Articles | Volume 19, issue 2
https://doi.org/10.5194/os-19-499-2023
© Author(s) 2023. 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-19-499-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Apr 2023
Research article |
| 21 Apr 2023
| 21 Apr 2023
Improving statistical projections of ocean dynamic sea-level change using pattern recognition techniques
Víctor Malagón-Santos
CORRESPONDING AUTHOR
NIOZ Royal Netherlands Institute for Sea Research, Department of Estuarine & Delta Systems, P.O. Box 140, 4400 AC Yerseke, the Netherlands
Aimée B. A. Slangen
NIOZ Royal Netherlands Institute for Sea Research, Department of Estuarine & Delta Systems, P.O. Box 140, 4400 AC Yerseke, the Netherlands
Tim H. J. Hermans
NIOZ Royal Netherlands Institute for Sea Research, Department of Estuarine & Delta Systems, P.O. Box 140, 4400 AC Yerseke, the Netherlands
University of Utrecht, Institute for Marine and Atmospheric Research Utrecht (IMAU), Utrecht, the Netherlands
Sönke Dangendorf
Department of River–Coastal Science and Engineering, Tulane University, New Orleans, USA
Marta Marcos
Mediterranean Institute for Advanced Studies (IMEDEA), Spanish National Research Council–University of Balearic Islands (CSIC-UIB), Esporles, Spain
Nicola Maher
Cooperative Institute for Research in Environmental Science, University of Colorado, Boulder, CO, USA
Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO, USA
Max Planck Institute for Meteorology, Hamburg, Germany
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Alexander Nauels, Tessa Möller, Victor Couplet, Robert E. Kopp, Praveen Kumar, Matthias Mengel, Gregory Munday, Zebedee R. J. Nicholls, Lennart Ramme, Aimée B. A. Slangen, Chris Smith, Jennifer H. Weeks, and Tony E. Wong
EGUsphere, https://doi.org/10.5194/egusphere-2026-3874, https://doi.org/10.5194/egusphere-2026-3874, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Sea levels will keep rising for centuries, so coastal planning needs long-term outlooks. For the first time, we brought together seven simplified models, called emulators, and combined their estimates of future sea level rise to year 2300, including a scenario with strong temperature overshoot before returning to 1.5 °C of warming. The emulators differ most over how much ice Antarctica will lose. Even if global temperatures fall again, extra sea level rise stays locked in for centuries.
Angel Amores, Roberto Alcaraz, Marta Marcos, Philip Thompson, Ariadna Martín, and Thomas Wahl
EGUsphere, https://doi.org/10.5194/egusphere-2026-5073, https://doi.org/10.5194/egusphere-2026-5073, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Coastal sea level records are short, full of gaps and often affected by instrument faults, which limits the study of extreme events and of how they are changing. We trained a neural network on these records to rebuild hourly sea level at 373 coastal sites worldwide, from 1940 to the present, driven mainly by weather data. It reproduces the observed sea level down to the largest storm surges, extends the records back in time, and can also flag faulty stretches in the measurements themselves.
Piers M. Forster, Tristram Walsh, Chris Smith, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Robbie M. Andrew, Chris Atkinson, Richard A. Betts, Antonio Bombelli, Samantha N. Burgess, Lijing Cheng, Helen E. Claxton, Pierre Friedlingstein, Thomas L. Frölicher, Catia M. Domingues, Thomas Gasser, Catherine H. Gregory, Rachel M. Hoesly, Daniel Huppmann, Masayoshi Ishii, Christopher Kadow, Alexia Karwat, John Kennedy, Rachel E. Killick, Mahesh V. M. Kovilakam, Paul B. Krummel, Xin Lan, Jean-François Lamarque, Aurélien Liné, Belén Martín-Míguez, Didier P. Monselesan, Colin Morice, Jens Mühle, Pino Mussak, Glen P. Peters, Anna Pirani, Julia Pongratz, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Steven J. Smith, Ghassan Taha, Caterina Tassone, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Marco Zecchetto, Junting Zhong, Xiao-Ye Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 18, 3889–3933, https://doi.org/10.5194/essd-18-3889-2026, https://doi.org/10.5194/essd-18-3889-2026, 2026
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We give our annual update of key climate indicators. Our work quantifies the human contribution to global warming and the pace of climate change. This represents a large effort by the international community akin to an Intergovernmental Panel on Climate Change (IPCC) report.
Marina Lévy, Karina von Schuckmann, Mahé Butel, William W. L. Cheung, Joachim Claudet, Thomas L. Frölicher, Patrice Guillotreau, Peter Haugan, Janine Adams, Diva Amon, Tamatoa Bambridge, Cynthia Barzuna, Bruno Blanke, Lijing Cheng, Sanae Chiba, Jorge Cortés, Pierre Friedlingstein, Jean-Pierre Gattuso, Stefan Gelcich, Jessica Gephart, Deborah Greaves, Audrey Hasson, Claire Jolly, Daoji Li, Yunne-Jai Shin, Aimée Slangen, Mere Takoko, Olivier Thébaud, Adrien Vincent, and Patrick Vincent
State Planet, 7-osr10, 1, https://doi.org/10.5194/sp-7-osr10-1-2026, https://doi.org/10.5194/sp-7-osr10-1-2026, 2026
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The Starfish Barometer provides an annual, science-based synthesis of global Ocean-related developments, structured around five interconnected dimensions: the Ocean state, human pressures, societal harms, protection efforts, and opportunities for humanity. It is released each year on World Ocean Day. This article presents the second edition of the Barometer, which shows a growing gap between increasing human pressures on the Ocean and the efforts being made to protect it and drive change.
Michael G. Hart-Davis, Roman Sulzbach, Stefan A. Talke, Ivan D. Haigh, Marta Marcos, Philip Woodworth, Richard Ray, Ole B. Andersen, Florent Lyard, Ergane Fouchet, Denise Dettmering, Maik Thomas, and Florian Seitz
Ocean Sci., 22, 1681–1709, https://doi.org/10.5194/os-22-1681-2026, https://doi.org/10.5194/os-22-1681-2026, 2026
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Ocean tides are a critical component of the global climate system, influencing a wide range of geophysical processes. Tide gauges have been a valuable source for developing the theory of ocean tides and for understanding their variability. We provide updated and new insights on tidal properties using the Global Extreme Sea Level Analysis tide gauge dataset, intended to be useful to a range of applications, from navigation and fishing communities to ocean scientists and tidal experts.
Pravin Maduwantha, Thomas Wahl, Sara Santamaria-Aguilar, Robert Jane, Sönke Dangendorf, Hanbeen Kim, and Gabriele Villarini
Hydrol. Earth Syst. Sci., 30, 401–420, https://doi.org/10.5194/hess-30-401-2026, https://doi.org/10.5194/hess-30-401-2026, 2026
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Compound flooding occurs when multiple drivers, such as heavy rain and storm surge, occur simultaneously. Comprehensive compound flood risk assessments require simulating many storm events using flood models, but such historical data are limited. To address this, we developed a statistical framework to generate large numbers of synthetic yet realistic storm events for use in compound flood modeling.
Ming Cheng, Nicola Maher, and Michael J. Ellwood
Biogeosciences, 22, 7269–7291, https://doi.org/10.5194/bg-22-7269-2025, https://doi.org/10.5194/bg-22-7269-2025, 2025
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The Southern Ocean helps regulate Earth’s climate by cycling nutrients and carbon. We studied how well 14 modern climate models represent key ocean properties, such as plant growth, nutrients, and carbon particles. By comparing model results with real-world observations, we found large differences in model performance. Some models captured certain features better than others. Our findings can guide future improvements in ocean and climate predictions.
Tim H. J. Hermans, Chiheb Ben Hammouda, Simon Treu, Timothy Tiggeloven, Anaïs Couasnon, Julius J. M. Busecke, and Roderik S. W. van de Wal
Nat. Hazards Earth Syst. Sci., 25, 4593–4612, https://doi.org/10.5194/nhess-25-4593-2025, https://doi.org/10.5194/nhess-25-4593-2025, 2025
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We studied the performance of different types of neural networks at predicting extreme storm surges. We found that that performance improves when during model training, storm surges that are rarer are given a higher weight than moderate storm surges. Additionally, we found that the performance of some of the neural networks approaches that of a state-of-the-art hydrodynamic model. This is promising for the future application of neural networks to climate model simulations.
Nicola Maher, Adam S. Phillips, Clara Deser, Robert C. Jnglin Wills, Flavio Lehner, John Fasullo, Julie M. Caron, Lukas Brunner, Urs Beyerle, and Jemma Jeffree
Geosci. Model Dev., 18, 6341–6365, https://doi.org/10.5194/gmd-18-6341-2025, https://doi.org/10.5194/gmd-18-6341-2025, 2025
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We present the new Multi-Model Large Ensemble Archive (MMLEAv2) and introduce the newly updated Climate Variability Diagnostics Package version 6 (CVDPv6), which is designed specifically for use with large ensembles. For highly variable quantities, we demonstrate that a model might perform evaluation poorly or favourably compared to the single realisation of the world that the observations represent, highlighting the need for large ensembles for model evaluation.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 17, 2641–2680, https://doi.org/10.5194/essd-17-2641-2025, https://doi.org/10.5194/essd-17-2641-2025, 2025
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In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets to track real-world changes over time. To make our work relevant to policymakers, we follow methods from the Intergovernmental Panel on Climate Change (IPCC). Human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the IPCC assessment.
Andrew D. King, Tilo Ziehn, Matthew Chamberlain, Alexander R. Borowiak, Josephine R. Brown, Liam Cassidy, Andrea J. Dittus, Michael Grose, Nicola Maher, Seungmok Paik, Sarah E. Perkins-Kirkpatrick, and Aditya Sengupta
Earth Syst. Dynam., 15, 1353–1383, https://doi.org/10.5194/esd-15-1353-2024, https://doi.org/10.5194/esd-15-1353-2024, 2024
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Governments are targeting net-zero emissions later this century with the aim of limiting global warming in line with the Paris Agreement. However, few studies explore the long-term consequences of reaching net-zero emissions and the effects of a delay in reaching net-zero. We use the Australian Earth system model to examine climate evolution under net-zero emissions. We find substantial changes which differ regionally, including continued Southern Ocean warming and Antarctic sea ice reduction.
Angélique Melet, Roderik van de Wal, Angel Amores, Arne Arns, Alisée A. Chaigneau, Irina Dinu, Ivan D. Haigh, Tim H. J. Hermans, Piero Lionello, Marta Marcos, H. E. Markus Meier, Benoit Meyssignac, Matthew D. Palmer, Ronja Reese, Matthew J. R. Simpson, and Aimée B. A. Slangen
State Planet, 3-slre1, 4, https://doi.org/10.5194/sp-3-slre1-4-2024, https://doi.org/10.5194/sp-3-slre1-4-2024, 2024
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The EU Knowledge Hub on Sea Level Rise’s Assessment Report strives to synthesize the current scientific knowledge on sea level rise and its impacts across local, national, and EU scales to support evidence-based policy and decision-making, primarily targeting coastal areas. This paper complements IPCC reports by documenting the state of knowledge of observed and 21st century projected changes in mean and extreme sea levels with more regional information for EU seas as scoped with stakeholders.
Sönke Dangendorf, Qiang Sun, Thomas Wahl, Philip Thompson, Jerry X. Mitrovica, and Ben Hamlington
Earth Syst. Sci. Data, 16, 3471–3494, https://doi.org/10.5194/essd-16-3471-2024, https://doi.org/10.5194/essd-16-3471-2024, 2024
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Sea-level information from the global ocean is sparse in time and space, with comprehensive data being limited to the period since 2005. Here we provide a novel reconstruction of sea level and its contributing causes, as determined by a Kalman smoother approach applied to tide gauge records over the period 1900–2021. The new reconstruction shows a continuing acceleration in global mean sea-level rise since 1970 that is dominated by melting land ice. Contributors vary significantly by region.
Nil Carrion-Bertran, Albert Falqués, Francesca Ribas, Daniel Calvete, Rinse de Swart, Ruth Durán, Candela Marco-Peretó, Marta Marcos, Angel Amores, Tim Toomey, Àngels Fernández-Mora, and Jorge Guillén
Earth Surf. Dynam., 12, 819–839, https://doi.org/10.5194/esurf-12-819-2024, https://doi.org/10.5194/esurf-12-819-2024, 2024
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The sensitivity to the wave and sea-level forcing sources in predicting a 6-month embayed beach evolution is assessed using two different morphodynamic models. After a successful model calibration using in situ data, other sources are applied. The wave source choice is critical: hindcast data provide wrong results due to an angle bias, whilst the correct dynamics are recovered with the wave conditions from an offshore buoy. The use of different sea-level sources gives no significant differences.
Simon Treu, Sanne Muis, Sönke Dangendorf, Thomas Wahl, Julius Oelsmann, Stefanie Heinicke, Katja Frieler, and Matthias Mengel
Earth Syst. Sci. Data, 16, 1121–1136, https://doi.org/10.5194/essd-16-1121-2024, https://doi.org/10.5194/essd-16-1121-2024, 2024
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This article describes a reconstruction of monthly coastal water levels from 1900–2015 and hourly data from 1979–2015, both with and without long-term sea level rise. The dataset is based on a combination of three datasets that are focused on different aspects of coastal water levels. Comparison with tide gauge records shows that this combination brings reconstructions closer to the observations compared to the individual datasets.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
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Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Nicola Maher, Robert C. Jnglin Wills, Pedro DiNezio, Jeremy Klavans, Sebastian Milinski, Sara C. Sanchez, Samantha Stevenson, Malte F. Stuecker, and Xian Wu
Earth Syst. Dynam., 14, 413–431, https://doi.org/10.5194/esd-14-413-2023, https://doi.org/10.5194/esd-14-413-2023, 2023
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Understanding whether the El Niño–Southern Oscillation (ENSO) is likely to change in the future is important due to its widespread impacts. By using large ensembles, we can robustly isolate the time-evolving response of ENSO variability in 14 climate models. We find that ENSO variability evolves in a nonlinear fashion in many models and that there are large differences between models. These nonlinear changes imply that ENSO impacts may vary dramatically throughout the 21st century.
Ariadna Martín, Angel Amores, Alejandro Orfila, Tim Toomey, and Marta Marcos
Nat. Hazards Earth Syst. Sci., 23, 587–600, https://doi.org/10.5194/nhess-23-587-2023, https://doi.org/10.5194/nhess-23-587-2023, 2023
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Tropical cyclones (TCs) are among the potentially most hazardous phenomena affecting the coasts of the Caribbean Sea. This work simulates the coastal hazards in terms of sea surface elevation and waves that originate through the passage of these events. A set of 1000 TCs have been simulated, obtained from a set of synthetic cyclones that are consistent with present-day climate. Given the large number of hurricanes used, robust values of extreme sea levels and waves are computed along the coasts.
Carolina M. L. Camargo, Riccardo E. M. Riva, Tim H. J. Hermans, Eike M. Schütt, Marta Marcos, Ismael Hernandez-Carrasco, and Aimée B. A. Slangen
Ocean Sci., 19, 17–41, https://doi.org/10.5194/os-19-17-2023, https://doi.org/10.5194/os-19-17-2023, 2023
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Sea-level change is mainly caused by variations in the ocean’s temperature and salinity and land ice melting. Here, we quantify the contribution of the different drivers to the regional sea-level change. We apply machine learning techniques to identify regions that have similar sea-level variability. These regions reduce the observational uncertainty that has limited the regional sea-level budget so far and highlight how large-scale ocean circulation controls regional sea-level change.
Carolina M. L. Camargo, Riccardo E. M. Riva, Tim H. J. Hermans, and Aimée B. A. Slangen
Earth Syst. Dynam., 13, 1351–1375, https://doi.org/10.5194/esd-13-1351-2022, https://doi.org/10.5194/esd-13-1351-2022, 2022
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The mass loss from Antarctica, Greenland and glaciers and variations in land water storage cause sea-level changes. Here, we characterize the regional trends within these sea-level contributions, taking into account mass variations since 1993. We take a comprehensive approach to determining the uncertainties of these sea-level changes, considering different types of errors. Our study reveals the importance of clearly quantifying the uncertainties of sea-level change trends.
Nicola Maher, Thibault P. Tabarin, and Sebastian Milinski
Earth Syst. Dynam., 13, 1289–1304, https://doi.org/10.5194/esd-13-1289-2022, https://doi.org/10.5194/esd-13-1289-2022, 2022
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El Niño events occur as two broad types: eastern Pacific (EP) and central Pacific (CP). EP and CP events differ in strength, evolution, and in their impacts. In this study we create a new machine learning classifier to identify the two types of El Niño events using observed sea surface temperature data. We apply our new classifier to climate models and show that CP events are unlikely to change in frequency or strength under a warming climate, with model disagreement for EP events.
Begoña Pérez Gómez, Ivica Vilibić, Jadranka Šepić, Iva Međugorac, Matjaž Ličer, Laurent Testut, Claire Fraboul, Marta Marcos, Hassen Abdellaoui, Enrique Álvarez Fanjul, Darko Barbalić, Benjamín Casas, Antonio Castaño-Tierno, Srđan Čupić, Aldo Drago, María Angeles Fraile, Daniele A. Galliano, Adam Gauci, Branislav Gloginja, Víctor Martín Guijarro, Maja Jeromel, Marcos Larrad Revuelto, Ayah Lazar, Ibrahim Haktan Keskin, Igor Medvedev, Abdelkader Menassri, Mohamed Aïssa Meslem, Hrvoje Mihanović, Sara Morucci, Dragos Niculescu, José Manuel Quijano de Benito, Josep Pascual, Atanas Palazov, Marco Picone, Fabio Raicich, Mohamed Said, Jordi Salat, Erdinc Sezen, Mehmet Simav, Georgios Sylaios, Elena Tel, Joaquín Tintoré, Klodian Zaimi, and George Zodiatis
Ocean Sci., 18, 997–1053, https://doi.org/10.5194/os-18-997-2022, https://doi.org/10.5194/os-18-997-2022, 2022
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This description and mapping of coastal sea level monitoring networks in the Mediterranean and Black seas reveals the existence of 240 presently operational tide gauges. Information is provided about the type of sensor, time sampling, data availability, and ancillary measurements. An assessment of the fit-for-purpose status of the network is also included, along with recommendations to mitigate existing bottlenecks and improve the network, in a context of sea level rise and increasing extremes.
Benjamin Ward, Francesco S. R. Pausata, and Nicola Maher
Earth Syst. Dynam., 12, 975–996, https://doi.org/10.5194/esd-12-975-2021, https://doi.org/10.5194/esd-12-975-2021, 2021
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Using the largest ensemble of a climate model currently available, the Max Planck Institute Grand Ensemble (MPI-GE), we investigated the impact of the spatial distribution of volcanic aerosols on the El Niño–Southern Oscillation (ENSO) response. By selecting three eruptions with different aerosol distributions, we found that the shift of the Intertropical Convergence Zone (ITCZ) is the main driver of the ENSO response, while other mechanisms commonly invoked seem less important in our model.
Cited articles
Becker, M., Karpytchev, M., and Lennartz-Sassinek, S.:
Long-term sea level trends: Natural or anthropogenic?, Geophys. Res. Lett., 41, 5571–5580, https://doi.org/10.1002/2014GL061027, 2014.
Bilbao, R. A. F., Gregory, J. M., and Bouttes, N.:
Analysis of the regional pattern of sea level change due to ocean dynamics and density change for 1993–2099 in observations and CMIP5 AOGCMs, Clim. Dynam., 45, 2647–2666, https://doi.org/10.1007/s00382-015-2499-z, 2015.
Bouttes, N., Gregory, J. M., Kuhlbrodt, T., and Smith, R. S.:
The drivers of projected North Atlantic sea level change, Clim. Dynam., 43, 1531–1544, https://doi.org/10.1007/s00382-013-1973-8, 2014.
Church, J. A., Clark, P. U., Cazenave, A., Gregory, J. M., Jevrejeva, S., Levermann, A., Merrifield, M. A., Milne, G. A., Nerem, R. S., Nunn, P. D., Payne, A. J., Pfeffer, W. T., Stammer, D., and Unnikrishnan, A. S.:
Sea Level Change, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013.
CMIP5: CMIP5 data search, ESGF-cog – Lawrence Livermore National [data set], https://esgf-node.llnl.gov/search/cmip5/, last access: 18 April 2023.
Collins, M., Knutti, R., Arblaster, J., Dufresne, J.-L., Fichefet, T., Friedlingstein, P., Gao, X., Gutowski, W. J., Johns, T., Krinner, G., Shongwe, M., Tebaldi, C., Weaver, A. J., and Wehner, M.: Long-term Climate Change: Projections, Commitments and Irreversibility, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013.
Cooley, S., Schoeman, D., Bopp, L., Boyd, P., Donner, S., Ghebrehiwet, D. Y., Ito, S.-I., Kiessling, W., Martinetto, P., Ojea, E., Racault, M.-F., Rost, B., and Skern-Mauritzen, M.: Oceans and Coastal Ecosystems and Their Services, in: Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Pörtner, H.-O., Roberts, D. C., Tignor, M., Poloczanska, E. S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., and Rama, B., Cambridge University Press, Cambridge, UK and New York, NY, USA, 379–550, 2022.
Couldrey, M. P., Gregory, J. M., Boeira Dias, F., Dobrohotoff, P., Domingues, C. M., Garuba, O., Griffies, S. M., Haak, H., Hu, A., Ishii, M., Jungclaus, J., Köhl, A., Marsland, S. J., Ojha, S., Saenko, O. A., Savita, A., Shao, A., Stammer, D., Suzuki, T., Todd, A., and Zanna, L.:
What causes the spread of model projections of ocean dynamic sea-level change in response to greenhouse gas forcing?, Clim. Dynam., 56, 155–187, https://doi.org/10.1007/s00382-020-05471-4, 2021.
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., and Gettelman, A.:
The community earth system model version 2 (CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020.
Dangendorf, S., Rybski, D., Mudersbach, C., Müller, A., Kaufmann, E., Zorita, E., and Jensen, J.:
Evidence for long-term memory in sea level, Geophys. Res. Lett., 41, 5530–5537, https://doi.org/10.1002/2014GL060538, 2014.
Dangendorf, S., Hay, C., Calafat, F. M., Marcos, M., Piecuch, C. G., Berk, K., and Jensen, J.:
Persistent acceleration in global sea-level rise since the 1960s, Nat. Clim. Change, 9, 705–710, https://doi.org/10.1038/s41558-019-0531-8, 2019.
DelSole, T., Tippett, M. K., and Shukla, J.:
A significant component of unforced multidecadal variability in the recent acceleration of global warming, J. Climate, 24, 909–926, 2011.
Deser, C., Lehner, F., Rodgers, K. B., Ault, T., Delworth, T. L., DiNezio, P. N., Fiore, A., Frankignoul, C., Fyfe, J. C., Horton, D. E., Kay, J. E., Knutti, R., Lovenduski, N. S., Marotzke, J., McKinnon, K. A., Minobe, S., Randerson, J., Screen, J. A., Simpson, I. R., and Ting, M.:
Insights from Earth system model initial-condition large ensembles and future prospects, Nat. Clim. Change, 10, 277–286, https://doi.org/10.1038/s41558-020-0731-2, 2020.
Duchon, C. E.:
Lanczos Filtering in One and Two Dimensions, J. Appl. Meteorol. Clim., 18, 1016–1022, https://doi.org/10.1175/1520-0450(1979)018<1016:LFIOAT>2.0.CO;2, 1979.
Durand, G., van den Broeke, M. R., Le Cozannet, G., Edwards, T. L., Holland, P. R., Jourdain, N. C., Marzeion, B., Mottram, R., Nicholls, R. J., Pattyn, F., Paul, F., Slangen, A. B. A., Winkelmann, R., Burgard, C., van Calcar, C. J., Barré, J.-B., Bataille, A., and Chapuis, A.:
Sea-Level Rise: From Global Perspectives to Local Services, Frontiers in Marine Science, 8, https://doi.org/10.3389/fmars.2021.709595, 2022.
Edwards, T. L., Nowicki, S., Marzeion, B., Hock, R., Goelzer, H., Seroussi, H., Jourdain, N. C., Slater, D. A., Turner, F. E., Smith, C. J., McKenna, C. M., Simon, E., Abe-Ouchi, A., Gregory, J. M., Larour, E., Lipscomb, W. H., Payne, A. J., Shepherd, A., Agosta, C., Alexander, P., Albrecht, T., Anderson, B., Asay-Davis, X., Aschwanden, A., Barthel, A., Bliss, A., Calov, R., Chambers, C., Champollion, N., Choi, Y., Cullather, R., Cuzzone, J., Dumas, C., Felikson, D., Fettweis, X., Fujita, K., Galton-Fenzi, B. K., Gladstone, R., Golledge, N. R., Greve, R., Hattermann, T., Hoffman, M. J., Humbert, A., Huss, M., Huybrechts, P., Immerzeel, W., Kleiner, T., Kraaijenbrink, P., Le Clec'h, S., Lee, V., Leguy, G. R., Little, C. M., Lowry, D. P., Malles, J.-H., Martin, D. F., Maussion, F., Morlighem, M., O'Neill, J. F., Nias, I., Pattyn, F., Pelle, T., Price, S. F., Quiquet, A., Radić, V., Reese, R., Rounce, D. R., Rückamp, M., Sakai, A., Shafer, C., Schlegel, N.-J., Shannon, S., Smith, R. S., Straneo, F., Sun, S., Tarasov, L., Trusel, L. D., Van Breedam, J., van de Wal, R., van den Broeke, M., Winkelmann, R., Zekollari, H., Zhao, C., Zhang, T., and Zwinger, T.:
Projected land ice contributions to twenty-first-century sea level rise, Nature, 593, 74–82, https://doi.org/10.1038/s41586-021-03302-y, 2021.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.:
Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Farrell, W. E. and Clark, J. A.:
On postglacial sea level, Geophys. J. Int., 46, 647–667, 1976.
Fasullo, J. T., Gent, P. R., and Nerem, R. S.:
Forced Patterns of Sea Level Rise in the Community Earth System Model Large Ensemble From 1920 to 2100, J. Geophys. Res.-Oceans, 125, e2019JC016030, https://doi.org/10.1029/2019JC016030, 2020.
Ferrero, B., Tonelli, M., Marcello, F., and Wainer, I.:
Long-term Regional Dynamic Sea Level Changes from CMIP6 Projections, Adv. Atmos. Sci., 38, 157–167, https://doi.org/10.1007/s00376-020-0178-4, 2021.
Fox-Kemper, B., Hewitt, H. T., Xiao, C., A.algeirsd.ttir, G., Drijfhout, S. S., Edwards, T. L., Golledge, N. R., Hemer, M., Kopp, R. E., Krinner, G., Mix, A., Notz, D., Nowicki, S., Nurhati, I. S., Ruiz, L., Sallée, J.-B., Slangen, A. B. A., and Yu, Y.:
Ocean, Cryosphere and Sea Level Change, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1211–1362, 2021.
Frankcombe, L. M., Spence, P., Hogg, A. M., England, M. H., and Griffies, S. M.:
Sea level changes forced by Southern Ocean winds, Geophys. Res. Lett., 40, 5710–5715, 2013.
Frankcombe, L. M., England, M. H., Mann, M. E., and Steinman, B. A.:
Separating Internal Variability from the Externally Forced Climate Response, J. Climate, 28, 8184–8202, https://doi.org/10.1175/JCLI-D-15-0069.1, 2015.
Frederikse, T., Landerer, F., Caron, L., Adhikari, S., Parkes, D., Humphrey, V. W., Dangendorf, S., Hogarth, P., Zanna, L., and Cheng, L.:
The causes of sea-level rise since 1900, Nature, 584, 393–397, 2020.
Geoffroy, O., Saint-Martin, D., Olivié, D. J., Voldoire, A., Bellon, G., and Tytéca, S.:
Transient climate response in a two-layer energy-balance model. Part I: Analytical solution and parameter calibration using CMIP5 AOGCM experiments, J. Climate, 26, 1841–1857, 2013a.
Geoffroy, O., Saint-Martin, D., Bellon, G., Voldoire, A., Olivié, D. J. L., and Tytéca, S.:
Transient climate response in a two-layer energy-balance model. Part II: Representation of the efficacy of deep-ocean heat uptake and validation for CMIP5 AOGCMs, J. Climate, 26, 1859–1876, 2013b.
Goodwin, P., Katavouta, A., Roussenov, V. M., Foster, G. L., Rohling, E. J., and Williams, R. G.:
Pathways to 1.5 ∘C and 2 ∘C warming based on observational and geological constraints, Nat. Geosci., 11, 102–107, 2018.
Gregory, J. M., Griffies, S. M., Hughes, C. W., Lowe, J. A., Church, J. A., Fukimori, I., Gomez, N., Kopp, R. E., Landerer, F., Cozannet, G. L., Ponte, R. M., Stammer, D., Tamisiea, M. E., and van de Wal, R. S. W.:
Concepts and Terminology for Sea Level: Mean, Variability and Change, Both Local and Global, Surv. Geophys., 40, 1251–1289, https://doi.org/10.1007/s10712-019-09525-z, 2019.
Griffies, S. M., Danabasoglu, G., Durack, P. J., Adcroft, A. J., Balaji, V., Böning, C. W., Chassignet, E. P., Curchitser, E., Deshayes, J., Drange, H., Fox-Kemper, B., Gleckler, P. J., Gregory, J. M., Haak, H., Hallberg, R. W., Heimbach, P., Hewitt, H. T., Holland, D. M., Ilyina, T., Jungclaus, J. H., Komuro, Y., Krasting, J. P., Large, W. G., Marsland, S. J., Masina, S., McDougall, T. J., Nurser, A. J. G., Orr, J. C., Pirani, A., Qiao, F., Stouffer, R. J., Taylor, K. E., Treguier, A. M., Tsujino, H., Uotila, P., Valdivieso, M., Wang, Q., Winton, M., and Yeager, S. G.:
OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project, Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, 2016.
Gupta, A. S., Jourdain, N. C., Brown, J. N., and Monselesan, D.:
Climate drift in the CMIP5 models, J. Climate, 26, 8597–8615, 2013.
Haasnoot, M., Brown, S., Scussolini, P., Jimenez, J. A., Vafeidis, A. T., and Nicholls, R. J.:
Generic adaptation pathways for coastal archetypes under uncertain sea-level rise, Environ. Res. Commun., 1, 071006, https://doi.org/10.1088/2515-7620/ab1871, 2019.
Haasnoot, M., Winter, G., Brown, S., Dawson, R. J., Ward, P. J., and Eilander, D.:
Long-term sea-level rise necessitates a commitment to adaptation: A first order assessment, Climate Risk Management, 34, 100355, https://doi.org/10.1016/j.crm.2021.100355, 2021.
Haigh, I. D., Pickering, M. D., Green, J. A. M., Arbic, B. K., Arns, A., Dangendorf, S., Hill, D. F., Horsburgh, K., Howard, T., Idier, D., Jay, D. A., Jänicke, L., Lee, S. B., Müller, M., Schindelegger, M., Talke, S. A., Wilmes, S.-B., and Woodworth, P. L.:
The Tides They Are A-Changin': A Comprehensive Review of Past and Future Nonastronomical Changes in Tides, Their Driving Mechanisms, and Future Implications, Rev. Geophys., 58, e2018RG000636, https://doi.org/10.1029/2018RG000636, 2020.
Hasselmann, K.:
Stochastic climate models part I. Theory, Tellus, 28, 473–485, 1976.
Hawkins, E. and Sutton, R.:
Time of emergence of climate signals, Geophys. Res. Lett., 39, https://doi.org/10.1029/2011GL050087, 2012.
Hawkins, E., Smith, R. S., Gregory, J. M., and Stainforth, D. A.:
Irreducible uncertainty in near-term climate projections, Clim. Dynam., 46, 3807–3819, https://doi.org/10.1007/s00382-015-2806-8, 2016.
Herger, N., Sanderson, B. M., and Knutti, R.:
Improved pattern scaling approaches for the use in climate impact studies, Geophys. Res. Lett., 42, 3486–3494, https://doi.org/10.1002/2015GL063569, 2015.
Hermans, T. H. J., Tinker, J., Palmer, M. D., Katsman, C. A., Vermeersen, B. L. A., and Slangen, A. B. A.:
Improving sea-level projections on the Northwestern European shelf using dynamical downscaling, Clim. Dynam., 54, 1987–2011, https://doi.org/10.1007/s00382-019-05104-5, 2020.
Hinkel, J., Lincke, D., Vafeidis, A. T., Perrette, M., Nicholls, R. J., Tol, R. S., Marzeion, B., Fettweis, X., Ionescu, C., and Levermann, A.:
Coastal flood damage and adaptation costs under 21st century sea-level rise, P. Natl. Acad. Sci. USA, 111, 3292–3297, 2014.
Hobbs, W., Palmer, M. D., and Monselesan, D.:
An energy conservation analysis of ocean drift in the CMIP5 global coupled models, J. Climate, 29, 1639–1653, 2016.
Imawaki, S., Bower, A. S., Beal, L., and Qiu, B.:
Chapter 13 – Western Boundary Currents, in: International Geophysics, vol. 103, edited by: Siedler, G., Griffies, S. M., Gould, J., and Church, J. A., Academic Press, 305–338, https://doi.org/10.1016/B978-0-12-391851-2.00013-1, 2013.
Kay, J. E., Deser, C., Phillips, A., Mai, A., Hannay, C., Strand, G., Arblaster, J. M., Bates, S. C., Danabasoglu, G., and Edwards, J.:
The Community Earth System Model (CESM) large ensemble project: A community resource for studying climate change in the presence of internal climate variability, B. Am. Meteorol. Soc., 96, 1333–1349, 2015.
Labe, Z. M. and Barnes, E. A.:
Detecting Climate Signals Using Explainable AI With Single-Forcing Large Ensembles, J. Adv. Model. Earth Sy., 13, e2021MS002464, https://doi.org/10.1029/2021MS002464, 2021.
Landerer, F. W., Jungclaus, J. H., and Marotzke, J.:
Regional dynamic and steric sea level change in response to the IPCC-A1B scenario, J. Phys. Oceanogr., 37, 296–312, 2007.
Lowe, J. A. and Gregory, J. M.:
Understanding projections of sea level rise in a Hadley Centre coupled climate model, J. Geophys. Res.-Oceans, 111, C11014, https://doi.org/10.1029/2005JC003421, 2006.
Lyu, K., Zhang, X., and Church, J. A.:
Regional Dynamic Sea Level Simulated in the CMIP5 and CMIP6 Models: Mean Biases, Future Projections, and Their Linkages, J. Climate, 33, 6377–6398, https://doi.org/10.1175/JCLI-D-19-1029.1, 2020.
Maher, N., Milinski, S., Suarez-Gutierrez, L., Botzet, M., Dobrynin, M., Kornblueh, L., Kröger, J., Takano, Y., Ghosh, R., Hedemann, C., Li, C., Li, H., Manzini, E., Notz, D., Putrasahan, D., Boysen, L., Claussen, M., Ilyina, T., Olonscheck, D., Raddatz, T., Stevens, B., and Marotzke, J.:
The Max Planck Institute Grand Ensemble: Enabling the Exploration of Climate System Variability, J. Adv. Model. Earth Sy., 11, 2050–2069, https://doi.org/10.1029/2019MS001639, 2019.
Maher, N., Milinski, S., and Ludwig, R.:
Large ensemble climate model simulations: introduction, overview, and future prospects for utilising multiple types of large ensemble, Earth Syst. Dynam., 12, 401–418, https://doi.org/10.5194/esd-12-401-2021, 2021a.
Maher, N., Power, S., and Marotzke, J.:
More accurate quantification of model-to-model agreement in externally forced climatic responses over the coming century, Nat. Commun., 12, 788, https://doi.org/10.1038/s41467-020-20635-w, 2021b.
Mankin, J. S., Lehner, F., Coats, S., and McKinnon, K. A.:
The Value of Initial Condition Large Ensembles to Robust Adaptation Decision-Making, Earths Future, 8, e2012EF001610, https://doi.org/10.1029/2020EF001610, 2020.
Marcos, M. and Amores, A.:
Quantifying anthropogenic and natural contributions to thermosteric sea level rise, Geophys. Res. Lett., 41, 2502–2507, https://doi.org/10.1002/2014GL059766, 2014.
Meinshausen, M., Raper, S. C. B., and Wigley, T. M. L.:
Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 1: Model description and calibration, Atmos. Chem. Phys., 11, 1417–1456, https://doi.org/10.5194/acp-11-1417-2011, 2011.
Millar, R. J., Nicholls, Z. R., Friedlingstein, P., and Allen, M. R.:
A modified impulse-response representation of the global near-surface air temperature and atmospheric concentration response to carbon dioxide emissions, Atmos. Chem. Phys., 17, 7213–7228, https://doi.org/10.5194/acp-17-7213-2017, 2017.
Mitchell, T. D.:
Pattern Scaling: An Examination of the Accuracy of the Technique for Describing Future Climates, Climatic Change, 60, 217–242, https://doi.org/10.1023/A:1026035305597, 2003.
Mitrovica, J. X., Tamisiea, M. E., Davis, J. L., and Milne, G. A.:
Recent mass balance of polar ice sheets inferred from patterns of global sea-level change, Nature, 409, 1026–1029, 2001.
Moftakhari, H. R., AghaKouchak, A., Sanders, B. F., Feldman, D. L., Sweet, W., Matthew, R. A., and Luke, A.:
Increased nuisance flooding along the coasts of the United States due to sea level rise: Past and future, Geophys. Res. Lett., 42, 9846–9852, 2015.
ESGF: MPI Grand Ensemble – ESGF [data set], https://esgf-data.dkrz.de/projects/mpi-ge/, last access: 18 April 2023.
Nerem, R. S., Leuliette, É., and Cazenave, A.:
Present-day sea-level change: A review, C. R. Geosci., 338, 1077–1083, https://doi.org/10.1016/j.crte.2006.09.001, 2006.
Nicholls, R. J., Lincke, D., Hinkel, J., Brown, S., Vafeidis, A. T., Meyssignac, B., Hanson, S. E., Merkens, J.-L., and Fang, J.:
A global analysis of subsidence, relative sea-level change and coastal flood exposure, Nat. Clim. Change, 11, 338–342, https://doi.org/10.1038/s41558-021-00993-z, 2021.
O'Neill, B. C., Kriegler, E., Ebi, K. L., Kemp-Benedict, E., Riahi, K., Rothman, D. S., van Ruijven, B. J., van Vuuren, D. P., Birkmann, J., Kok, K., Levy, M., and Solecki, W.:
The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century, Global Environ. Chang., 42, 169–180, https://doi.org/10.1016/j.gloenvcha.2015.01.004, 2017.
Osborn, T. J., Wallace, C. J., Harris, I. C., and Melvin, T. M.:
Pattern scaling using ClimGen: monthly-resolution future climate scenarios including changes in the variability of precipitation, Climatic Change, 134, 353–369, https://doi.org/10.1007/s10584-015-1509-9, 2016.
Peltier, W. R.:
Global sea level rise and glacial isostatic adjustment, Global Planet. Change, 20, 93–123, 1999.
Peltier, W. R.:
Chap. 4, Global glacial isostatic adjustment and modern instrumental records of relative sea level history,
edited by: Bruce, C. D., Kearney, M. S., and Leatherman, S. P.,
International Geophysics,
Academic Press,
Vol. 75,
65–95,
ISBN 9780122213458,
https://doi.org/10.1016/S0074-6142(01)80007-3, 2001.
Perrette, M., Landerer, F., Riva, R., Frieler, K., and Meinshausen, M.:
A scaling approach to project regional sea level rise and its uncertainties, Earth Syst. Dynam., 4, 11–29, https://doi.org/10.5194/esd-4-11-2013, 2013.
Riahi, K., van Vuuren, D. P., Kriegler, E., Edmonds, J., O'Neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., Lutz, W., Popp, A., Cuaresma, J. C., Kc, S., Leimbach, M., Jiang, L., Kram, T., Rao, S., Emmerling, J., Ebi, K., Hasegawa, T., Havlik, P., Humpenöder, F., Da Silva, L. A., Smith, S., Stehfest, E., Bosetti, V., Eom, J., Gernaat, D., Masui, T., Rogelj, J., Strefler, J., Drouet, L., Krey, V., Luderer, G., Harmsen, M., Takahashi, K., Baumstark, L., Doelman, J. C., Kainuma, M., Klimont, Z., Marangoni, G., Lotze-Campen, H., Obersteiner, M., Tabeau, A., and Tavoni, M.:
The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview, Global Environ. Chang., 42, 153–168, https://doi.org/10.1016/j.gloenvcha.2016.05.009, 2017.
Rintoul, S. R., Hughes, C. W., and Olbers, D. J.:
Chapter 4.6 The antarctic circumpolar current system, in: International Geophysics, vol. 77, edited by: Siedler, G., Church, J., and Gould, J., Academic Press, 271–XXXVI, https://doi.org/10.1016/S0074-6142(01)80124-8, 2001.
Santer, B. D., Wigley, T. M., Schlesinger, M. E., and Mitchell, J. F.:
Developing climate scenarios from equilibrium GCM results, Max-Planck-Institut für Meteorologie, 1990.
Schneider, T. and Held, I. M.:
Discriminants of twentieth-century changes in Earth surface temperatures, J. Climate, 14, 249–254, 2001.
Schwarber, A. K., Smith, S. J., Hartin, C. A., Vega-Westhoff, B. A., and Sriver, R.:
Evaluating climate emulation: fundamental impulse testing of simple climate models, Earth Syst. Dynam., 10, 729–739, https://doi.org/10.5194/esd-10-729-2019, 2019.
Schwarzwald, K. and Lenssen, N.:
The importance of internal climate variability in climate impact projections, P. Natl. Acad. Sci. USA, 119, e2208095119, https://doi.org/10.1073/pnas.2208095119, 2022.
Slangen, A. B. A., Carson, M., Katsman, C. A., Van de Wal, R. S. W., Köhl, A., Vermeersen, L. L. A., and Stammer, D.:
Projecting twenty-first century regional sea-level changes, Climatic Change, 124, 317–332, 2014.
Slangen, A. B. A., Adloff, F., Jevrejeva, S., Leclercq, P. W., Marzeion, B., Wada, Y., and Winkelmann, R.:
A Review of Recent Updates of Sea-Level Projections at Global and Regional Scales, Surv. Geophys., 38, 385–406, https://doi.org/10.1007/s10712-016-9374-2, 2017.
Smith, C. J., Forster, P. M., Allen, M., Leach, N., Millar, R. J., Passerello, G. A., and Regayre, L. A.:
FAIR v1.3: a simple emissions-based impulse response and carbon cycle model, Geosci. Model Dev., 11, 2273–2297, https://doi.org/10.5194/gmd-11-2273-2018, 2018.
Stainforth, D. A., Allen, M. R., Tredger, E. R., and Smith, L. A.:
Confidence, uncertainty and decision-support relevance in climate predictions, Philos. T. R. Soc. A, 365, 2145–2161, https://doi.org/10.1098/rsta.2007.2074, 2007.
Stammer, D. and Hüttemann, S.:
Response of regional sea level to atmospheric pressure loading in a climate change scenario, J. Climate, 21, 2093–2101, 2008.
Steffelbauer, D. B., Riva, R. E. M., Timmermans, J. S., Kwakkel, J. H., and Bakker, M.:
Evidence of regional sea-level rise acceleration for the North Sea, Environ. Res. Lett., 17, 074002, https://doi.org/10.1088/1748-9326/ac753a, 2022.
Suarez-Gutierrez, L., Milinski, S., and Maher, N.:
Exploiting large ensembles for a better yet simpler climate model evaluation, Clim. Dynam., 57, 2557–2580, https://doi.org/10.1007/s00382-021-05821-w, 2021.
Tebaldi, C. and Arblaster, J. M.:
Pattern scaling: Its strengths and limitations, and an update on the latest model simulations, Climatic Change, 122, 459–471, https://doi.org/10.1007/s10584-013-1032-9, 2014.
Thomas, M. A. and Lin, T.:
A dual model for emulation of thermosteric and dynamic sea-level change, Climatic Change, 148, 311–324, 2018.
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.:
The representative concentration pathways: an overview, Climatic Change, 109, 5, https://doi.org/10.1007/s10584-011-0148-z, 2011.
Vitousek, S., Barnard, P. L., Fletcher, C. H., Frazer, N., Erikson, L., and Storlazzi, C. D.:
Doubling of coastal flooding frequency within decades due to sea-level rise, Sci. Rep.-UK, 7, 1–9, 2017.
Wahl, T., Haigh, I. D., Nicholls, R. J., Arns, A., Dangendorf, S., Hinkel, J., and Slangen, A. B. A.:
Understanding extreme sea levels for broad-scale coastal impact and adaptation analysis, Nat. Commun., 8, 16075, https://doi.org/10.1038/ncomms16075, 2017.
Wells, C. D., Jackson, L. S., Maycock, A. C., and Forster, P. M.:
Understanding pattern scaling errors across a range of emissions pathways, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-914, 2022.
Wills, R. C., Schneider, T., Wallace, J. M., Battisti, D. S., and Hartmann, D. L.:
Disentangling Global Warming, Multidecadal Variability, and El Niño in Pacific Temperatures, Geophys. Res. Lett., 45, 2487–2496, https://doi.org/10.1002/2017GL076327, 2018.
Wills, R. C. J., Battisti, D. S., Armour, K. C., Schneider, T., and Deser, C.:
Pattern Recognition Methods to Separate Forced Responses from Internal Variability in Climate Model Ensembles and Observations, J. Climate, 33, 8693–8719, https://doi.org/10.1175/JCLI-D-19-0855.1, 2020.
Wu, Q., Zhang, X., Church, J. A., Hu, J., and Gregory, J. M.:
Evolving patterns of sterodynamic sea-level rise under mitigation scenarios and insights from linear system theory, Clim. Dynam., 57, 635–656, https://doi.org/10.1007/s00382-021-05727-7, 2021.
Yuan, J. and Kopp, R. E.:
Emulating Ocean Dynamic Sea Level by Two-Layer Pattern Scaling, J. Adv. Model. Earth Sy., 13, e2020MS002323, https://doi.org/10.1029/2020MS002323, 2021.
Short summary
Climate change will alter heat and freshwater fluxes as well as ocean circulation, driving local changes in sea level. This sea-level change component is known as ocean dynamic sea level (DSL), and it is usually projected using computationally expensive global climate models. Statistical models are a cheaper alternative for projecting DSL but may contain significant errors. Here, we partly remove those errors (driven by internal climate variability) by using pattern recognition techniques.
Climate change will alter heat and freshwater fluxes as well as ocean circulation, driving local...
