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Remote Sensing Data Assimilation in Ocean Modelling

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

Deadline for manuscript submissions: closed (26 September 2023) | Viewed by 2624

Special Issue Editors


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Guest Editor
Department of Oceanography, Chonnam National University, Gwangju 61186, Korea
Interests: ocean modeling; data assimilation; currents and mesoscale eddy from remote sensing

E-Mail Website
Guest Editor
Division of Earth Environmental System Science, Pukyong National University, Pusan 48531, Korea
Interests: physical oceanography; numerical modeling; data assimilation

Special Issue Information

Dear Colleagues,

Ocean data assimilation is a mathematical and statistical process to find the best estimate of the ocean state by combining the ocean observation data with the ocean model simulations. Remote sensing data are assimilated into ocean model to improve predictability and to correct bias in an ocean modeling system. Satellite observation data, such as sea surface temperature and sea surface height data, are considered essential for ocean reanalysis and prediction. Recently, remotely sensed ocean color data have been assimilated to correct biogeochemistry in ocean models.  Remote sensing data are also used for validation of ocean modeling results.

In this Special Issue, we invite studies focusing on assimilation methods for new remote sensing data, the effects of various remote sensing datasets assimilation on predictability of ocean models, and designing of remote sensing observational system for operational oceanography using ocean modeling and data assimilation.

Original research articles are solicited over a wide range of topics which may focus on but are not limited to:

  • The most recent advances in assimilation of temperature, salinity, sea surface height anomaly, currents, waves, ocean colour, sea ice, high-frequency radar, and synthetic aperture radar data based on remote sensing
  • Development of assimilation methods for new remote sensing data
  • Coupled data assimilation in ocean modelling
  • Improvement of search and rescue applications in the ocean
  • Ocean reanalysis incorporating remote sensing data
  • Improvement of ocean remote sensing data product using ocean modelling and data assimilation
  • Use of ocean remote sensing data for validation and bias correction in ocean modeling
  • Design of remote sensing observation system for operational oceanography.

Prof. Dr. Byoung-Ju Choi
Dr. Young-Ho Kim
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • remote sensing data
  • data assimilation
  • ocean modeling
  • ocean reanalysis
  • satellite observations
  • operational oceanography

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Published Papers (1 paper)

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Research

22 pages, 8595 KiB  
Article
Mesoscale Eddy Chain Structures in the Black Sea and Their Interaction with River Plumes: Numerical Modeling and Satellite Observations
by Konstantin Korotenko, Alexander Osadchiev and Vasiliy Melnikov
Remote Sens. 2023, 15(6), 1606; https://doi.org/10.3390/rs15061606 - 15 Mar 2023
Viewed by 2031
Abstract
The northeastern part of the cyclonic Rim Current, which encircles the entire basin of the Black Sea, is named as the Northeast Caucasian Current. It periodically approaches the coast, triggering the formation of topographic generated eddies, including long-living isolated anticyclonic eddies and short-living [...] Read more.
The northeastern part of the cyclonic Rim Current, which encircles the entire basin of the Black Sea, is named as the Northeast Caucasian Current. It periodically approaches the coast, triggering the formation of topographic generated eddies, including long-living isolated anticyclonic eddies and short-living multiple anticyclonic eddies, which group and merge into eddy chain structures. Both types of eddies affect coastal dynamics and interact with multiple river plumes formed in the study area. This interaction determines cross- and along-shelf transport of fluvial water, enhancing the processes of self-cleaning of the coastal zone. In this study, we used a 3D low-dissipation model, DieCAST, coupled with a Lagrangian particle tracking model, and supported by analysis of satellite images, to study the generation and evolution of eddy chains and their interaction with river plumes along the Caucasian coast. Using Fourier and wavelet analyses of kinetic energy time series, we revealed that the occurrence of eddy chains ranges from 10 to 20 days, predominantly in spring-summer season in the area between the Pitsunda and Iskuria capes. During the period of eddy merging, the angular velocities of the orbiting eddies reach maximal values of 7 × 10−6 rad s−1, while after merging, the angular velocities of the resulting eddies decreased to 5 × 10−6 rad s−1. Numerical experiments with Lagrangian particle tracking showed that eddy chains effectively capture water from river plumes localized along the coast and then eject it to the open sea. This process provides an effective mechanism of cross-shelf transport of fluvial water, albeit less intense than the influence of isolated anticyclonic eddies, which are typical for autumn-winter season. Full article
(This article belongs to the Special Issue Remote Sensing Data Assimilation in Ocean Modelling)
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