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Linking Upper Ocean Dynamics with Extreme Weather and Climate Events over the Ocean (Second Edition)

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

Deadline for manuscript submissions: 30 October 2025 | Viewed by 5172

Special Issue Editors

Dr. Hailun He

E-Mail Website
Guest Editor
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
Interests: tropical cyclone–ocean interaction; upper ocean dynamics; ocean modelling; deep learning; wave–current interaction
Dr. Gad Levy

E-Mail Website
Guest Editor
NorthWest Research Associates, Seattle, WA 98105, USA
Interests: remote sensing; weather and climate prediction and modeling; meteorology; climatology; ocean–atmosphere and air–sea interactions
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Extreme weather and climate events have a huge impact on the earth system and on human society. These occurrences often lead to natural hazards, underscoring the significance of studying such extreme weather and climate phenomena.

In the coupled earth system, extreme weather events and climate patterns trigger responses evident in the upper ocean. The feedback, whether positive or negative, plays a crucial role in the development of extreme weather and climate events. Furthermore, the complexities of ocean dynamics, spanning multiple scales, further emphasize the importance of understanding the interplay between ocean and extreme weather and climate events. New methodological and technological developments, including but not limited to, remote sensing, in situ observation, numerical modelling and artificial intelligence, have facilitated our understanding of these extreme events.

This Special Issue aims to publish research articles addressing the role the ocean plays in the occurrence, development, and prediction of extreme events. Field work, satellite remote sensing, theoretical derivation, and numerical modelling studies, aimed at better understanding the phenomena and processes of coupled atmosphere–ice–ocean system and their related interactions are all welcome. As a new path, deep learning or other new artificial intelligence technologies are particularly welcome.

Dr. Hailun He
Dr. Gad Levy
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

  • extreme weather and climate
  • air–sea interaction
  • tropical cyclone
  • extratropical cyclone
  • ocean dynamics
  • biological response
  • in situ observation
  • remote sensing observation
  • ocean modelling
  • operational forecast

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Related Special Issue

Published Papers (4 papers)

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Research

19 pages, 5267 KiB  
Article
Remote-Sensed Spatio-Temporal Study of the Tropical Cyclone Freddy Exceptional Case
by Giuseppe Ciardullo, Leonardo Primavera, Fabrizio Ferrucci, Fabio Lepreti and Vincenzo Carbone
Remote Sens. 2025, 17(6), 981; https://doi.org/10.3390/rs17060981 - 11 Mar 2025
Viewed by 564
Abstract
Dynamical processes during the different stages of evolution of tropical cyclones play crucial roles in their development and intensification, making them one of the most powerful natural forces on Earth. Given their classification as extreme atmospheric events resulting from multiple interacting factors, it [...] Read more.
Dynamical processes during the different stages of evolution of tropical cyclones play crucial roles in their development and intensification, making them one of the most powerful natural forces on Earth. Given their classification as extreme atmospheric events resulting from multiple interacting factors, it is significant to study their dynamical behavior and the nonlinear effects generated by emerging structures during scales and intensity transitions, correlating them with the surrounding environment. This study investigates the extraordinary and record-breaking case of Tropical Cyclone Freddy (2023 Indian Ocean tropical season) from a purely dynamical perspective, examining the superposition of energetic structures at different spatio-temporal scales, by mainly considering thermal fluctuations over 12 days of its evolution. The tool used for this investigation is the Proper Orthogonal Decomposition (POD), in which a set of empirical basis functions is built up, retaining the maximum energetic content of the turbulent flow. The method is applied on a satellite imagery dataset acquired from the SEVIRI radiometer onboard the Meteosat Second Generation-8 (MSG-8) geostationary platform, from which the cloud-top temperature scalar field is remote sensed looking at the cloud’s associated system. For this application, considering Freddy’s very long life period and exceptionally wide path of evolution, reanalysis and tracking data archives are taken into account in order to create an appropriately dynamic spatial grid. Freddy’s eye is followed after its first shape formation with very high temporal resolution snapshots of the temperature field. The energy content in three different characteristic scale ranges is analyzed through the associated spatial and temporal component spectra, focusing both on the total period and on the transitions between different categories. The results of the analysis outline several interesting aspects of the dynamics of Freddy related to both its transitions stages and total period. The reconstructions of the temperature field point out that the most consistent vortexes are found in the outermost cyclonic regions and in proximity of the eyewall. Additionally, we find a significant consistency of the results of the investigation of the maximum intensity phase of Freddy’s life cycle, in the spatio-temporal characteristics of its dynamics, and in comparison with one analogous case study of the Faraji tropical cyclone. Full article
(This article belongs to the Special Issue Linking Upper Ocean Dynamics with Extreme Weather and Climate Events over the Ocean (Second Edition))
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35 pages, 20527 KiB  
Article
Dual Effects of Marine Heatwaves on Typhoon Intensity and Associated Heat Dissipation
by Thi-Kieu-Diem Nguyen and Po-Chun Hsu
Remote Sens. 2025, 17(6), 968; https://doi.org/10.3390/rs17060968 - 9 Mar 2025
Viewed by 915
Abstract
Based on the positions of 1027 typhoons that passed through the Western Pacific (WP), East China Sea (ECS), and South China Sea (SCS), the results indicate that the category of marine heatwaves (MHWs) significantly decreases or dissipates after a typhoon’s passage, with stronger [...] Read more.
Based on the positions of 1027 typhoons that passed through the Western Pacific (WP), East China Sea (ECS), and South China Sea (SCS), the results indicate that the category of marine heatwaves (MHWs) significantly decreases or dissipates after a typhoon’s passage, with stronger typhoons causing more pronounced dissipation. The presence of MHWs does not necessarily enhance typhoon intensity; in as many as 151 cases, typhoons weakened despite the presence of MHWs. Furthermore, case studies were conducted using three typhoons that traversed different regions—Hinnamnor (2022), Mawar (2023), and Koinu (2023)—to investigate the dual effects of MHWs on typhoon intensity and their dissipation using satellite observations and ocean reanalysis datasets. Results show that MHWs enhance typhoon intensity by increasing sea surface temperature (SST) and ocean heat content (OHC), while also strengthening stratification through a shallower mixed layer depth (MLD), creating favorable conditions for intensification. While MHWs may initially enhance typhoon intensity, the passage of a typhoon triggers intense vertical mixing and upwelling, which disrupts MHW structures and alters heat distribution, potentially leading to intensity fluctuations. The impact of MHWs on typhoon intensity varies in time and space, MHWs can sustain typhoon strength despite heat loss induced by the typhoon. Additionally, variations in OHC and the mean upper 100 m temperature (T100¯) were more pronounced in the inner-core region (R50) than in the outer-core region (R30), indicating that energy exchange is concentrated in the inner core, while broader air–sea interactions occur in the outer core. The results show that MHWs can enhance typhoon development by increasing stratification and SST but are also highly susceptible to rapid dissipation due to typhoon-induced impacts, forming a highly dynamic two-way interaction. Full article
(This article belongs to the Special Issue Linking Upper Ocean Dynamics with Extreme Weather and Climate Events over the Ocean (Second Edition))
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20 pages, 3531 KiB  
Article
Sea Surface Temperature Prediction Using ConvLSTM-Based Model with Deformable Attention
by Benyun Shi, Conghui Ge, Hongwang Lin, Yanpeng Xu, Qi Tan, Yue Peng and Hailun He
Remote Sens. 2024, 16(22), 4126; https://doi.org/10.3390/rs16224126 - 5 Nov 2024
Cited by 5 | Viewed by 1826
Abstract
Sea surface temperature (SST) prediction has received increasing attention in recent years due to its paramount importance in the various fields of oceanography. Existing studies have shown that neural networks are particularly effective in making accurate SST predictions by efficiently capturing spatiotemporal dependencies [...] Read more.
Sea surface temperature (SST) prediction has received increasing attention in recent years due to its paramount importance in the various fields of oceanography. Existing studies have shown that neural networks are particularly effective in making accurate SST predictions by efficiently capturing spatiotemporal dependencies in SST data. Among various models, the ConvLSTM framework is notably prominent. This model skillfully combines convolutional neural networks (CNNs) with recurrent neural networks (RNNs), enabling it to simultaneously capture spatiotemporal dependencies within a single computational framework. To overcome the limitation that CNNs primarily capture local spatial information, in this paper we propose a novel model named DatLSTM that integrates a deformable attention transformer (DAT) module into the ConvLSTM framework, thereby enhancing its ability to process more complex spatial relationships effectively. Specifically, the DAT module adaptively focuses on salient features in space, while ConvLSTM further captures the temporal dependencies of spatial correlations in the SST data. In this way, DatLSTM can adaptively capture complex spatiotemporal dependencies between the preceding and current states within ConvLSTM. To evaluate the performance of the DatLSTM model, we conducted short-term SST forecasts in the Bohai Sea region with forecast lead times ranging from 1 to 10 days and compared its efficacy against several benchmark models, including ConvLSTM, PredRNN, TCTN, and SwinLSTM. Our experimental results show that the proposed model outperforms all of these models in terms of multiple evaluation metrics short-term SST prediction. The proposed model offers a new predictive learning method for improving the accuracy of spatiotemporal predictions in various domains, including meteorology, oceanography, and climate science. Full article
(This article belongs to the Special Issue Linking Upper Ocean Dynamics with Extreme Weather and Climate Events over the Ocean (Second Edition))
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21 pages, 13437 KiB  
Article
The Remote Effects of Typhoons on the Cold Filaments in the Southwestern South China Sea
by Zezheng Zhao, Shengmu Yang, Huipeng Wang, Taikang Yuan and Kaijun Ren
Remote Sens. 2024, 16(17), 3293; https://doi.org/10.3390/rs16173293 - 4 Sep 2024
Cited by 1 | Viewed by 1094
Abstract
Cold filaments (CFs) in the southwestern South China Sea (SCS) impact local hydrodynamics and the ecological environment. In this study, the effects of typhoons passing over the northern SCS on CFs are investigated using multi-source observational and reanalysis data. Statistical analysis of CF [...] Read more.
Cold filaments (CFs) in the southwestern South China Sea (SCS) impact local hydrodynamics and the ecological environment. In this study, the effects of typhoons passing over the northern SCS on CFs are investigated using multi-source observational and reanalysis data. Statistical analysis of CF responses to typhoons over the past 24 years shows that during typhoon periods in the northern SCS, the CFs are intensified. We further analyze the remote effect of typhoons on the CF during Typhoon Kalmaegi in 2014, which caused a sea surface temperature (SST) drop of more than 3 °C in the CF region. The strengthened along-coast wind induced strong upwelling off the Vietnam coast. The maximum vertical velocity in the CF reaches three times the usual value. Meanwhile, influenced by the peripheral wind field of Kalmaegi, cold coastal water accumulated at the CF region due to the shafting of the offshore current. Both strong offshore currents and coastal upwellings enhanced the intensity of the CF. These findings demonstrate that typhoons not only directly affect ocean dynamic processes along their path but also present significant remote influences on coastal dynamics in other regions. This study enhances the understanding of CF evolution and sea–air interactions during extreme events. Full article
(This article belongs to the Special Issue Linking Upper Ocean Dynamics with Extreme Weather and Climate Events over the Ocean (Second Edition))
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