os-21-199-2025, 2025
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Ocean surface currents are routinely derived from satellite observations of the sea level, allowing regional- to global-scale synoptic monitoring. In order to overcome the theoretical and instrumental limits of this methodology, we exploit the synergy of multi-sensor satellite observations. We rely on deep learning, physics-informed algorithms to predict ocean currents from sea surface height and sea surface temperature observations. Results are validated by means of in situ measurements.
Maxime Ballarotta, Clément Ubelmann, Valentin Bellemin-Laponnaz, Florian Le Guillou, Guillaume Meda, Cécile Anadon, Alice Laloue, Antoine Delepoulle, Yannice Faugère, Marie-Isabelle Pujol, Ronan Fablet, and Gérald Dibarboure
Ocean Sci., 21, 63–80, https://doi.org/10.5194/os-21-63-2025, https://doi.org/10.5194/os-21-63-2025, 2025
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The Surface Water and Ocean Topography (SWOT) mission provides unprecedented swath altimetry data. This study examines SWOT's impact on mapping systems, showing a moderate effect with the current nadir altimetry constellation and a stronger impact with a reduced one. Integrating SWOT with dynamic mapping techniques improves the resolution of satellite-derived products, offering promising solutions for studying and monitoring sea-level variability at finer scales.
Georges Baaklini, Julien Brajard, Leila Issa, Gina Fifani, Laurent Mortier, and Roy El Hourany
Ocean Sci., 20, 1707–1720, https://doi.org/10.5194/os-20-1707-2024, https://doi.org/10.5194/os-20-1707-2024, 2024
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Understanding the flow of the Levantine Sea surface current is not straightforward. We propose a study based on learning techniques to follow interactions between water near the shore and further out at sea. Our results show changes in the coastal currents past 33.8° E, with frequent instances of water breaking away along the Lebanese coast. These events happen quickly and sometimes lead to long-lasting eddies. This study underscores the need for direct observations to improve our knowledge.
Edwin Goh, Alice Yepremyan, Jinbo Wang, and Brian Wilson
Ocean Sci., 20, 1309–1323, https://doi.org/10.5194/os-20-1309-2024, https://doi.org/10.5194/os-20-1309-2024, 2024
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An AI model was used to fill in missing parts of sea temperature (SST) maps caused by cloud cover. We found masked autoencoders can recreate missing SSTs with less than 0.2 °C error, even when 80 % are missing. This is 5000 times faster than conventional methods tested on a single central processing unit. This can enhance our ability in monitoring global small-scale ocean fronts that affect heat, carbon, and nutrient exchange in the ocean. The method is promising for future research.
Xiaoya Zhang, Lei Liu, Jianfang Fei, Zhijin Li, Zexun Wei, Zhiwei Zhang, Xingliang Jiang, Zexin Dong, and Feng Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2773, https://doi.org/10.5194/egusphere-2024-2773, 2024
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Our research evaluated the precision of mapping the ocean's surface with combined data from a couple of satellites, focusing on dynamic aspects revealed by sea level changes. Results show that 2DVAR, a new mapping product, aligns more closely and with less error with the most advanced satellite detailed observations than a widely used mapping product called AVISO. The results suggest that 2DVAR better detects minor ocean movements, making it more valuable and reliable for ocean dynamics study.
Claudia Fanelli, Daniele Ciani, Andrea Pisano, and Bruno Buongiorno Nardelli
Ocean Sci., 20, 1035–1050, https://doi.org/10.5194/os-20-1035-2024, https://doi.org/10.5194/os-20-1035-2024, 2024
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Sea surface temperature (SST) is an essential variable to understanding the Earth's climate system, and its accurate monitoring from space is essential. Since satellite measurements are hindered by cloudy/rainy conditions, data gaps are present even in merged multi-sensor products. Since optimal interpolation techniques tend to smooth out small-scale features, we developed a deep learning model to enhance the effective resolution of gap-free SST images over the Mediterranean Sea to address this.
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.
Florian Le Guillou, Lucile Gaultier, Maxime Ballarotta, Sammy Metref, Clément Ubelmann, Emmanuel Cosme, and Marie-Helène Rio
Ocean Sci., 19, 1517–1527, https://doi.org/10.5194/os-19-1517-2023, https://doi.org/10.5194/os-19-1517-2023, 2023
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Altimetry provides sea surface height (SSH) data along one-dimensional tracks. For many applications, the tracks are interpolated in space and time to provide gridded SSH maps. The operational SSH gridded products filter out the small-scale signals measured on the tracks. This paper evaluates the performances of a recently implemented dynamical method to retrieve the small-scale signals from real SSH data. We show a net improvement in the quality of SSH maps when compared to independent data.
Elisa Carli, Rosemary Morrow, Oscar Vergara, Robin Chevrier, and Lionel Renault
Ocean Sci., 19, 1413–1435, https://doi.org/10.5194/os-19-1413-2023, https://doi.org/10.5194/os-19-1413-2023, 2023
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Oceanic eddies are the structures carrying most of the energy in our oceans. They are key to climate regulation and nutrient transport. We prepare for the Surface Water and Ocean Topography mission, studying eddy dynamics in the region south of Africa, where the Indian and Atlantic oceans meet, using models and simulated satellite data. SWOT will provide insights into the structures smaller than what is currently observable, which appear to greatly contribute to eddy kinetic energy and strain.
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Short summary
We employed a gradient-based algorithm to identify the position and intensity of the fronts in a coastal sea using sea surface temperature data, thereby quantifying their variations. Our study provides a comprehensive analysis of these fronts, elucidating their seasonal variability, intra-tidal dynamics, and the influence of winds on the fronts. By capturing the temporal and spatial dynamics of these fronts, our understanding of the complex oceanographic processes within this region is enhanced.
We employed a gradient-based algorithm to identify the position and intensity of the fronts in a...