Articles | Volume 21, issue 3
https://doi.org/10.5194/os-21-1033-2025
© Author(s) 2025. 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-21-1033-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Advances in surface water and ocean topography for fine-scale eddy identification from altimeter sea surface height merging maps in the South China Sea
Xiaoya Zhang
College of Meteorology and Oceanology, National University of Defense Technology, Changsha 410073, China
Key Laboratory of High Impact Weather (special), China Meteorological Administration, Changsha 410073, China
Lei Liu
CORRESPONDING AUTHOR
College of Meteorology and Oceanology, National University of Defense Technology, Changsha 410073, China
Key Laboratory of High Impact Weather (special), China Meteorological Administration, Changsha 410073, China
Jianfang Fei
College of Meteorology and Oceanology, National University of Defense Technology, Changsha 410073, China
Zhijin Li
Department of Atmosphere and Ocean Sciences, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China
Zexun Wei
First Institute of Oceanography, and Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266061, China
Zhiwei Zhang
Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory/Key Laboratory of Ocean Observation and Information of Hainan Province, Sanya Oceanographic Institution, Ocean University of China, Qingdao/Sanya, China
Xingliang Jiang
Department of Atmosphere and Ocean Sciences, Institute of Atmospheric Sciences, Fudan University, Shanghai 200433, China
Zexin Dong
College of Meteorology and Oceanology, National University of Defense Technology, Changsha 410073, China
Feng Xu
College of Meteorology and Oceanology, National University of Defense Technology, Changsha 410073, China
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Noir Primadona Purba, Ghelby Muhammad Faid, Wang Zheng, Mohd. Fadzil Akhir, Weidong Yu, Rangga Adithya Mulya, Fadli Syamsudin, Ibnu Faizal, Buntora Pasaribu, Teguh Agustiadi, Bayu Priyono, Muhammad Fadli, Priyadi Dwi Santoso, Wahyu Widodo Pandoe, Huiwu Wang, Shujiang Li, Zexun Wei, R. Dwi Susanto, Dwiyoga Nugroho, and Adi Purwandana
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-196, https://doi.org/10.5194/essd-2025-196, 2025
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This research examines ocean conditions in the Indonesian seas, a key area linking the Pacific and Indian Oceans. We analyzed two centuries of direct ocean measurements and found large gaps in deep-sea and coastal data that limit climate and marine studies. We suggest better monitoring, technology, and collaboration to improve understanding of ocean changes. These efforts will help predict climate impacts and support marine conservation and sustainable resource use.
Faisal Hamzah, Iis Triyulianti, Agus Setiawan, Intan Suci Nurhati, Bayu Priyono, Dessy Berlianty, Muhammad Fadli, Rafidha D. Ahmad Opier, Teguh Agustiadi, Marsya J. Rugebregt, Weidong Yu, Zexun Wei, Huiwu Wang, R. Dwi Susanto, and Priyadi D. Santoso
EGUsphere, https://doi.org/10.5194/egusphere-2024-451, https://doi.org/10.5194/egusphere-2024-451, 2024
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We provide new insights on the presence of oxygen-depleted waters along the Indonesian coasts of Sumatra and Java attributed to the eastward advection of the northern Indian Ocean waters and monsoon-driven upwelling. Combined in situ and reanalysis data elucidate the complex interplay of oceanographic processes responsible for the observed oxygen in the region. The knowledge is crucial for research and management strategies to mitigate deoxygenation impacts on marine ecosystems in Indonesia.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
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Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Zhijin Li, Matthew R. Archer, Jinbo Wang, and Lee-Lueng Fu
EGUsphere, https://doi.org/10.5194/egusphere-2022-1399, https://doi.org/10.5194/egusphere-2022-1399, 2022
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The Surface Water and Ocean Topography (SWOT) satellite mission will carry a new-generation altimeter to measure sea surface height in two-dimensions at unprecedented spatial resolution. An integration of SWOT measurements into an oceanic numerical model will improve our oceanic prediction in spatial resolution and accuracy. It has been demonstrated that the methodology used is ready to integrate SWOT measurements into the model, and the result may be used to interpret SWOT measurements.
Yiwen Hu, Zengliang Zang, Xiaoyan Ma, Yi Li, Yanfei Liang, Wei You, Xiaobin Pan, and Zhijin Li
Atmos. Chem. Phys., 22, 13183–13200, https://doi.org/10.5194/acp-22-13183-2022, https://doi.org/10.5194/acp-22-13183-2022, 2022
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This study developed a four-dimensional variational assimilation (4DVAR) system based on WRF–Chem to optimise SO2 emissions. The 4DVAR system was applied to obtain the SO2 emissions during the early period of the COVID-19 pandemic over China. The results showed that the 4DVAR system effectively optimised emissions to describe the actual changes in SO2 emissions related to the COVID lockdown, and it can thus be used to improve the accuracy of forecasts.
Dingqi Wang, Guohong Fang, Shuming Jiang, Qinzeng Xu, Guanlin Wang, Zexun Wei, Yonggang Wang, and Tengfei Xu
EGUsphere, https://doi.org/10.5194/egusphere-2022-547, https://doi.org/10.5194/egusphere-2022-547, 2022
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The JES is a mid-latitude “Miniature Ocean” featured by multiscale oceanic dynamical processes and sea ice, which strongly influence the JES SSC. However, the dominant factors that favor and/or restrict SSC and how they influence JES SSC on different time scales are not clear. In this study, these issues are investigated using EOF and PCA methods based on high-resolution satellite-derived SSC data provided by the Copernicus Marine Environment Monitoring Service (CMEMS).
Zhijin Li, Matthew Archer, Jinbo Wang, and Lee-Lueng Fu
Ocean Sci. Discuss., https://doi.org/10.5194/os-2021-89, https://doi.org/10.5194/os-2021-89, 2021
Preprint withdrawn
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We developed a data assimilation (DA) system coupled to a high-resolution model of the California Current region. This three-dimensional variational DA system has been extended to effectively assimilate a longer window of high-density ocean observations, in anticipation of the upcoming SWOT (surface water and ocean topography) satellite mission. The new era of swath-altimetry ushered in by SWOT will challenge existing DA systems, and this study presents a first approach to this challenge.
Di Wu, Guohong Fang, Zexun Wei, and Xinmei Cui
Ocean Sci., 17, 579–591, https://doi.org/10.5194/os-17-579-2021, https://doi.org/10.5194/os-17-579-2021, 2021
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The Korea Strait is a major navigation passage linking the Japan Sea to the East China Sea and Yellow Sea. This paper establishes a theoretical model for the tides in the Korea Strait and Japan Sea using the extended Taylor method. The model solution explains the formation mechanism of the tidal amphidromic systems in the Korea Strait, and why the K1 amphidromic point is located farther away from the shelf break separating the Korea Strait and Japan Sea in comparison to the M2 amphidromic point.
Sha Feng, Thomas Lauvaux, Sally Newman, Preeti Rao, Ravan Ahmadov, Aijun Deng, Liza I. Díaz-Isaac, Riley M. Duren, Marc L. Fischer, Christoph Gerbig, Kevin R. Gurney, Jianhua Huang, Seongeun Jeong, Zhijin Li, Charles E. Miller, Darragh O'Keeffe, Risa Patarasuk, Stanley P. Sander, Yang Song, Kam W. Wong, and Yuk L. Yung
Atmos. Chem. Phys., 16, 9019–9045, https://doi.org/10.5194/acp-16-9019-2016, https://doi.org/10.5194/acp-16-9019-2016, 2016
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We developed a high-resolution land–atmosphere modelling system for urban CO2 emissions over the LA Basin. We evaluated various model configurations, FFCO2 products, and the impact of the model resolution. FFCO2 emissions outpace the atmospheric model resolution to represent the CO2 concentration variability across the basin. A novel forward model approach is presented to evaluate the surface measurement network, reinforcing the importance of using high-resolution emission products.
Zexun Wei, Guohong Fang, R. Dwi Susanto, Tukul Rameyo Adi, Bin Fan, Agus Setiawan, Shujiang Li, Yonggang Wang, and Xiumin Gao
Ocean Sci., 12, 517–531, https://doi.org/10.5194/os-12-517-2016, https://doi.org/10.5194/os-12-517-2016, 2016
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Harmonic constants of tides and tidal currents are obtained from long-term observations. Diurnal tides and tidal currents dominate in southern Natuna Sea and Karimata and Gaspar straits. Existing numerical model results are not accurate in the study area. Existing tidal models based on satellite observation need to be improved for the area.
Related subject area
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
Multiple timescale variations in fronts in the Seto Inland Sea, Japan
MAESSTRO: Masked Autoencoders for Sea Surface Temperature Reconstruction under Occlusion
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.
Menghong Dong and Xinyu Guo
Ocean Sci., 20, 1527–1546, https://doi.org/10.5194/os-20-1527-2024, https://doi.org/10.5194/os-20-1527-2024, 2024
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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.
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.
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.
Cited articles
Abdalla, S., Abdeh Kolahchi, A., Ablain, M., et al.: Altimetry for the future: Building on 25 years of progress, Adv. Space Res., 68, 319–363, https://doi.org/10.1016/j.asr.2021.01.022, 2021.
Archer, M. R., Li, Z., and Fu, L.: Increasing the Space–Time Resolution of Mapped Sea Surface Height From Altimetry, J. Geophys. Res.-Oceans, 125, e2019JC015878, https://doi.org/10.1029/2019JC015878, 2020.
AVISO/DUACS: SWOT Level-3 KaRIn Low Rate SSH Basic (1.0), Aviso [data set], https://doi.org/10.24400/527896/A01-2023.017, 2024.
Ballarotta, M., Ubelmann, C., Pujol, M.-I., Taburet, G., Fournier, F., Legeais, J.-F., Faugère, Y., Delepoulle, A., Chelton, D., Dibarboure, G., and Picot, N.: On the resolutions of ocean altimetry maps, Ocean Sci., 15, 1091–1109, https://doi.org/10.5194/os-15-1091-2019, 2019.
Ballarotta, M., Ubelmann, C., Rogé, M., Fournier, F., Faugère, Y., Dibarboure, G., Morrow, R., and Picot, N.: Dynamic Mapping of Along-Track Ocean Altimetry: Performance from Real Observations, J. Atmos. Ocean. Tech., 37, 1593–1601, https://doi.org/10.1175/JTECH-D-20-0030.1, 2020.
Ballarotta, M., Ubelmann, C., Veillard, P., Prandi, P., Etienne, H., Mulet, S., Faugère, Y., Dibarboure, G., Morrow, R., and Picot, N.: Improved global sea surface height and current maps from remote sensing and in situ observations, Earth Syst. Sci. Data, 15, 295–315, https://doi.org/10.5194/essd-15-295-2023, 2023.
Cai, S., Long, X., Wu, R., and Wang, S.: Geographical and monthly variability of the first baroclinic Rossby radius of deformation in the South China Sea, J. Marine Syst., 74, 711–720, https://doi.org/10.1016/j.jmarsys.2007.12.008, 2008.
Chelton, D. B., Schlax, M. G., Samelson, R. M., and De Szoeke, R. A.: Global observations of large oceanic eddies, Geophys. Res. Lett., 34, 2007GL030812, https://doi.org/10.1029/2007GL030812, 2007.
Chelton, D. B., Schlax, M. G., and Samelson, R. M.: Global observations of nonlinear mesoscale eddies, Prog. Oceanogr., 91, 167–216, https://doi.org/10.1016/j.pocean.2011.01.002, 2011.
Chen, G., Yang, J., Tian, F., Chen, S., Zhao, C., Tang, J., Liu, Y., Wang, Y., Yuan, Z., He, Q., and Cao, C.: Remote sensing of oceanic eddies: Progresses and challenges, National Remote Sensing Bulletin, 25, 302–322, https://doi.org/10.11834/jrs.20210400, 2021.
Chen, J., Zhu, X.-H., Zheng, H., and Wang, M.: Submesoscale dynamics accompanying the Kuroshio in the East China Sea, Front. Mar. Sci., 9, 1124457, https://doi.org/10.3389/fmars.2022.1124457, 2023.
Chen, Y. and Yu, L.: Mesoscale Meridional Heat Transport Inferred From Sea Surface Observations, Geophys. Res. Lett., 51, e2023GL106376, https://doi.org/10.1029/2023GL106376, 2024.
Cohn, S. E.: Estimation theory for data assimilation problems: Basic conceptual framework and some open questions, J. Meteorol. Soc. Jpn., 75, 257–288, 1997.
Copernicus Marine Service repository: Gridded Level-4 Sea Surface Heights Nrt, Copernicus Marine Service [data set], https://doi.org/10.48670/moi-00149, 2023a.
Copernicus Marine Service repository: Gridded Level-4 Sea Surface Heights Reprocessed, Copernicus Marine Service [data set], https://doi.org/10.48670/moi-00148, 2023b.
Dufau, C., Orsztynowicz, M., Dibarboure, G., Morrow, R., and Le Traon, P.: Mesoscale resolution capability of altimetry: Present and future, J. Geophys. Res.-Oceans, 121, 4910–4927, https://doi.org/10.1002/2015JC010904, 2016.
Elipot, S., Lumpkin, R., Perez, R. C., Lilly, J. M., Early, J. J., and Sykulski, A. M.: A global surface drifter data set at hourly resolution, J. Geophys. Res.-Oceans, 121, 2937–2966, https://doi.org/10.1002/2016JC011716, 2016.
Fu, L., Pavelsky, T., Cretaux, J., Morrow, R., Farrar, J. T., Vaze, P., Sengenes, P., Vinogradova-Shiffer, N., Sylvestre-Baron, A., Picot, N., and Dibarboure, G.: The Surface Water and Ocean Topography Mission: A Breakthrough in Radar Remote Sensing of the Ocean and Land Surface Water, Geophys. Res. Lett., 51, e2023GL107652, https://doi.org/10.1029/2023GL107652, 2024.
Huang, Z., Liu, H., Lin, P., and Hu, J.: Influence of island chains on the Kuroshio intrusion in the Luzon Strait, Adv. Atmos. Sci., 34, 397–410, https://doi.org/10.1007/s00376-016-6159-y, 2017.
Jia, Y. and Chassignet, E. P.: Seasonal variation of eddy shedding from the Kuroshio intrusion in the Luzon Strait, J. Oceanogr., 67, 601–611, https://doi.org/10.1007/s10872-011-0060-1, 2011.
Jiang, X., Liu, L., Li, Z., Liu, L., Lim Kam Sian, K. T. C., and Dong, C.: A Two-Dimensional Variational Scheme for Merging Multiple Satellite Altimetry Data and Eddy Analysis, Remote Sensing, 14, 3026, https://doi.org/10.3390/rs14133026, 2022.
Laxenaire, R., Speich, S., Blanke, B., Chaigneau, A., Pegliasco, C., and Stegner, A.: Anticyclonic Eddies Connecting the Western Boundaries of Indian and Atlantic Oceans, J. Geophys. Res.-Oceans, 7651–7677, https://doi.org/10.1029/2018JC014270, 2018.
Le Traon, P. Y., Nadal, F., and Ducet, N.: An Improved Mapping Method of Multisatellite Altimeter Data, J. Atmos. Ocean. Tech., 15, 522–534, https://doi.org/10.1175/1520-0426(1998)015<0522:AIMMOM>2.0.CO;2, 1998.
Lévy, M., Couespel, D., Haëck, C., Keerthi, M. G., Mangolte, I., and Prend, C. J.: The Impact of Fine-Scale Currents on Biogeochemical Cycles in a Changing Ocean, Annu. Rev. Mar. Sci., 16, 191–215, https://doi.org/10.1146/annurev-marine-020723-020531, 2024.
Lin, H., Liu, Z., Hu, J., Menemenlis, D., and Huang, Y.: Characterizing meso- to submesoscale features in the South China Sea, Prog. Oceanogr., 188, 102420, https://doi.org/10.1016/j.pocean.2020.102420, 2020.
Liu, L., Jiang, X., Fei, J., and Li, Z.: Development and evaluation of a new merged sea surface height product from multi-satellite altimeters, Chinese Sci. Bull., 65, 1888–1897, https://doi.org/10.1360/TB-2020-0097, 2020.
Liu, L., Zhang, X., Fei, J., Li, Z., Shi, W., Wang, H., Jiang, X., Zhang, Z., and Lv, X.: Key Factors for Improving the Resolution of Mapped Sea Surface Height from Multi-Satellite Altimeters in the South China Sea, Remote Sensing, 15, 4275, https://doi.org/10.3390/rs15174275, 2023.
Lumpkin, R. and Elipot, S.: Surface drifter pair spreading in the North Atlantic, J. Geophys. Res., 115, 2010JC006338, https://doi.org/10.1029/2010JC006338, 2010.
Ma, X., Jing, Z., Chang, P., Liu, X., Montuoro, R., Small, R. J., Bryan, F. O., Greatbatch, R. J., Brandt, P., Wu, D., Lin, X., and Wu, L.: Western boundary currents regulated by interaction between ocean eddies and the atmosphere, Nature, 535, 533–537, https://doi.org/10.1038/nature18640, 2016.
Mahadevan, A.: The Impact of Submesoscale Physics on Primary Productivity of Plankton, Annu. Rev. Mar. Sci., 8, 161–184, https://doi.org/10.1146/annurev-marine-010814-015912, 2016.
Martin, A., Lemerle, E., Mccann, D., Macedo, K., Andrievskaia, D., Gommenginger, C., and Casal, T.: Towards mapping total currents and winds during the BioSWOT-Med campaign with the OSCAR airborne instrument, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16040, https://doi.org/10.5194/egusphere-egu24-16040, 2024.
Mason, E., Pascual, A., and McWilliams, J. C.: A New Sea Surface Height–Based Code for Oceanic Mesoscale Eddy Tracking, J. Atmos. Ocean. Tech., 31, 1181–1188, https://doi.org/10.1175/JTECH-D-14-00019.1, 2014.
Mcwilliams, J. C.: The vortices of two-dimensional turbulence, J. Fluid Mech., 219, 361–385, https://doi.org/10.1017/S0022112090002981, 1990.
Mkhinini, N., Coimbra, A. L. S., Stegner, A., Arsouze, T., Taupier-Letage, I., and Béranger, K.: Long-lived mesoscale eddies in the eastern Mediterranean Sea: Analysis of 20 years of AVISO geostrophic velocities, J. Geophys. Res.-Oceans, 119, 8603–8626, https://doi.org/10.1002/2014JC010176, 2014.
Morrow, R., Fu, L.-L., Ardhuin, F., Benkiran, M., Chapron, B., Cosme, E., d'Ovidio, F., Farrar, J. T., Gille, S. T., Lapeyre, G., Le Traon, P.-Y., Pascual, A., Ponte, A., Qiu, B., Rascle, N., Ubelmann, C., Wang, J., and Zaron, E. D.: Global Observations of Fine-Scale Ocean Surface Topography With the Surface Water and Ocean Topography (SWOT) Mission, Front. Mar. Sci., 6, 232, https://doi.org/10.3389/fmars.2019.00232, 2019.
Ni, Q., Zhai, X., Wilson, C., Chen, C., and Chen, D.: Submesoscale Eddies in the South China Sea, Geophys. Res. Lett., 48, e2020GL091555, https://doi.org/10.1029/2020GL091555, 2021.
Ohlmann, J. C., Molemaker, M. J., Baschek, B., Holt, B., Marmorino, G., and Smith, G.: Drifter observations of submesoscale flow kinematics in the coastal ocean, Geophys. Res. Lett., 44, 330–337, https://doi.org/10.1002/2016GL071537, 2017.
Okubo, A.: Horizontal dispersion of floatable particles in the vicinity of velocity singularities such as convergences, Deep Sea Research and Oceanographic Abstracts, 445–454, https://doi.org/10.1016/0011-7471(70)90059-8, 1970.
Pascual, A., Pujol, M.-I., Larnicol, G., Le Traon, P.-Y., and Rio, M.-H.: Mesoscale mapping capabilities of multisatellite altimeter missions: First results with real data in the Mediterranean Sea, J. Marine Syst., 65, 190–211, https://doi.org/10.1016/j.jmarsys.2004.12.004, 2007.
Pujol, M.-I., Faugère, Y., Taburet, G., Dupuy, S., Pelloquin, C., Ablain, M., and Picot, N.: DUACS DT2014: the new multi-mission altimeter data set reprocessed over 20 years, Ocean Sci., 12, 1067–1090, https://doi.org/10.5194/os-12-1067-2016, 2016.
Sadarjoen, I. A. and Post, F. H. P.: Detection, quantification, and tracking of vortices using streamline geometry, Computers and Graphics, 24, 333–341, https://doi.org/10.1016/S0097-8493(00)00029-7, 2000.
Su, D., Lin, P., Mao, H., Wu, J., Liu, H., Cui, Y., and Qiu, C.: Features of Slope Intrusion Mesoscale Eddies in the Northern South China Sea, J. Geophys. Res.-Oceans, 125, e2019JC015349, https://doi.org/10.1029/2019JC015349, 2020.
Taburet, G., Sanchez-Roman, A., Ballarotta, M., Pujol, M.-I., Legeais, J.-F., Fournier, F., Faugere, Y., and Dibarboure, G.: DUACS DT2018: 25 years of reprocessed sea level altimetry products, Ocean Sci., 15, 1207–1224, https://doi.org/10.5194/os-15-1207-2019, 2019.
Ubelmann, C., Le Guillou, F., Ballarotta, M., Cosme, E., Metref, S., and Rio, M.-H.: Dynamical mapping of SWOT: performances from real observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10460, https://doi.org/10.5194/egusphere-egu24-10460, 2024.
Verger-Miralles, E., Mourre, B., Barceló-Llull, B., Gómez-Navarro, L., R. Tarry, D., Zarokanellos, N., and Pascual, A.: Analysis of fine-scale dynamics in the Balearic Sea through high-resolution observations and SWOT satellite data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17643, https://doi.org/10.5194/egusphere-egu24-17643, 2024.
Wang, J. and Fu, L.-L.: On the Long-Wavelength Validation of the SWOT KaRIn Measurement, J. Atmos. Ocean. Tech., 36, 843–848, https://doi.org/10.1175/JTECH-D-18-0148.1, 2019.
Wang, Y., Chen, X., Han, G., Jin, P., and Yang, J.: From ° to °: Influence of Spatial Resolution on Eddy Detection Using Altimeter Data, Remote Sensing, 14, 149, https://doi.org/10.3390/rs14010149, 2021.
Weiss, J.: The dynamics of enstrophy transfer in 2-dimensional hydrodynamics, Physica D, 273–294, https://doi.org/10.1016/0167-2789(91)90088-Q, 1991.
Wunsch, C. and Heimbach, P.: Dynamically and Kinematically Consistent Global Ocean Circulation and Ice State Estimates, in: International Geophysics, vol. 103, Elsevier, 553–579, https://doi.org/10.1016/B978-0-12-391851-2.00021-0, 2013.
Yu, X., Ponte, A. L., Elipot, S., Menemenlis, D., Zaron, E. D., and Abernathey, R.: Surface Kinetic Energy Distributions in the Global Oceans From a High-Resolution Numerical Model and Surface Drifter Observations, Geophys. Res. Lett., 46, 9757–9766, https://doi.org/10.1029/2019GL083074, 2019.
Zhang, X.: Code for paper “Advances in surface water and ocean topography for fine-scale eddy identification from altimeter sea surface height merging maps in the South China Sea”, Zenodo [code], https://doi.org/10.5281/zenodo.13629576, 2024a.
Zhang, X.: 2DVAR Dataset for paper “Advances in surface water and ocean topography for fine-scale eddy identification from altimeter sea surface height merging maps in the South China Sea”, Zenodo [data set], https://doi.org/10.5281/zenodo.11219285, 2024b.
Zhang, G., Chen, R., Li, L., Wei, H., and Sun, S.: Global trends in surface eddy mixing from satellite altimetry, Front. Mar. Sci., 10, 1157049, https://doi.org/10.3389/fmars.2023.1157049, 2023.
Zhang, Z. and Qiu, B.: Evolution of Submesoscale Ageostrophic Motions Through the Life Cycle of Oceanic Mesoscale Eddies, Geophys. Res. Lett., 45, 11847–11855, https://doi.org/10.1029/2018GL080399, 2018.
Zhang, Z., Miao, M., Qiu, B., Tian, J., Jing, Z., Chen, G., Chen, Z., and Zhao, W.: Submesoscale Eddies Detected by SWOT and Moored Observations in the Northwestern Pacific, Geophys. Res. Lett., 51, e2024GL110000, https://doi.org/10.1029/2024GL110000, 2024.
Zu, T., Xue, H., Wang, D., Geng, B., Zeng, L., Liu, Q., Chen, J., and He, Y.: Interannual variation of the South China Sea circulation during winter: intensified in the southern basin, Clim. Dynam., 52, 1917–1933, https://doi.org/10.1007/s00382-018-4230-3, 2019.
Short summary
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. The results show that 2DVAR (two-dimensional variation), a new mapping product, aligns more closely and with less error with the most advanced satellite observations than a widely used mapping product called AVISO (Archiving, Validation, and Interpretation of Satellite Oceanographic). The results suggest that 2DVAR detects minor ocean movements better, making it more valuable and reliable for ocean dynamic study.
Our research evaluated the precision of mapping the ocean's surface with combined data from a...