Articles | Volume 21, issue 4
https://doi.org/10.5194/os-21-1663-2025
© 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-21-1663-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Indications of improved seasonal sea level forecasts for the United States Gulf Coast and East Coast using ocean dynamic persistence
Xue Feng
CORRESPONDING AUTHOR
Cooperative Institute for Marine and Atmospheric Research, School of Ocean and Earth Science and Technology (SOEST), University of Hawai`i at Mānoa, Honolulu, HI, USA
Matthew J. Widlansky
CORRESPONDING AUTHOR
Cooperative Institute for Marine and Atmospheric Research, School of Ocean and Earth Science and Technology (SOEST), University of Hawai`i at Mānoa, Honolulu, HI, USA
Department of Oceanography, SOEST, University of Hawai`i at Mānoa, Honolulu, HI, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Magdalena A. Balmaseda
European Centre for Medium-Range Weather Forecasts, Reading, UK
European Centre for Medium-Range Weather Forecasts, Reading, UK
Gregory Dusek
National Ocean Service, NOAA, Silver Spring, MD, USA
William Sweet
National Ocean Service, NOAA, Silver Spring, MD, USA
Malte F. Stuecker
Department of Oceanography, SOEST, University of Hawai`i at Mānoa, Honolulu, HI, USA
International Pacific Research Center, SOEST, University of Hawai`i at Mānoa, Honolulu, HI, USA
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Jozef Skákala, David Ford, Keith Haines, Amos Lawless, Matthew J. Martin, Philip Browne, Marcin Chrust, Stefano Ciavatta, Alison Fowler, Daniel Lea, Matthew Palmer, Andrea Rochner, Jennifer Waters, Hao Zuo, Deep S. Banerjee, Mike Bell, Davi M. Carneiro, Yumeng Chen, Susan Kay, Dale Partridge, Martin Price, Richard Renshaw, Georgy Shapiro, and James While
Ocean Sci., 21, 1709–1734, https://doi.org/10.5194/os-21-1709-2025, https://doi.org/10.5194/os-21-1709-2025, 2025
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UK marine data assimilation (MDA) involves a closely collaborating research community. In this paper, we offer both an overview of the state of the art and a vision for the future across all of the main areas of UK MDA, ranging from physics to biogeochemistry to coupled DA. We discuss the current UK MDA stakeholder applications, highlight theoretical developments needed to advance our systems, and reflect upon upcoming opportunities with respect to hardware and observational missions.
Ja-Yeon Moon, Jan Streffing, Sun-Seon Lee, Tido Semmler, Miguel Andrés-Martínez, Jiao Chen, Eun-Byeoul Cho, Jung-Eun Chu, Christian L. E. Franzke, Jan P. Gärtner, Rohit Ghosh, Jan Hegewald, Songyee Hong, Dae-Won Kim, Nikolay Koldunov, June-Yi Lee, Zihao Lin, Chao Liu, Svetlana N. Loza, Wonsun Park, Woncheol Roh, Dmitry V. Sein, Sahil Sharma, Dmitry Sidorenko, Jun-Hyeok Son, Malte F. Stuecker, Qiang Wang, Gyuseok Yi, Martina Zapponini, Thomas Jung, and Axel Timmermann
Earth Syst. Dynam., 16, 1103–1134, https://doi.org/10.5194/esd-16-1103-2025, https://doi.org/10.5194/esd-16-1103-2025, 2025
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Based on a series of storm-resolving greenhouse warming simulations conducted with the AWI-CM3 model at 9 km global atmosphere and 4–25 km ocean resolution, we present new projections of regional climate change, modes of climate variability, and extreme events. The 10-year-long high-resolution simulations for the 2000s, 2030s, 2060s, and 2090s were initialized from a coarser-resolution transient run (31 km atmosphere) which follows the SSP5-8.5 greenhouse gas emission scenario from 1950–2100 CE.
Ingo Richter, Ping Chang, Ping-Gin Chiu, Gokhan Danabasoglu, Takeshi Doi, Dietmar Dommenget, Guillaume Gastineau, Zoe E. Gillett, Aixue Hu, Takahito Kataoka, Noel S. Keenlyside, Fred Kucharski, Yuko M. Okumura, Wonsun Park, Malte F. Stuecker, Andréa S. Taschetto, Chunzai Wang, Stephen G. Yeager, and Sang-Wook Yeh
Geosci. Model Dev., 18, 2587–2608, https://doi.org/10.5194/gmd-18-2587-2025, https://doi.org/10.5194/gmd-18-2587-2025, 2025
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Tropical ocean basins influence each other through multiple pathways and mechanisms, referred to here as tropical basin interaction (TBI). Many researchers have examined TBI using comprehensive climate models but have obtained conflicting results. This may be partly due to differences in experiment protocols and partly due to systematic model errors. The Tropical Basin Interaction Model Intercomparison Project (TBIMIP) aims to address this problem by designing a set of TBI experiments that will be performed by multiple models.
John R. Albers, Matthew Newman, Magdalena A. Balmaseda, William Sweet, Yan Wang, and Tongtong Xu
EGUsphere, https://doi.org/10.5194/egusphere-2025-897, https://doi.org/10.5194/egusphere-2025-897, 2025
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Providing early warning of coastal flooding is an emerging priority for the National Oceanic and Atmospheric Administration. We assess whether current operational forecast models can provide the basis for predicting the risks of higher than normal coastal sea level values up to six weeks in advance. For many United States coastal locations, models have sufficient prediction skill to be used as the basis for the development of a high tide flooding prediction system on subseasonal timescales.
Fiona Raphaela Spuler, Marlene Kretschmer, Magdalena Alonso Balmaseda, Yevgeniya Kovalchuk, and Theodore G. Shepherd
EGUsphere, https://doi.org/10.5194/egusphere-2024-4115, https://doi.org/10.5194/egusphere-2024-4115, 2025
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Large-scale atmospheric dynamics modulate the occurrence of extreme events and can be leveraged to improve their predictability. In this paper, we introduce a generative machine learning method to identify dynamical drivers of a relevant impact variable in the form of targeted circulation regimes. Applying the method to study extreme precipitation over Morocco, we show that these regimes are more predictive of the impact while maintaining their own predictability and physical consistency.
Yoshihiro Nakayama, Alena Malyarenko, Hong Zhang, Ou Wang, Matthis Auger, Yafei Nie, Ian Fenty, Matthew Mazloff, Armin Köhl, and Dimitris Menemenlis
Geosci. Model Dev., 17, 8613–8638, https://doi.org/10.5194/gmd-17-8613-2024, https://doi.org/10.5194/gmd-17-8613-2024, 2024
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Global- and basin-scale ocean reanalyses are becoming easily accessible. However, such ocean reanalyses are optimized for their entire model domains and their ability to simulate the Southern Ocean requires evaluation. We conduct intercomparison analyses of Massachusetts Institute of Technology General Circulation Model (MITgcm)-based ocean reanalyses. They generally perform well for the open ocean, but open-ocean temporal variability and Antarctic continental shelves require improvements.
Karina von Schuckmann, Lorena Moreira, Mathilde Cancet, Flora Gues, Emmanuelle Autret, Jonathan Baker, Clément Bricaud, Romain Bourdalle-Badie, Lluis Castrillo, Lijing Cheng, Frederic Chevallier, Daniele Ciani, Alvaro de Pascual-Collar, Vincenzo De Toma, Marie Drevillon, Claudia Fanelli, Gilles Garric, Marion Gehlen, Rianne Giesen, Kevin Hodges, Doroteaciro Iovino, Simon Jandt-Scheelke, Eric Jansen, Melanie Juza, Ioanna Karagali, Thomas Lavergne, Simona Masina, Ronan McAdam, Audrey Minière, Helen Morrison, Tabea Rebekka Panteleit, Andrea Pisano, Marie-Isabelle Pujol, Ad Stoffelen, Sulian Thual, Simon Van Gennip, Pierre Veillard, Chunxue Yang, and Hao Zuo
State Planet, 4-osr8, 1, https://doi.org/10.5194/sp-4-osr8-1-2024, https://doi.org/10.5194/sp-4-osr8-1-2024, 2024
Thomas P. Collings, Niall D. Quinn, Ivan D. Haigh, Joshua Green, Izzy Probyn, Hamish Wilkinson, Sanne Muis, William V. Sweet, and Paul D. Bates
Nat. Hazards Earth Syst. Sci., 24, 2403–2423, https://doi.org/10.5194/nhess-24-2403-2024, https://doi.org/10.5194/nhess-24-2403-2024, 2024
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Coastal areas are at risk of flooding from rising sea levels and extreme weather events. This study applies a new approach to estimating the likelihood of coastal flooding around the world. The method uses data from observations and computer models to create a detailed map of where these coastal floods might occur. The approach can predict flooding in areas for which there are few or no data available. The results can be used to help prepare for and prevent this type of flooding.
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.
Jonathan Andrew Baker, Richard Renshaw, Laura Claire Jackson, Clotilde Dubois, Doroteaciro Iovino, Hao Zuo, Renellys C. Perez, Shenfu Dong, Marion Kersalé, Michael Mayer, Johannes Mayer, Sabrina Speich, and Tarron Lamont
State Planet, 1-osr7, 4, https://doi.org/10.5194/sp-1-osr7-4-2023, https://doi.org/10.5194/sp-1-osr7-4-2023, 2023
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We use ocean reanalyses, in which ocean models are combined with observations, to infer past changes in ocean circulation and heat transport in the South Atlantic. Comparing these estimates with other observation-based estimates, we find differences in their trends, variability, and mean heat transport but closer agreement in their mean overturning strength. Ocean reanalyses can help us understand the cause of these differences, which could improve estimates of ocean transports in this region.
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.
Susanna Winkelbauer, Michael Mayer, Vanessa Seitner, Ervin Zsoter, Hao Zuo, and Leopold Haimberger
Hydrol. Earth Syst. Sci., 26, 279–304, https://doi.org/10.5194/hess-26-279-2022, https://doi.org/10.5194/hess-26-279-2022, 2022
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We evaluate Arctic river discharge using in situ observations and state-of-the-art reanalyses, inter alia the most recent Global Flood Awareness System (GloFAS) river discharge reanalysis version 3.1. Furthermore, we combine reanalysis data, in situ observations, ocean reanalyses, and satellite data and use a Lagrangian optimization scheme to close the Arctic's volume budget on annual and seasonal scales, resulting in one reliable and up-to-date estimate of every volume budget term.
Keith B. Rodgers, Sun-Seon Lee, Nan Rosenbloom, Axel Timmermann, Gokhan Danabasoglu, Clara Deser, Jim Edwards, Ji-Eun Kim, Isla R. Simpson, Karl Stein, Malte F. Stuecker, Ryohei Yamaguchi, Tamás Bódai, Eui-Seok Chung, Lei Huang, Who M. Kim, Jean-François Lamarque, Danica L. Lombardozzi, William R. Wieder, and Stephen G. Yeager
Earth Syst. Dynam., 12, 1393–1411, https://doi.org/10.5194/esd-12-1393-2021, https://doi.org/10.5194/esd-12-1393-2021, 2021
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A large ensemble of simulations with 100 members has been conducted with the state-of-the-art CESM2 Earth system model, using historical and SSP3-7.0 forcing. Our main finding is that there are significant changes in the variance of the Earth system in response to anthropogenic forcing, with these changes spanning a broad range of variables important to impacts for human populations and ecosystems.
Yoshihiro Nakayama, Dimitris Menemenlis, Ou Wang, Hong Zhang, Ian Fenty, and An T. Nguyen
Geosci. Model Dev., 14, 4909–4924, https://doi.org/10.5194/gmd-14-4909-2021, https://doi.org/10.5194/gmd-14-4909-2021, 2021
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High ice shelf melting in the Amundsen Sea has attracted many observational campaigns in the past decade. One method to combine observations with numerical models is the adjoint method. After 20 iterations, the cost function, defined as a sum of the weighted model–data difference, is reduced by 65 % by adjusting initial conditions, atmospheric forcing, and vertical diffusivity. This study demonstrates adjoint-method optimization with explicit representation of ice shelf cavity circulation.
Kyung-Sook Yun, Axel Timmermann, and Malte F. Stuecker
Earth Syst. Dynam., 12, 121–132, https://doi.org/10.5194/esd-12-121-2021, https://doi.org/10.5194/esd-12-121-2021, 2021
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Changes in the Hadley and Walker cells cause major climate disruptions across our planet. What has been overlooked so far is the question of whether these two circulations can shift their positions in a synchronized manner. We here show the synchronized spatial shifts between Walker and Hadley cells and further highlight a novel aspect of how tropical sea surface temperature anomalies can couple these two circulations. The re-positioning has important implications for extratropical rainfall.
Beena Balan-Sarojini, Steffen Tietsche, Michael Mayer, Magdalena Balmaseda, Hao Zuo, Patricia de Rosnay, Tim Stockdale, and Frederic Vitart
The Cryosphere, 15, 325–344, https://doi.org/10.5194/tc-15-325-2021, https://doi.org/10.5194/tc-15-325-2021, 2021
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Our study for the first time shows the impact of measured sea ice thickness (SIT) on seasonal forecasts of all the seasons. We prove that the long-term memory present in the Arctic winter SIT is helpful to improve summer sea ice forecasts. Our findings show that realistic SIT initial conditions to start a forecast are useful in (1) improving seasonal forecasts, (2) understanding errors in the forecast model, and (3) recognizing the need for continuous monitoring of world's ice-covered oceans.
Hao Zuo, Magdalena Alonso Balmaseda, Steffen Tietsche, Kristian Mogensen, and Michael Mayer
Ocean Sci., 15, 779–808, https://doi.org/10.5194/os-15-779-2019, https://doi.org/10.5194/os-15-779-2019, 2019
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OCEAN5 is the fifth generation of the ocean and sea-ice analysis system at ECMWF. It was used for production of historical ocean and sea-ice states from 1979 onwards and is also used for generating real-time ocean and sea-ice states responsible for initializing the operational ECMWF weather forecasting system. This is a valuable data set with broad applications. A description of the OCEAN5 system and an assessment of the historical data set have been documented in this reference paper.
Steffen Tietsche, Magdalena Alonso-Balmaseda, Patricia Rosnay, Hao Zuo, Xiangshan Tian-Kunze, and Lars Kaleschke
The Cryosphere, 12, 2051–2072, https://doi.org/10.5194/tc-12-2051-2018, https://doi.org/10.5194/tc-12-2051-2018, 2018
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We compare Arctic sea-ice thickness from L-band microwave satellite observations and an ocean–sea ice reanalysis. There is good agreement for some regions and times but systematic discrepancy in others. Errors in both the reanalysis and observational products contribute to these discrepancies. Thus, we recommend proceeding with caution when using these observations for model validation or data assimilation. At the same time we emphasise their unique value for improving sea-ice forecast models.
Jean-François Legeais, Michaël Ablain, Lionel Zawadzki, Hao Zuo, Johnny A. Johannessen, Martin G. Scharffenberg, Luciana Fenoglio-Marc, M. Joana Fernandes, Ole Baltazar Andersen, Sergei Rudenko, Paolo Cipollini, Graham D. Quartly, Marcello Passaro, Anny Cazenave, and Jérôme Benveniste
Earth Syst. Sci. Data, 10, 281–301, https://doi.org/10.5194/essd-10-281-2018, https://doi.org/10.5194/essd-10-281-2018, 2018
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Sea level is one of the best indicators of climate change and has been listed as one of the essential climate variables. Sea level measurements have been provided by satellite altimetry for 25 years, and the Climate Change Initiative (CCI) program of the European Space Agency has given the opportunity to provide a long-term, homogeneous and accurate sea level record. It will help scientists to better understand climate change and its variability.
Chris Houser, Sarah Trimble, Robert Brander, B. Chris Brewster, Greg Dusek, Deborah Jones, and John Kuhn
Nat. Hazards Earth Syst. Sci., 17, 1003–1024, https://doi.org/10.5194/nhess-17-1003-2017, https://doi.org/10.5194/nhess-17-1003-2017, 2017
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Rip currents pose a major global beach hazard. Despite increased social research into beach-goer experience, little is known about levels of rip current knowledge within the general population. This study describes results of an online survey to determine the extent of rip current knowledge across the United States, with the aim of improving and enhancing existing beach safety education materials. Results suggest a need for locally specific and verified rip forecasts and signage.
Joseph Park, Jamie MacMahan, William V. Sweet, and Kevin Kotun
Ocean Sci., 12, 355–368, https://doi.org/10.5194/os-12-355-2016, https://doi.org/10.5194/os-12-355-2016, 2016
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Bays and harbors naturally resonate with standing waves, known as seiches. Seiches are usually considered temporary, however, we identify small-amplitude, continuously present seiches in six bays around the Pacific and suggest that tidally forced, continental shelf resonances are a primary driver of continuous seiches.
J. Park and W. Sweet
Ocean Sci., 11, 607–615, https://doi.org/10.5194/os-11-607-2015, https://doi.org/10.5194/os-11-607-2015, 2015
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Changes in mass transport of the Florida Current induce significant coastal sea level changes along the Florida Straits and middle Atlantic coast of North America. Analysis of Florida Current transport data finds a decrease in mean transport over the last decade. This decrease coincides with a decrease in AMOC and acceleration of coastal sea levels along the Florida Straits.
J. Park, W. V. Sweet, and R. Heitsenrether
Ocean Sci., 11, 439–453, https://doi.org/10.5194/os-11-439-2015, https://doi.org/10.5194/os-11-439-2015, 2015
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Seiches in coastal bays can produce significant water level oscillations that impact maritime operations and introduce ecological stress. Monterey Bay, California, is found to have wave-driven short-period oscillations that can reinforce themselves, resulting in water level amplification. At longer periods the oscillations are not wave-driven and several potential forcing mechanisms are examined. A gyre offshore the bay is suggested as the driver, while other potential drivers are discounted.
Related subject area
Approach: Numerical Models | Properties and processes: Sea level, tides, tsunamis and surges
Constraining local ocean dynamic sea-level projections using observations
Application of the HIDRA2 deep-learning model for sea level forecasting along the Estonian coast of the Baltic Sea
Investigation of the impact of complex coastline geometry on the evolution of storm surges along the eastern coast of India: a sensitivity study using a numerical model
Assessing storm surge model performance: what error indicators can measure the model's skill?
The characteristics of tides and their effects on the general circulation of the Mediterranean Sea
Effect of nonlinear tide-surge interaction in the Pearl River Estuary during Typhoon Nida (2016)
Effects of sea level rise and tidal flat growth on tidal dynamics and geometry of the Elbe estuary
Technical note: Extending sea level time series for the analysis of extremes with statistical methods and neighbouring station data
Uncertainties and discrepancies in the representation of recent storm surges in a non-tidal semi-enclosed basin: a hindcast ensemble for the Baltic Sea
Observations and modeling of tidally generated high-frequency velocity fluctuations downstream of a channel constriction
Dewi Le Bars, Iris Keizer, and Sybren Drijfhout
Ocean Sci., 21, 1303–1314, https://doi.org/10.5194/os-21-1303-2025, https://doi.org/10.5194/os-21-1303-2025, 2025
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While preparing a new set of sea level scenarios for the Netherlands, we found out that many climate models overestimate the changes in ocean circulation for the last 30 years. To quantify this effect, we defined three methods that rely on diverse and independent observations: tide gauges, satellite altimetry, temperature and salinity in the ocean, land ice melt, etc. Based on these observations, we define a few methods to select models and discuss their advantages and disadvantages.
Amirhossein Barzandeh, Matjaž Ličer, Marko Rus, Matej Kristan, Ilja Maljutenko, Jüri Elken, Priidik Lagemaa, and Rivo Uiboupin
Ocean Sci., 21, 1315–1327, https://doi.org/10.5194/os-21-1315-2025, https://doi.org/10.5194/os-21-1315-2025, 2025
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We evaluated a deep-learning model, HIDRA2, for predicting sea levels along the Estonian coast and compared it to traditional numerical models. HIDRA2 performed better overall, offering faster forecasts and valuable uncertainty estimates using ensemble predictions.
Pawan Tiwari, Ambarukhana D. Rao, Smita Pandey, and Vimlesh Pant
Ocean Sci., 21, 381–399, https://doi.org/10.5194/os-21-381-2025, https://doi.org/10.5194/os-21-381-2025, 2025
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Concave coasts act as funnels, concentrating storm waters and leading to higher storm surges (SSs); convex coasts redistribute waters, reducing surges. We use the ADCIRC model to simulate peak surges (PSs) for different cyclone tracks, showing how coastline geometry, landfall location, and cyclone angle influence PSs. Cyclones passing near concave coasts without landfall can still cause high SSs, highlighting vulnerability in these regions. This insight aids in assessing coastal flood risks.
Rodrigo Campos-Caba, Jacopo Alessandri, Paula Camus, Andrea Mazzino, Francesco Ferrari, Ivan Federico, Michalis Vousdoukas, Massimo Tondello, and Lorenzo Mentaschi
Ocean Sci., 20, 1513–1526, https://doi.org/10.5194/os-20-1513-2024, https://doi.org/10.5194/os-20-1513-2024, 2024
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Here we show the development of high-resolution simulations of storm surge in the northern Adriatic Sea employing different atmospheric forcing data and physical configurations. Traditional metrics favor a simulation forced by a coarser database and employing a less sophisticated setup. Closer examination allows us to identify a baroclinic model forced by a high-resolution dataset as being better able to capture the variability and peak values of the storm surge.
Bethany McDonagh, Emanuela Clementi, Anna Chiara Goglio, and Nadia Pinardi
Ocean Sci., 20, 1051–1066, https://doi.org/10.5194/os-20-1051-2024, https://doi.org/10.5194/os-20-1051-2024, 2024
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Tides in the Mediterranean Sea are typically of low amplitude, but twin experiments with and without tides demonstrate that tides affect the circulation directly at scales away from those of the tides. Analysis of the energy changes due to tides shows that they enhance existing oscillations, and internal tides interact with other internal waves. Tides also increase the mixed layer depth and enhance deep water formation in key regions. Internal tides are widespread in the Mediterranean Sea.
Linxu Huang, Tianyu Zhang, Shouwen Zhang, and Hui Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-1940, https://doi.org/10.5194/egusphere-2024-1940, 2024
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This study utilized a hydrodynamic model to explore the complex dynamics between storm surges and tides, the result shows that the nonlinear effect is mainly generated by local acceleration and convection while it is predominantly governed by wind stress and bottom friction in shallow water regions. By adjusting typhoon landfall times, we demonstrated that the contribution ratio of each nonlinear term changes little, their magnitudes fluctuate depending on the timing of landfall.
Tara F. Mahavadi, Rita Seiffert, Jessica Kelln, and Peter Fröhle
Ocean Sci., 20, 369–388, https://doi.org/10.5194/os-20-369-2024, https://doi.org/10.5194/os-20-369-2024, 2024
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To analyse the influence of potential future mean sea level rise (SLR) and tidal flat elevation scenarios on the tidal dynamics in the Elbe estuary, we used a highly resolved hydrodynamic numerical model. The results show increasing tidal range in the Elbe estuary due to SLR alone. In combination with different tidal flat growth scenarios, they reveal strongly varying changes in tidal range. We discuss how changes in estuarine geometry can provide an explanation for the changes in tidal range.
Kévin Dubois, Morten Andreas Dahl Larsen, Martin Drews, Erik Nilsson, and Anna Rutgersson
Ocean Sci., 20, 21–30, https://doi.org/10.5194/os-20-21-2024, https://doi.org/10.5194/os-20-21-2024, 2024
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Coastal floods occur due to extreme sea levels (ESLs) which are difficult to predict because of their rarity. Long records of accurate sea levels at the local scale increase ESL predictability. Here, we apply a machine learning technique to extend sea level observation data in the past based on a neighbouring tide gauge. We compared the results with a linear model. We conclude that both models give reasonable results with a better accuracy towards the extremes for the machine learning model.
Marvin Lorenz and Ulf Gräwe
Ocean Sci., 19, 1753–1771, https://doi.org/10.5194/os-19-1753-2023, https://doi.org/10.5194/os-19-1753-2023, 2023
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We study the variability of extreme sea levels in a 13 member hindcast ensemble for the Baltic Sea. The ensemble mean shows good agreement with observations regarding return levels and trends. However, we find great variability and uncertainty within the ensemble. We argue that the variability of storms in the atmospheric data directly translates into the variability of the return levels. These results highlight the need for large regional ensembles to minimise uncertainties.
Håvard Espenes, Pål Erik Isachsen, and Ole Anders Nøst
Ocean Sci., 19, 1633–1648, https://doi.org/10.5194/os-19-1633-2023, https://doi.org/10.5194/os-19-1633-2023, 2023
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We show that tidally generated eddies generated near the constriction of a channel can drive a strong and fluctuating flow field far downstream of the channel constriction itself. The velocity signal has been observed in other studies, but this is the first study linking it to a physical process. Eddies such as those we found are generated because of complex coastal geometry, suggesting that, for example, land-reclamation projects in channels may enhance current shear over a large area.
Cited articles
Albers, J. R., Newman, M., Balmaseda, M. A., Sweet, W., Wang, Y., and Xu, T.: Assessing Subseasonal Forecast Skill for Use in Predicting US Coastal Inundation Risk, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-897, 2025.
Balmaseda, M. A., McAdam, R., Masina, S., Mayer, M., Senan, R., de Bosisséson, E., and Gualdi, S.: Skill assessment of seasonal forecasts of ocean variables, Front. Mar. Sci., 11, 1380545, https://doi.org/10.3389/fmars.2024.1380545, 2024.
Calafat, F. M., Wahl, T., Lindsten, F., Williams, J., and Frajka-Williams, E.: Coherent modulation of the sea-level annual cycle in the United States by Atlantic Rossby waves, Nat. Commun., 9, 2571, https://doi.org/10.1038/s41467-018-04898-y, 2018.
Chelton, D. B. and Schlax, M. G.: Global observations of oceanic Rossby Waves, Science, 272, 234–238, https://doi.org/10.13053/CyS-18-3-2043, 1996.
Copernicus Climate Change Service: Seasonal forecast monthly averages of ocean variables, Copernicus Climate Change Service [data set], https://doi.org/10.24381/cds.2f9be611, 2018.
Copernicus Climate Change Service: ORAS5 global ocean reanalysis monthly data from 1958 to present, Copernicus Climate Change Service [data set], https://doi.org/10.24381/cds.67e8eeb7, 2021.
Copernicus Marine Service: Global Ocean Gridded L 4 Sea Surface Heights And Derived Variables Reprocessed, Copernicus Climate Service [data set], https://doi.org/10.48670/moi-00145, 2018.
Dangendorf, S., Hendricks, N., Sun, Q., Klinck, J., Ezer, T., Frederikse, T., Calafat, F. M., Wahl, T., and Törnqvist, T. E.: Acceleration of U.S. Southeast and Gulf coast sea-level rise amplified by internal climate variability, Nat. Commun., 14, 1935, https://doi.org/10.1038/s41467-023-37649-9, 2023.
Deser, C., Alexander, M. A., and Timlin, M. S.: Understanding the persistence of sea surface temperature anomalies in midlatitudes, J. Climate, 16, 57–72, https://doi.org/10.1175/1520-0442(2003)016<0057:UTPOSS>2.0.CO;2, 2003.
Dusek, G., Sweet, W. V., Widlansky, M. J., Thompson, P. R., and Marra, J. J.: A novel statistical approach to predict seasonal high tide flooding, Front. Mar. Sci., 9, 1073792, https://doi.org/10.3389/fmars.2022.1073792, 2022.
ECCO Consortium, Fukumori, I., Wang, O., Fenty, I., Forget, G., Heimbach, P., and Ponte, R. M.: ECCO Central Estimate (Version 4 Release 4), NASA [data set], https://podaac.jpl.nasa.gov/ECCO (last access: April 2024), 2019.
Feng, X., Widlansky, M. J., Balmaseda, M. A., Zuo, H., Spillman, C. M., Smith, G., Long, X., Thompson, P., Kumar, A., Dusek, G., and Sweet, W.: Improved capabilities of global ocean reanalyses for analysing sea level variability near the Atlantic and Gulf of Mexico Coastal U.S., Front. Mar. Sci., 11, 1–21, https://doi.org/10.3389/fmars.2024.1338626, 2024.
Forget, G., Campin, J. M., Heimbach, P., Hill, C. N., Ponte, R. M., and Wunsch, C.: ECCO version 4: An integrated framework for non-linear inverse modeling and global ocean state estimation, Geosci. Model Dev., 8, 3071–3104, https://doi.org/10.5194/gmd-8-3071-2015, 2015.
Frankignoul, C. and Hasselmann, K.: Stochastic climate models, Part I Application to sea-surface temperature anomalies and thermocline variability, Tellus, 29, 289–305, https://doi.org/10.1111/j.2153-3490.1977.tb00740.x, 1977.
Frederikse, T., Simon, K., Katsman, C. A., and Riva, R.: The sea-level budget along the Northwest Atlantic coast: GIA, mass changes, and large-scale ocean dynamics, J. Geophys. Res.-Oceans, 122, 5486–5501, https://doi.org/10.1002/2017JC012699, 2017.
Frederikse, T., Lee, T., Wang, O., Kirtman, B., Becker, E., Hamlington, B., Limonadi, D., and Waliser, D.: A Hybrid Dynamical Approach for Seasonal Prediction of Sea-Level Anomalies: A Pilot Study for Charleston, South Carolina, J. Geophys. Res.-Oceans, 127, e2021JC018137, https://doi.org/10.1029/2021JC018137, 2022.
Fujii, Y., Balmaseda, M., and Remy, E.: SynObs Flagship OSEs Guideline Version 1, OceanPredict website, https://oceanpredict.org/docs/Documents/SynObs/SynObs_FlagshipOSE_Guideline_Ver1.pdf (last access: 8 January 2025), 2023.
Hasselmann, K.: Stochastic climate models Part I. Theory, Tellus, 28, 473–485, https://doi.org/10.1111/j.2153-3490.1976.tb00696.x, 1976.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 monthly averaged data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.f17050d7, 2023.
Johnson, S. J., Stockdale, T. N., Ferranti, L., Balmaseda, M. A., Molteni, F., Magnusson, L., Tietsche, S., Decremer, D., Weisheimer, A., Balsamo, G., Keeley, S. P. E., Mogensen, K., Zuo, H., and Monge-Sanz, B. M.: SEAS5: the new ECMWF seasonal forecast system, Geosci. Model Dev., 12, 1087–1117, https://doi.org/10.5194/gmd-12-1087-2019, 2019.
Lee, C. C., Sheridan, S. C., Dusek, G. P., and Pirhalla, D. E.: Atmospheric Pattern-Based Predictions of S2S Sea Level Anomalies for Two Selected U.S. Locations, Artific. Intel. Earth Syst., 2, 220057, https://doi.org/10.1175/AIES-D-22-0057.1, 2023.
Little, C. M., Yeager, S. G., Ponte, R. M., Chang, P., and Kim, W. M.: Influence of Ocean Model Horizontal Resolution on the Representation of Global Annual-To-Multidecadal Coastal Sea Level Variability, J. Geophys. Res.-Oceans, 129, e2024JC021679, https://doi.org/10.1029/2024JC021679, 2024.
Long, X., Widlansky, M. J., Spillman, C. M., Kumar, A., Balmaseda, M., Thompson, P. R., Chikamoto, Y., Smith, G. A., Huang, B., Shin, C. S., Merrifield, M. A., Sweet, W. V., Leuliette, E., Annamalai, H. S., Marra, J. J., and Mitchum, G.: Seasonal Forecasting Skill of Sea-Level Anomalies in a Multi-Model Prediction Framework, J. Geophys. Res.-Oceans, 126, e2020JC017060, https://doi.org/10.1029/2020JC017060, 2021.
Long, X., Newman, M., Shin, S.-I., Balmeseda, M., Callahan, J., Dusek, G., Jia, L., Kirtman, B., Krasting, J., Lee, C. C., Lee, T., Sweet, W., Wang, O., Wang, Y., and Widlansky, M. J.: Evaluating Current Statistical and Dynamical Forecasting Techniques for Seasonal Coastal Sea Level Prediction, J. Climate, 38, 1477–1503, https://doi.org/10.1175/JCLI-D-24-0214.1, 2025.
Meehl, G. A., Richter, J. H., Teng, H., Capotondi, A., Cobb, K., Doblas-Reyes, F., Donat, M. G., England, M. H., Fyfe, J. C., Han, W., Kim, H., Kirtman, B. P., Kushnir, Y., Lovenduski, N. S., Mann, M. E., Merryfield, W. J., Nieves, V., Pegion, K., Rosenbloom, N., Sanchez, S. C., Scaife, A. A., Smith, D., Subramanian, A. C., Sun, L., Thompson, D., Ummenhofer, C. C., and Xie, S.-P.: Initialized Earth System prediction from subseasonal to decadal timescales, Nat. Rev. Earth Environ., 2, 340–357, https://doi.org/10.1038/s43017-021-00155-x, 2021.
Minobe, S., Terada, M., Qiu, B., and Schneider, N.: Western boundary sea level: A theory, rule of thumb, and application to climate models, J. Phys. Oceanogr., 47, 957–977, https://doi.org/10.1175/JPO-D-16-0144.1, 2017.
Newman, M., Sardeshmukh, P. D., Winkler, C. R., and Whitaker, J. S.: A Study of Subseasonal Predictability, Mon. Weather Rev., 131, 1715–1732, https://doi.org/10.1175//2558.1, 2003.
NOAA: Hourly tide gauge data [data set], National Oceanic and Atmospheric Administration [data set], https://api.tidesandcurrents.noaa.gov/api/prod/ (last access: 30 July 2025), 2025.
Obarein, O. A., Lee, C. C., Smith, E. T., and Sheridan, S. C.: Evaluating Medium-Range Forecast Performance of Regional-Scale Circulation Patterns, Weather Forecast., 38, 1467–1480, https://doi.org/10.1175/WAF-D-22-0149.1, 2023.
Roberts, C. D., Vitart, F., and Balmaseda, M. A.: Hemispheric Impact of North Atlantic SSTs in Subseasonal Forecasts, Geophys. Res. Lett., 48, e2020GL0911446, https://doi.org/10.1029/2020GL091446, 2021.
Sérazin, G., Penduff, T., Grégorio, S., Barnier, B., Molines, J.-M., and Terray, L.: Intrinsic Variability of Sea Level from Global Ocean Simulations: Spatiotemporal Scales, J. Climate, 28, 4279–4292, https://doi.org/10.1175/jcli-d-14-00554.1, 2014.
Shi, H., Jin, F.-F., Wills, R. C. J., Jacox, M. G., Amaya, D. J., Black, B. A., Rykaczewski, R. R., Bograd, S. J., García-Reyes, M., and Sydeman, W. J.: Global decline in ocean memory over the 21st century, Sci. Adv., 8, eabm3468, https://doi.org/10.1126/sciadv.abm3468, 2022.
Wang, O. and Lee, T.: Monthly Mean Sea Surface Height from Dynamic Persistence Forecasts Based on ECCO Version 4 Release 4 (V4r4) (1.0), Zenodo [data set], https://doi.org/10.5281/zenodo.16707942, 2025.
Wang, O., Lee, T., Piecuch, C. G., Fukumori, I., Fenty, I., Frederikse, T., Menemenlis, D., Ponte, R. M., and Zhang, H.: Local and Remote Forcing of Interannual Sea-Level Variability at Nantucket Island, J. Geophys. Res.-Oceans, 127, e2021JC018275, https://doi.org/10.1029/2021JC018275, 2022.
Wang, O., Lee, T., Frederikse, T., Ponte, R. M., Fenty, I., Fukumori, I., and Hamlington, B. D.: What Forcing Mechanisms Affect the Interannual Sea Level Co-Variability Between the Northeast and Southeast Coasts of the United States?, J. Geophys. Res.-Oceans, 129, e2023JC019873, https://doi.org/10.1029/2023JC019873, 2024.
Widlansky, M. J., Marra, J. J., Chowdhury, M. R., Stephens, S. A., Miles, E. R., Fauchereau, N., Spillman, C. M., Smith, G., Beard, G., and Wells, J.: Multimodel ensemble sea level forecasts for tropical Pacific Islands, J. Appl. Meteorol. Clim., 56, 849–862, https://doi.org/10.1175/JAMC-D-16-0284.1, 2017.
Widlansky, M. J., Long, X., Balmaseda, M. A., Spillman, C. M., Smith, G., Zuo, H., Yin, Y., Alves, O., and Kumar, A.: Quantifying the Benefits of Altimetry Assimilation in Seasonal Forecasts of the Upper Ocean, J. Geophys. Res.-Oceans, 128, e2022JC019342, https://doi.org/10.1029/2022JC019342, 2023.
Zhu, Y., Han, W., Alexander, M. A., and Shin, S.-I.: Interannual Sea Level Variability along the U.S. East Coast during the Satellite Altimetry Era: Local versus Remote Forcing, J. Climate, 37, 21–39, https://doi.org/10.1175/JCLI-D-23-0065.1, 2024.
Zuo, H., Balmaseda, M. A., Tietsche, S., Mogensen, K., and Mayer, M.: The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment, Ocean Sci., 15, 779–808, https://doi.org/10.5194/os-15-779-2019, 2019.
Zuo, H., Balmaseda, M. A., de Boisseson, E., Browne, P., Chrust, M., Keeley, S., Mogensen, K., Pelletier, C., de Rosnay, P., and Takakura, T.: ECMWF's next ensemble reanalysis system for ocean and sea ice: ORAS6, ECMWF Newsletter, 30–36, https://doi.org/10.21957/hzd5y821lk, 2024.
Short summary
Forecasting sea level changes months in advance along the Gulf Coast and East Coast of the United States is challenging. Here, we present a method that uses past ocean states to forecast future sea levels, while assuming no knowledge of how the atmosphere will evolve other than its typical annual cycle near the ocean's surface. Our findings indicate that this method improves sea level outlooks for many locations along the Gulf Coast and East Coast, especially south of Cape Hatteras.
Forecasting sea level changes months in advance along the Gulf Coast and East Coast of the...