Articles | Volume 21, issue 2
https://doi.org/10.5194/os-21-767-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-21-767-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Ocean wave spectrum bias correction through energy conservation for climate change impacts
Andrea Lira Loarca
CORRESPONDING AUTHOR
Department of Civil, Chemical and Environmental Engineering, University of Genoa, Via Montallegro 1, 16145, Genoa, Italy
Giovanni Besio
Department of Civil, Chemical and Environmental Engineering, University of Genoa, Via Montallegro 1, 16145, Genoa, Italy
Related authors
Francesco Ferrari, Carmen Zarzuelo, Alejandro López-Ruiz, and Andrea Lira-Loarca
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-92, https://doi.org/10.5194/essd-2025-92, 2025
Preprint under review for ESSD
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This study presents a high-resolution, open-access dataset for Deception Island, Antarctica, covering 2005–2020. Using WRF and DELFT3D models, it includes 161 atmospheric variables (e.g., wind, precipitation, pressure) and hydrodynamic data (e.g., sea surface height, currents, wave height). Capturing spatial, seasonal, and extreme event variability, it enhances understanding of Antarctic coastal dynamics, supporting research on glacial melt, nutrient transport, and climate change impacts.
Eva Sebok, Hans Jørgen Henriksen, Ernesto Pastén-Zapata, Peter Berg, Guillaume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellström, Jens Hesselbjerg Christensen, Jean Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, María José Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 26, 5605–5625, https://doi.org/10.5194/hess-26-5605-2022, https://doi.org/10.5194/hess-26-5605-2022, 2022
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Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
Francesco Ferrari, Carmen Zarzuelo, Alejandro López-Ruiz, and Andrea Lira-Loarca
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-92, https://doi.org/10.5194/essd-2025-92, 2025
Preprint under review for ESSD
Short summary
Short summary
This study presents a high-resolution, open-access dataset for Deception Island, Antarctica, covering 2005–2020. Using WRF and DELFT3D models, it includes 161 atmospheric variables (e.g., wind, precipitation, pressure) and hydrodynamic data (e.g., sea surface height, currents, wave height). Capturing spatial, seasonal, and extreme event variability, it enhances understanding of Antarctic coastal dynamics, supporting research on glacial melt, nutrient transport, and climate change impacts.
Eva Sebok, Hans Jørgen Henriksen, Ernesto Pastén-Zapata, Peter Berg, Guillaume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellström, Jens Hesselbjerg Christensen, Jean Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, María José Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 26, 5605–5625, https://doi.org/10.5194/hess-26-5605-2022, https://doi.org/10.5194/hess-26-5605-2022, 2022
Short summary
Short summary
Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
Francesco De Leo, Sebastián Solari, and Giovanni Besio
Nat. Hazards Earth Syst. Sci., 20, 1233–1246, https://doi.org/10.5194/nhess-20-1233-2020, https://doi.org/10.5194/nhess-20-1233-2020, 2020
Francesco De Leo, Giovanni Besio, Guido Zolezzi, and Marco Bezzi
Nat. Hazards Earth Syst. Sci., 19, 287–298, https://doi.org/10.5194/nhess-19-287-2019, https://doi.org/10.5194/nhess-19-287-2019, 2019
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This paper reviews the computation of vulnerability levels (VLs) of a coast to inundation with a known model. We refer to the original proposal, detailing the VL computation through an accurate investigation of the local wave climate. We prove that the resulting vulnerability is very sensitive due to the wave features taken into account, which have to be properly assessed. The research is the follow-up of a wider project set along the Bay of Lalzit (Albania).
Giovanni Besio, Riccardo Briganti, Alessandro Romano, Lorenzo Mentaschi, and Paolo De Girolamo
Nat. Hazards Earth Syst. Sci., 17, 505–514, https://doi.org/10.5194/nhess-17-505-2017, https://doi.org/10.5194/nhess-17-505-2017, 2017
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Results of 36-years of hindcast in the Mediterranean Sea are analysed to detect time clustering of wave storms using the Allan factor. The analysis reveals that some areas of the basin are characterized by storm clustering for timescales t < 50 days, while seasonality is dominant at large scales. The findings highlight a deviation from the Poisson distribution in some sub-basins of the Mediterranean Sea. Implications for coastal erosion/flooding need to be studied further.
Lorenzo Mentaschi, Michalis Vousdoukas, Evangelos Voukouvalas, Ludovica Sartini, Luc Feyen, Giovanni Besio, and Lorenzo Alfieri
Hydrol. Earth Syst. Sci., 20, 3527–3547, https://doi.org/10.5194/hess-20-3527-2016, https://doi.org/10.5194/hess-20-3527-2016, 2016
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The climate is subject to variations which must be considered
studying the intensity and frequency of extreme events.
We introduce in this paper a new methodology
for the study of variable extremes, which consists in detecting
the pattern of variability of a time series, and applying these patterns
to the analysis of the extreme events.
This technique comes with advantages with respect to the previous ones
in terms of accuracy, simplicity, and robustness.
Related subject area
Approach: Numerical Models | Properties and processes: Climate and modes of variability
A new vision of the Adriatic Dense Water future under extreme warming
Marine Heatwaves in the Mediterranean Sea: A Convolutional Neural Network study for extreme event prediction
Seafloor marine heatwaves outpace surface events in future on the northwest European shelf
Dynamically downscaled seasonal ocean forecasts for North American east coast ecosystems
On the response of the Equatorial Atmosphere and Ocean to changes in Sea Surface Temperature along the Path of the North Equatorial Counter Current
Exploring variability in climate change projections on the Nemunas River and Curonian Lagoon: coupled SWAT and SHYFEM modeling approach
An assessment of equatorial Atlantic interannual variability in Ocean Model Intercomparison Project (OMIP) simulations
Twenty-first century marine climate projections for the NW European shelf seas based on a perturbed parameter ensemble
AdriE: a high-resolution ocean model ensemble for the Adriatic Sea under severe climate change conditions
Predictability of marine heatwaves: assessment based on the ECMWF seasonal forecast system
The Mediterranean Forecasting System – Part 1: Evolution and performance
Cléa Denamiel, Iva Tojčić, and Petra Pranić
Ocean Sci., 21, 37–62, https://doi.org/10.5194/os-21-37-2025, https://doi.org/10.5194/os-21-37-2025, 2025
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We use a high-resolution atmosphere–ocean model to project Adriatic Dense Water dynamics under extreme warming. We find that a 15 % increase in sea surface evaporation will offset a 25 % decrease in extreme windstorms. As a result, future dense water will form at the same rate as today but will be too light to reach the Adriatic's deepest parts, making deep-water presence reliant on exchanges with the Ionian Sea.
Antonios Parasyris, Vassiliki Metheniti, Nikolaos Kampanis, and Sofia Darmaraki
EGUsphere, https://doi.org/10.5194/egusphere-2024-4003, https://doi.org/10.5194/egusphere-2024-4003, 2025
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The Mediterranean faces more frequent and intense Marine Heatwaves, harming ecosystems and fisheries. Using Machine Learning, we developed a model to forecast these events up to seven days in the future, outperforming traditional methods. This approach enables faster, accurate forecasts, helping authorities mitigate impacts and protect marine resources.
Robert J. Wilson, Yuri Artioli, Giovanni Galli, James Harle, Jason Holt, Ana M. Queiros, and Sarah Wakelin
EGUsphere, https://doi.org/10.5194/egusphere-2024-3810, https://doi.org/10.5194/egusphere-2024-3810, 2024
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Marine heatwaves are of growing concern around the world. We use a state of the art ensemble of downscaled climate models to project how often heatwaves will occur in future across northwest Europe under a high-emissions scenario. The projections show that without emissions reductions, heatwaves will occur more than half of the time in future. We show that the seafloor is expected to experience much more frequent heatwaves than the sea surface in future.
Andrew C. Ross, Charles A. Stock, Vimal Koul, Thomas L. Delworth, Feiyu Lu, Andrew Wittenberg, and Michael A. Alexander
Ocean Sci., 20, 1631–1656, https://doi.org/10.5194/os-20-1631-2024, https://doi.org/10.5194/os-20-1631-2024, 2024
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In this paper, we use a high-resolution regional ocean model to downscale seasonal ocean forecasts from the Seamless System for Prediction and EArth System Research (SPEAR) model of the Geophysical Fluid Dynamics Laboratory (GFDL). We find that the downscaled model has significantly higher prediction skill in many cases.
David John Webb
EGUsphere, https://doi.org/10.5194/egusphere-2024-3560, https://doi.org/10.5194/egusphere-2024-3560, 2024
Preprint withdrawn
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A modern climate model is used to test the hypothesis that changes observed during El Niños are, in part, forced by changes in the temperature of the North Equatorial Counter Current. This is a warm current that flows eastwards across the Pacific, a few degrees north of the Equator, close to the Inter-Tropical Convection Zone, a major region of deep atmospheric convection. The tests generate a significant El Niño type response in the ocean, giving confidence that the hypothesis is correct.
Natalja Čerkasova, Jovita Mėžinė, Rasa Idzelytė, Jūratė Lesutienė, Ali Ertürk, and Georg Umgiesser
Ocean Sci., 20, 1123–1147, https://doi.org/10.5194/os-20-1123-2024, https://doi.org/10.5194/os-20-1123-2024, 2024
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This study advances the understanding of climate projection variability in the Nemunas River, Curonian Lagoon, and southeastern Baltic Sea continuum by analyzing a subset of climate models with a focus on a coupled ocean and drainage basin model. This study investigates the variability and trends in environmental parameters, such as water fluxes, timing, nutrient load, water temperature, ice cover, and saltwater intrusions in Representative Concentration Pathway 4.5 and 8.5 scenarios.
Arthur Prigent and Riccardo Farneti
Ocean Sci., 20, 1067–1086, https://doi.org/10.5194/os-20-1067-2024, https://doi.org/10.5194/os-20-1067-2024, 2024
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We evaluate the eastern equatorial Atlantic's (EEA's) seasonal cycle and interannual variability in the Ocean Model Intercomparison Project Phases 1 and 2 (OMIP1 and OMIP2) for 1985–2004. While both simulate EEA patterns, biases like a diffusive thermocline and insufficient cooling exist during the development of the Atlantic cold tongue. OMIP1 exhibits 51% (33%) larger interannual sea surface temperature (sea surface height) variability than OMIP2, attributed to differences in wind forcing.
Jonathan Tinker, Matthew D. Palmer, Benjamin J. Harrison, Enda O'Dea, David M. H. Sexton, Kuniko Yamazaki, and John W. Rostron
Ocean Sci., 20, 835–885, https://doi.org/10.5194/os-20-835-2024, https://doi.org/10.5194/os-20-835-2024, 2024
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The northwest European shelf (NWS) seas are economically and environmentally important but poorly represented in global climate models (GCMs). We combine use of a shelf sea model with GCM output to provide improved 21st century projections of the NWS. We project a NWS warming of 3.11 °C and freshening of −1.01, and we provide uncertainty estimates. We calculate the climate signal emergence and consider warming levels. We have released our data for the UK's Climate Change Risk Assessment.
Davide Bonaldo, Sandro Carniel, Renato R. Colucci, Cléa Denamiel, Petra Pranic, Fabio Raicich, Antonio Ricchi, Lorenzo Sangelantoni, Ivica Vilibic, and Maria Letizia Vitelletti
EGUsphere, https://doi.org/10.5194/egusphere-2024-1468, https://doi.org/10.5194/egusphere-2024-1468, 2024
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We present a high-resolution modelling effort to investigate the possible end-of-century evolution of the main physical processes in the Adriatic Sea in a severe climate change scenario, with an ensemble approach (viz., use a of multiple simulations) allowing to control the uncertainty of the predictions. Our model exhibits a satisfactory capability to reproduce the recent past and provides a ground for a set of multidisciplinary studies in this area over a multi-decadal horizon.
Eric de Boisséson and Magdalena Alonso Balmaseda
Ocean Sci., 20, 265–278, https://doi.org/10.5194/os-20-265-2024, https://doi.org/10.5194/os-20-265-2024, 2024
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Marine heatwaves are long periods of extremely warm ocean surface temperatures. Predicting such events a few months in advance would help decision-making to mitigate their impacts on marine ecosystems. This work investigates how well operational seasonal forecasts can predict marine heatwaves. Results show that such events can be predicted a few months in advance in the tropics but that extending the predictability skill to other regions will require additional work on the forecast models.
Giovanni Coppini, Emanuela Clementi, Gianpiero Cossarini, Stefano Salon, Gerasimos Korres, Michalis Ravdas, Rita Lecci, Jenny Pistoia, Anna Chiara Goglio, Massimiliano Drudi, Alessandro Grandi, Ali Aydogdu, Romain Escudier, Andrea Cipollone, Vladyslav Lyubartsev, Antonio Mariani, Sergio Cretì, Francesco Palermo, Matteo Scuro, Simona Masina, Nadia Pinardi, Antonio Navarra, Damiano Delrosso, Anna Teruzzi, Valeria Di Biagio, Giorgio Bolzon, Laura Feudale, Gianluca Coidessa, Carolina Amadio, Alberto Brosich, Arnau Miró, Eva Alvarez, Paolo Lazzari, Cosimo Solidoro, Charikleia Oikonomou, and Anna Zacharioudaki
Ocean Sci., 19, 1483–1516, https://doi.org/10.5194/os-19-1483-2023, https://doi.org/10.5194/os-19-1483-2023, 2023
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The paper presents the Mediterranean Forecasting System evolution and performance developed in the framework of the Copernicus Marine Service.
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Short summary
A new method improves the accuracy of climate models by adjusting wave spectrum simulations in the Mediterranean Sea. It corrects biases and accounts for changes in wave patterns due to climate change, such as shifts in direction and frequency. This technique was applied to multiple climate models, assessing future wave conditions for mid-century and end-of-century scenarios. The results underline the importance of precise corrections for better predicting how waves may evolve as the climate changes.
A new method improves the accuracy of climate models by adjusting wave spectrum simulations in...