Advanced Studies in Coastal Ocean Observation

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Physical Oceanography".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 16507

Special Issue Editors


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Guest Editor
Laboratoire Océan Côtier, French Research Institute for Exploitation of the Sea (IFREMER), Centre Bretagne, 29280 Plouzané, France
Interests: coastal dynamics; coastal environment; physical oceanography; continental shelf and slope dynamics; observing networks

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Guest Editor
Laboratoire Environnement Ressources de Boulogne-sur-Mer, French Research Institute for Exploitation of the Sea (IFREMER), 62200 Boulogne-sur-Mer, France
Interests: dynamics and diversity of phytoplankton; harmful algal blooms; eutrophication; development and implementation of automated and high-resolution systems to support monitoring; Marine Strategy Framework Directive (MSFD)
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Special Issue Information

Dear Colleagues,

The coastal ocean and nearshore zones are complex environments which are currently suffering from the effects of anthropogenic pressure and climate change. The wide range of temporal and spatial scales involved in driving physical, biogeochemical and biological processes requires the development of dedicated observation strategies for coastal ocean areas that are able to capture regular events as well as abrupt changes (e.g., extreme events). In addition to contributing to key scientific challenges, these observing strategies are of the utmost importance for ecological assessment and, therefore, for environmental management. The purpose of the current Special Issue is to publish the most recent advances in the research dedicated to or based upon coastal ocean observation, which is implemented to explore the different aspects of this environment (e.g., hydrodynamics, sediment dynamics, biogeochemistry, and biology). Authors are welcome to submit high-quality papers that can address an ecosystemic approach or can be focused on targeted parameters (in the same vein as the essential ocean/biodiversity variables framework). Innovative and original research, technologies and methods for understanding and observing coastal oceans are encouraged.

Dr. Guillaume Charria
Dr. Alain Lefebvre
Guest Editors

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Keywords

  • coastal ocean
  • ocean observation
  • coastal ecosystems
  • technological developments
  • numerical developments
  • data integration
  • extreme events
  • in situ observation

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Published Papers (8 papers)

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Research

17 pages, 7485 KiB  
Article
Ocean Color Image Sequences Reveal Diurnal Changes in Water Column Stability Driven by Air–Sea Interactions
by Jason K. Jolliff, Travis A. Smith, Sherwin Ladner, Ewa Jarosz, Mark David Lewis, Stephanie Anderson, Sean McCarthy and Adam Lawson
J. Mar. Sci. Eng. 2023, 11(11), 2118; https://doi.org/10.3390/jmse11112118 - 6 Nov 2023
Viewed by 1419
Abstract
The southward propagation of cold-air frontal boundaries into the Gulf of Mexico region initiates a cascade of coupled air–sea processes that manifests along the coastlines as an apparent brightness anomaly in the ocean color signals. Our hypothesis is that the color anomaly is [...] Read more.
The southward propagation of cold-air frontal boundaries into the Gulf of Mexico region initiates a cascade of coupled air–sea processes that manifests along the coastlines as an apparent brightness anomaly in the ocean color signals. Our hypothesis is that the color anomaly is largely due to the turbulent resuspension of sedimentary particles. Initially, there is significant wind-driven ocean turbulence as the frontal boundary passes, followed by the potential for sustained convective instability due to significant heat losses from the ocean surface. These cold front events occur during boreal autumn, winter, and into early spring, and the latter episodes occur in the context of the seasonally recurring thermal stratification of shelf waters. Here, we show that as stratification reasserts thermal stability in the waning days of a cold front episode, daily to hourly ocean color patterns are temporally coherent with the air–sea heat flux changes and the resulting impact on water column stability. Concomitant results from a nested, data-assimilative, and two-way coupled ocean-atmosphere numerical modeling system provides both corroboration and insight into how surface air–sea fluxes and in-water turbulent mixing manifest as hourly changes in apparent surface water turbidity due to the potential excitation and settling of reflective particles. A simple model of particle mixing and settling driven by the simulated turbulence mimics patterns seen in the satellite image sequences. This study offers a preview of potential application areas that may emerge following the launch of a dedicated ocean color geostationary sensor. Full article
(This article belongs to the Special Issue Advanced Studies in Coastal Ocean Observation)
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36 pages, 898 KiB  
Article
Fit-for-Purpose Information for Offshore Wind Farming Applications—Part-II: Gap Analysis and Recommendations
by Johannes Schulz-Stellenfleth, Anouk Blauw, Lauri Laakso, Baptiste Mourre, Jun She and Henning Wehde
J. Mar. Sci. Eng. 2023, 11(9), 1817; https://doi.org/10.3390/jmse11091817 - 18 Sep 2023
Cited by 2 | Viewed by 1886
Abstract
Offshore wind energy installations in coastal areas have grown massively over the last decade. This development comes with a large number of technological, environmental, economic, and scientific challenges, which need to be addressed to make the use of offshore wind energy sustainable. One [...] Read more.
Offshore wind energy installations in coastal areas have grown massively over the last decade. This development comes with a large number of technological, environmental, economic, and scientific challenges, which need to be addressed to make the use of offshore wind energy sustainable. One important component in these optimization activities is suitable information from observations and numerical models. The purpose of this study is to analyze the gaps that exist in the present monitoring systems and their respective integration with models. This paper is the second part of two manuscripts and uses results from the first part about the requirements for different application fields. The present solutions to provide measurements for the required information products are described for several European countries with growing offshore wind operations. The gaps are then identified and discussed in different contexts, like technology evolution, trans-European monitoring and modeling initiatives, legal aspects, and cooperation between industry and science. The monitoring gaps are further quantified in terms of missing observed quantities, spatial coverage, accuracy, and continuity. Strategies to fill the gaps are discussed, and respective recommendations are provided. The study shows that there are significant information deficiencies that need to be addressed to ensure the economical and environmentally friendly growth of the offshore wind farm sector. It was also found that many of these gaps are related to insufficient information about connectivities, e.g., concerning the interactions of wind farms from different countries or the coupling between physical and biological processes. Full article
(This article belongs to the Special Issue Advanced Studies in Coastal Ocean Observation)
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23 pages, 2810 KiB  
Article
Fit-for-Purpose Information for Offshore Wind Farming Applications—Part-I: Identification of Needs and Solutions
by Jun She, Anouk Blauw, Lauri Laakso, Baptiste Mourre, Johannes Schulz-Stellenfleth and Henning Wehde
J. Mar. Sci. Eng. 2023, 11(8), 1630; https://doi.org/10.3390/jmse11081630 - 21 Aug 2023
Cited by 5 | Viewed by 2031
Abstract
The rapid expansion of offshore wind farms (OWFs) in European seas is accompanied by many challenges, including efficient and safe operation and maintenance, environmental protection, and biodiversity conservation. Effective decision-making for industry and environmental agencies relies on timely, multi-disciplinary marine data to assess [...] Read more.
The rapid expansion of offshore wind farms (OWFs) in European seas is accompanied by many challenges, including efficient and safe operation and maintenance, environmental protection, and biodiversity conservation. Effective decision-making for industry and environmental agencies relies on timely, multi-disciplinary marine data to assess the current state and predict the future state of the marine system. Due to high connectivity in space (land–estuarial–coastal sea), socioeconomic (multi-sectoral and cross-board), and environmental and ecological processes in sea areas containing OWFs, marine observations should be fit for purpose in relation to multiple OWF applications. This study represents an effort to map the major observation requirements (Part-I), identify observation gaps, and recommend solutions to fill those gaps (Part-II) in order to address multi-dimension challenges for the OWF industry. In Part-I, six targeted areas are selected, including OWF operation and maintenance, protection of submarine cables, wake and lee effects, transport and security, contamination, and ecological impact assessments. For each application area, key information products are identified, and integrated modeling–monitoring solutions for generating the information products are proposed based on current state-of-the-art methods. The observation requirements for these solutions, in terms of variables and spatial and temporal sampling needs, are therefore identified. Full article
(This article belongs to the Special Issue Advanced Studies in Coastal Ocean Observation)
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24 pages, 8327 KiB  
Article
Estimation of Seawater Hydrophysical Characteristics from Thermistor Strings and CTD Data in the Sea of Japan Shelf Zone
by Igor Yaroshchuk, Alexandra Kosheleva, Alexander Lazaryuk, Grigory Dolgikh, Alexander Pivovarov, Aleksandr Samchenko, Alex Shvyrev, Oleg Gulin and Roman Korotchenko
J. Mar. Sci. Eng. 2023, 11(6), 1204; https://doi.org/10.3390/jmse11061204 - 9 Jun 2023
Cited by 2 | Viewed by 1713
Abstract
The knowledge of salinity in a specific sea area with high accuracy is required to solve several acoustic and hydrophysical problems on the ocean shelf. Unlike temperature, which can be measured continuously for a long time, with, for example, thermistor strings (thermostrings), salinity [...] Read more.
The knowledge of salinity in a specific sea area with high accuracy is required to solve several acoustic and hydrophysical problems on the ocean shelf. Unlike temperature, which can be measured continuously for a long time, with, for example, thermistor strings (thermostrings), salinity values of required accuracy can be obtained only using CTD profiling. This is why methods of estimating salinity from temperature could be helpful. In this paper, the authors propose using the regression method for solving this type of problem and demonstrate the efficiency of this method using examples of temperature measurements from anchored thermostrings. For the correct construction of regressions, the authors analyzed the errors of CTD measurements and suggested a method for the dynamic correction of raw CTD data. From CTD profiling datasets of 12 years (2011–2022), after their dynamic correction, the authors obtained regression polynomial formulas for calculating salinity from temperature and studied data stability in space and time at the hydrophysical test site, located in the shelf zone of the Sea of Japan. The authors consider this method efficient and applicable in solving a variety of acoustic and hydrophysical problems. Full article
(This article belongs to the Special Issue Advanced Studies in Coastal Ocean Observation)
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17 pages, 3091 KiB  
Article
Analysis of the Distribution and Seasonal Variability of the South China Sea Water Masses Based on the K-means Cluster Method
by Shanshan Jin, Xunwei Nie, Guanlin Wang, Fei Teng and Tengfei Xu
J. Mar. Sci. Eng. 2023, 11(3), 485; https://doi.org/10.3390/jmse11030485 - 24 Feb 2023
Cited by 2 | Viewed by 2293
Abstract
Influenced by local mixing and coastal runoff, water masses in the South China Sea degenerate significantly. The K-means algorithm is used to classify the water masses based on WOD13 temperature and salinity observations from 1966 to 2013 because its principle is consistent with [...] Read more.
Influenced by local mixing and coastal runoff, water masses in the South China Sea degenerate significantly. The K-means algorithm is used to classify the water masses based on WOD13 temperature and salinity observations from 1966 to 2013 because its principle is consistent with the definition of a shallow water mass. The numbers and initial centers of the water masses are determined using functions of in-cluster distance and density values. The result shows that there are ten water masses in the South China Sea. In combination with the T-S scatter diagram, the properties of the South China Sea water masses were analyzed, including their distribution, the seasonal variability, and the degeneration processes. The temperatures of water masses were higher in summer and lower in winter, with the amplitudes of variation gradually reduced from the surface to the bottom. The seasonal variation in salinity of the surface water masses was high in winter and low in summer, which mainly depends on the amount of river discharge and precipitation. The subsurface water masses were strongly affected by water from the Pacific Ocean; thus, the seasonal variability of these water masses is weak, especially for the intermediate water mass that characterized by prominent low salinity. The water mass formed by the Kuroshio water invading the South China Sea has insignificant seasonal variations in temperature and salinity. The properties and seasonal variabilities of the water masses derived from the K-means algorithm are in agreement with the existing conclusions, suggesting that the improved K-means algorithm is efficient and accurate in the shallow water mass division. Full article
(This article belongs to the Special Issue Advanced Studies in Coastal Ocean Observation)
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17 pages, 5781 KiB  
Article
Fitting Cotidal Charts of Eight Major Tidal Components in the Bohai Sea, Yellow Sea Based on Chebyshev Polynomial Method
by Qixiang Wang, Yibo Zhang, Yonggang Wang, Minjie Xu and Xianqing Lv
J. Mar. Sci. Eng. 2022, 10(9), 1219; https://doi.org/10.3390/jmse10091219 - 1 Sep 2022
Cited by 5 | Viewed by 1917
Abstract
High-precision tidal harmonic constants are necessary for studies involving tides. This study proposes a new method combined with the adjoint assimilation model and the Chebyshev polynomial fitting (CPF) method to obtain the tidal harmonic constants in the shallow-water region of the Bohai and [...] Read more.
High-precision tidal harmonic constants are necessary for studies involving tides. This study proposes a new method combined with the adjoint assimilation model and the Chebyshev polynomial fitting (CPF) method to obtain the tidal harmonic constants in the shallow-water region of the Bohai and Yellow Sea (BYS). Based on the CPF method, the full-field harmonic constants and reliable cotidal charts of the eight major constituents (M2, S2, K1, O1, N2, K2, P1 and Q1) were fitted from the X-TRACK products briefly and this method was effectively for coastal conditions. Compared with the observations of the X-TRACK products and tidal gauges, for the M2 constituent, the TPXO9, Finite Element Solutions 2014 (FES2014), National Astronomical Observatory 99b (NAO.99b) and Empirical Ocean Tide 20 (EOT20) models yield the root-mean-square errors (RMSEs) of 18.50, 7.31, 18.73 and 13.32 cm, respectively, while the CPF method yields an RMSE of 10.74 cm. These results indicate that the CPF method could maintain high resolution and obtain accurate cotidal charts consistent with the simulations of the four models in shallow-water regions. Full article
(This article belongs to the Special Issue Advanced Studies in Coastal Ocean Observation)
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16 pages, 5249 KiB  
Article
Application of the Trigonometric Polynomial Interpolation for the Estimation of the Vertical Eddy Viscosity Coefficient Based on the Ekman Adjoint Assimilation Model
by Xinping Wu, Minjie Xu, Guandong Gao, Baoshu Yin and Xianqing Lv
J. Mar. Sci. Eng. 2022, 10(8), 1165; https://doi.org/10.3390/jmse10081165 - 22 Aug 2022
Cited by 3 | Viewed by 2165
Abstract
In this study, a triangular polynomial interpolation (TPI) scheme was developed to estimate the vertical eddy viscosity coefficient (VEVC) on the basis of the Ekman model with adjoint assimilation. In the twin experiments, the advantages and disadvantages of estimating the VEVC using the [...] Read more.
In this study, a triangular polynomial interpolation (TPI) scheme was developed to estimate the vertical eddy viscosity coefficient (VEVC) on the basis of the Ekman model with adjoint assimilation. In the twin experiments, the advantages and disadvantages of estimating the VEVC using the TPI scheme under different factors are discussed. The results indicated that (1) the TPI scheme proves to be better than the cubic spline interpolation (CSI) and Cressman interpolation (CI) schemes; (2) the inversion results are more sensitive to observations from upper ocean layers than those from lower layers, and the TPI scheme is less likely to be influenced by missing data; (3) for various boundary layer depths, the inversion results of the TPI scheme remain consistent with the given distributions; (4) the inversion results can be influenced considerably by observational errors, and the TPI scheme is more resistant to noise than the CSI and CI schemes; and (5) the inversion accuracy of the TPI scheme can be improved by selecting the temporal wind stress drag coefficients. In practical experiments, the adjoint method with the TPI scheme was developed to estimate the Ekman currents by assimilating the observations from a buoy stationed in the Yellow Sea. The results showed the successful estimation of the VEVC and demonstrated that more precise current velocities can be obtained with this estimation scheme. In summary, this study provides a useful approach for the effective estimation of the VEVC. Full article
(This article belongs to the Special Issue Advanced Studies in Coastal Ocean Observation)
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20 pages, 8723 KiB  
Article
Assessment of Three-Dimensional Interpolation Method in Hydrologic Analysis in the East China Sea
by Yuchun Gao, Junting Guo, Jianfeng Wang and Xianqing Lv
J. Mar. Sci. Eng. 2022, 10(7), 877; https://doi.org/10.3390/jmse10070877 - 26 Jun 2022
Cited by 3 | Viewed by 1740
Abstract
The water mass in the East China Sea (ECS) shelf has a complicated three-dimensional (3D) hydrologic structure. However, previous studies mostly concentrated on the sea surface based on the sparse in situ and incomplete satellite-derived observations. Therefore, the 3D interpolation technology was introduced [...] Read more.
The water mass in the East China Sea (ECS) shelf has a complicated three-dimensional (3D) hydrologic structure. However, previous studies mostly concentrated on the sea surface based on the sparse in situ and incomplete satellite-derived observations. Therefore, the 3D interpolation technology was introduced for the reconstruction of hydrologic structure in the ECS shelf using in situ temperature and salinity observations in the summer and autumn of 2010 to 2011. Considering the high accuracy and good fitness of the radial basis function (RBF) methods, we applied the RBF methods to the in situ observations to completely reconstruct the 3D hydrologic fields. Other 3D interpolation methods and 2D methods were also tested for a comparison. The cubic and thin plate spline RBFs were recommended because their mean absolute error (MAE) in the 10-fold cross-validation experiments maintained the order of ~10−2. The 3D RBF reconstructions showed a reasonable 3D hydrologic structure and extra details of the water masses in the ECS shelf. It also helps evaluate regional satellite-derived sea surface temperature (SST). Comparisons between the interpolated and satellite-derived SST indicates that the large bias of satellite-derived SST in the daytime corresponds to weak mixing during low-speed wind and shows seasonal variation. Full article
(This article belongs to the Special Issue Advanced Studies in Coastal Ocean Observation)
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