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Marine Climate Models and Environmental Dynamics
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Marine Climate Models and Environmental Dynamics

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean and Global Climate".

Deadline for manuscript submissions: 15 October 2026 | Viewed by 1580

Special Issue Editors

Dr. Nerea Portillo Juan

E-Mail Website
Guest Editor
Environment, Coast and Ocean Research Laboratory, Universidad Politécnica de Madrid, Campus Ciudad Universitaria, Calle del Profesor Aranguren 3, 28040 Madrid, Spain
Interests: climate estimations; Artificial Intelligence; climate change
Dr. Jose del Campo

E-Mail Website
Guest Editor
Marine, Coastal and Port Environment and Other Sensitive Areas Research Group, Department of Civil Engineering: Hydraulics, Energy and Environment, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Interests: wave climate; ocean engineering; construction processes

Special Issue Information

Dear Colleagues,

The world's oceans are a critical component of the global climate system and are currently undergoing significant changes due to anthropogenic pressures. Understanding and predicting these changes require sophisticated modelling and a deep comprehension of environmental dynamics. This Special Issue, titled "Marine Climate Models and Environmental Dynamics", aims to bring together the latest research and advancements in the field of marine climate modelling to better understand the complex interactions between physical, chemical, and biological processes in the marine environment.

A primary challenge in this field is the accurate representation of the coupling between different components of the Earth system, which involves linking processes that occur across a wide range of spatial and temporal scales. This is a critical aspect of understanding ocean dynamics and their impact on marine ecosystems and the global climate.

In recent years, the integration of Artificial Intelligence (AI) and machine learning has opened new frontiers in marine science. AI-based models offer powerful new methods for analysing vast datasets, improving forecast accuracy, and uncovering complex, non-linear patterns that traditional models may miss. These technologies are revolutionising our ability to model everything from ocean hydrodynamics to the health of marine ecosystems.

For this Special Issue, we invite contributions that explore both the development and application of traditional marine climate models and, in particular, the innovative use of AI in marine and oceanographic studies. We are especially interested in manuscripts that address the following topics:

  • Development and validation of new marine climate models, including hybrid models combining mechanistic and AI approaches.
  • AI applied to ocean engineering and environmental models.
  • AI-based models for forecasting, hindcasting, and analysing marine environmental dynamics.
  • Coupled physical–biogeochemical models.
  • High-resolution ocean modelling.
  • The role of the ocean in climate variability and change, investigated with novel data analysis methods.
  • Impacts of climate change on marine ecosystems.
  • Modelling and prediction of extreme events and their impacts on the marine environment.
  • Advanced data assimilation, model optimisation, and uncertainty quantification using AI.

Dr. Nerea Portillo Juan
Dr. Jose del Campo
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. Journal of Marine Science and Engineering 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 2600 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 modelling
  • marine climate
  • Artificial Intelligence (AI)
  • machine learning
  • environmental dynamics
  • climate change impacts
  • coupled models
  • physical oceanography
  • biogeochemical models
  • marine ecosystems

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

27 pages, 2909 KB  
Article
Integrated Spatial Planning as a Framework for Climate Adaptation in Coastal and Marine Systems
by Francisco Javier Córdoba-Donado, Vicente Negro-Valdecantos, Gregorio Gómez-Pina, Juan J. Muñoz-Pérez and Luis Juan Moreno-Blasco
J. Mar. Sci. Eng. 2026, 14(8), 732; https://doi.org/10.3390/jmse14080732 - 15 Apr 2026
Viewed by 558
Abstract
Coastal socio-ecological systems are increasingly exposed to the combined pressures of climate change, land-use intensification, hydrological alterations and expanding infrastructure networks. These pressures interact across the land–catchment–lagoon–sea continuum, generating complex feedbacks that challenge traditional planning instruments, which remain sectoral and fragmented. The Mar [...] Read more.
Coastal socio-ecological systems are increasingly exposed to the combined pressures of climate change, land-use intensification, hydrological alterations and expanding infrastructure networks. These pressures interact across the land–catchment–lagoon–sea continuum, generating complex feedbacks that challenge traditional planning instruments, which remain sectoral and fragmented. The Mar Menor (SE Spain), a semi-enclosed Mediterranean lagoon affected by intensive agriculture, urbanisation, hydrological modifications and recurrent extreme climatic events, exemplifies this systemic vulnerability. Existing planning frameworks—local urban plans, regional territorial plans, river basin management plans, maritime spatial plans and lagoon-specific strategies—operate independently, each addressing only a fragment of the system and none integrating climate change as a structuring axis. This article introduces Integrated Spatial Planning (ISP) as a novel territorial–climatic framework designed to overcome these limitations. ISP integrates climate forcing, land uses, catchment processes, lagoon dynamics, marine conditions, critical infrastructures, intermodal and energy corridors and multilevel governance into a single analytical structure. A central component of the methodology is a four-zone multilevel zoning system that connects municipal, regional, basin, marine and EEZ planning domains within a unified territorial–climatic logic. The ISP matrix is applied to the Mar Menor to produce the first holistic diagnosis of the system. Results reveal strong land–sea–catchment interactions, high climatic exposure, vulnerable infrastructures and structural governance fragmentation. The matrix exposes systemic incompatibilities and vulnerabilities that remain invisible in sectoral planning instruments. The discussion demonstrates how ISP clarifies the roles and responsibilities of each governance level, supports multilevel coherence and integrates critical infrastructures and intermodal corridors into climate-resilient planning. ISP reframes climate change as the organising principle of territorial planning and provides a replicable, scalable methodology for coastal socio-ecological systems facing accelerating climate pressures. The Mar Menor case illustrates the urgent need for integrated territorial–climatic governance and positions ISP as a scientifically robust and operationally viable pathway for long-term adaptation and resilience. Full article
(This article belongs to the Special Issue Marine Climate Models and Environmental Dynamics)
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22 pages, 3190 KB  
Article
An Artificial Intelligence Approach for Coastal Structures Adaptation to Climate Change: Insights from a Case Study in the Mediterranean Sea
by Nerea Portillo Juan, Javier Olalde Rodríguez, Vicente Negro Valdecantos, Jose María del Campo and Peter Troch
J. Mar. Sci. Eng. 2026, 14(5), 455; https://doi.org/10.3390/jmse14050455 - 27 Feb 2026
Viewed by 514
Abstract
The application of artificial intelligence (AI) models in maritime and coastal engineering has gained increasing relevance, demonstrating performance comparable to traditional approaches in wave climate analysis and propagation. However, their use in climate change impact and adaptation studies remains limited, particularly for the [...] Read more.
The application of artificial intelligence (AI) models in maritime and coastal engineering has gained increasing relevance, demonstrating performance comparable to traditional approaches in wave climate analysis and propagation. However, their use in climate change impact and adaptation studies remains limited, particularly for the design and upgrading of coastal protection structures. To address this gap, this study focuses on the development of an AI-based framework to support the adaptation of breakwaters to future climate conditions. A hybrid approach combining artificial neural networks (ANNs) and genetic algorithms (GAs) was implemented, with two feedforward neural networks-based models developed and applied to different sections of the north breakwater of the Port of Valencia, specifically a vertical section and a compound breakwater. The results indicate that, under future climate scenarios (2050), increases of up to 1.2 m in crest elevation, together with reinforcement of the armor layer, are required to ensure adequate structural performance. The analysis also highlights the critical role of extreme events, as approximately 60% of the model errors were concentrated in the upper 90th percentile of wave conditions. Overall, the proposed hybrid ANN-GA framework demonstrated very strong performance, achieving computational efficiencies 30 to 40 times greater than ANN-only models in terms of computational time. These findings underscore the necessity of adapting coastal structures to climate change and confirm the potential of AI-based models as effective tools for climate-resilient coastal engineering, while emphasizing the importance of accurately representing extreme wave conditions. Full article
(This article belongs to the Special Issue Marine Climate Models and Environmental Dynamics)
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