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Remote Sensing of Ocean Surface Currents: Measurement, Validation and Applications

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: 15 November 2024 | Viewed by 6489

Special Issue Editors


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Guest Editor
Department of Ocean Engineering, Pukyoung National University, Busan, Republic of Korea
Interests: multi-scale oceanic flows; coastal structures and waves; contaminant dispersion; turbulence; physical processes in inland and coastal waters

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Guest Editor
Department of Earth, Ocean and Atmospheric Science, Florida State University, EOAS Building 1011 Academic Way, Tallahassee, FL 32306, USA
Interests: remote sensing of the surface and boundary layer; boundary layers (ocean and atmosphere); air–sea interaction; the observing system
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Special Issue Information

Dear Colleagues,

Ocean surface currents play a pivotal role in Earth's climate system and marine ecosystems, as well as in human activities. The accurate monitoring and understanding of surface currents are essential for a wide range of applications, including weather forecasting, coastal management, shipping, and search and rescue operations. Remote sensing technologies offer unique capabilities for observing ocean surface currents, ranging from the submesoscale to mesoscale, and provide critical information on the underlying processes involved in air–sea interactions.

This Special Issue invites contributions that explore the latest advances, challenges and applications in the remote sensing of ocean surface currents. Topics of interest include, but are not limited to, the development and improvement of remote sensing techniques such as Synthetic Aperture Radar (SAR), scatterometry, altimetry, and optical remote sensing, as well as emerging observational platforms, including autonomous underwater vehicles (AUVs), gliders, and other in situ measurement systems. Submissions addressing air–sea interactions and upper ocean dynamic measurements using these platforms are particularly encouraged. Furthermore, we welcome studies focusing on the validation and uncertainty assessment of remote sensing-derived surface current data using various validation techniques such as drifters, moored buoys, and other in situ observations. Contributions may address the challenges associated with spatial and temporal resolution, accuracy, data coverage, and the impact of environmental factors on accuracy and detection.

This Special Issue aims to bring together researchers, practitioners, and stakeholders from diverse fields to share their knowledge, insights, and experiences, fostering interdisciplinary collaboration and promoting the advancement of remote sensing techniques for the study and management of ocean surface currents.

Dr. Jun Myoung Choi
Prof. Dr. Mark Bourassa
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • ocean surface current
  • remote sensing
  • altimetry
  • scatterometry
  • optical remote sensing
  • synthetic aperture radar
  • autonomous underwater vehicles
  • air–sea interactions
  • data validation

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Published Papers (5 papers)

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20 pages, 7943 KiB  
Article
Decomposition of Submesoscale Ocean Wave and Current Derived from UAV-Based Observation
by Sin-Young Kim, Jong-Seok Lee, Youchul Jeong and Young-Heon Jo
Remote Sens. 2024, 16(13), 2275; https://doi.org/10.3390/rs16132275 - 21 Jun 2024
Viewed by 597
Abstract
The consecutive submesoscale sea surface processes observed by an unmanned aerial vehicle (UAV) were used to decompose into spatial waves and current features. For the image decomposition, the Fast and Adaptive Multidimensional Empirical Mode Decomposition (FA-MEMD) method was employed to disintegrate multicomponent signals [...] Read more.
The consecutive submesoscale sea surface processes observed by an unmanned aerial vehicle (UAV) were used to decompose into spatial waves and current features. For the image decomposition, the Fast and Adaptive Multidimensional Empirical Mode Decomposition (FA-MEMD) method was employed to disintegrate multicomponent signals identified in sea surface optical images into modulated signals characterized by their amplitudes and frequencies. These signals, referred to as Bidimensional Intrinsic Mode Functions (BIMFs), represent the inherent two-dimensional oscillatory patterns within sea surface optical data. The BIMFs, separated into seven modes and a residual component, were subsequently reconstructed based on the physical frequencies. A two-dimensional Fast Fourier Transform (2D FFT) for each high-frequency mode was used for surface wave analysis to illustrate the wave characteristics. Wavenumbers (Kx, Ky) ranging between 0.01–0.1 radm−1 and wave directions predominantly in the northeastward direction were identified from the spectral peak ranges. The Optical Flow (OF) algorithm was applied to the remaining consecutive low-frequency modes as the current signal under 0.1 Hz for surface current analysis and to estimate a current field with a 1 m spatial resolution. The accuracy of currents in the overall region was validated with in situ drifter measurements, showing an R-squared (R2) value of 0.80 and an average root-mean-square error (RMSE) of 0.03 ms−1. This study proposes a novel framework for analyzing individual sea surface dynamical processes acquired from high-resolution UAV imagery using a multidimensional signal decomposition method specialized in nonlinear and nonstationary data analysis. Full article
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17 pages, 7771 KiB  
Article
Near-Surface Dispersion and Current Observations Using Dye, Drifters, and HF Radar in Coastal Waters
by Keunyong Kim, Hong Thi My Tran, Kyu-Min Song, Young Baek Son, Young-Gyu Park, Joo-Hyung Ryu, Geun-Ho Kwak and Jun Myoung Choi
Remote Sens. 2024, 16(11), 1985; https://doi.org/10.3390/rs16111985 - 31 May 2024
Viewed by 691
Abstract
This study explores the near-surface dispersion mechanisms of contaminants in coastal waters, leveraging a comprehensive method that includes using dye and drifters as tracers, coupled with diverse observational platforms like drones, satellites, in situ sampling, and HF radar. The aim is to deepen [...] Read more.
This study explores the near-surface dispersion mechanisms of contaminants in coastal waters, leveraging a comprehensive method that includes using dye and drifters as tracers, coupled with diverse observational platforms like drones, satellites, in situ sampling, and HF radar. The aim is to deepen our understanding of surface currents’ impact on contaminant dispersion, thereby improving predictive models for managing environmental incidents such as pollutant releases. Rhodamine WT dye, chosen for its significant fluorescent properties and detectability, along with drifter data, allowed us to investigate the dynamics of near-surface physical phenomena such as the Ekman current, Stokes drift, and wind-driven currents. Our research emphasizes the importance of integrating scalar tracers and Lagrangian markers in experimental designs, revealing differential dispersion behaviors due to near-surface vertical shear caused by the Ekman current and Stokes drift. During slow-current conditions, the elongation direction of the dye patch aligned well with the direction of a depth-averaged Ekman spiral, or Ekman transport. Analytical calculations of vertical shear, based on the Ekman current and Stokes drift, closely matched those derived from tracer observations. Over a 7 h experiment, the vertical diffusivity near the surface was first observed at the early stages of scalar mixing, with a value of 1.9×104 m2/s, and the horizontal eddy diffusivity of the dye patch and drifters reached the order of 1 m2/s at a 1000 m length scale. Particle tracking models demonstrate that while HF radar currents can effectively predict the trajectories of tracers near the surface, incorporating near-surface currents, including the Ekman current, Stokes drift, and windage, is essential for a more accurate prediction of the fate of surface floats. Full article
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23 pages, 10525 KiB  
Article
Ocean Satellite Data Fusion for High-Resolution Surface Current Maps
by Alisa Kugusheva, Hannah Bull, Evangelos Moschos, Artemis Ioannou, Briac Le Vu and Alexandre Stegner
Remote Sens. 2024, 16(7), 1182; https://doi.org/10.3390/rs16071182 - 28 Mar 2024
Cited by 2 | Viewed by 1463
Abstract
Real-time reconstruction of ocean surface currents is a challenge due to the complex, non-linear dynamics of the ocean, the small number of in situ measurements, and the spatio-temporal heterogeneity of satellite altimetry observations. To address this challenge, we introduce HIRES-CURRENTS-Net, an operational real-time [...] Read more.
Real-time reconstruction of ocean surface currents is a challenge due to the complex, non-linear dynamics of the ocean, the small number of in situ measurements, and the spatio-temporal heterogeneity of satellite altimetry observations. To address this challenge, we introduce HIRES-CURRENTS-Net, an operational real-time convolutional neural network (CNN) model for daily ocean current reconstruction. This study focuses on the Mediterranean Sea, a region where operational models have great difficulty predicting surface currents. Notably, our model showcases higher accuracy compared to commonly used alternative methods. HIRES-CURRENTS-Net integrates high-resolution measurements from the infrared or visible spectrum—high resolution Sea Surface Temperature (SST) or chlorophyll (CHL) images—in addition to the low-resolution Sea Surface Height (SSH) maps derived from satellite altimeters. In the first stage, we apply a transfer learning method which uses a high-resolution numerical model to pre-train our CNN model on simulated SSH and SST data with synthetic clouds. The observation of System Simulation Experiments (OSSEs) offers us a sufficient training dataset with reference surface currents at very high resolution, and a model trained on this data can then be applied to real data. In the second stage, to enhance the real-time operational performance of our model over previous methods, we fine-tune the CNN model on real satellite data using a novel pseudo-labeling strategy. We validate HIRES-CURRENTS-Net on real data from drifters and demonstrate that our data-driven approach proves effective for real-time sea surface current reconstruction with potential operational applications such as ship routing. Full article
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15 pages, 2944 KiB  
Article
Increasing the Observability of Near Inertial Oscillations by a Future ODYSEA Satellite Mission
by Jinbo Wang, Hector Torres, Patrice Klein, Alexander Wineteer, Hong Zhang, Dimitris Menemenlis, Clement Ubelmann and Ernesto Rodriguez
Remote Sens. 2023, 15(18), 4526; https://doi.org/10.3390/rs15184526 - 14 Sep 2023
Cited by 2 | Viewed by 1378
Abstract
Near Inertial Oscillations (NIOs) are ocean oscillations forced by intermittent winds. They are most energetic at mid-latitudes, particularly in regions with atmospheric storm tracks. Wind-driven, large-scale NIOs are quickly scattered by ocean mesoscale eddies (with sizes ranging from 100 to 400 km), causing [...] Read more.
Near Inertial Oscillations (NIOs) are ocean oscillations forced by intermittent winds. They are most energetic at mid-latitudes, particularly in regions with atmospheric storm tracks. Wind-driven, large-scale NIOs are quickly scattered by ocean mesoscale eddies (with sizes ranging from 100 to 400 km), causing a significant portion of the NIO energy to propagate into the subsurface ocean interior. This kinetic energy pathway illustrates that the wind energy input to NIO is critical for maintaining deep ocean stratification and thus closing the total energy budget, as emphasised by numerous modelling studies. However, this wind energy input to NIO remains poorly observed on a global scale. A remote sensing approach that observes winds and ocean currents co-located in time and space with high resolution is necessary to capture the intermittent air-sea coupling. The current satellite observations do not meet these requirements. This study assesses the potential of a new satellite mission concept, Ocean DYnamics and Surface Exchange with the Atmosphere (OSYSEA), to recover wind-forced NIOs from co-located winds and currents. To do this, we use an Observation System Simulation Experiment (OSSE) based on hourly observations of ocean surface currents and surface winds from five surface moorings covering latitudes from 15° to 50°. ODYSEA wind and current observations are expected to have a spatial resolution of 10 km with about a 12 h sampling frequency in mid-latitudes. Results show that NIOs can be recovered with high accuracy using the ODYSEA spatial and temporal resolution, but only if observations are made over a wide area of 1800 km. A narrower swath (1000 km) may lead to significant aliasing. Full article
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15 pages, 3826 KiB  
Technical Note
Asymmetric Drifter Trajectories in an Anticyclonic Mesoscale Eddy
by Pengfei Tuo, Zhiyuan Hu, Shengli Chen, Jianyu Hu and Peining Yu
Remote Sens. 2023, 15(15), 3806; https://doi.org/10.3390/rs15153806 - 31 Jul 2023
Viewed by 1416
Abstract
The influences of sea surface wind on the oceanic mesoscale eddy are complex. By integrating our self-developed surface drifters with satellite observations, we examined the influence of sea surface wind on the distribution of water masses and biomass within the interior of an [...] Read more.
The influences of sea surface wind on the oceanic mesoscale eddy are complex. By integrating our self-developed surface drifters with satellite observations, we examined the influence of sea surface wind on the distribution of water masses and biomass within the interior of an anticyclonic eddy. Ten drifters were deployed in the northern South China Sea in the spring of 2021. Eventually, six were trapped in an anticyclonic mesoscale eddy for an extended period. Interestingly, the drifters’ trajectories were not symmetric around the eddy center, displaying a significant offset of the distance from the wind turns to the southerly wind. Particle tracking experiments demonstrated that this departure could mainly be attributed to wind-driven ageostrophic currents. This is due to the strength of wind-driven ageostrophic currents being more comparable to geostrophic currents when accompanied by a deflection between the directions of the wind-driven current and the eddy’s translation. The drifters’ derived data indicated that sub-mesoscale ageostrophic currents within the eddy contributed to this asymmetric trajectory, with Ekman and non-Ekman components playing a role. Furthermore, the evolution of ocean color data provided corroborating evidence of these dynamic processes, highlighting the importance of ageostrophic processes within mesoscale eddies. Full article
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