Jose A. A. Antolinez

Verified @gmail.com

Coastal Engineering, Hydraulic Engineering, Civil Engineering and Geosciences Faculty
Delft University of Technology

Jose A. A. Antolinez


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https://researchid.co/josseaaa
63

Scopus Publications

1493

Scholar Citations

22

Scholar h-index

35

Scholar i10-index

Scopus Publications

  • Coastal process understanding through automated identification of recurring surface dynamics in permanent laser scanning data of a sandy beach
    Daan Hulskemper, José A. Á. Antolínez, Roderik Lindenbergh, Katharina Anders
    Earth Surface Dynamics, 2026
    Four-dimensional (4D) topographic datasets are increasingly available at high spatial and temporal resolution, particularly from permanent terrestrial laser scanning (PLS) time series. These data offer unprecedented opportunities to analyse rapid and complex morphological processes occurring in sandy coastal environments, such as sandbar welding or bulldozer activity, as well as their longer-term impacts on sandy beaches. However, studying these processes requires the extraction and recognition of recurrent topographical surface dynamics across time, which in turn demands novel, automated methods. This study presents a novel workflow that combines 4D objects-by-change (4D-OBCs) with unsupervised classification using Self-Organizing Maps (SOMs) and hierarchical clustering. Applied to a three-year PLS time series comprising 21 194 hourly point clouds, the method identifies 4412 instances of short-term surface dynamics. These are organized into two SOMs (64 nodes each) and further grouped into 31 clusters representing distinct dynamic types, such as berm deposition, large-scale backshore erosion, and human interventions (e.g., bulldozer activity). The classification results enable detailed spatiotemporal analyses of coastal morphodynamics. The SOM topology reveals seasonal patterns in surface activity, where, for example, winter is dominated by erosional activity over the whole beach but depositional activity mainly occurs in the intertidal area. The broader clusters facilitate interpretation of environmental responses and identification of changes in cross-shore zonation of types of dynamics, like berm formation. This approach demonstrates the potential of integrating PLS and unsupervised learning to characterize complex surface dynamics, through a fully automated extraction and classification workflow. While the interpretation of clusters and their relation to environmental variables in this study is performed through expert-based analysis, the methods provide a framework for targeted, data-driven investigation and prediction of morphodynamic processes in high-resolution 4D remote sensing datasets.
  • Tail dependence of surge height and wind speed along the Dutch coast for storm clusters from large simulated datasets
    Paulina E. Kindermann, José A. Á. Antolínez, Oswaldo Morales-Nápoles
    Natural Hazards, 2026
    This study explores the statistical dependence between wind speed and surge height along the Dutch coast using a large synthetic dataset. Storms were clustered based on wind direction, tidal offset, wind rotation, tidal peak, surge and wind exceedance duration, resulting in 16 clusters per wind direction and per location. Apart from wind direction, comparing clusters revealed a limited impact of clustering based on these storm characteristics on the choice of the best-fitting copula model, suggesting sub-clustering may not be necessary for accurately representing the statistical dependence between extreme wind speeds and surge heights. The BB8 copula generally provided the best fit to the data. However, the observed upper tail dependence did not decrease to zero, particularly for western to northern wind directions, indicating non-negligible dependence in joint extremes of wind speed and surge height. Therefore, applying the BB8 copula (or any other copula model without upper tail dependence) may lead to underestimation of the flood risk, when applied in probabilistic analyses. The findings from this study provide valuable insights for refining hydraulic load models for reliability assessments and design of flood defenses.
  • Vulnerability of Key Sea Turtle Nesting Beaches to Future Erosion and Sea Level Rise
    Jakob C. Christiaanse, Sean Vitousek, Ad J. H. M. Reniers, José A. A. Antolínez
    Earth S Future, 2026
    Threatened sea turtles rely on sandy beaches for nesting, linking their long‐term survival to global beach availability. However, beaches worldwide are increasingly threatened by anthropogenic stressors and sea level rise (SLR). Reliable vulnerability assessments require understanding beach dynamics across multiple time scales, informed by long‐term coastal change records. While many nesting beaches lie in remote, data‐poor environments, recent advances in coastal remote sensing now allow us to monitor coastal change worldwide. Here, we combine satellite‐derived shorelines (CoastSat), shoreline modeling (CoSMoS‐COAST), and global data sets to investigate shoreline evolution and future vulnerability at nine globally important sea turtle nesting sites. We investigate seasonal and long‐term shoreline change, hindcast (1980–2024) and forecast (2025–2100) shoreline positions under various SLR scenarios, and quantify available accommodation space based on backbeach elevation and infrastructure footprints. We find that shoreline evolution and vulnerability vary considerably, with three sites showing historical accretion trends and four sites showing erosion. This demonstrates that the previously widely applied bathtub approach—adding SLR to a static beach profile—is not suitable to assess the vulnerability of sea turtle nesting beaches to erosion. Three eroding beaches emerge as particularly vulnerable due to projected shoreline retreat coupled with limited accommodation space. Despite significant uncertainties arising from long‐term shoreline projections, our results provide important insights into seasonal and long‐term morphodynamics, identify vulnerable nesting sites, and offer a comprehensive, transferable framework for assessing shoreline evolution and relative erosion vulnerability at other sites. Understanding these dynamics is crucial to inform conservation and management strategies to future‐proof these critical nesting habitats.
  • Beyond understanding the role of far-field climate in the Gulf of Panama coastal dynamics: an analysis of long-term and seasonal variability of wave systems
    Ruby Vallarino-Castillo, José A. A. Antolínez, Vicente Negro-Valdecantos, Jesús Portilla-Yandún
    Climate Dynamics, 2026
  • Spatial Clustering of Sea Level Hydrographs Across the Dutch Coast
    Mia Pupić Vurilj, José A. A. Antolínez, Oswaldo Morales-Nápoles
    Coastal Research Library, 2026
    Extreme sea level events pose significant risks to coastal regions, with non-tidal residuals (NTRs) being a primary driver in low-lying areas like the Netherlands, where shallow seas amplify their impact. This study investigates the spatial patterns of NTRs along the Dutch coast using time series clustering on historical NTR hydrographs. The design of hydraulic boundary conditions divides the Netherlands into three coastal regions. To evaluate whether this division sufficiently captures regional variability, three clustering scenarios (k = 3, k = 4, and k = 5) were explored. The analysis identified k = 5 as the optimal configuration based on the Davies-Bouldin index. This result emphasized the importance of fine-scale approaches to understanding regional spatial variations in NTR dynamics. Regional bathymetry and tide-surge interactions were explored as drivers of these spatial patterns. Southern stations near river systems and deeper waters displayed characteristics distinct from northern stations in the Wadden Sea, which are influenced by shallow tidal flats. Analysis of the M2 tidal constituent and the timing of NTR maxima relative to high tides underscored the role of tidal dynamics in shaping spatial clusters. Future research will focus on integrating spatio-temporal patterns and environmental drivers into clustering methodologies, providing deeper insights for coastal risk management and adaptation strategies.
  • Evaluation of Clustering Techniques for Revealing Dependence Between Wind Speed and Surge Height
    Paulina E. Kindermann, José A. A. Antolínez, Oswaldo Morales-Nápoles
    Coastal Research Library, 2026
    Extreme storms over the North Sea drive coastal flood risk in the Netherlands, causing high waves and extreme sea levels. Designing flood defenses requires accurate statistical extrapolation of hydraulic load conditions with return periods of 1,000 years or more. This is a challenging task given limited observational data. This study uses a large, simulated dataset (~9,000 years) to explore the statistical dependence between extreme wind speed u and surge height s . Storms were clustered using several techniques. Self-organizing maps (SOM) effectively captured physical relationships, such as the influence of wind direction and tidal offset on storm dynamics, however variability in statistical dependence between u and s for different clusters was better represented using manual clusters. Copula models were fitted to the cluster data, with the BB8 copula outperforming others. This study illustrates the potential of machine learning to identify patterns in large datasets while emphasizing the relevance of manual clustering approaches for revealing nuanced statistical dependencies critical to flood risk assessment.
  • Editorial: Prediction of coastal morphological evolution in the context of climate change adaptation and nature-based engineering
    Sergio Maldonado, José A. A. Antolinez, Nicholas Dodd, Rodolfo Silva
    Frontiers in Marine Science, 2026
  • Uncovering Causation of Short-Term Sandy Beach Surface Dynamics Measured by Permanent Laser Scanning
    Daan Hulskemper, Katharina Anders, José A. A. Antolínez, Roderik Lindenbergh
    Coastal Research Library, 2026
    The causal drivers of short-term changes (days to months) in human-, wind-, and wave-driven sand transport on a sandy beach are not often considered in an integral and data-driven approach. However, improving current knowledge on (urban) sandy beach topographical change requires the incorporation of multi-scale, cross-sectional and human factors. In this research we process a time series of 21,194 hourly point clouds, obtained in a Permanent Terrestrial Laser Scanning setup. From this 3D time series we extract 5,102 short-term temporary surface dynamics, through a method called 4D objects-by-change (4D-OBCs). The causal drivers of two of these 4D-OBCs are investigated in detail. One is interpreted as an aeolian depositional surface dynamic (1), and one as a bulldozer deposit, that consecutively eroded under high wave energy conditions (2). The dynamics show clear correlation to a particular combination of wind direction and intensity (1), and wave height and wave period (2), indicating that point cloud time series derived 4D-OBCs are useful data to study causality of short-term surface dynamics of different origins. However, to study these surface dynamics systematically and derive statistical proof of causal relations we must consider multivariate correlations, as well as spatiotemporal dependence between sediment dynamics and larger scale morphological changes on the beach.
  • Predicting Shoreline Orientation on Diverse Coastal Environments
    Mayowa Basit Abdulsalam, Camilo Jaramillo, Lucas de Freitas, Mauricio González, José A. A. Antolínez
    Coastal Research Library, 2026
    Coastal zones are highly dynamic environments shaped by various environmental forcing agents such as waves and nearshore currents operating across diverse spatio-temporal scales. For effective decision-making, coastal managers require simplified, computationally efficient models to predict future shoreline morphodynamics. Among the models developed over the years, equilibrium-based shoreline evolution models (EBSEMs) have garnered significant attention for their computational efficiency. However, their application has mainly been limited to microtidal sandy beaches when simulating shoreline orientation, necessitating further evaluation across broader coastal settings. This study investigates the applicability of EBSEMs in predicting shoreline rotational variability at two morphologically distinct sites: Narrabeen Beach, Australia, and Moncofa Beach, Spain. These sites differ in sediment size, tidal regimes, data sources, observation periods, and monitoring frequencies, providing a robust framework for model evaluation. Results demonstrate that the EBSEM successfully replicates the general trends of shoreline orientation variability on both sites, qualitatively and quantitatively. Seasonal rotation trends were accurately captured, emphasizing the model’s capability to operate across varying spatial and temporal scales. These findings further reinforced the capabilities of EBSEMs as practical tools for coastal management, particularly for predicting shoreline orientation changes under diverse environmental conditions.
  • Probabilistic Forecasting of Shoreline Evolution: A Case Study Using Genetic Algorithms
    Lucas de Freitas, Camilo Jaramillo, José A. A. Antolínez, Mauricio González, Raúl Medina
    Coastal Research Library, 2026
    Sandy beach erosion is a pressing concern for coastal regions worldwide, driven by both natural processes and human-induced pressures. This study presents an ensemble modeling approach for predicting sandy shoreline dynamics using an equilibrium-based shoreline evolution model (EBSEM). A genetic algorithm (NSGA-II) was employed to calibrate multiple parameter sets, capturing the inherent uncertainty in model parameters. The method was tested with a publicly available dataset from Tairua Beach (New Zealand), spanning 14 years of high-resolution shoreline measurements. Results reveal a near-linear relationship between the slope and intercept parameters governing equilibrium wave energy, and demonstrate that the best-fit solution generally lies within the ensemble range. Comparisons of ensemble simulations with observed data indicate strong agreement in both calibration and validation phases, although certain extreme accretion and erosion events were underestimated. Overall, this ensemble framework provides a robust tool for medium- to long-term shoreline predictions, bringing coastal managers with stochastic/probabilistic estimates of shoreline change, which can be useful in the assessment of resilience of adaptive strategies for risk mitigation.
  • The Effect of Beach Buildings on Decadal Dune Volume Development
    Sander Vos, Daan Hulskemper, Christa IJzendoorn, Alain de Wulf, Roderik Lindenbergh, et al.
    Coastal Research Library, 2026
  • Runup Modeling in Low-Data Coral Reef Environments: Implications for Nesting Sea Turtles
    Daniel Dédina, Jakob C. Christiaanse, Floortje Roelvink, Ahmed I. A. Elshinnawy, Robert T. McCall, et al.
    Coastal Research Library, 2026
  • BlueMath-Hub: A Cloud-Based, Open-Source, Python Framework with Interactive Notebooks for Statistical Analysis and Simulation of Coastal Climate Hazards in a Changing Climate
    Laura Cagigal, Valvanuz Fernandez-Quiruelas, Fernando Méndez, Javier Tausia, Jared Ortiz-Angulo, et al.
    Coastal Research Library, 2026
  • Publisher Correction: Quantifying uncertainty in wave attenuation by mangroves to inform coastal green belt policies (Communications Earth & Environment, (2025), 6, 1, (258), 10.1038/s43247-025-02178-4)
    Bregje K. van Wesenbeeck, Vincent T. M. van Zelst, Jose A. A Antolinez, Wiebe P. de Boer
    Communications Earth and Environment, 2025
  • Quantifying uncertainty in wave attenuation by mangroves to inform coastal green belt policies
    Bregje K. van Wesenbeeck, Vincent T. M. van Zelst, Jose A. A Antolinez, Wiebe P. de Boer
    Communications Earth and Environment, 2025
  • Measurements of groundwater, hydrodynamics, and sand characteristics at a dissipative sea turtle nesting beach
    Jakob C. Christiaanse, José A. A. Antolínez, Meye J. van der Grinten, Falco Taal, Jens Figlus, et al.
    Scientific Data, 2025
  • Benchmarking shoreline prediction models over multi-decadal timescales
    Yongjing Mao, Giovanni Coco, Sean Vitousek, Jose A. A. Antolinez, Georgios Azorakos, et al.
    Communications Earth and Environment, 2025
  • Global Analysis of Storm Surge Seasonality
    Ayoola Apolola, Philip J. Ward, Timothy Tiggeloven, José A. Á. Antolínez, Wiebke Jäger, et al.
    Journal of Geophysical Research Oceans, 2025
  • Beach groundwater response to ocean processes and rain on a mild-sloping barrier island: Implications for sea turtle nest flooding
    Jakob C. Christiaanse, José A.A. Antolínez, Christopher D. Marshall, Jens Figlus, Timothy M. Dellapenna, et al.
    Coastal Engineering, 2025
  • Assessing shoreline orientation variation across diverse coastal environments
    Mayowa Basit Abdulsalam, Camilo Jaramillo, Lucas de Freitas, Mauricio González, José A.Á. Antolínez
    Coastal Engineering, 2025
  • Wave runup extraction on dissipative beaches: New video-based methods
    Meye J. van der Grinten, Jakob C. Christiaanse, Ad J.H.M. Reniers, Falco Taal, Jens Figlus, et al.
    Coastal Engineering, 2025
  • Storm surge hydrographs from historical observations of sea level along the Dutch North Sea coast
    Mia Pupić Vurilj, José A. Á. Antolínez, Sanne Muis, Oswaldo Morales Napoles
    Natural Hazards, 2025
  • Evaluating five shoreline change models against 40 years of field survey data at an embayed sandy beach
    Oxana Repina, Rafael C. Carvalho, Giovanni Coco, José A.Á. Antolínez, Iñaki de Santiago, et al.
    Coastal Engineering, 2025
  • Accelerating compound flood risk assessments through active learning: A case study of Charleston County (USA)
    Lucas Terlinden-Ruhl, Anaïs Couasnon, Dirk Eilander, Gijs G. Hendrickx, Patricia Mares-Nasarre, et al.
    Natural Hazards and Earth System Sciences, 2025
  • Aiding sea turtle conservation through coastal management
    Jakob C. Christiaanse, Ad J. H. M. Reniers, Stefan G. J. Aarninkhof, Elias F. Ostertag, Ronel Nel, et al.
    Frontiers in Marine Science, 2025

RECENT SCHOLAR PUBLICATIONS

  • The influence of climate variability on global storm surges
    A Apolola, PJ Ward, FJ Méndez, V Collado, T Tiggeloven, W Jäger, ...
    2026
  • Coastal process understanding through automated identification of recurring surface dynamics in permanent laser scanning data of a sandy beach
    D Hulskemper, JAÁ Antolínez, R Lindenbergh, K Anders
    Earth Surface Dynamics 14 (3), 329-359 , 2026
    2026
  • Spatial Clustering of Sea Level Hydrographs
    MP Vurilj, JAA Antolínez, O Morales-Nápoles
    Coastal Dynamics 2025: Volume 2 2, 114 , 2026
    2026
  • Salt march Leaf Area Index determination with AI driven aerial lidar and multispectral data fusion
    S Vos, T Blount, R Lindenbergh, J Antolinez, M Marani
    EGU26 , 2026
    2026
  • Hybrid spectral downscaling and climate-driven variability of multimodal wave systems in the Gulf of Panama
    R Vallarino-Castillo, G Bellido, L Cagigal, V Negro-Valdecantos, ...
    EGU26 , 2026
    2026
  • Vulnerability of key sea turtle nesting beaches to future erosion and sea level rise
    JC Christiaanse, S Vitousek, AJHM Reniers, JAA Antolínez
    Earth's Future 14 (3), e2025EF007191 , 2026
    2026
  • Tail dependence of surge height and wind speed along the Dutch coast for storm clusters from large simulated datasets
    PE Kindermann, JAÁ Antolínez, O Morales-Nápoles
    Natural Hazards 122 (5), 196 , 2026
    2026
    Citations: 1
  • Navigating Complexity in Tidal Marsh Restoration: Hydrodynamic–Vegetation Interactions at Fir Island Farm
    N Villa, G Hood, JAA Antolínez, MC Stone
    2026 Ocean Sciences Meeting , 2026
    2026
  • BlueMath: A Collaborative Open-Source Repository for Statistical Analysis and Fast, Efficient Hydrodynamic Emulators of Coastal Climate Hazards
    L Cagigal, J Tausia, FJ Mendez, V Fernandez, GB Prieto, JOA Cantos, ...
    2026 Ocean Sciences Meeting , 2026
    2026
  • The influence of climate variability on global extreme sea level
    A Apolola, P Ward, T Tiggeloven, JAA Antolínez, FJ Mendez, S Muis
    2026 Ocean Sciences Meeting , 2026
    2026
  • Managing Coasts and Conserving Sea Turtle Habitats
    JAA Antolínez, J Christiaanse, AJHM Reniers, SGJ Aarninkhof, BJ Godley, ...
    2026 Ocean Sciences Meeting , 2026
    2026
  • GreenSurge 2.0: A Scalable and Efficient Additive model for Storm Surge Modeling
    E Faugere, BP Díaz, L Cagigal, P Camus, V Fernandez, J Tausia, ...
    2026 Ocean Sciences Meeting , 2026
    2026
  • Beyond understanding the role of far-field climate in the Gulf of Panama coastal dynamics: an analysis of long-term and seasonal variability of wave systems
    R Vallarino-Castillo, JAA Antolínez, V Negro-Valdecantos, ...
    Climate Dynamics 64 (2), 39 , 2026
    2026
    Citations: 1
  • Probabilistic forecasting of shoreline evolution: a case study using genetic algorithms
    L De Freitas Pereira, C Jaramillo Cardona, JAA Antolínez, ...
    2026
  • Coastal process understanding through automated identification of recurring surface dynamics in permanent laser scanning data of a sandy beach
    DC Hulskemper, JAÁ Antolínez, R Lindenbergh, K Anders
    EGUsphere 2025, 1-41 , 2025
    2025
  • Global analysis of storm surge seasonality
    A Apolola, PJ Ward, T Tiggeloven, JA Á. Antolínez, W Jäger, S Muis
    Journal of Geophysical Research: Oceans 130 (11), e2025JC022841 , 2025
    2025
  • Beach groundwater response to ocean processes and rain on a mild-sloping barrier island: Implications for sea turtle nest flooding
    JC Christiaanse, JAA Antolínez, CD Marshall, J Figlus, TM Dellapenna, ...
    Coastal Engineering 201, 104795 , 2025
    2025
    Citations: 4
  • Aiding sea turtle conservation through coastal management
    JC Christiaanse, AJHM Reniers, SGJ Aarninkhof, EF Ostertag, R Nel, ...
    Frontiers in Marine Science 12, 1669885 , 2025
    2025
    Citations: 5
  • Benchmarking shoreline prediction models over multi-decadal timescales
    Y Mao, G Coco, S Vitousek, JAA Antolinez, G Azorakos, M Banno, ...
    Communications Earth & Environment 6 (1), 581 , 2025
    2025
    Citations: 13
  • Assessing shoreline orientation variation across diverse coastal environments
    MB Abdulsalam, C Jaramillo, L de Freitas, M González, JAÁ Antolínez
    Coastal Engineering 200, 104770 , 2025
    2025
    Citations: 3

MOST CITED SCHOLAR PUBLICATIONS

  • Blind testing of shoreline evolution models
    J Montaño, G Coco, JAA Antolínez, T Beuzen, KR Bryan, L Cagigal, ...
    Scientific reports 10 (1), 2137 , 2020
    2020
    Citations: 189
  • Predicting climate driven coastlines with a simple and efficient multi‐scale model
    JAA Antolínez, FJ Méndez, D Anderson, P Ruggiero, GM Kaminsky
    Journal of Geophysical Research: Earth Surface , 2019
    2019
    Citations: 102
  • A Climate Index Optimized for Longshore Sediment Transport Reveals Interannual and Multidecadal Littoral Cell Rotations
    D Anderson, P Ruggiero, JAA Antolínez, FJ Méndez, J Allan
    Journal of Geophysical Research: Earth Surface 123 (8), 1958-1981 , 2018
    2018
    Citations: 84
  • A multiscale climate emulator for long‐term morphodynamics (MUSCLE‐morpho)
    JAA Antolínez, FJ Méndez, P Camus, S Vitousek, EM González, ...
    Journal of Geophysical Research: Oceans 121 (1), 775-791 , 2016
    2016
    Citations: 82
  • Time‐Varying Emulator for Short and Long‐Term Analysis of Coastal Flood Hazard Potential
    D Anderson, A Rueda, L Cagigal, JAA Antolinez, FJ Mendez, P Ruggiero
    Journal of Geophysical Research: Oceans 124 (12), 9209-9234 , 2019
    2019
    Citations: 81
  • Wave attenuation through forests under extreme conditions
    BK van Wesenbeeck, G Wolters, JAA Antolínez, SA Kalloe, B Hofland, ...
    Scientific reports 12 (1), 1884 , 2022
    2022
    Citations: 78
  • A multimodal wave spectrum–based approach for statistical downscaling of local wave climate
    CA Hegermiller, JAA Antolinez, A Rueda, P Camus, J Perez, LH Erikson, ...
    Journal of Physical Oceanography 47 (2), 375-386 , 2017
    2017
    Citations: 68
  • HyCReWW: A Hybrid Coral Reef Wave and Water level metamodel
    A Rueda, L Cagigal, S Pearson, JAA Antolínez, C Storlazzi, ...
    Computers & geosciences 127, 85-90 , 2019
    2019
    Citations: 53
  • Global Projections of Storm Surges Using High‐Resolution CMIP6 Climate Models
    S Muis, JCJH Aerts, JA Á. Antolínez, JC Dullaart, TM Duong, L Erikson, ...
    Earth's Future 11 (9), e2023EF003479 , 2023
    2023
    Citations: 52
  • Downscaling changing coastlines in a changing climate: The hybrid approach
    JAA Antolínez, AB Murray, FJ Méndez, LJ Moore, G Farley, J Wood
    Journal of Geophysical Research: Earth Surface 123 (2), 229-251 , 2018
    2018
    Citations: 52
  • Measurements of hydrodynamics, sediment, morphology and benthos on Ameland ebb-tidal delta and lower shoreface
    BC Van Prooijen, MFS Tissier, FP De Wit, SG Pearson, LB Brakenhoff, ...
    Earth System Science Data 12 (4), 2775-2786 , 2020
    2020
    Citations: 40
  • Multiscale climate emulator of multimodal wave spectra: MUSCLE‐spectra
    A Rueda, CA Hegermiller, JAA Antolinez, P Camus, S Vitousek, ...
    Journal of Geophysical Research: Oceans 122 (2), 1400-1415 , 2017
    2017
    Citations: 36
  • Hydro-morphological characterization of coral reefs for wave runup prediction
    F Scott, JAA Antolinez, R McCall, C Storlazzi, A Reniers, S Pearson
    Frontiers in Marine Science 7, 361 , 2020
    2020
    Citations: 35
  • Marine climate variability based on weather patterns for a complicated island setting: The New Zealand case
    A Rueda, L Cagigal, JAA Antolínez, JC Albuquerque, S Castanedo, ...
    Int. J. Climatol 39 (3), 1777-1786 , 2019
    2019
    Citations: 33
  • Directional correction of modeled sea and swell wave heights using satellite altimeter data
    J Albuquerque, JAA Antolínez, A Rueda, FJ Méndez, G Coco
    Ocean Modelling 131, 103-114 , 2018
    2018
    Citations: 33
  • Controls of multimodal wave conditions in a complex coastal setting
    CA Hegermiller, A Rueda, LH Erikson, PL Barnard, JAA Antolinez, ...
    Geophysical Research Letters 44 (24), 12,315-12,323 , 2017
    2017
    Citations: 31
  • Statistical simulation of ocean current patterns using autoregressive logistic regression models: A case study in the Gulf of Mexico
    H Chiri, AJ Abascal, S Castanedo, JAA Antolínez, Y Liu, RH Weisberg, ...
    Ocean Modelling 136, 1-12 , 2019
    2019
    Citations: 28
  • Distribution of global sea turtle nesting explained from regional-scale coastal characteristics
    JC Christiaanse, JAA Antolínez, AP Luijendijk, P Athanasiou, CM Duarte, ...
    Scientific Reports 14 (1), 752 , 2024
    2024
    Citations: 25
  • Seas and swells throughout New Zealand: A new partitioned hindcast
    J Albuquerque, JAA Antolínez, RM Gorman, FJ Méndez, G Coco
    Ocean Modelling 168, 101897 , 2021
    2021
    Citations: 25
  • Sensitivity of salt intrusion to estuary-scale changes: A systematic modelling study towards nature-based mitigation measures
    GG Hendrickx, WM Kranenburg, JAA Antolínez, Y Huismans, ...
    Estuarine, Coastal and Shelf Science 295, 108564 , 2023
    2023
    Citations: 24