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 2030
Special Issue Editors
Interests: ocean modeling; data assimilation; currents and mesoscale eddy from remote sensing
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
