Articles | Volume 15, issue 5
https://doi.org/10.5194/gmd-15-2035-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-2035-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
10 Mar 2022
Model evaluation paper |
| 10 Mar 2022
| 10 Mar 2022
IBI-CCS: a regional high-resolution model to simulate sea level in western Europe
Alisée A. Chaigneau
CORRESPONDING AUTHOR
CNRM UMR 3589, Météo-France/CNRS, Toulouse, France
Mercator Ocean International, Research and development department, Toulouse, France
Guillaume Reffray
Mercator Ocean International, Research and development department, Toulouse, France
Aurore Voldoire
CNRM UMR 3589, Météo-France/CNRS, Toulouse, France
Angélique Melet
Mercator Ocean International, Research and development department, Toulouse, France
Related authors
Alisée A. Chaigneau, Melisa Menéndez, Marta Ramírez-Pérez, and Alexandra Toimil
Nat. Hazards Earth Syst. Sci., 24, 4109–4131, https://doi.org/10.5194/nhess-24-4109-2024, https://doi.org/10.5194/nhess-24-4109-2024, 2024
Short summary
Short summary
Tropical cyclones drive extreme sea levels, causing large storm surges due to low atmospheric pressure and strong winds. This study explores factors affecting the numerical modelling of storm surges induced by hurricanes in the tropical Atlantic. Two ocean models are compared and used for sensitivity experiments. ERA5 atmospheric reanalysis forcing generally improves surge estimates compared to parametric wind models. Including ocean circulations reduces errors in surge estimates in some areas.
Alisée A. Chaigneau, Angélique Melet, Aurore Voldoire, Maialen Irazoqui Apecechea, Guillaume Reffray, Stéphane Law-Chune, and Lotfi Aouf
Nat. Hazards Earth Syst. Sci., 24, 4031–4048, https://doi.org/10.5194/nhess-24-4031-2024, https://doi.org/10.5194/nhess-24-4031-2024, 2024
Short summary
Short summary
Climate-change-induced sea level rise increases the frequency of extreme sea levels. We analyze projected changes in extreme sea levels for western European coasts produced with high-resolution models (∼ 6 km). Unlike commonly used coarse-scale global climate models, this approach allows us to simulate key processes driving coastal sea level variations, such as long-term sea level rise, tides, storm surges induced by low atmospheric surface pressure and winds, waves, and their interactions.
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
Short summary
Short summary
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.
Alisée A. Chaigneau, Stéphane Law-Chune, Angélique Melet, Aurore Voldoire, Guillaume Reffray, and Lotfi Aouf
Ocean Sci., 19, 1123–1143, https://doi.org/10.5194/os-19-1123-2023, https://doi.org/10.5194/os-19-1123-2023, 2023
Short summary
Short summary
Wind waves and swells are major drivers of coastal environment changes and can drive coastal marine hazards such as coastal flooding. In this paper, by using numerical modeling along the European Atlantic coastline, we assess how present and future wave characteristics are impacted by sea level changes. For example, at the end of the century under the SSP5-8.5 climate change scenario, extreme significant wave heights are higher by up to +40 % due to the effect of tides and mean sea level rise.
Alisée A. Chaigneau, Melisa Menéndez, Marta Ramírez-Pérez, and Alexandra Toimil
Nat. Hazards Earth Syst. Sci., 24, 4109–4131, https://doi.org/10.5194/nhess-24-4109-2024, https://doi.org/10.5194/nhess-24-4109-2024, 2024
Short summary
Short summary
Tropical cyclones drive extreme sea levels, causing large storm surges due to low atmospheric pressure and strong winds. This study explores factors affecting the numerical modelling of storm surges induced by hurricanes in the tropical Atlantic. Two ocean models are compared and used for sensitivity experiments. ERA5 atmospheric reanalysis forcing generally improves surge estimates compared to parametric wind models. Including ocean circulations reduces errors in surge estimates in some areas.
Alisée A. Chaigneau, Angélique Melet, Aurore Voldoire, Maialen Irazoqui Apecechea, Guillaume Reffray, Stéphane Law-Chune, and Lotfi Aouf
Nat. Hazards Earth Syst. Sci., 24, 4031–4048, https://doi.org/10.5194/nhess-24-4031-2024, https://doi.org/10.5194/nhess-24-4031-2024, 2024
Short summary
Short summary
Climate-change-induced sea level rise increases the frequency of extreme sea levels. We analyze projected changes in extreme sea levels for western European coasts produced with high-resolution models (∼ 6 km). Unlike commonly used coarse-scale global climate models, this approach allows us to simulate key processes driving coastal sea level variations, such as long-term sea level rise, tides, storm surges induced by low atmospheric surface pressure and winds, waves, and their interactions.
Marc Mallet, Aurore Voldoire, Fabien Solmon, Pierre Nabat, Thomas Drugé, and Romain Roehrig
Atmos. Chem. Phys., 24, 12509–12535, https://doi.org/10.5194/acp-24-12509-2024, https://doi.org/10.5194/acp-24-12509-2024, 2024
Short summary
Short summary
This study investigates the interactions between smoke aerosols and climate in tropical Africa using a coupled ocean–atmosphere–aerosol climate model. The work shows that smoke plumes have a significant impact by increasing the low-cloud fraction, decreasing the ocean and continental surface temperature and reducing the precipitation of coastal western Africa. It also highlights the role of the ocean temperature response and its feedbacks for the September–November season.
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
Short summary
Short summary
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.
Roderik van de Wal, Angélique Melet, Debora Bellafiore, Paula Camus, Christian Ferrarin, Gualbert Oude Essink, Ivan D. Haigh, Piero Lionello, Arjen Luijendijk, Alexandra Toimil, Joanna Staneva, and Michalis Vousdoukas
State Planet, 3-slre1, 5, https://doi.org/10.5194/sp-3-slre1-5-2024, https://doi.org/10.5194/sp-3-slre1-5-2024, 2024
Short summary
Short summary
Sea level rise has major impacts in Europe, which vary from place to place and in time, depending on the source of the impacts. Flooding, erosion, and saltwater intrusion lead, via different pathways, to various consequences for coastal regions across Europe. This causes damage to assets, the environment, and people for all three categories of impacts discussed in this paper. The paper provides an overview of the various impacts in Europe.
Bart van den Hurk, Nadia Pinardi, Alexander Bisaro, Giulia Galluccio, José A. Jiménez, Kate Larkin, Angélique Melet, Lavinia Giulia Pomarico, Kristin Richter, Kanika Singh, Roderik van de Wal, and Gundula Winter
State Planet, 3-slre1, 1, https://doi.org/10.5194/sp-3-slre1-1-2024, https://doi.org/10.5194/sp-3-slre1-1-2024, 2024
Short summary
Short summary
The Summary for Policymakers compiles findings from “Sea Level Rise in Europe: 1st Assessment Report of the Knowledge Hub on Sea Level Rise”. It covers knowledge gaps, observations, projections, impacts, adaptation measures, decision-making principles, and governance challenges. It provides information for each European basin (Mediterranean, Black Sea, North Sea, Baltic Sea, Atlantic, and Arctic) and aims to assist policymakers in enhancing the preparedness of European coasts for sea level rise.
Fabrice Hernandez, Marcos Garcia Sotillo, and Angelique Melet
State Planet Discuss., https://doi.org/10.5194/sp-2024-39, https://doi.org/10.5194/sp-2024-39, 2024
Preprint under review for SP
Short summary
Short summary
An historical review over the last three decades on intercomparison projects of ocean numerical reanalysis or forecast is first proposed. From this, main issues and lessons learned are discussed in order to propose an overview of best practices and key considerations to facilitate intercomparison activities in operational oceanography.
Angelique Melet, Begoña Pérez Gómez, and Pascal Matte
State Planet Discuss., https://doi.org/10.5194/sp-2024-27, https://doi.org/10.5194/sp-2024-27, 2024
Preprint under review for SP
Short summary
Short summary
Forecasting the sea level is crucial for supporting coastal management through early warning systems and for adopting adaptation strategies to climate changes impacts. We provide here an overview on models commonly used for sea level forecasting, that can be based on storm surge models or ocean circulation ones, integrated on structured or unstructured grids, including an outlook on new approaches based on ensemble methods.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
Short summary
Short summary
In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
Short summary
Short summary
In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Stefania A. Ciliberti, Enrique Alvarez Fanjul, Jay Pearlman, Kirsten Wilmer-Becker, Pierre Bahurel, Fabrice Ardhuin, Alain Arnaud, Mike Bell, Segolene Berthou, Laurent Bertino, Arthur Capet, Eric Chassignet, Stefano Ciavatta, Mauro Cirano, Emanuela Clementi, Gianpiero Cossarini, Gianpaolo Coro, Stuart Corney, Fraser Davidson, Marie Drevillon, Yann Drillet, Renaud Dussurget, Ghada El Serafy, Katja Fennel, Marcos Garcia Sotillo, Patrick Heimbach, Fabrice Hernandez, Patrick Hogan, Ibrahim Hoteit, Sudheer Joseph, Simon Josey, Pierre-Yves Le Traon, Simone Libralato, Marco Mancini, Pascal Matte, Angelique Melet, Yasumasa Miyazawa, Andrew M. Moore, Antonio Novellino, Andrew Porter, Heather Regan, Laia Romero, Andreas Schiller, John Siddorn, Joanna Staneva, Cecile Thomas-Courcoux, Marina Tonani, Jose Maria Garcia-Valdecasas, Jennifer Veitch, Karina von Schuckmann, Liying Wan, John Wilkin, and Romane Zufic
State Planet, 1-osr7, 2, https://doi.org/10.5194/sp-1-osr7-2-2023, https://doi.org/10.5194/sp-1-osr7-2-2023, 2023
Alisée A. Chaigneau, Stéphane Law-Chune, Angélique Melet, Aurore Voldoire, Guillaume Reffray, and Lotfi Aouf
Ocean Sci., 19, 1123–1143, https://doi.org/10.5194/os-19-1123-2023, https://doi.org/10.5194/os-19-1123-2023, 2023
Short summary
Short summary
Wind waves and swells are major drivers of coastal environment changes and can drive coastal marine hazards such as coastal flooding. In this paper, by using numerical modeling along the European Atlantic coastline, we assess how present and future wave characteristics are impacted by sea level changes. For example, at the end of the century under the SSP5-8.5 climate change scenario, extreme significant wave heights are higher by up to +40 % due to the effect of tides and mean sea level rise.
Thibault Guinaldo, Aurore Voldoire, Robin Waldman, Stéphane Saux Picart, and Hervé Roquet
Ocean Sci., 19, 629–647, https://doi.org/10.5194/os-19-629-2023, https://doi.org/10.5194/os-19-629-2023, 2023
Short summary
Short summary
In the summer of 2022, France experienced a series of unprecedented heatwaves. This study is the first to examine the response of sea surface temperatures to these events, using spatial operational data and attributing the observed abnormally warm SSTs to atmospheric forcings. The findings of this study underscore the critical need for an efficient and sustainable operational system to monitor alterations that threaten the oceans in the context of climate change.
Aurore Voldoire, Romain Roehrig, Hervé Giordani, Robin Waldman, Yunyan Zhang, Shaocheng Xie, and Marie-Nöelle Bouin
Geosci. Model Dev., 15, 3347–3370, https://doi.org/10.5194/gmd-15-3347-2022, https://doi.org/10.5194/gmd-15-3347-2022, 2022
Short summary
Short summary
A single-column version of the global climate model CNRM-CM6-1 has been designed to ease development and validation of the model physics at the air–sea interface in a simplified environment. This model is then used to assess the ability to represent the sea surface temperature diurnal cycle. We conclude that the sea surface temperature diurnal variability is reasonably well represented in CNRM-CM6-1 with a 1 h coupling time step and the upper-ocean model resolution of 1 m.
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
Short summary
Short summary
We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Daniel T. McCoy, Paul R. Field, Gregory S. Elsaesser, Alejandro Bodas-Salcedo, Brian H. Kahn, Mark D. Zelinka, Chihiro Kodama, Thorsten Mauritsen, Benoit Vanniere, Malcolm Roberts, Pier L. Vidale, David Saint-Martin, Aurore Voldoire, Rein Haarsma, Adrian Hill, Ben Shipway, and Jonathan Wilkinson
Atmos. Chem. Phys., 19, 1147–1172, https://doi.org/10.5194/acp-19-1147-2019, https://doi.org/10.5194/acp-19-1147-2019, 2019
Short summary
Short summary
The largest single source of uncertainty in the climate sensitivity predicted by global climate models is how much low-altitude clouds change as the climate warms. Models predict that the amount of liquid within and the brightness of low-altitude clouds increase in the extratropics with warming. We show that increased fluxes of moisture into extratropical storms in the midlatitudes explain the majority of the observed trend and the modeled increase in liquid water within these storms.
Aurore Voldoire, Bertrand Decharme, Joris Pianezze, Cindy Lebeaupin Brossier, Florence Sevault, Léo Seyfried, Valérie Garnier, Soline Bielli, Sophie Valcke, Antoinette Alias, Mickael Accensi, Fabrice Ardhuin, Marie-Noëlle Bouin, Véronique Ducrocq, Stéphanie Faroux, Hervé Giordani, Fabien Léger, Patrick Marsaleix, Romain Rainaud, Jean-Luc Redelsperger, Evelyne Richard, and Sébastien Riette
Geosci. Model Dev., 10, 4207–4227, https://doi.org/10.5194/gmd-10-4207-2017, https://doi.org/10.5194/gmd-10-4207-2017, 2017
Short summary
Short summary
This study presents the principles of the new coupling interface based on the SURFEX multi-surface model and the OASIS3-MCT coupler. As SURFEX can be plugged into several atmospheric models, it can be used in a wide range of applications. The objective of this development is to build and share a common structure for the atmosphere–surface coupling of all these applications, involving on the one hand atmospheric models and on the other hand ocean, ice, hydrology, and wave models.
Roland Séférian, Christine Delire, Bertrand Decharme, Aurore Voldoire, David Salas y Melia, Matthieu Chevallier, David Saint-Martin, Olivier Aumont, Jean-Christophe Calvet, Dominique Carrer, Hervé Douville, Laurent Franchistéguy, Emilie Joetzjer, and Séphane Sénési
Geosci. Model Dev., 9, 1423–1453, https://doi.org/10.5194/gmd-9-1423-2016, https://doi.org/10.5194/gmd-9-1423-2016, 2016
Short summary
Short summary
This paper presents the first IPCC-class Earth system model developed at Centre National de Recherches Météorologiques (CNRM-ESM1). We detail how the various carbon reservoirs were initialized and analyze the behavior of the carbon cycle and its prominent physical drivers, comparing model results to the most up-to-date climate and carbon cycle dataset over the latest decades.
G. Reffray, R. Bourdalle-Badie, and C. Calone
Geosci. Model Dev., 8, 69–86, https://doi.org/10.5194/gmd-8-69-2015, https://doi.org/10.5194/gmd-8-69-2015, 2015
Y. Drillet, J. M. Lellouche, B. Levier, M. Drévillon, O. Le Galloudec, G. Reffray, C. Regnier, E. Greiner, and M. Clavier
Ocean Sci., 10, 1013–1029, https://doi.org/10.5194/os-10-1013-2014, https://doi.org/10.5194/os-10-1013-2014, 2014
P. Huszar, H. Teyssèdre, M. Michou, A. Voldoire, D. J. L. Olivié, D. Saint-Martin, D. Cariolle, S. Senesi, D. Salas Y Melia, A. Alias, F. Karcher, P. Ricaud, and T. Halenka
Atmos. Chem. Phys., 13, 10027–10048, https://doi.org/10.5194/acp-13-10027-2013, https://doi.org/10.5194/acp-13-10027-2013, 2013
V. Masson, P. Le Moigne, E. Martin, S. Faroux, A. Alias, R. Alkama, S. Belamari, A. Barbu, A. Boone, F. Bouyssel, P. Brousseau, E. Brun, J.-C. Calvet, D. Carrer, B. Decharme, C. Delire, S. Donier, K. Essaouini, A.-L. Gibelin, H. Giordani, F. Habets, M. Jidane, G. Kerdraon, E. Kourzeneva, M. Lafaysse, S. Lafont, C. Lebeaupin Brossier, A. Lemonsu, J.-F. Mahfouf, P. Marguinaud, M. Mokhtari, S. Morin, G. Pigeon, R. Salgado, Y. Seity, F. Taillefer, G. Tanguy, P. Tulet, B. Vincendon, V. Vionnet, and A. Voldoire
Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, https://doi.org/10.5194/gmd-6-929-2013, 2013
Related subject area
Oceanography
A revised ocean mixed layer model for better simulating the diurnal variation in ocean skin temperature
Evaluating an accelerated forcing approach for improving computational efficiency in coupled ice sheet–ocean modelling
An optimal transformation method for inferring ocean tracer sources and sinks
PPCon 1.0: Biogeochemical-Argo profile prediction with 1D convolutional networks
Experimental design for the Marine Ice Sheet–Ocean Model Intercomparison Project – phase 2 (MISOMIP2)
Development of a total variation diminishing (TVD) sea ice transport scheme and its application in an ocean (SCHISM v5.11) and sea ice (Icepack v1.3.4) coupled model on unstructured grids
Spurious numerical mixing under strong tidal forcing: a case study in the south-east Asian seas using the Symphonie model (v3.1.2)
Modelling the water isotope distribution in the Mediterranean Sea using a high-resolution oceanic model (NEMO-MED12-watiso v1.0): evaluation of model results against in situ observations
LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry
Towards a real-time modeling of global ocean waves by the fully GPU-accelerated spectral wave model WAM6-GPU v1.0
A simple approach to represent precipitation-derived freshwater fluxes into nearshore ocean models: an FVCOM4.1 case study of Quatsino Sound, British Columbia
An optimal transformation method applied to diagnose the ocean carbon budget
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 2: Towards a better representation of total alkalinity when modeling the carbonate system and air–sea CO2 fluxes
DALROMS-NWA12 v1.0, a coupled circulation-ice-biogeochemistry modelling system for the northwest Atlantic Ocean: Development and validation
Development of a novel storm surge inundation model framework for efficient prediction
Skin sea surface temperature schemes in coupled ocean–atmosphere modelling: the impact of chlorophyll-interactive e-folding depth
A wave-resolving 2DV Lagrangian approach to model microplastic transport in the nearshore
DELWAVE 1.0: deep learning surrogate model of surface wave climate in the Adriatic Basin
StraitFlux – precise computations of water strait fluxes on various modeling grids
Comparison of the Coastal and Regional Ocean COmmunity model (CROCO) and NCAR-LES in non-hydrostatic simulations
HOTSSea v1: a NEMO-based physical Hindcast of the Salish Sea (1980–2018) supporting ecosystem model development
Intercomparisons of Tracker v1.1 and four other ocean particle-tracking software packages in the Regional Ocean Modeling System
CAR36, a regional high-resolution ocean forecasting system for improving drift and beaching of Sargassum in the Caribbean archipelago
Implementation of additional spectral wave field exchanges in a three-dimensional wave–current coupled WAVEWATCH-III (version 6.07) and CROCO (version 1.2) configuration: assessment of their implications for macro-tidal coastal hydrodynamics
Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system
LOCATE v1.0: numerical modelling of floating marine debris dispersion in coastal regions using Parcels v2.4.2
New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4
MQGeometry-1.0: a multi-layer quasi-geostrophic solver on non-rectangular geometries
Parameter estimation for ocean background vertical diffusivity coefficients in the Community Earth System Model (v1.2.1) and its impact on El Niño–Southern Oscillation forecasts
Great Lakes wave forecast system on high-resolution unstructured meshes
Impact of increased resolution on Arctic Ocean simulations in Ocean Model Intercomparison Project phase 2 (OMIP-2)
A high-resolution physical–biogeochemical model for marine resource applications in the northwest Atlantic (MOM6-COBALT-NWA12 v1.0)
A flexible z-layers approach for the accurate representation of free surface flows in a coastal ocean model (SHYFEM v. 7_5_71)
Implementation and assessment of a model including mixotrophs and the carbonate cycle (Eco3M_MIX-CarbOx v1.0) in a highly dynamic Mediterranean coastal environment (Bay of Marseille, France) – Part 1: Evolution of ecosystem composition under limited light and nutrient conditions
Ocean wave tracing v.1: a numerical solver of the wave ray equations for ocean waves on variable currents at arbitrary depths
Design and evaluation of an efficient high-precision ocean surface wave model with a multiscale grid system (MSG_Wav1.0)
Evaluation of the CMCC global eddying ocean model for the Ocean Model Intercomparison Project (OMIP2)
Barents-2.5km v2.0: an operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard
Open-ocean tides simulated by ICON-O, version icon-2.6.6
Using Probability Density Functions to Evaluate Models (PDFEM, v1.0) to compare a biogeochemical model with satellite-derived chlorophyll
Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
Using the COAsT Python package to develop a standardised validation workflow for ocean physics models
Improving Antarctic Bottom Water precursors in NEMO for climate applications
Formulation, optimization, and sensitivity of NitrOMZv1.0, a biogeochemical model of the nitrogen cycle in oceanic oxygen minimum zones
Waves in SKRIPS: WAVEWATCH III coupling implementation and a case study of Tropical Cyclone Mekunu
Adding sea ice effects to a global operational model (NEMO v3.6) for forecasting total water level: approach and impact
Enhanced ocean wave modeling by including effect of breaking under both deep- and shallow-water conditions
An internal solitary wave forecasting model in the northern South China Sea (ISWFM-NSCS)
The 3D biogeochemical marine mercury cycling model MERCY v2.0 – linking atmospheric Hg to methylmercury in fish
Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev., 17, 8553–8568, https://doi.org/10.5194/gmd-17-8553-2024, https://doi.org/10.5194/gmd-17-8553-2024, 2024
Short summary
Short summary
Sea surface temperature (SST) is vital in climate, weather, and ocean sciences because it influences air–sea interactions. Errors in the ECMWF model's scheme for predicting ocean skin temperature prompted a revision of the ocean mixed layer model. Validation against infrared measurements and buoys showed a good correlation with minimal deviations. The revised model accurately simulates SST variations and aligns with solar radiation distributions, showing promise for weather and climate models.
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev., 17, 8243–8265, https://doi.org/10.5194/gmd-17-8243-2024, https://doi.org/10.5194/gmd-17-8243-2024, 2024
Short summary
Short summary
We introduce an accelerated forcing approach to address timescale discrepancies between the ice sheets and ocean components in coupled modelling by reducing the ocean simulation duration. The approach is evaluated using idealized coupled models, and its limitations in real-world applications are discussed. Our results suggest it can be a valuable tool for process-oriented coupled ice sheet–ocean modelling and downscaling climate simulations with such models.
Jan D. Zika and Taimoor Sohail
Geosci. Model Dev., 17, 8049–8068, https://doi.org/10.5194/gmd-17-8049-2024, https://doi.org/10.5194/gmd-17-8049-2024, 2024
Short summary
Short summary
We describe a method to relate fluxes of heat and freshwater at the sea surface to the resulting distribution of seawater among categories such as warm and salty or cold and salty. The method exploits the laws that govern how heat and salt change when water mixes. The method will allow the climate community to improve estimates of how much heat the ocean is absorbing and how rainfall and evaporation are changing across the globe.
Gloria Pietropolli, Luca Manzoni, and Gianpiero Cossarini
Geosci. Model Dev., 17, 7347–7364, https://doi.org/10.5194/gmd-17-7347-2024, https://doi.org/10.5194/gmd-17-7347-2024, 2024
Short summary
Short summary
Monitoring the ocean is essential for studying marine life and human impact. Our new software, PPCon, uses ocean data to predict key factors like nitrate and chlorophyll levels, which are hard to measure directly. By leveraging machine learning, PPCon offers more accurate and efficient predictions.
Jan De Rydt, Nicolas C. Jourdain, Yoshihiro Nakayama, Mathias van Caspel, Ralph Timmermann, Pierre Mathiot, Xylar S. Asay-Davis, Hélène Seroussi, Pierre Dutrieux, Ben Galton-Fenzi, David Holland, and Ronja Reese
Geosci. Model Dev., 17, 7105–7139, https://doi.org/10.5194/gmd-17-7105-2024, https://doi.org/10.5194/gmd-17-7105-2024, 2024
Short summary
Short summary
Global climate models do not reliably simulate sea-level change due to ice-sheet–ocean interactions. We propose a community modelling effort to conduct a series of well-defined experiments to compare models with observations and study how models respond to a range of perturbations in climate and ice-sheet geometry. The second Marine Ice Sheet–Ocean Model Intercomparison Project will continue to lay the groundwork for including ice-sheet–ocean interactions in global-scale IPCC-class models.
Qian Wang, Yang Zhang, Fei Chai, Y. Joseph Zhang, and Lorenzo Zampieri
Geosci. Model Dev., 17, 7067–7081, https://doi.org/10.5194/gmd-17-7067-2024, https://doi.org/10.5194/gmd-17-7067-2024, 2024
Short summary
Short summary
We coupled an unstructured hydro-model with an advanced column sea ice model to meet the growing demand for increased resolution and complexity in unstructured sea ice models. Additionally, we present a novel tracer transport scheme for the sea ice coupled model and demonstrate that this scheme fulfills the requirements for conservation, accuracy, efficiency, and monotonicity in an idealized test. Our new coupled model also has good performance in realistic tests.
Adrien Garinet, Marine Herrmann, Patrick Marsaleix, and Juliette Pénicaud
Geosci. Model Dev., 17, 6967–6986, https://doi.org/10.5194/gmd-17-6967-2024, https://doi.org/10.5194/gmd-17-6967-2024, 2024
Short summary
Short summary
Mixing is a crucial aspect of the ocean, but its accurate representation in computer simulations is made challenging by errors that result in unwanted mixing, compromising simulation realism. Here we illustrate the spurious effect that tides can have on simulations of south-east Asia. Although they play an important role in determining the state of the ocean, they can increase numerical errors and make simulation outputs less realistic. We also provide insights into how to reduce these errors.
Mohamed Ayache, Jean-Claude Dutay, Anne Mouchet, Kazuyo Tachikawa, Camille Risi, and Gilles Ramstein
Geosci. Model Dev., 17, 6627–6655, https://doi.org/10.5194/gmd-17-6627-2024, https://doi.org/10.5194/gmd-17-6627-2024, 2024
Short summary
Short summary
Water isotopes (δ18O, δD) are one of the most widely used proxies in ocean climate research. Previous studies using water isotope observations and modelling have highlighted the importance of understanding spatial and temporal isotopic variability for a quantitative interpretation of these tracers. Here we present the first results of a high-resolution regional dynamical model (at 1/12° horizontal resolution) developed for the Mediterranean Sea, one of the hotspots of ongoing climate change.
Cara Nissen, Nicole S. Lovenduski, Mathew Maltrud, Alison R. Gray, Yohei Takano, Kristen Falcinelli, Jade Sauvé, and Katherine Smith
Geosci. Model Dev., 17, 6415–6435, https://doi.org/10.5194/gmd-17-6415-2024, https://doi.org/10.5194/gmd-17-6415-2024, 2024
Short summary
Short summary
Autonomous profiling floats have provided unprecedented observational coverage of the global ocean, but uncertainties remain about whether their sampling frequency and density capture the true spatiotemporal variability of physical, biogeochemical, and biological properties. Here, we present the novel synthetic biogeochemical float capabilities of the Energy Exascale Earth System Model version 2 and demonstrate their utility as a test bed to address these uncertainties.
Ye Yuan, Fujiang Yu, Zhi Chen, Xueding Li, Fang Hou, Yuanyong Gao, Zhiyi Gao, and Renbo Pang
Geosci. Model Dev., 17, 6123–6136, https://doi.org/10.5194/gmd-17-6123-2024, https://doi.org/10.5194/gmd-17-6123-2024, 2024
Short summary
Short summary
Accurate and timely forecasting of ocean waves is of great importance to the safety of marine transportation and offshore engineering. In this study, GPU-accelerated computing is introduced in WAve Modeling Cycle 6 (WAM6). With this effort, global high-resolution wave simulations can now run on GPUs up to tens of times faster than the currently available models can on a CPU node with results that are just as accurate.
Krysten Rutherford, Laura Bianucci, and William Floyd
Geosci. Model Dev., 17, 6083–6104, https://doi.org/10.5194/gmd-17-6083-2024, https://doi.org/10.5194/gmd-17-6083-2024, 2024
Short summary
Short summary
Nearshore ocean models often lack complete information about freshwater fluxes due to numerous ungauged rivers and streams. We tested a simple rain-based hydrological model as inputs into an ocean model of Quatsino Sound, Canada, with the aim of improving the representation of the land–ocean connection in the nearshore model. Through multiple tests, we found that the performance of the ocean model improved when providing 60 % or more of the freshwater inputs from the simple runoff model.
Neill Mackay, Taimoor Sohail, Jan David Zika, Richard G. Williams, Oliver Andrews, and Andrew James Watson
Geosci. Model Dev., 17, 5987–6005, https://doi.org/10.5194/gmd-17-5987-2024, https://doi.org/10.5194/gmd-17-5987-2024, 2024
Short summary
Short summary
The ocean absorbs carbon dioxide from the atmosphere, mitigating climate change, but estimates of the uptake do not always agree. There is a need to reconcile these differing estimates and to improve our understanding of ocean carbon uptake. We present a new method for estimating ocean carbon uptake and test it with model data. The method effectively diagnoses the ocean carbon uptake from limited data and therefore shows promise for reconciling different observational estimates.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 17, 5851–5882, https://doi.org/10.5194/gmd-17-5851-2024, https://doi.org/10.5194/gmd-17-5851-2024, 2024
Short summary
Short summary
The carbonate system is typically studied using measurements, but modeling can contribute valuable insights. Using a biogeochemical model, we propose a new representation of total alkalinity, dissolved inorganic carbon, pCO2, and pH in a highly dynamic Mediterranean coastal area, the Bay of Marseille, a useful addition to measurements. Through a detailed analysis of pCO2 and air–sea CO2 fluxes, we show that variations are strongly impacted by the hydrodynamic processes that affect the bay.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
EGUsphere, https://doi.org/10.5194/egusphere-2024-1372, https://doi.org/10.5194/egusphere-2024-1372, 2024
Short summary
Short summary
We developed a modelling system of the northwest Atlantic Ocean that simulates the currents, temperature, salinity, and parts of the biochemical cycle of the ocean, as well as sea ice. The system combines advanced, open-source models and can be used to study, for example, the oceans’ capture of atmospheric carbon dioxide which is a key process in the global climate. The system produces realistic results, and we use it to investigate the roles of tides and sea ice in the northwest Atlantic Ocean.
Xuanxuan Gao, Shuiqing Li, Dongxue Mo, Yahao Liu, and Po Hu
Geosci. Model Dev., 17, 5497–5509, https://doi.org/10.5194/gmd-17-5497-2024, https://doi.org/10.5194/gmd-17-5497-2024, 2024
Short summary
Short summary
Storm surges generate coastal inundation and expose populations and properties to danger. We developed a novel storm surge inundation model for efficient prediction. Estimates compare well with in situ measurements and results from a numerical model. The new model is a significant improvement on existing numerical models, with much higher computational efficiency and stability, which allows timely disaster prevention and mitigation.
Vincenzo de Toma, Daniele Ciani, Yassmin Hesham Essa, Chunxue Yang, Vincenzo Artale, Andrea Pisano, Davide Cavaliere, Rosalia Santoleri, and Andrea Storto
Geosci. Model Dev., 17, 5145–5165, https://doi.org/10.5194/gmd-17-5145-2024, https://doi.org/10.5194/gmd-17-5145-2024, 2024
Short summary
Short summary
This study explores methods to reconstruct diurnal variations in skin sea surface temperature in a model of the Mediterranean Sea. Our new approach, considering chlorophyll concentration, enhances spatial and temporal variations in the warm layer. Comparative analysis shows context-dependent improvements. The proposed "chlorophyll-interactive" method brings the surface net total heat flux closer to zero annually, despite a net heat loss from the ocean to the atmosphere.
Isabel Jalón-Rojas, Damien Sous, and Vincent Marieu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-100, https://doi.org/10.5194/gmd-2024-100, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This study presents a novel modeling approach for understanding microplastic transport in coastal waters. The model accurately replicates experimental data and reveals key transport mechanisms. The findings enhance our knowledge of how microplastics move in nearshore environments, aiding in coastal management and efforts to combat plastic pollution globally.
Peter Mlakar, Antonio Ricchi, Sandro Carniel, Davide Bonaldo, and Matjaž Ličer
Geosci. Model Dev., 17, 4705–4725, https://doi.org/10.5194/gmd-17-4705-2024, https://doi.org/10.5194/gmd-17-4705-2024, 2024
Short summary
Short summary
We propose a new point-prediction model, the DEep Learning WAVe Emulating model (DELWAVE), which successfully emulates the Simulating WAves Nearshore model (SWAN) over synoptic to climate timescales. Compared to control climatology over all wind directions, the mismatch between DELWAVE and SWAN is generally small compared to the difference between scenario and control conditions, suggesting that the noise introduced by surrogate modelling is substantially weaker than the climate change signal.
Susanna Winkelbauer, Michael Mayer, and Leopold Haimberger
Geosci. Model Dev., 17, 4603–4620, https://doi.org/10.5194/gmd-17-4603-2024, https://doi.org/10.5194/gmd-17-4603-2024, 2024
Short summary
Short summary
Oceanic transports shape the global climate, but the evaluation and validation of this key quantity based on reanalysis and model data are complicated by the distortion of the used modelling grids and the large number of different grid types. We present two new methods that allow the calculation of oceanic fluxes of volume, heat, salinity, and ice through almost arbitrary sections for various models and reanalyses that are independent of the used modelling grids.
Xiaoyu Fan, Baylor Fox-Kemper, Nobuhiro Suzuki, Qing Li, Patrick Marchesiello, Peter P. Sullivan, and Paul S. Hall
Geosci. Model Dev., 17, 4095–4113, https://doi.org/10.5194/gmd-17-4095-2024, https://doi.org/10.5194/gmd-17-4095-2024, 2024
Short summary
Short summary
Simulations of the oceanic turbulent boundary layer using the nonhydrostatic CROCO ROMS and NCAR-LES models are compared. CROCO and the NCAR-LES are accurate in a similar manner, but CROCO’s additional features (e.g., nesting and realism) and its compressible turbulence formulation carry additional costs.
Greig Oldford, Tereza Jarníková, Villy Christensen, and Michael Dunphy
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-58, https://doi.org/10.5194/gmd-2024-58, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We developed a physical ocean model called the Hindcast of the Salish Sea (HOTSSea) that recreates conditions throughout the Salish Sea from 1980 to 2018, filling in the gaps in patchy measurements. The model predicts physical ocean properties with sufficient accuracy to be useful for a variety of applications. The model corroborates observed ocean temperature trends and was used to examine areas with few observations. Results indicate that some seasons and areas are warming faster than others.
Jilian Xiong and Parker MacCready
Geosci. Model Dev., 17, 3341–3356, https://doi.org/10.5194/gmd-17-3341-2024, https://doi.org/10.5194/gmd-17-3341-2024, 2024
Short summary
Short summary
The new offline particle tracking package, Tracker v1.1, is introduced to the Regional Ocean Modeling System, featuring an efficient nearest-neighbor algorithm to enhance particle-tracking speed. Its performance was evaluated against four other tracking packages and passive dye. Despite unique features, all packages yield comparable results. Running multiple packages within the same circulation model allows comparison of their performance and ease of use.
Sylvain Cailleau, Laurent Bessières, Léonel Chiendje, Flavie Dubost, Guillaume Reffray, Jean-Michel Lellouche, Simon van Gennip, Charly Régnier, Marie Drevillon, Marc Tressol, Matthieu Clavier, Julien Temple-Boyer, and Léo Berline
Geosci. Model Dev., 17, 3157–3173, https://doi.org/10.5194/gmd-17-3157-2024, https://doi.org/10.5194/gmd-17-3157-2024, 2024
Short summary
Short summary
In order to improve Sargassum drift forecasting in the Caribbean area, drift models can be forced by higher-resolution ocean currents. To this goal a 3 km resolution regional ocean model has been developed. Its assessment is presented with a particular focus on the reproduction of fine structures representing key features of the Caribbean region dynamics and Sargassum transport. The simulated propagation of a North Brazil Current eddy and its dissipation was found to be quite realistic.
Gaetano Porcile, Anne-Claire Bennis, Martial Boutet, Sophie Le Bot, Franck Dumas, and Swen Jullien
Geosci. Model Dev., 17, 2829–2853, https://doi.org/10.5194/gmd-17-2829-2024, https://doi.org/10.5194/gmd-17-2829-2024, 2024
Short summary
Short summary
Here a new method of modelling the interaction between ocean currents and waves is presented. We developed an advanced coupling of two models, one for ocean currents and one for waves. In previous couplings, some wave-related calculations were based on simplified assumptions. Our method uses more complex calculations to better represent wave–current interactions. We tested it in a macro-tidal coastal area and found that it significantly improves the model accuracy, especially during storms.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
Short summary
Short summary
Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Ivan Hernandez, Leidy M. Castro-Rosero, Manuel Espino, and Jose M. Alsina Torrent
Geosci. Model Dev., 17, 2221–2245, https://doi.org/10.5194/gmd-17-2221-2024, https://doi.org/10.5194/gmd-17-2221-2024, 2024
Short summary
Short summary
The LOCATE numerical model was developed to conduct Lagrangian simulations of the transport and dispersion of marine debris at coastal scales. High-resolution hydrodynamic data and a beaching module that used particle distance to the shore for land–water boundary detection were used on a realistic debris discharge scenario comparing hydrodynamic data at various resolutions. Coastal processes and complex geometric structures were resolved when using nested grids and distance-to-shore beaching.
Ngoc B. Trinh, Marine Herrmann, Caroline Ulses, Patrick Marsaleix, Thomas Duhaut, Thai To Duy, Claude Estournel, and R. Kipp Shearman
Geosci. Model Dev., 17, 1831–1867, https://doi.org/10.5194/gmd-17-1831-2024, https://doi.org/10.5194/gmd-17-1831-2024, 2024
Short summary
Short summary
A high-resolution model was built to study the South China Sea (SCS) water, heat, and salt budgets. Model performance is demonstrated by comparison with observations and simulations. Important discards are observed if calculating offline, instead of online, lateral inflows and outflows of water, heat, and salt. The SCS mainly receives water from the Luzon Strait and releases it through the Mindoro, Taiwan, and Karimata straits. SCS surface interocean water exchanges are driven by monsoon winds.
Louis Thiry, Long Li, Guillaume Roullet, and Etienne Mémin
Geosci. Model Dev., 17, 1749–1764, https://doi.org/10.5194/gmd-17-1749-2024, https://doi.org/10.5194/gmd-17-1749-2024, 2024
Short summary
Short summary
We present a new way of solving the quasi-geostrophic (QG) equations, a simple set of equations describing ocean dynamics. Our method is solely based on the numerical methods used to solve the equations and requires no parameter tuning. Moreover, it can handle non-rectangular geometries, opening the way to study QG equations on realistic domains. We release a PyTorch implementation to ease future machine-learning developments on top of the presented method.
Zheqi Shen, Yihao Chen, Xiaojing Li, and Xunshu Song
Geosci. Model Dev., 17, 1651–1665, https://doi.org/10.5194/gmd-17-1651-2024, https://doi.org/10.5194/gmd-17-1651-2024, 2024
Short summary
Short summary
Parameter estimation is the process that optimizes model parameters using observations, which could reduce model errors and improve forecasting. In this study, we conducted parameter estimation experiments using the CESM and the ensemble adjustment Kalman filter. The obtained initial conditions and parameters are used to perform ensemble forecast experiments for ENSO forecasting. The results revealed that parameter estimation could reduce analysis errors and improve ENSO forecast skills.
Ali Abdolali, Saeideh Banihashemi, Jose Henrique Alves, Aron Roland, Tyler J. Hesser, Mary Anderson Bryant, and Jane McKee Smith
Geosci. Model Dev., 17, 1023–1039, https://doi.org/10.5194/gmd-17-1023-2024, https://doi.org/10.5194/gmd-17-1023-2024, 2024
Short summary
Short summary
This article presents an overview of the development and implementation of Great Lake Wave Unstructured (GLWUv2.0), including the core model and workflow design and development. The validation was conducted against in situ data for the re-forecasted duration for summer and wintertime (ice season). The article describes the limitations and challenges encountered in the operational environment and the path forward for the next generation of wave forecast systems in enclosed basins like the GL.
Qiang Wang, Qi Shu, Alexandra Bozec, Eric P. Chassignet, Pier Giuseppe Fogli, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Nikolay Koldunov, Julien Le Sommer, Yiwen Li, Pengfei Lin, Hailong Liu, Igor Polyakov, Patrick Scholz, Dmitry Sidorenko, Shizhu Wang, and Xiaobiao Xu
Geosci. Model Dev., 17, 347–379, https://doi.org/10.5194/gmd-17-347-2024, https://doi.org/10.5194/gmd-17-347-2024, 2024
Short summary
Short summary
Increasing resolution improves model skills in simulating the Arctic Ocean, but other factors such as parameterizations and numerics are at least of the same importance for obtaining reliable simulations.
Andrew C. Ross, Charles A. Stock, Alistair Adcroft, Enrique Curchitser, Robert Hallberg, Matthew J. Harrison, Katherine Hedstrom, Niki Zadeh, Michael Alexander, Wenhao Chen, Elizabeth J. Drenkard, Hubert du Pontavice, Raphael Dussin, Fabian Gomez, Jasmin G. John, Dujuan Kang, Diane Lavoie, Laure Resplandy, Alizée Roobaert, Vincent Saba, Sang-Ik Shin, Samantha Siedlecki, and James Simkins
Geosci. Model Dev., 16, 6943–6985, https://doi.org/10.5194/gmd-16-6943-2023, https://doi.org/10.5194/gmd-16-6943-2023, 2023
Short summary
Short summary
We evaluate a model for northwest Atlantic Ocean dynamics and biogeochemistry that balances high resolution with computational economy by building on the new regional features in the MOM6 ocean model and COBALT biogeochemical model. We test the model's ability to simulate impactful historical variability and find that the model simulates the mean state and variability of most features well, which suggests the model can provide information to inform living-marine-resource applications.
Luca Arpaia, Christian Ferrarin, Marco Bajo, and Georg Umgiesser
Geosci. Model Dev., 16, 6899–6919, https://doi.org/10.5194/gmd-16-6899-2023, https://doi.org/10.5194/gmd-16-6899-2023, 2023
Short summary
Short summary
We propose a discrete multilayer shallow water model based on z-layers which, thanks to the insertion and removal of surface layers, can deal with an arbitrarily large tidal oscillation independently of the vertical resolution. The algorithm is based on a two-step procedure used in numerical simulations with moving boundaries (grid movement followed by a grid topology change, that is, the insertion/removal of surface layers), which avoids the appearance of very thin surface layers.
Lucille Barré, Frédéric Diaz, Thibaut Wagener, France Van Wambeke, Camille Mazoyer, Christophe Yohia, and Christel Pinazo
Geosci. Model Dev., 16, 6701–6739, https://doi.org/10.5194/gmd-16-6701-2023, https://doi.org/10.5194/gmd-16-6701-2023, 2023
Short summary
Short summary
While several studies have shown that mixotrophs play a crucial role in the carbon cycle, the impact of environmental forcings on their dynamics remains poorly investigated. Using a biogeochemical model that considers mixotrophs, we study the impact of light and nutrient concentration on the ecosystem composition in a highly dynamic Mediterranean coastal area: the Bay of Marseille. We show that mixotrophs cope better with oligotrophic conditions compared to strict auto- and heterotrophs.
Trygve Halsne, Kai Håkon Christensen, Gaute Hope, and Øyvind Breivik
Geosci. Model Dev., 16, 6515–6530, https://doi.org/10.5194/gmd-16-6515-2023, https://doi.org/10.5194/gmd-16-6515-2023, 2023
Short summary
Short summary
Surface waves that propagate in oceanic or coastal environments get influenced by their surroundings. Changes in the ambient current or the depth profile affect the wave propagation path, and the change in wave direction is called refraction. Some analytical solutions to the governing equations exist under ideal conditions, but for realistic situations, the equations must be solved numerically. Here we present such a numerical solver under an open-source license.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
Short summary
Short summary
Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Doroteaciro Iovino, Pier Giuseppe Fogli, and Simona Masina
Geosci. Model Dev., 16, 6127–6159, https://doi.org/10.5194/gmd-16-6127-2023, https://doi.org/10.5194/gmd-16-6127-2023, 2023
Short summary
Short summary
This paper describes the model performance of three global ocean–sea ice configurations, from non-eddying (1°) to eddy-rich (1/16°) resolutions. Model simulations are obtained following the Ocean Model Intercomparison Project phase 2 (OMIP2) protocol. We compare key global climate variables across the three models and against observations, emphasizing the relative advantages and disadvantages of running forced ocean–sea ice models at higher resolution.
Johannes Röhrs, Yvonne Gusdal, Edel S. U. Rikardsen, Marina Durán Moro, Jostein Brændshøi, Nils Melsom Kristensen, Sindre Fritzner, Keguang Wang, Ann Kristin Sperrevik, Martina Idžanović, Thomas Lavergne, Jens Boldingh Debernard, and Kai H. Christensen
Geosci. Model Dev., 16, 5401–5426, https://doi.org/10.5194/gmd-16-5401-2023, https://doi.org/10.5194/gmd-16-5401-2023, 2023
Short summary
Short summary
A model to predict ocean currents, temperature, and sea ice is presented, covering the Barents Sea and northern Norway. To quantify forecast uncertainties, the model calculates ensemble forecasts with 24 realizations of ocean and ice conditions. Observations from satellites, buoys, and ships are ingested by the model. The model forecasts are compared with observations, and we show that the ocean model has skill in predicting sea surface temperatures.
Jin-Song von Storch, Eileen Hertwig, Veit Lüschow, Nils Brüggemann, Helmuth Haak, Peter Korn, and Vikram Singh
Geosci. Model Dev., 16, 5179–5196, https://doi.org/10.5194/gmd-16-5179-2023, https://doi.org/10.5194/gmd-16-5179-2023, 2023
Short summary
Short summary
The new ocean general circulation model ICON-O is developed for running experiments at kilometer scales and beyond. One targeted application is to simulate internal tides crucial for ocean mixing. To ensure their realism, which is difficult to assess, we evaluate the barotropic tides that generate internal tides. We show that ICON-O is able to realistically simulate the major aspects of the observed barotropic tides and discuss the aspects that impact the quality of the simulated tides.
Bror F. Jönsson, Christopher L. Follett, Jacob Bien, Stephanie Dutkiewicz, Sangwon Hyun, Gemma Kulk, Gael L. Forget, Christian Müller, Marie-Fanny Racault, Christopher N. Hill, Thomas Jackson, and Shubha Sathyendranath
Geosci. Model Dev., 16, 4639–4657, https://doi.org/10.5194/gmd-16-4639-2023, https://doi.org/10.5194/gmd-16-4639-2023, 2023
Short summary
Short summary
While biogeochemical models and satellite-derived ocean color data provide unprecedented information, it is problematic to compare them. Here, we present a new approach based on comparing probability density distributions of model and satellite properties to assess model skills. We also introduce Earth mover's distances as a novel and powerful metric to quantify the misfit between models and observations. We find that how 3D chlorophyll fields are aggregated can be a significant source of error.
Rafael Santana, Helen Macdonald, Joanne O'Callaghan, Brian Powell, Sarah Wakes, and Sutara H. Suanda
Geosci. Model Dev., 16, 3675–3698, https://doi.org/10.5194/gmd-16-3675-2023, https://doi.org/10.5194/gmd-16-3675-2023, 2023
Short summary
Short summary
We show the importance of assimilating subsurface temperature and velocity data in a model of the East Auckland Current. Assimilation of velocity increased the representation of large oceanic vortexes. Assimilation of temperature is needed to correctly simulate temperatures around 100 m depth, which is the most difficult region to simulate in ocean models. Our simulations showed improved results in comparison to the US Navy global model and highlight the importance of regional models.
David Byrne, Jeff Polton, Enda O'Dea, and Joanne Williams
Geosci. Model Dev., 16, 3749–3764, https://doi.org/10.5194/gmd-16-3749-2023, https://doi.org/10.5194/gmd-16-3749-2023, 2023
Short summary
Short summary
Validation is a crucial step during the development of models for ocean simulation. The purpose of validation is to assess how accurate a model is. It is most commonly done by comparing output from a model to actual observations. In this paper, we introduce and demonstrate usage of the COAsT Python package to standardise the validation process for physical ocean models. We also discuss our five guiding principles for standardised validation.
Katherine Hutchinson, Julie Deshayes, Christian Éthé, Clément Rousset, Casimir de Lavergne, Martin Vancoppenolle, Nicolas C. Jourdain, and Pierre Mathiot
Geosci. Model Dev., 16, 3629–3650, https://doi.org/10.5194/gmd-16-3629-2023, https://doi.org/10.5194/gmd-16-3629-2023, 2023
Short summary
Short summary
Bottom Water constitutes the lower half of the ocean’s overturning system and is primarily formed in the Weddell and Ross Sea in the Antarctic due to interactions between the atmosphere, ocean, sea ice and ice shelves. Here we use a global ocean 1° resolution model with explicit representation of the three large ice shelves important for the formation of the parent waters of Bottom Water. We find doing so reduces salt biases, improves water mass realism and gives realistic ice shelf melt rates.
Daniele Bianchi, Daniel McCoy, and Simon Yang
Geosci. Model Dev., 16, 3581–3609, https://doi.org/10.5194/gmd-16-3581-2023, https://doi.org/10.5194/gmd-16-3581-2023, 2023
Short summary
Short summary
We present NitrOMZ, a new model of the oceanic nitrogen cycle that simulates chemical transformations within oxygen minimum zones (OMZs). We describe the model formulation and its implementation in a one-dimensional representation of the water column before evaluating its ability to reproduce observations in the eastern tropical South Pacific. We conclude by describing the model sensitivity to parameter choices and environmental factors and its application to nitrogen cycling in the ocean.
Rui Sun, Alison Cobb, Ana B. Villas Bôas, Sabique Langodan, Aneesh C. Subramanian, Matthew R. Mazloff, Bruce D. Cornuelle, Arthur J. Miller, Raju Pathak, and Ibrahim Hoteit
Geosci. Model Dev., 16, 3435–3458, https://doi.org/10.5194/gmd-16-3435-2023, https://doi.org/10.5194/gmd-16-3435-2023, 2023
Short summary
Short summary
In this work, we integrated the WAVEWATCH III model into the regional coupled model SKRIPS. We then performed a case study using the newly implemented model to study Tropical Cyclone Mekunu, which occurred in the Arabian Sea. We found that the coupled model better simulates the cyclone than the uncoupled model, but the impact of waves on the cyclone is not significant. However, the waves change the sea surface temperature and mixed layer, especially in the cold waves produced due to the cyclone.
Pengcheng Wang and Natacha B. Bernier
Geosci. Model Dev., 16, 3335–3354, https://doi.org/10.5194/gmd-16-3335-2023, https://doi.org/10.5194/gmd-16-3335-2023, 2023
Short summary
Short summary
Effects of sea ice are typically neglected in operational flood forecast systems. In this work, we capture these effects via the addition of a parameterized ice–ocean stress. The parameterization takes advantage of forecast fields from an advanced ice–ocean model and features a novel, consistent representation of the tidal relative ice–ocean velocity. The new parameterization leads to improved forecasts of tides and storm surges in polar regions. Associated physical processes are discussed.
Yue Xu and Xiping Yu
Geosci. Model Dev., 16, 2811–2831, https://doi.org/10.5194/gmd-16-2811-2023, https://doi.org/10.5194/gmd-16-2811-2023, 2023
Short summary
Short summary
An accurate description of the wind energy input into ocean waves is crucial to ocean wave modeling, and a physics-based consideration of the effect of wave breaking is absolutely necessary to obtain such an accurate description, particularly under extreme conditions. This study evaluates the performance of a recently improved formula, taking into account not only the effect of breaking but also the effect of airflow separation on the leeside of steep wave crests in a reasonably consistent way.
Yankun Gong, Xueen Chen, Jiexin Xu, Jieshuo Xie, Zhiwu Chen, Yinghui He, and Shuqun Cai
Geosci. Model Dev., 16, 2851–2871, https://doi.org/10.5194/gmd-16-2851-2023, https://doi.org/10.5194/gmd-16-2851-2023, 2023
Short summary
Short summary
Internal solitary waves (ISWs) play crucial roles in mass transport and ocean mixing in the northern South China Sea. Massive numerical investigations have been conducted in this region, but there was no systematic evaluation of a three-dimensional model about precisely simulating ISWs. Here, an ISW forecasting model is employed to evaluate the roles of resolution, tidal forcing and stratification in accurately reproducing wave properties via comparison to field and remote-sensing observations.
Johannes Bieser, David J. Amptmeijer, Ute Daewel, Joachim Kuss, Anne L. Soerensen, and Corinna Schrum
Geosci. Model Dev., 16, 2649–2688, https://doi.org/10.5194/gmd-16-2649-2023, https://doi.org/10.5194/gmd-16-2649-2023, 2023
Short summary
Short summary
MERCY is a 3D model to study mercury (Hg) cycling in the ocean. Hg is a highly harmful pollutant regulated by the UN Minamata Convention on Mercury due to widespread human emissions. These emissions eventually reach the oceans, where Hg transforms into the even more toxic and bioaccumulative pollutant methylmercury. MERCY predicts the fate of Hg in the ocean and its buildup in the food chain. It is the first model to consider Hg accumulation in fish, a major source of Hg exposure for humans.
Y. Joseph Zhang, Tomas Fernandez-Montblanc, William Pringle, Hao-Cheng Yu, Linlin Cui, and Saeed Moghimi
Geosci. Model Dev., 16, 2565–2581, https://doi.org/10.5194/gmd-16-2565-2023, https://doi.org/10.5194/gmd-16-2565-2023, 2023
Short summary
Short summary
Simulating global ocean from deep basins to coastal areas is a daunting task but is important for disaster mitigation efforts. We present a new 3D global ocean model on flexible mesh to study both tidal and nontidal processes and total water prediction. We demonstrate the potential for
seamlesssimulation, on a single mesh, from the global ocean to a few estuaries along the US West Coast. The model can serve as the backbone of a global tide surge and compound flooding forecasting framework.
Cited articles
Adloff, F., Somot, S., Sevault, F., Jordà, G., Aznar, R., Déqué,
M., Herrmann, M., Marcos, M., Dubois, C., Padorno, E., Alvarez-Fanjul, E.,
and Gomis, D.: Mediterranean Sea response to climate change in an ensemble
of twenty first century scenarios, Clim. Dynam., 45, 2775–2802,
https://doi.org/10.1007/s00382-015-2507-3, 2015.
Adloff, F., Jordà, G., Somot, S., Sevault, F., Arsouze, T., Meyssignac,
B., Li, L., and Planton, S.: Improving sea level simulation in Mediterranean
regional climate models, Clim. Dynam., 51, 1167–1178,
https://doi.org/10.1007/s00382-017-3842-3, 2018.
Aviso+: MDT data, https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/mdt/mdt-global-cnes-cls18.html, last access: 8 March 2022.
Baladrón, A. A., Levier, B., and Sotillo, M. G.: Product User Manual (CMEMS-IBI-PUM-005-002), https://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-IBI-PUM-005-002.pdf (last access: 7 March 2022), 2020.
Barnier, B., Madec, G., Penduff, T., Molines, J.-M., Treguier, A.-M., Le
Sommer, J., Beckmann, A., Biastoch, A., Böning, C., Dengg, J., Derval,
C., Durand, E., Gulev, S., Remy, E., Talandier, C., Theetten, S., Maltrud,
M., McClean, J., and De Cuevas, B.: Impact of partial steps and momentum
advection schemes in a global ocean circulation model at eddy-permitting
resolution, Ocean Dynam., 56, 543–567,
https://doi.org/10.1007/s10236-006-0082-1, 2006.
Berrisford, P., Dee, D., Fielding, K., Fuentes, M., Kallberg, P., Kobayashi,
S., and Uppala, S.: The ERA-Interim Archive, ERA report series, European
Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, 16 pp., https://www.ecmwf.int/node/8173 (last access: 7 March 2022), 2009.
Blanke, B. and Delecluse, P.: Variability of the Tropical Atlantic Ocean
Simulated by a General Circulation Model with Two Different Mixed-Layer
Physics, J. Phys. Oceanogr., 23, 1363–1388,
https://doi.org/10.1175/1520-0485(1993)023<1363:VOTTAO>2.0.CO;2, 1993.
Bozec, A., Lozier, M. S., Chassignet, E. P., and Halliwell, G. R.: On the
variability of the Mediterranean Outflow Water in the North Atlantic from
1948 to 2006, J. Geophys. Res.-Oceans, 116,
https://doi.org/10.1029/2011JC007191, 2011.
Brodeau, L., Barnier, B., Gulev, S. K., and Woods, C.: Climatologically
Significant Effects of Some Approximations in the Bulk Parameterizations of
Turbulent Air–Sea Fluxes, J. Phys. Oceanogr., 47, 5–28,
https://doi.org/10.1175/JPO-D-16-0169.1, 2017.
Chen, X., Zhou, T., Wu, P., Guo, Z., and Wang, M.: Emergent constraints on
future projections of the western North Pacific Subtropical High, Nat.
Commun., 11, 2802, https://doi.org/10.1038/s41467-020-16631-9, 2020.
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, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., et al., Contribution of Working Group I to
the Fifth Assessment Report of the Intergovernmental Panel on Climate
Change, Cambridge University Press, Cambridge, New York, 1137–1216,
2013.
Copernicus: Reanalysis data, https://doi.org/10.48670/moi-00029, last access: 8 March 2022a.
Copernicus: Observational data, https://doi.org/10.48670/moi-00148, last access: 8 March 2022b.
Cordeiro, N. G. F., Dubert, J., Nolasco, R., and Barton, E. D.: Transient
response of the Northwestern Iberian upwelling regime, PLOS ONE, 13,
e0197627, https://doi.org/10.1371/journal.pone.0197627, 2018.
Craig, A., Valcke, S., and Coquart, L.: Development and performance of a new version of the OASIS coupler, OASIS3-MCT_3.0, Geosci. Model Dev., 10, 3297–3308, https://doi.org/10.5194/gmd-10-3297-2017, 2017.
Dosio, A.: Projections of climate change indices of temperature and
precipitation from an ensemble of bias-adjusted high-resolution EURO-CORDEX
regional climate models, J. Geophys. Res.-Atmos., 121, 5488–5511,
https://doi.org/10.1002/2015JD024411, 2016.
ECMWF: IFS documentation – Cy40r1. Operational implementation 22 November 2013, Part IV: Physical processes, https://www.ecmwf.int/en/elibrary/9204-ifs-documentation-cy40r1-part-iv-physical-processes (last access: 7 March 2022), 2014.
ESGF: Historical data, http://esgf-data.dkrz.de/search/cmip6-dkrz/?mip_era=CMIP6&activity_id=CMIP&institution_id=CNRM-CERFACS&source_id=CNRM-CM6-1-HR&experiment_id=historical, last access: 8 March 2022a.
ESGF: piControl data, http://esgf-data.dkrz.de/search/cmip6-dkrz/?mip_era=CMIP6&activity_id=CMIP&institution_id=CNRM-CERFACS&source_id=CNRM-CM6-1-HR&experiment_id=piControl, last access: 8 March 2022b.
ESGF: ssp126 data, http://esgf-data.dkrz.de/search/cmip6-dkrz/?mip_era=CMIP6&activity_id=ScenarioMIP&institution_id=CNRM-CERFACS&source_id=CNRM-CM6-1-HR&experiment_id=ssp126, last access: 8 March 2022c.
ESGF: ssp585 data, http://esgf-data.dkrz.de/search/cmip6-dkrz/?mip_era=CMIP6&activity_id=ScenarioMIP&institution_id=CNRM-CERFACS&source_id=CNRM-CM6-1-HR&experiment_id=ssp585, last access: 8 March 2022d.
Egbert, G. D. and Erofeeva, S. Y.: Efficient Inverse Modeling of Barotropic
Ocean Tides, J. Atmos. Ocean. Technol., 19, 183–204,
https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2, 2002.
Fasullo, J. T.: Evaluating simulated climate patterns from the CMIP archives
using satellite and reanalysis datasets using the Climate Model Assessment
Tool (CMATv1), Geosci. Model Dev., 13, 3627–3642,
https://doi.org/10.5194/gmd-13-3627-2020, 2020.
Flather, R. A. and Davies, A. M.: Note on a preliminary scheme for storm
surge prediction using numerical models, Q. J. Roy. Meteor. Soc., 102,
123–132, https://doi.org/10.1002/qj.49710243110, 1976.
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S. C., Collins,
W., Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P.,
Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., and Rummukainen, M.:
Evaluation of Climate Models, 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
Fofonoff, N. P. and Millard Jr., R. C.: Algorithms for the computation of
fundamental properties of seawater, Unesco techn. pap. mar. sci., 44, 1–53, https://doi.org/10.25607/OBP-1450,
1983.
Forget, G. and Ponte, R. M.: The partition of regional sea level
variability, Prog. Oceanogr., 137, 173–195,
https://doi.org/10.1016/j.pocean.2015.06.002, 2015.
Forster, P., Storelvmo, T., Armour, K., Collins, W., Dufresne, J.-L., Frame,
D., Lunt, D. J., Mauritsen, T., Palmer, M. D., Watanabe, M., Wild, M., and
Zhang, H.: The Earth's Energy Budget, Climate Feedbacks, and Climate
Sensitivity, 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, in press, 2021.
Fox-Kemper, B., Hewitt, H. T., Xiao, C., Aðalgeirsdóttir, 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, in press, 2021.
Garric G. and Parent L.,: Quality Information Document (CMEMS-GLO-QUID-001-025-011-017), https://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-GLO-QUID-001-025-011-017.pdf (last access: 7 March 2022), 2017.
Gaspar, P., Grégoris, Y., and Lefevre, J.-M.: A simple eddy kinetic
energy model for simulations of the oceanic vertical mixing: Tests at
station Papa and long-term upper ocean study site, J. Geophys. Res.-Oceans,
95, 16179–16193, https://doi.org/10.1029/JC095iC09p16179, 1990.
GESLA Version 2: High frequency sea level dataset, https://www.bodc.ac.uk/data/published_data_library/catalogue/10.5285/3b602f74-8374-1e90-e053-6c86abc08d39/, last access: 8 March 2022.
Gomis, D., Álvarez-Fanjul, E., Jordà, G., Marcos, M., Aznar, R.,
Rodríguez-Camino, E., Sánchez-Perrino, J. C.,
Rodríguez-González, J. M., Martínez-Asensio, A., Llasses, J.,
Pérez, B., and Sotillo, M. G.: Regional marine climate scenarios in the
NE Atlantic sector close to the Spanish shores, Sci. Mar., 80, 215–234,
https://doi.org/10.3989/scimar.04328.07A, 2016.
Greatbatch, R. J.: A note on the representation of steric sea level in
models that conserve volume rather than mass, J. Geophys. Res.-Oceans, 99,
12767–12771, https://doi.org/10.1029/94JC00847, 1994.
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. and Greatbatch, R. J.: Physical processes that impact the
evolution of global mean sea level in ocean climate models, Ocean Model.,
51, 37–72, https://doi.org/10.1016/j.ocemod.2012.04.003, 2012.
Grinsted, A. and Christensen, J. H.: The transient sensitivity of sea level rise, Ocean Sci., 17, 181–186, https://doi.org/10.5194/os-17-181-2021, 2021.
Grinsted, A., Jevrejeva, S., Riva, R. E. M., and Dahl-Jensen, D.: Sea level
rise projections for northern Europe under RCP8.5, Clim. Res., 64, 15–23,
https://doi.org/10.3354/cr01309, 2015.
Gupta, A. S., Jourdain, N. C., Brown, J. N., and Monselesan, D.: Climate
Drift in the CMIP5 Models, J. Climate, 26, 8597–8615,
https://doi.org/10.1175/JCLI-D-12-00521.1, 2013.
Hallberg, R.: Using a resolution function to regulate parameterizations of
oceanic mesoscale eddy effects, Ocean Model., 72, 92–103,
https://doi.org/10.1016/j.ocemod.2013.08.007, 2013.
Hermans, T. H. J., Le Bars, D., Katsman, C. A., Camargo, C. M. L., Gerkema,
T., Calafat, F. M., Tinker, J., and Slangen, A. B. A.: Drivers of
Interannual Sea Level Variability on the Northwestern European Shelf, J.
Geophys. Res.-Oceans, 125, e2020JC016325,
https://doi.org/10.1029/2020JC016325, 2020a.
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, 2020b.
Hermans, T. H. J., Gregory, J. M., Palmer, M. D., Ringer, M. A., Katsman, C.
A., and Slangen, A. B. A.: Projecting Global Mean Sea-Level Change Using
CMIP6 Models, Geophys. Res. Lett., 48, e2020GL092064,
https://doi.org/10.1029/2020GL092064, 2021.
Hernández-Díaz, L., Nikiéma, O., Laprise, R., Winger, K., and Dandoy, S.: Effect of empirical correction of sea-surface temperature biases on the CRCM5-simulated climate and projected climate changes over North America, Clim. Dyn., 53, 453–476, https://doi.org/10.1007/s00382-018-4596-2, 2019.
Hock, R., Bliss, A., Marzeion, B., Giesen, R. H., Hirabayashi, Y., Huss, M.,
Radić, V., and Slangen, A. B. A.: GlacierMIP – A model intercomparison
of global-scale glacier mass-balance models and projections, J. Glaciol.,
65, 453–467, https://doi.org/10.1017/jog.2019.22, 2019.
Hui, Y., Xu, Y., Chen, J., Xu, C.-Y., and Chen, H.: Impacts of bias
nonstationarity of climate model outputs on hydrological simulations,
Hydrol. Res., 51, 925–941, https://doi.org/10.2166/nh.2020.254, 2020.
Idier, D., Paris, F., Cozannet, G. L., Boulahya, F., and Dumas, F.:
Sea-level rise impacts on the tides of the European Shelf, Cont. Shelf Res.,
137, 56–71, https://doi.org/10.1016/j.csr.2017.01.007, 2017.
Irving, D., Hobbs, W., Church, J., and Zika, J.: A Mass and Energy
Conservation Analysis of Drift in the CMIP6 Ensemble, J. Climate, 34,
3157–3170, https://doi.org/10.1175/JCLI-D-20-0281.1, 2021.
Jin, Y., Zhang, X., Church, J. A., and Bao, X.: Projected Sea Level Changes
in the Marginal Seas near China Based on Dynamical Downscaling, J. Climate,
34, 7037–7055, https://doi.org/10.1175/JCLI-D-20-0796.1, 2021.
Kirezci, E., Young, I. R., Ranasinghe, R., Muis, S., Nicholls, R. J.,
Lincke, D., and Hinkel, J.: Projections of global-scale extreme sea levels
and resulting episodic coastal flooding over the 21st Century, Sci. Rep.,
10, 11629, https://doi.org/10.1038/s41598-020-67736-6, 2020.
Kopp, R. E., Horton, R. M., Little, C. M., Mitrovica, J. X., Oppenheimer,
M., Rasmussen, D. J., Strauss, B. H., and Tebaldi, C.: Probabilistic 21st
and 22nd century sea-level projections at a global network of tide-gauge
sites, Earths Future, 2, 383–406, https://doi.org/10.1002/2014EF000239,
2014.
Krinner, G. and Flanner, M. G.: Striking stationarity of large-scale climate
model bias patterns under strong climate change, P. Natl. Acad. Sci. USA, 115, 9462–9466, https://doi.org/10.1073/pnas.1807912115, 2018.
Lavergne, C. de, Vic, C., Madec, G., Roquet, F., Waterhouse, A. F., Whalen,
C. B., Cuypers, Y., Bouruet-Aubertot, P., Ferron, B., and Hibiya, T.: A
Parameterization of Local and Remote Tidal Mixing, J. Adv. Model. Earth
Syst., 12, e2020MS002065, https://doi.org/10.1029/2020MS002065, 2020.
Lee, J.-Y., Marotzke, J., Bala, G., Cao, L., Corti, S., Dunne, J. P.,
Engelbrecht, F., Fischer, E., Fyfe, J. C., Jones, C., Maycock, A., Mutemi,
J., Ndiaye, O., Panickal, S., and Zhou, T.: Future Global Climate:
Scenario-Based Projections and Near-Term Information, 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,
in press, 2021.
Leonard, B. P.: A stable and accurate convective modelling procedure based
on quadratic upstream interpolation, Comput. Methods Appl. Mech. Eng., 19,
59–98, https://doi.org/10.1016/0045-7825(79)90034-3, 1979.
Levier, B., Lorente, P., and Reffray, G., Sotillo M.: Quality Information Document (CMEMS-IBI-QUID-005-002), https://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-IBI-QUID-005-002.pdf (last access: 7 March 2022), 2020.
Liu, Z.-J., Minobe, S., Sasaki, Y. N., and Terada, M.: Dynamical downscaling
of future sea level change in the western North Pacific using ROMS, J.
Oceanogr., 72, 905–922, https://doi.org/10.1007/s10872-016-0390-0, 2016.
Lyard, F., Lefevre, F., Letellier, T., and Francis, O.: Modelling the global
ocean tides: modern insights from FES2004, Ocean. Dynam., 56, 394–415,
https://doi.org/10.1007/s10236-006-0086-x, 2006.
Macias, D., Garcia-Gorriz, E., Dosio, A., Stips, A., and Keuler, K.:
Obtaining the correct sea surface temperature: bias correction of regional
climate model data for the Mediterranean Sea, Clim. Dynam., 51, 1095–1117,
https://doi.org/10.1007/s00382-016-3049-z, 2018.
Madec, G., Bourdallé-Badie, R., Bouttier, P.-A., Bricaud, C.,
Bruciaferri, D., Calvert, D., Chanut, J., Clementi, E., Coward, A.,
Delrosso, D., Ethé, C., Flavoni, S., Graham, T., Harle, J., Iovino, D.,
Lea, D., Lévy, C., Lovato, T., Martin, N., Masson, S., Mocavero, S.,
Paul, J., Rousset, C., Storkey, D., Storto, A., and Vancoppenolle, M.: NEMO
ocean engine, Zenodo [code], https://doi.org/10.5281/zenodo.3248739, 2017.
Maraldi, C., Chanut, J., Levier, B., Ayoub, N., De Mey, P., Reffray, G., Lyard, F., Cailleau, S., Drévillon, M., Fanjul, E. A., Sotillo, M. G., Marsaleix, P., and the Mercator Research and Development Team: NEMO on the shelf: assessment of the Iberia–Biscay–Ireland configuration, Ocean Sci., 9, 745–771, https://doi.org/10.5194/os-9-745-2013, 2013.
Maraun, D.: Nonstationarities of regional climate model biases in European
seasonal mean temperature and precipitation sums, Geophys. Res. Lett., 39, L06706, https://doi.org/10.1029/2012GL051210, 2012.
Mathis, M., Mayer, B., and Pohlmann, T.: An uncoupled dynamical downscaling
for the North Sea: Method and evaluation, Ocean Model., 72, 153–166,
https://doi.org/10.1016/j.ocemod.2013.09.004, 2013.
McGranahan, G., Balk, D., and Anderson, B.: The rising tide: assessing the
risks of climate change and human settlements in low elevation coastal
zones, Environ. Urban., 19, 17–37,
https://doi.org/10.1177/0956247807076960, 2007.
Melet, A., Meyssignac, B., Almar, R., and Le Cozannet, G.: Under-estimated
wave contribution to coastal sea-level rise, Nat. Clim. Change, 8, 234–239,
https://doi.org/10.1038/s41558-018-0088-y, 2018.
Melet, A., Almar, R., Hemer, M., Cozannet, G. L., Meyssignac, B., and
Ruggiero, P.: Contribution of Wave Setup to Projected Coastal Sea Level
Changes, J. Geophys. Res.-Oceans, 125, e2020JC016078,
https://doi.org/10.1029/2020JC016078, 2020.
Menéndez, M. and Woodworth, P. L.: Changes in extreme high water levels
based on a quasi-global tide-gauge data set, J. Geophys. Res., 115, C10011, https://doi.org/10.1029/2009JC005997, 2010.
Meyssignac, B., Piecuch, C. G., Merchant, C. J., Racault, M.-F., Palanisamy,
H., MacIntosh, C., Sathyendranath, S., and Brewin, R.: Causes of the
Regional Variability in Observed Sea Level, Sea Surface Temperature and
Ocean Colour Over the Period 1993–2011, Surv. Geophys., 38, 187–215,
https://doi.org/10.1007/s10712-016-9383-1, 2017a.
Meyssignac, B., Slangen, A. B. A., Melet, A., Church, J. A., Fettweis, X.,
Marzeion, B., Agosta, C., Ligtenberg, S. R. M., Spada, G., Richter, K.,
Palmer, M. D., Roberts, C. D., and Champollion, N.: Evaluating Model
Simulations of Twentieth-Century Sea-Level Rise. Part II: Regional Sea-Level
Changes, J. Climate, 30, 8565–8593, https://doi.org/10.1175/JCLI-D-17-0112.1,
2017b.
Muis, S., Apecechea, M. I., Dullaart, J., de Lima Rego, J., Madsen, K. S.,
Su, J., Yan, K., and Verlaan, M.: A High-Resolution Global Dataset of
Extreme Sea Levels, Tides, and Storm Surges, Including Future Projections,
Front. Mar. Sci., 7, 263, https://doi.org/10.3389/fmars.2020.00263, 2020.
Mulet, S., Rio, M.-H., Etienne, H., Artana, C., Cancet, M., Dibarboure, G., Feng, H., Husson, R., Picot, N., Provost, C., and Strub, P. T.: The new CNES-CLS18 global mean dynamic topography, Ocean Sci., 17, 789–808, https://doi.org/10.5194/os-17-789-2021, 2021.
Nahar, J., Johnson, F., and Sharma, A.: Assessing the extent of
non-stationary biases in GCMs, J. Hydrol., 549, 148–162,
https://doi.org/10.1016/j.jhydrol.2017.03.045, 2017.
NEMO: code, https://www.nemo-ocean.eu/, last access: 8 March 2022.
Neumann, B., Vafeidis, A. T., Zimmermann, J., and Nicholls, R. J.: Future
Coastal Population Growth and Exposure to Sea-Level Rise and Coastal
Flooding – A Global Assessment, PLOS ONE, 10, e0118571,
https://doi.org/10.1371/journal.pone.0118571, 2015.
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., Meehl, G. A., Moss, R., Riahi, K., and Sanderson, B. M.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016.
Oppenheimer, M., Glavovic, B. C., Hinkel, J., van de Wal, R., Magnan, A. K.,
Abd-Elgawad, A., Cai, R., Cifuentes-Jara, M., DeConto, R. M., Ghosh, T., Hay,
J., Isla, F., Marzeion, B., Meyssignac, B., and Sebesvari, Z.: Sea Level
Rise and Implications for Low-Lying Islands, Coasts and Communities, in: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H.-O., Roberts, D. C., Masson-Delmotte, V., Zhai, P., Tignor, M.,
Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A.,
Petzold, J., Rama, B., and Weyer, N. M., in press, 2019
Pujol, M. and Mertz, F.: Product User Manual, available at: https://catalogue.marine.copernicus.eu/documents/PUM/CMEMS-SL-PUM-008-032-062.pdf (last access: 7 March 2022), 2020.
Reffray, G., Bourdalle-Badie, R., and Calone, C.: Modelling turbulent vertical mixing sensitivity using a 1-D version of NEMO, Geosci. Model Dev., 8, 69–86, https://doi.org/10.5194/gmd-8-69-2015, 2015.
Richter, K., Riva, R. E. M., and Drange, H.: Impact of self-attraction and
loading effects induced by shelf mass loading on projected regional sea
level rise, Geophys. Res. Lett., 40, 1144–1148,
https://doi.org/10.1002/grl.50265, 2013.
Roehrig, R., Beau, I., Saint-Martin, D., Alias, A., Decharme, B.,
Guérémy, J.-F., Voldoire, A., Abdel-Lathif, A. Y., Bazile, E.,
Belamari, S., Blein, S., Bouniol, D., Bouteloup, Y., Cattiaux, J., Chauvin,
F., Chevallier, M., Colin, J., Douville, H., Marquet, P., Michou, M., Nabat,
P., Oudar, T., Peyrillé, P., Piriou, J.-M., Salas y Mélia, D.,
Séférian, R., and Sénési, S.: The CNRM Global Atmosphere
Model ARPEGE-Climat 6.3: Description and Evaluation, J. Adv. Model. Earth
Syst., 12, e2020MS002075, https://doi.org/10.1029/2020MS002075, 2020.
Roquet, F., Madec, G., Brodeau, L., and Nycander, J.: Defining a Simplified
Yet “Realistic” Equation of State for Seawater, J. Phys. Oceanogr., 45,
2564–2579, https://doi.org/10.1175/JPO-D-15-0080.1, 2015.
Shin, S.-I. and Alexander, M. A.: Dynamical Downscaling of Future
Hydrographic Changes over the Northwest Atlantic Ocean, J. Climate, 33,
2871–2890, https://doi.org/10.1175/JCLI-D-19-0483.1, 2020.
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, Clim. Change, 124, 317–332,
https://doi.org/10.1007/s10584-014-1080-9, 2014.
Slangen, A. B. A., Meyssignac, B., Agosta, C., Champollion, N., Church, J.
A., Fettweis, X., Ligtenberg, S. R. M., Marzeion, B., Melet, A., Palmer, M.
D., Richter, K., Roberts, C. D., and Spada, G.: Evaluating Model Simulations
of Twentieth-Century Sea Level Rise. Part I: Global Mean Sea Level Change,
J. Climate, 30, 8539–8563, https://doi.org/10.1175/JCLI-D-17-0110.1, 2017.
Sotillo, M. G., Cailleau, S., Lorente, P., Levier, B., Aznar, R., Reffray,
G., Amo-Baladrón, A., Chanut, J., Benkiran, M., and Alvarez-Fanjul, E.:
The MyOcean IBI Ocean Forecast and Reanalysis Systems: operational products
and roadmap to the future Copernicus Service, J. Oper. Oceanogr., 8, 63–79,
https://doi.org/10.1080/1755876X.2015.1014663, 2015.
Soto-Navarro, J., Criado-Aldeanueva, F., García-Lafuente, J., and
Sánchez-Román, A.: Estimation of the Atlantic inflow through the
Strait of Gibraltar from climatological and in situ data, J. Geophys. Res., 115, C10023, https://doi.org/10.1029/2010JC006302, 2010.
Soto-Navarro, J., Somot, S., Sevault, F., Beuvier, J., Criado-Aldeanueva,
F., García-Lafuente, J., and Béranger, K.: Evaluation of regional
ocean circulation models for the Mediterranean Sea at the Strait of
Gibraltar: volume transport and thermohaline properties of the outflow,
Clim. Dynam., 44, 1277–1292, https://doi.org/10.1007/s00382-014-2179-4, 2015.
Soto-Navarro, J., Jordá, G., Amores, A., Cabos, W., Somot, S., Sevault,
F., Macías, D., Djurdjevic, V., Sannino, G., Li, L., and Sein, D.:
Evolution of Mediterranean Sea water properties under climate change
scenarios in the Med-CORDEX ensemble, Clim. Dynam., 54, 2135–2165,
https://doi.org/10.1007/s00382-019-05105-4, 2020.
Stammer, D. and Hüttemann, S.: Response of Regional Sea Level to
Atmospheric Pressure Loading in a Climate Change Scenario, J. Climate, 21,
2093–2101, https://doi.org/10.1175/2007JCLI1803.1, 2008.
Taburet, G. and Pujol, M.: Quality Information Document (CMEMS-SL-QUID-008-032-062), https://catalogue.marine.copernicus.eu/documents/QUID/CMEMS-SL-QUID-008-032-062.pdf (last access: 7 March 2022), 2021.
Takayabu, I., Kanamaru, H., Dairaku, K., Benestad, R., Storch, H. von, and
Christensen, J. H.: Reconsidering the Quality and Utility of Downscaling, J.
Meteorol. Soc. Jpn. Ser II, 94A, 31–45,
https://doi.org/10.2151/jmsj.2015-042, 2016.
Umlauf, L. and Burchard, H.: A generic length-scale equation for geophysical
turbulence models, J. Mar. Res., 61, 235–265,
https://doi.org/10.1357/002224003322005087, 2003.
Voldoire, A.: CMIP6 simulations of the CNRM-CERFACS based on CNRM-CM6-1 model for CMIP experiment historical, Version YYYYMMDD[1], Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4066, 2018.
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6 CMIP historical, Version YYYYMMDD[1], Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4067, 2019a.
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6 CMIP piControl, Version YYYYMMDD[1], Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4164, 2019b.
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6 ScenarioMIP ssp585, Version YYYYMMDD[1], Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4225, 2019c.
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6 ScenarioMIP ssp126, Version YYYYMMDD[1], Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4185, 2020a.
Voldoire, A.: River to ocean models interpolation, report, CNRM,
Université de Toulouse, Météo-France, CNRS, https://hal-meteofrance.archives-ouvertes.fr/meteo-02986574/document, (last access: 7 March 2022), 2020.
Voldoire, A., Saint-Martin, D., Sénési, S., Decharme, B., Alias, A.,
Chevallier, M., Colin, J., Guérémy, J.-F., Michou, M., Moine, M.-P.,
Nabat, P., Roehrig, R., Salas y Mélia, D., Séférian, R., Valcke,
S., Beau, I., Belamari, S., Berthet, S., Cassou, C., Cattiaux, J., Deshayes,
J., Douville, H., Ethé, C., Franchistéguy, L., Geoffroy, O.,
Lévy, C., Madec, G., Meurdesoif, Y., Msadek, R., Ribes, A.,
Sanchez-Gomez, E., Terray, L., and Waldman, R.: Evaluation of CMIP6 DECK
Experiments With CNRM-CM6-1, J. Adv. Model. Earth Syst., 11, 2177–2213,
https://doi.org/10.1029/2019MS001683, 2019.
Vousdoukas, M. I., Mentaschi, L., Voukouvalas, E., Bianchi, A., Dottori, F.,
and Feyen, L.: Climatic and socioeconomic controls of future coastal flood
risk in Europe, Nat. Clim. Change, 8, 776–780,
https://doi.org/10.1038/s41558-018-0260-4, 2018a.
Vousdoukas, M. I., Mentaschi, L., Voukouvalas, E., Verlaan, M., Jevrejeva,
S., Jackson, L. P., and Feyen, L.: Global probabilistic projections of
extreme sea levels show intensification of coastal flood hazard, Nat.
Commun., 9, 2360, https://doi.org/10.1038/s41467-018-04692-w, 2018b.
van Westen, R. M., Dijkstra, H. A., van der Boog, C. G., Katsman, C. A.,
James, R. K., Bouma, T. J., Kleptsova, O., Klees, R., Riva, R. E. M.,
Slobbe, D. C., Zijlema, M., and Pietrzak, J. D.: Ocean model resolution
dependence of Caribbean sea-level projections, Sci. Rep., 10, 14599,
https://doi.org/10.1038/s41598-020-71563-0, 2020.
Woodworth, P. L., Hunter, J. R., Marcos, M., Caldwell, P., Menéndez, M.,
and Haigh, I.: Towards a global higher-frequency sea level dataset, Geosci.
Data J. [data set], 3, 50–59, https://doi.org/10.1002/gdj3.42, 2017.
Woodworth, P. L., Melet, A., Marcos, M., Ray, R. D., Wöppelmann, G.,
Sasaki, Y. N., Cirano, M., Hibbert, A., Huthnance, J. M., Monserrat, S., and
Merrifield, M. A.: Forcing Factors Affecting Sea Level Changes at the Coast,
Surv. Geophys., 40, 1351–1397, https://doi.org/10.1007/s10712-019-09531-1,
2019.
Xu, Z., Han, Y., and Yang, Z.: Dynamical downscaling of regional climate: A
review of methods and limitations, Sci. China Earth Sci., 62, 365–375,
https://doi.org/10.1007/s11430-018-9261-5, 2019.
Zalesak, S. T.: Fully multidimensional flux-corrected transport algorithms
for fluids, J. Comput. Phys., 31, 335–362,
https://doi.org/10.1016/0021-9991(79)90051-2, 1979.
Zhang, X., Church, J. A., Monselesan, D., and McInnes, K. L.: Sea level
projections for the Australian region in the 21st century, Geophys. Res.
Lett., 44, 8481–8491, https://doi.org/10.1002/2017GL074176, 2017.
Short summary
Climate-change-induced sea level rise is a major threat for coastal and low-lying regions. Projections of coastal sea level changes are thus of great interest for coastal risk assessment and have significantly developed in recent years. In this paper, the objective is to provide high-resolution (6 km) projections of sea level changes in the northeastern Atlantic region bordering western Europe. For that purpose, a regional model is used to refine existing coarse global projections.
Climate-change-induced sea level rise is a major threat for coastal and low-lying regions....
