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Air-Sea Interaction and Climate Variability in the Ocean: Observations and Modeling Based on Remote Sensing Techniques

This special issue belongs to the section “Ocean Remote Sensing“.

Special Issue Information

Dear Colleagues,

The ocean and atmosphere are a complex coupled system, with air- sea interactions occurring on multiple spatial and temporal scales. The study of large-scale sea-air interactions has made remarkable achievements in the last half century. Small- to meso-scale air-sea interactions are current frontier scientific issues that play an important role in heat, water vapor, and momentum fluxes at the sea-air interface. The use of high-resolution observations or model data to study the processes and mechanisms of small- and meso-scale air-sea interactions are expected to deepen the understanding of the global climate system and effectively improve the accuracy of air-sea coupled models and climate models.

Remote sensing observations of the ocean have played a critical role in our understanding of the real ocean and air-sea interaction system and have greatly contributed to the study of global air-sea interactions. The accumulated large number of high-resolution, high-quality remote sensing datasets brings a novel opportunity to break the bottleneck of small- and meso-scale air- sea interaction studies and deepen the understanding of the global climate system. This special issue focus on the air-sea interaction and climate variability in the high-resolution ocean observations and modeling based on remote sensing techniques, aiming to provide new insights and methods in the study of small- and meso-scale sea-air interaction processes and mechanisms.

Nowadays, an increasing amount of high-resolution ocean remote sensing data, including sea surface temperature, salinity, precipitation, winds, sea level height, seawater color, and soon-to-be-realized total currents, provide new opportunities to better understand sea-air interactions and climate variability. This Special Issue calls for innovative research results, methods and models for air- sea interactions and climate change based on remote sensing. Acceptable topics include, but are not limited to, processes, mechanisms, and drivers of regional or global sea-air interactions, model simulation and parameterization schemes, and drivers of climate change, methods and key parameters for improving climate model simulation results, etc.

Dr. Yuhong Zhang
Dr. Xiaomei Liao
Prof. Dr. Vladimir N. Kudryavtsev
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 250 words) can be sent to the Editorial Office for assessment.

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

  • air-sea interactions
  • climate variability
  • oceanic dynamics
  • small- and meso-scale processes
  • remote sensing observations
  • high-resolution modeling

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Remote Sens. - ISSN 2072-4292