Coastal Climate Variability and Predictability: Challenges and Emerging Solutions

A special issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: 30 June 2026 | Viewed by 936

Special Issue Editors


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Guest Editor
CIRES, University of Colorado Boulder, Boulder, CO 80309, USA
Interests: climate variability and change; sea level; seasonal prediction

E-Mail Website
Guest Editor
CIRES, University of Colorado Boulder, Boulder, CO 80309, USA
Interests: climate variability and change; marine heatwaves; seasonal prediction

E-Mail Website
Guest Editor
1. Department of Mathematical and Physical Sciences, The University of Technology, Sydney, Australia
2. Climate Change Research Centre, Faculty of Science, The University of New South Wales, Sydney, Australia
Interests: severe weather; climate variability and change; synoptic and mesoscale meteorology
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Special Issue Information

Dear Colleagues,

Coastal regions are particularly vulnerable to climate variability and change, with rising sea levels, shifting ocean currents, extreme events, and compound hazards posing significant threats to ecosystems, infrastructure, and communities. Despite their importance, the predictability of coastal climate systems remains limited due to the complex interplay of oceanic, atmospheric, and terrestrial processes across a range of spatial and temporal scales.

This Special Issue aims to bring together innovative research focused on understanding and improving the predictability of coastal climate. We welcome studies that address the physical mechanisms governing coastal variability, the role of coupled ocean-atmosphere dynamics, the influence of climate modes (e.g., ENSO, NAO, IOD, MJO), and the impacts of anthropogenic forcing. Submissions are encouraged from a range of disciplines, including climate modelling, novel machine learning applications, observational analysis, and coastal risk assessment.

We particularly invite contributions that present new methodologies, modelling frameworks, or interdisciplinary approaches that can advance predictive skill or support actionable climate information for coastal stakeholders. Comparative studies across different coastal regions, evaluations of forecast systems, and assessments of predictability limits under future climate scenarios are also highly relevant. By assembling a range of perspectives and approaches, this collection underscores the urgent need and growing opportunity for innovation in coastal climate prediction. We thank the authors for their contributions and hope the collection inspires continued cross-disciplinary collaboration.

Dr. Xiaoyu Long
Dr. Tongtong Xu
Dr. Milton S. Speer
Guest Editors

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Keywords

  • coastal climate variability
  • coastal compound flooding
  • coastal marine heatwaves
  • coupled ocean-atmosphere dynamics
  • climate extremes
  • regional climate modelling
  • machine learning in climate science
  • climate risk and resilience
  • forecast evaluation
  • anthropogenic impacts on coasts

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Published Papers (1 paper)

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Research

22 pages, 3654 KB  
Article
Assessing Coastal Vulnerability to Sea Level Rise in Qatar: An Index-Based Approach Using Analytic Hierarchy Process
by Ali Nasser A. A. Ba-Khamis, Hazrat Bilal and Tareq Al-Ansari
Climate 2025, 13(11), 236; https://doi.org/10.3390/cli13110236 - 17 Nov 2025
Viewed by 683
Abstract
Sea level rise (SLR) is a global phenomenon impacting coastlines worldwide, with its effects varying according to local geophysical and climatic conditions. The Arabian Gulf, characterized by hyper-arid conditions and low-lying coastal zones, is particularly vulnerable to SLR. This includes the eastern Arabian [...] Read more.
Sea level rise (SLR) is a global phenomenon impacting coastlines worldwide, with its effects varying according to local geophysical and climatic conditions. The Arabian Gulf, characterized by hyper-arid conditions and low-lying coastal zones, is particularly vulnerable to SLR. This includes the eastern Arabian Peninsula, where densely populated cities and critical infrastructure in countries such as Iraq, Kuwait, Saudi Arabia, Bahrain, Qatar, and the United Arab Emirates (UAE) face increasing risk. This study assesses the potential impact of SLR on Qatar’s coastline using CVI, which integrates both physical and socio-economic parameters. The analysis separately calculates the Physical Vulnerability Index (PVI) and the Socio-Economic Vulnerability Index (SVI), which are then combined to produce the final CVI score. Each variable is assigned a semi-quantitative score on a scale from 1 to 5, representing a gradient from very low to very high vulnerability. To determine the relative importance of each variable, the AHP is employed as a weighting method. The findings reveal that the majority of Qatar’s coastline falls within the high to very high vulnerability categories, with the exception of Doha, which is classified as low risk due to extensive coastal modifications and protective infrastructure. In contrast, areas such as Al Khor and Ras Laffan in the north and northeast, as well as Dukhan and Al Zubarah in the west, exhibit considerably higher vulnerability. These results highlight the urgent need for continued assessment of SLR impacts and the development of targeted adaptation and resilience strategies to safeguard Qatar’s coastal zones. Full article
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