Articles | Volume 20, issue 3
https://doi.org/10.5194/os-20-835-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-20-835-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Jun 2024
Research article |
| 21 Jun 2024
| 21 Jun 2024
Twenty-first century marine climate projections for the NW European shelf seas based on a perturbed parameter ensemble
Jonathan Tinker
CORRESPONDING AUTHOR
Met Office, Exeter, EX1 3PB, UK
Matthew D. Palmer
Met Office, Exeter, EX1 3PB, UK
School of Earth Sciences, University of Bristol, UK
Benjamin J. Harrison
Met Office, Exeter, EX1 3PB, UK
Enda O'Dea
Met Office, Exeter, EX1 3PB, UK
Met Éireann, Dublin, D09 Y921, Ireland
David M. H. Sexton
Met Office, Exeter, EX1 3PB, UK
Kuniko Yamazaki
Met Office, Exeter, EX1 3PB, UK
John W. Rostron
Met Office, Exeter, EX1 3PB, UK
Related authors
Jonathan Tinker, Justin Krijnen, Richard Wood, Rosa Barciela, and Stephen R. Dye
Ocean Sci., 14, 887–909, https://doi.org/10.5194/os-14-887-2018, https://doi.org/10.5194/os-14-887-2018, 2018
Short summary
Short summary
We consider the prospects for seasonal forecasts for the North-west European Shelf (NWS) seas. The recent maturation of global seasonal forecast systems and NWS marine reanalyses provide a basis for such forecasts. We assess the potential of three possible approaches: direct use of global forecast fields and empirical and dynamical downscaling. We conclude that there is potential for NWS seasonal forecasts and as an example show a skillful prototype SST forecast for the English Channel.
Heather Cannaby, Matthew D. Palmer, Tom Howard, Lucy Bricheno, Daley Calvert, Justin Krijnen, Richard Wood, Jonathan Tinker, Chris Bunney, James Harle, Andrew Saulter, Clare O'Neill, Clare Bellingham, and Jason Lowe
Ocean Sci., 12, 613–632, https://doi.org/10.5194/os-12-613-2016, https://doi.org/10.5194/os-12-613-2016, 2016
Short summary
Short summary
The Singapore government commissioned a modelling study of regional projections of changes in (i) long-term mean sea level and (ii) the frequency of extreme storm surge and wave events. We find that changes to long-term mean sea level constitute the dominant signal of change to the projected inundation risk for Singapore during the 21st century, these being 0.52 m(0.74 m) under the RCP 4.5(8.5) scenario.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Bradley Hall, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan P. Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Blair Trewin, Myles Allen, Robbie Andrew, Richard A. Betts, Alex Borger, Tim Boyer, Jiddu A. Broersma, Carlo Buontempo, Samantha Burgess, Chiara Cagnazzo, Lijing Cheng, Pierre Friedlingstein, Andrew Gettelman, Johannes Gütschow, Masayoshi Ishii, Stuart Jenkins, Xin Lan, Colin Morice, Jens Mühle, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Jan C. Minx, Gunnar Myhre, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, Sophie Szopa, Peter Thorne, Mahesh V. M. Kovilakam, Elisa Majamäki, Jukka-Pekka Jalkanen, Margreet van Marle, Rachel M. Hoesly, Robert Rohde, Dominik Schumacher, Guido van der Werf, Russell Vose, Kirsten Zickfeld, Xuebin Zhang, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 16, 2625–2658, https://doi.org/10.5194/essd-16-2625-2024, https://doi.org/10.5194/essd-16-2625-2024, 2024
Short summary
Short summary
This paper tracks some key indicators of global warming through time, from 1850 through to the end of 2023. It is designed to give an authoritative estimate of global warming to date and its causes. We find that in 2023, global warming reached 1.3 °C and is increasing at over 0.2 °C per decade. This is caused by all-time-high greenhouse gas emissions.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
Short summary
Short summary
Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Leighton A. Regayre, Lucia Deaconu, Daniel P. Grosvenor, David M. H. Sexton, Christopher Symonds, Tom Langton, Duncan Watson-Paris, Jane P. Mulcahy, Kirsty J. Pringle, Mark Richardson, Jill S. Johnson, John W. Rostron, Hamish Gordon, Grenville Lister, Philip Stier, and Ken S. Carslaw
Atmos. Chem. Phys., 23, 8749–8768, https://doi.org/10.5194/acp-23-8749-2023, https://doi.org/10.5194/acp-23-8749-2023, 2023
Short summary
Short summary
Aerosol forcing of Earth’s energy balance has persisted as a major cause of uncertainty in climate simulations over generations of climate model development. We show that structural deficiencies in a climate model are exposed by comprehensively exploring parametric uncertainty and that these deficiencies limit how much the model uncertainty can be reduced through observational constraint. This provides a future pathway towards building models with greater physical realism and lower uncertainty.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
Short summary
Short summary
This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Leighton A. Regayre, Lucia Deaconu, Daniel P. Grosvenor, David Sexton, Christopher C. Symonds, Tom Langton, Duncan Watson-Paris, Jane P. Mulcahy, Kirsty J. Pringle, Mark Richardson, Jill S. Johnson, John Rostron, Hamish Gordon, Grenville Lister, Philip Stier, and Ken S. Carslaw
EGUsphere, https://doi.org/10.5194/egusphere-2022-1330, https://doi.org/10.5194/egusphere-2022-1330, 2022
Preprint archived
Short summary
Short summary
We show that potential structural deficiencies in a climate model can be exposed by comprehensively exploring its parametric uncertainty, and that these deficiencies limit how much the model uncertainty can be reduced through observational constraint. Combined consideration of parametric and structural uncertainties provides a future pathway towards building models that have greater physical realism and lower uncertainty.
Amy H. Peace, Ben B. B. Booth, Leighton A. Regayre, Ken S. Carslaw, David M. H. Sexton, Céline J. W. Bonfils, and John W. Rostron
Earth Syst. Dynam., 13, 1215–1232, https://doi.org/10.5194/esd-13-1215-2022, https://doi.org/10.5194/esd-13-1215-2022, 2022
Short summary
Short summary
Anthropogenic aerosol emissions have been linked to driving climate responses such as shifts in the location of tropical rainfall. However, the interaction of aerosols with climate remains one of the most uncertain aspects of climate modelling and limits our ability to predict future climate change. We use an ensemble of climate model simulations to investigate what impact the large uncertainty in how aerosols interact with climate has on predicting future tropical rainfall shifts.
Shipra Jain, Ruth M. Doherty, David Sexton, Steven Turnock, Chaofan Li, Zixuan Jia, Zongbo Shi, and Lin Pei
Atmos. Chem. Phys., 22, 7443–7460, https://doi.org/10.5194/acp-22-7443-2022, https://doi.org/10.5194/acp-22-7443-2022, 2022
Short summary
Short summary
We provide a range of future projections of winter haze and clear conditions over the North China Plain (NCP) using multiple simulations from a climate model for the high-emission scenario (RCP8.5). The frequency of haze conducive weather is likely to increase whereas the frequency of clear weather is likely to decrease in future. The total number of hazy days for a given winter can be as much as ˜3.5 times higher than the number of clear days over the NCP.
Jie Zhang, Kalli Furtado, Steven T. Turnock, Jane P. Mulcahy, Laura J. Wilcox, Ben B. Booth, David Sexton, Tongwen Wu, Fang Zhang, and Qianxia Liu
Atmos. Chem. Phys., 21, 18609–18627, https://doi.org/10.5194/acp-21-18609-2021, https://doi.org/10.5194/acp-21-18609-2021, 2021
Short summary
Short summary
The CMIP6 ESMs systematically underestimate TAS anomalies in the NH midlatitudes, especially from 1960 to 1990. The anomalous cooling is concurrent in time and space with anthropogenic SO2 emissions. The spurious drop in TAS is attributed to the overestimated aerosol concentrations. The aerosol forcing sensitivity cannot well explain the inter-model spread of PHC biases. And the cloud-amount term accounts for most of the inter-model spread in aerosol forcing sensitivity.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
Short summary
Short summary
Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Jill S. Johnson, Leighton A. Regayre, Masaru Yoshioka, Kirsty J. Pringle, Steven T. Turnock, Jo Browse, David M. H. Sexton, John W. Rostron, Nick A. J. Schutgens, Daniel G. Partridge, Dantong Liu, James D. Allan, Hugh Coe, Aijun Ding, David D. Cohen, Armand Atanacio, Ville Vakkari, Eija Asmi, and Ken S. Carslaw
Atmos. Chem. Phys., 20, 9491–9524, https://doi.org/10.5194/acp-20-9491-2020, https://doi.org/10.5194/acp-20-9491-2020, 2020
Short summary
Short summary
We use over 9000 monthly aggregated grid-box measurements of aerosol to constrain the uncertainty in the HadGEM3-UKCA climate model. Measurements of AOD, PM2.5, particle number concentrations, sulfate and organic mass concentrations are compared to 1 million
variantsof the model using an implausibility metric. Despite many compensating effects in the model, the procedure constrains the probability distributions of many parameters, and direct radiative forcing uncertainty is reduced by 34 %.
Jill S. Johnson, Leighton A. Regayre, Masaru Yoshioka, Kirsty J. Pringle, Lindsay A. Lee, David M. H. Sexton, John W. Rostron, Ben B. B. Booth, and Kenneth S. Carslaw
Atmos. Chem. Phys., 18, 13031–13053, https://doi.org/10.5194/acp-18-13031-2018, https://doi.org/10.5194/acp-18-13031-2018, 2018
Short summary
Short summary
We estimate the uncertainty in an aerosol–climate model that has been tuned to match several common types of observations. We used a large set of model simulations and built emulators so that we could generate 4 million “variants” of our climate model. Even after using nine aerosol and cloud observations to constrain the model, the uncertainty remains large. We conclude that estimates of aerosol forcing from multi-model studies are likely to be more uncertain than currently estimated.
Jonathan Tinker, Justin Krijnen, Richard Wood, Rosa Barciela, and Stephen R. Dye
Ocean Sci., 14, 887–909, https://doi.org/10.5194/os-14-887-2018, https://doi.org/10.5194/os-14-887-2018, 2018
Short summary
Short summary
We consider the prospects for seasonal forecasts for the North-west European Shelf (NWS) seas. The recent maturation of global seasonal forecast systems and NWS marine reanalyses provide a basis for such forecasts. We assess the potential of three possible approaches: direct use of global forecast fields and empirical and dynamical downscaling. We conclude that there is potential for NWS seasonal forecasts and as an example show a skillful prototype SST forecast for the English Channel.
Leighton A. Regayre, Jill S. Johnson, Masaru Yoshioka, Kirsty J. Pringle, David M. H. Sexton, Ben B. B. Booth, Lindsay A. Lee, Nicolas Bellouin, and Kenneth S. Carslaw
Atmos. Chem. Phys., 18, 9975–10006, https://doi.org/10.5194/acp-18-9975-2018, https://doi.org/10.5194/acp-18-9975-2018, 2018
Short summary
Short summary
We sample uncertainty in one climate model by perturbing aerosol and physical atmosphere parameters. Our uncertainty is comparable to multi-model studies. Atmospheric parameters cause most of the top-of-atmosphere flux uncertainty; uncertainty in aerosol forcing is mostly caused by aerosols: both are important. The strongest aerosol forcings are inconsistent with top-of-atmosphere flux observations. Better constraint requires observations that share causes of uncertainty with aerosol forcing.
Simon F. B. Tett, Kuniko Yamazaki, Michael J. Mineter, Coralia Cartis, and Nathan Eizenberg
Geosci. Model Dev., 10, 3567–3589, https://doi.org/10.5194/gmd-10-3567-2017, https://doi.org/10.5194/gmd-10-3567-2017, 2017
Short summary
Short summary
The paper shows it is possible to automatically calibrate the parameters in the atmospheric component of two climate models. The resulting atmosphere–ocean models are often, but not always, stable and realistic. The computational cost to do this is feasible. The implications are that it is possible to generate multiple configurations of a single model with different parameter values but which all look similar to the standard model and that the techniques could be used to calibrate other models.
Doug McNeall, Jonny Williams, Ben Booth, Richard Betts, Peter Challenor, Andy Wiltshire, and David Sexton
Earth Syst. Dynam., 7, 917–935, https://doi.org/10.5194/esd-7-917-2016, https://doi.org/10.5194/esd-7-917-2016, 2016
Short summary
Short summary
We compare simulated with observed forests to constrain uncertain input parameters of the land surface component of a climate model.
We find that the model is unlikely to be able to simulate the Amazon and other major forests simultaneously at any one parameter set, suggesting a bias in the model's representation of the Amazon.
We find we cannot constrain parameters individually, but we can rule out large areas of joint parameter space.
Lijing Cheng, Kevin E. Trenberth, Matthew D. Palmer, Jiang Zhu, and John P. Abraham
Ocean Sci., 12, 925–935, https://doi.org/10.5194/os-12-925-2016, https://doi.org/10.5194/os-12-925-2016, 2016
Short summary
Short summary
A new method of observing ocean heat content throughout the entire ocean depth is provided. The new method is compared with simulated ocean heat content changes from climate models. The comparisons are carried out in various depth layers of the ocean waters. It is found that there is excellent agreement between the models and the observations. Furthermore, we propose that changes to ocean heat content be used as a fundamental metric to evaluate climate models.
Heather Cannaby, Matthew D. Palmer, Tom Howard, Lucy Bricheno, Daley Calvert, Justin Krijnen, Richard Wood, Jonathan Tinker, Chris Bunney, James Harle, Andrew Saulter, Clare O'Neill, Clare Bellingham, and Jason Lowe
Ocean Sci., 12, 613–632, https://doi.org/10.5194/os-12-613-2016, https://doi.org/10.5194/os-12-613-2016, 2016
Short summary
Short summary
The Singapore government commissioned a modelling study of regional projections of changes in (i) long-term mean sea level and (ii) the frequency of extreme storm surge and wave events. We find that changes to long-term mean sea level constitute the dominant signal of change to the projected inundation risk for Singapore during the 21st century, these being 0.52 m(0.74 m) under the RCP 4.5(8.5) scenario.
Related subject area
Approach: Numerical Models | Properties and processes: Climate and modes of variability
Exploring variability in climate change projections on the Nemunas River and Curonian Lagoon: coupled SWAT and SHYFEM modeling approach
An assessment of equatorial Atlantic interannual variability in Ocean Model Intercomparison Project (OMIP) simulations
Predictability of marine heatwaves: assessment based on the ECMWF seasonal forecast system
The Mediterranean Forecasting System – Part 1: Evolution and performance
Natalja Čerkasova, Jovita Mėžinė, Rasa Idzelytė, Jūratė Lesutienė, Ali Ertürk, and Georg Umgiesser
Ocean Sci., 20, 1123–1147, https://doi.org/10.5194/os-20-1123-2024, https://doi.org/10.5194/os-20-1123-2024, 2024
Short summary
Short summary
This study advances the understanding of climate projection variability in the Nemunas River, Curonian Lagoon, and southeastern Baltic Sea continuum by analyzing a subset of climate models with a focus on a coupled ocean and drainage basin model. This study investigates the variability and trends in environmental parameters, such as water fluxes, timing, nutrient load, water temperature, ice cover, and saltwater intrusions in Representative Concentration Pathway 4.5 and 8.5 scenarios.
Arthur Prigent and Riccardo Farneti
Ocean Sci., 20, 1067–1086, https://doi.org/10.5194/os-20-1067-2024, https://doi.org/10.5194/os-20-1067-2024, 2024
Short summary
Short summary
We evaluate the eastern equatorial Atlantic's (EEA's) seasonal cycle and interannual variability in the Ocean Model Intercomparison Project Phases 1 and 2 (OMIP1 and OMIP2) for 1985–2004. While both simulate EEA patterns, biases like a diffusive thermocline and insufficient cooling exist during the development of the Atlantic cold tongue. OMIP1 exhibits 51% (33%) larger interannual sea surface temperature (sea surface height) variability than OMIP2, attributed to differences in wind forcing.
Eric de Boisséson and Magdalena Alonso Balmaseda
Ocean Sci., 20, 265–278, https://doi.org/10.5194/os-20-265-2024, https://doi.org/10.5194/os-20-265-2024, 2024
Short summary
Short summary
Marine heatwaves are long periods of extremely warm ocean surface temperatures. Predicting such events a few months in advance would help decision-making to mitigate their impacts on marine ecosystems. This work investigates how well operational seasonal forecasts can predict marine heatwaves. Results show that such events can be predicted a few months in advance in the tropics but that extending the predictability skill to other regions will require additional work on the forecast models.
Giovanni Coppini, Emanuela Clementi, Gianpiero Cossarini, Stefano Salon, Gerasimos Korres, Michalis Ravdas, Rita Lecci, Jenny Pistoia, Anna Chiara Goglio, Massimiliano Drudi, Alessandro Grandi, Ali Aydogdu, Romain Escudier, Andrea Cipollone, Vladyslav Lyubartsev, Antonio Mariani, Sergio Cretì, Francesco Palermo, Matteo Scuro, Simona Masina, Nadia Pinardi, Antonio Navarra, Damiano Delrosso, Anna Teruzzi, Valeria Di Biagio, Giorgio Bolzon, Laura Feudale, Gianluca Coidessa, Carolina Amadio, Alberto Brosich, Arnau Miró, Eva Alvarez, Paolo Lazzari, Cosimo Solidoro, Charikleia Oikonomou, and Anna Zacharioudaki
Ocean Sci., 19, 1483–1516, https://doi.org/10.5194/os-19-1483-2023, https://doi.org/10.5194/os-19-1483-2023, 2023
Short summary
Short summary
The paper presents the Mediterranean Forecasting System evolution and performance developed in the framework of the Copernicus Marine Service.
Cited articles
Andrews, T., Andrews, M. B., Bodas-Salcedo, A., Jones, G. S., Kuhlbrodt, T., Manners, J., Menary, M. B., Ridley, J., Ringer, M. A., Sellar, A. A., Senior, C. A., and Tang, Y.: Forcings, Feedbacks, and Climate Sensitivity in HadGEM3-GC3.1 and UKESM1, J. Adv. Model. Earth Sy., 11, 4377–4394, https://doi.org/10.1029/2019MS001866, 2019.
Betts, R. A., Haward, A. B., and Pearson, K. V.: UK Climate Change Risk Assessment (CCRA3) Technical Report, Prepared for the Climate Change Committee, London, 1478 pp., https://www.ukclimaterisk.org/wp-content/uploads/2021/06/Technical-Report-The-Third-Climate-Change-Risk-Assessment.pdf (last access: 4 June 2024), 2021.
Boulahia, A. K., García-García, D., Vigo, M. I., Trottini, M., and Sayol, J.-M.: The Water Cycle of the Baltic Sea Region From GRACE/GRACE-FO Missions and ERA5 Data, Front. Earth Sci., 10, 879148, https://doi.org/10.3389/feart.2022.879148, 2022.
Brown, J., Hill, A. E., Fernand, L., and Horsburgh, K. J.: Observations of a seasonal jet-like circulation at the central North Sea cold pool margin, Estuar. Coast. Shelf S., 48, 343–355, 1999.
Bruciaferri, D., Shapiro, G. I., and Wobus, F.: A multi-envelope vertical coordinate system for numerical ocean modelling, Ocean Dynam., 68, 1239–1258, https://doi.org/10.1007/s10236-018-1189-x, 2018.
Bruciaferri, D., Tonani, M., Lewis, H. W., Siddorn, J. R., Saulter, A., Castillo Sanchez, J. M., Valiente, N. G., Conley, D., Sykes, P., Ascione, I., and McConnell, N.: The Impact of Ocean-Wave Coupling on the Upper Ocean Circulation During Storm Events, J. Geophys. Res.-Oceans, 126, e2021JC017343, https://doi.org/10.1029/2021JC017343, 2021.
Bush, M., Boutle, I., Edwards, J., Finnenkoetter, A., Franklin, C., Hanley, K., Jayakumar, A., Lewis, H., Lock, A., Mittermaier, M., Mohandas, S., North, R., Porson, A., Roux, B., Webster, S., and Weeks, M.: The second Met Office Unified Model–JULES Regional Atmosphere and Land configuration, RAL2, Geosci. Model Dev., 16, 1713–1734, https://doi.org/10.5194/gmd-16-1713-2023, 2023.
Berthou, S., Renshaw, R., Smyth, T., Tinker, J., Grist, J. P., Wihsgott, J. U., Jones, S., Inall, M., Nolan G., Berx, B., Arnold, A., Blunn, L. P., Castillo, J. M., Cotterill, D., Daly, E., Dow, G., Gómez, B., Fraser-Leonhardt, V., Hirschi, J. J. M., Lewis, H. W., Mahmood, S., and Worsfold, M.: Exceptional Atmospheric Conditions in June 2023 Generated a Northwest European Marine Heatwave Which Contributed to Breaking Land Temperature Records, Commun. Earth Environ., 5, 287, https://doi.org/10.1038/s43247-024-01413-8, 2024.
CBD: United Nations Environment Programme, Convention on biological diversity, June 1992, United Nations, Treaty Series, vol. 1760, p. 79, https://treaties.un.org/pages/ViewDetails.aspx?src=TREATY&mtdsg_no=XXVII-8&chapter=27 (last access: 4 June 2024), 1992.
Cotterill, D. F., Pope, J. O., and Stott, P. A.: Future extension of the UK summer and its impact on autumn precipitation, Clim. Dynam., 60, 1801–1814, https://doi.org/10.1007/s00382-022-06403-0, 2023.
Danielssen, D. S., Edler, L., Fonselius, S., Hernroth, L., Ostrowski, M., Svendsen, E., and Talpsepp, L.: Oceanographic variability in the Skagerrak and Northern Kattegat, May–June, 1990, ICES J. Mar. Sci., 54, 753–773, 1997.
Drijfhout, S.: Competition between global warming and an abrupt collapse of the AMOC in Earth's energy imbalance, Sci. Rep.-UK, 5, 14877, https://doi.org/10.1038/srep14877, 2015.
Drijfhout, S., van Oldenborgh, G. J., and Cimatoribus, A.: Is a decline of AMOC causing the warming hole above the North Atlantic in observed and modeled warming patterns?, J. Climate, 25, 8373–8379, https://doi.org/10.1175/JCLI-D-12-00490.1, 2012.
EU Habitats Directive: European Commission, Council Directive 92/43/EEC of 21 May 1992 on the conservation of natural habitats and of wild fauna and flora. Official Journal of the European Union L206, 7–50, 1992.
European Commission, Directive 2008/56/EC of the European Parliament and of the Council of 17 June 2008 establishing a framework for community action in the field of marine environmental policy (Marine Strategy Framework Directive): Official Journal of the European Union L164, 19–40, 2008.
European Commission, Council Regulation (EC) No 1380/2013 Regulation (EU) No 1380/2013 of the European Parliament and of the Council of 11 December 2013 on the Common Fisheries Policy, amending Council Regulations (EC) No 1954/2003 and (EC) No 1224/2009 and repealing Council Regulations (EC) No 2371/2002 and (EC) No 639/2004 and Council Decision 2004/585/EC: Official Journal of the European Union L354, 22–63, 2013.
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., and Taylor, K. E.: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev., 9, 1937–1958, https://doi.org/10.5194/gmd-9-1937-2016, 2016.
Fallmann, J., Lewis, H., Sanchez, J. C., and Lock, A.: Impact of high-resolution ocean–atmosphere coupling on fog formation over the North Sea, Q. J. Roy. Meteor. Soc., 145, 1180–1201, https://doi.org/10.1002/qj.3488, 2019.
Fernand, L., Nolan, G. D., Raine, R., Chambers, C. E., Dye, S. R., White, M., and Brown, J.: The Irish coastal current: A seasonal jet-like circulation, Cont. Shelf Res., 26, 1775–1793, https://doi.org/10.1016/j.csr.2006.05.010, 2006.
Fox-Kemper, B., Hewitt, H., Xiao, C., Aðalgeirsdóttir, G., Drijfhout, S., Edwards, T., Golledge, N., Hemer, M., Kopp, R., Krinner, G., Mix, A., Notz, D., Nowiciki, S., Nurhati, I., Ruiz, J., Sallée, J., Slangen, A., and Yu, Y.: Ocean, Cryosphere and Sea Level Change, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S. L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M. I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J. B. R., Maycock, T. K., Waterfield, T., Yelekçi, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1211–1362, https://doi.org/10.1017/9781009157896.011, 2021.
Frost, M., Bayliss-Brown, G., Buckley, P., Cox, M., Dye, S. R., Sanderson, W. G., Stoker, B., and Withers Harvey, N.: A review of climate change and the implementation of marine biodiversity legislation in the United Kingdom, Aquat. Conserv., 26, 576–595, https://doi.org/10.1002/aqc.2628, 2016.
Fyfe, J. C., Kharin, V. V., Santer, B. D., Cole, J. N. S., and Gillett, N. P.: Significant impact of forcing uncertainty in a large ensemble of climate model simulations, P. Natl. Acad. Sci. USA, 118, e2016549118, https://doi.org/10.1073/pnas.2016549118, 2021.
Gohar, L., Bernie, D., Good, P., and Lowe, J. A.: UKCP18 Derived Projections of Future Climate over the UK, Met Office, Exeter, EX1 3PB, UK, 2018.
González-Pola, C., Larsen, K. M. H., Fratantoni, P., and Beszczynska-Möller, A.: ICES Report on Ocean Climate 2020, ICES, 121 pp., https://doi.org/10.17895/ices.pub.19248602, 2022.
Good, S. A., Martin, M., and Rayner, N. A.: EN4: Quality controlled ocean temperature and salinity profiles and monthly objective analyses with uncertainty estimates, J. Geophys. Res.-Oceans, 118, 6704–6716, https://doi.org/10.1002/2013JC009067, 2013.
Gordon, C., Cooper, C., Senior, C. A., Banks, H., Gregory, J. M., Johns, T. C., Mitchell, J. F. B., and Wood, R. A.: The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments, Clim. Dynam., 16, 147–168, 2000.
Graham, J. A., O'Dea, E., Holt, J., Polton, J., Hewitt, H. T., Furner, R., Guihou, K., Brereton, A., Arnold, A., Wakelin, S., Castillo Sanchez, J. M., and Mayorga Adame, C. G.: AMM15: a new high-resolution NEMO configuration for operational simulation of the European north-west shelf, Geosci. Model Dev., 11, 681–696, https://doi.org/10.5194/gmd-11-681-2018, 2018.
Gröger, M., Maier-Reimer, E., Mikolajewicz, U., Moll, A., and Sein, D.: NW European shelf under climate warming: implications for open ocean – shelf exchange, primary production, and carbon absorption, Biogeosciences, 10, 3767–3792, https://doi.org/10.5194/bg-10-3767-2013, 2013.
Hagelin, S., Son, J., Swinbank, R., McCabe, A., Roberts, N., and Tennant, W.: The Met Office convective-scale ensemble, MOGREPS-UK, Q. J. Roy. Meteor. Soc., 143, 2846–2861, https://doi.org/10.1002/qj.3135, 2017.
Hausfather, Z. and Peters, G. P.: Emissions – the `business as usual' story is misleading, 577, 618–620, https://doi.org/10.1038/d41586-020-00177-3, 2020.
Herger, N., Sanderson, B. M., and Knutti, R.: Improved pattern scaling approaches for the use in climate impact studies, Geophys. Res. Lett., 42, 3486–3494, https://doi.org/10.1002/2015GL063569, 2015.
Hermans, T. H. J., 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 in the satellite altimetry era, J. Geophys. Res., 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.
Hermanson, L., Smith, D., Seabrook, M., Bilbao, R., Doblas-Reyes, F., Tourigny, E., Lapin, V., Kharin, V. V., Merryfield, W. J., Sospedra-Alfonso, R., Athanasiadis, P., Nicoli, D., Gualdi, S., Dunstone, N., Eade, R., Scaife, A., Collier, M., O'Kane, T., Kitsios, V., Sandery, P., Pankatz, K., Früh, B., Pohlmann, H., Müller, W., Kataoka, T., Tatebe, H., Ishii, M., Imada, Y., Kruschke, T., Koenigk, T., Karami, M. P., Yang, S., Tian, T., Zhang, L., Delworth, T., Yang, X., Zeng, F., Wang, Y., Counillon, F., Keenlyside, N., Bethke, I., Lean, J., Luterbacher, J., Kolli, R. K., and Kumar, A.: WMO Global Annual to Decadal Climate Update A Prediction for 2021-25, B. Am. Meteorol. Soc., 103, E1117–E1129, https://doi.org/10.1175/BAMS-D-20-0311.1, 2022.
Holgate, S. J., Matthews, A., Woodworth, P. L., Rickards, Lesley, J., Tamisiea, Mark, E., Bradshaw, E., Foden, Peter, R., Gordon, K. M., Jevrejeva, S., and Pugh, J.: New Data Systems and Products at the Permanent Service for Mean Sea Level, J. Coastal Res., 29, 493, https://doi.org/10.2112/JCOASTRES-D-12-00175.1, 2013.
Holt, J. and Proctor, R.: The seasonal circulation and volume transport on the northwest European continental shelf: A fine-resolution model study, J. Geophys. Res., 113, https://doi.org/10.1029/2006jc004034, 2008.
Holt, J., Wakelin, S., Lowe, J. A., and Tinker, J.: The potential impacts of climate change on the hydrography of the northwest European continental shelf, Prog. Oceanogr., 86, 361–379, https://doi.org/10.1016/j.pocean.2010.05.003, 2010.
Holt, J., Polton, J., Huthnance, J., Wakelin, S., O'Dea, E., Harle, J., Yool, A., Artioli, Y., Blackford, J., Siddorn, J., and Inall, M.: Climate-Driven Change in the North Atlantic and Arctic Oceans Can Greatly Reduce the Circulation of the North Sea, Geophys. Res. Lett., 45, 11827–11836, https://doi.org/10.1029/2018GL078878, 2018.
Holt, J. T. and James, I. D.: An s coordinate density evolving model of the northwest European continental shelf: 1. Model description and density structure, J. Geophys. Res., 106, 14015–14034, 2001.
Holt, J. T., James, I. D., and Jones, J. E.: An s coordinate density evolving model of the northwest European continental shelf: 2. Seasonal currents and tides, J. Geophys. Res., 106, 14035–14053, 2001.
Howard, T., Palmer, M. D., and Bricheno, L. M.: Contributions to 21st century projections of extreme sea-level change around the UK, Environ. Res. Commun., 1, 095002, https://doi.org/10.1088/2515-7620/ab42d7, 2019.
Hughes, S. L., Hindson, J., Berx, B., Gallego, A., and Turrell, W. R.: Scottish Ocean Climate Status Report 2016, Scottish Government, https://doi.org/10.7489/12086-1, 2018.
Hunke, E. C., Lipscomb, W. H., Turner, A. K., Jeffery, N., and Elliott, S. M.: CICE: The Los Alamos sea ice model, documentation and software, version 5.1, Tech. Rep. LA-CC-06-012, Los Alamos National Laboratory, Los Alamos, NM, 2015.
IPCC: Climate Change 2021: The Physical Science Basis. Working Group I Contribution to the IPCC Sixth Assessment Report, Clim. Chang. 2021 Phys. Sci. Basis., https://doi.org/10.1017/9781009157896, 2021a.
IPCC: Summary for Policymakers (AR6), 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 Zho, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 3–32, https://doi.org/10.1017/9781009157896.001, 2021b.
IPCC: The Earth's Energy Budget, Climate Feedbacks and Climate Sensitivity, in: Climate Change 2021 – The Physical Science Basis, https://doi.org/10.1017/9781009157896.009, 2021c.
Jardine, J. E., Palmer, M., Mahaffey, C., Holt, J., Wakelin, S. L., Düsterhus, A., Sharples, J., and Wihsgott, J.: Rain triggers seasonal stratification in a temperate shelf sea, Nat. Commun., 14, 293, https://doi.org/10.1038/s41467-023-38599-y, 2023.
Jones, R. G., Noguer, M., Hassell, D. C., Hudson, D., Wilson, S. S., Jenkins, G. J., and Mitchell, J. F. B.: Generating High Resolution Climate Change Scenarios Using PRECIS, Met Office Hadley Centre, Exeter, UK, 2004.
Kotlarski, S., Keuler, K., Christensen, O. B., Colette, A., Déqué, M., Gobiet, A., Goergen, K., Jacob, D., Lüthi, D., van Meijgaard, E., Nikulin, G., Schär, C., Teichmann, C., Vautard, R., Warrach-Sagi, K., and Wulfmeyer, V.: Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble, Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, 2014.
Legeais, J.-F., Ablain, M., Zawadzki, L., Zuo, H., Johannessen, J. A., Scharffenberg, M. G., Fenoglio-Marc, L., Fernandes, M. J., Andersen, O. B., Rudenko, S., Cipollini, P., Quartly, G. D., Passaro, M., Cazenave, A., and Benveniste, J.: An improved and homogeneous altimeter sea level record from the ESA Climate Change Initiative, Earth Syst. Sci. Data, 10, 281–301, https://doi.org/10.5194/essd-10-281-2018, 2018.
Lowe, J., Howard, T., Pardaens, A., Tinker, J., Holt, J., Wakelin, S., Milne, G., Leake, J., Wolf, J., Horsburgh, K., Reeder, T., Jenkins, G., Ridley, J., Dye, S., and Bradley, S.: UKCP09 Marine and coastal projections, Met Office, Exeter, 99 pp., ISBN 978-1-906360-03-0, 2009.
Lowe, J. A., Bernie, D., Bett, P., Bricheno, L., Brown, S., Calvert, D., Clark, R., Eagle, K., Edwards, T., Fosser, G., Fung, F., Gohar, L., Good, P., Gregory, J., Harris, G., Howard, T., Kaye, N., Kendon, E., Krijnen, J., Maisey, P., McDonald, R., McInnes, R., McSweeney, C., Mitchell, J. F., Murphy, J., Palmer, M., Roberts, C., Rostron, J., Sexton, D., Thornton, H., Tinker, J., Tucker, S., Yamazaki, K., and Belcher, S.: UKCP18 Science Overview Report version 2.0, Met Office, https://www.metoffice.gov.uk/pub/data/weather/uk/ukcp18/science-reports/UKCP18-Overview-report.pdf (last access: 28 May 2024), 2019.
Lyu, K., Zhang, X., Church, J. A., Slangen, A. B. A., and Hu, J.: Time of emergence for regional sea-level change, Nat. Clim. Change, 4, 1006–1010, https://doi.org/10.1038/nclimate2397, 2014.
MacLachlan, C., Arribas, A., Peterson, K. A., Maidens, A., Fereday, D., Scaife, A. A., Gordon, M., Vellinga, M., Williams, A., Comer, R. E., Camp, J., Xavier, P., and Madec, G.: Global Seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system, Q. J. Roy. Meteor. Soc., 141, 1072–1084, https://doi.org/10.1002/qj.2396, 2014.
Mathis, M. and Pohlmann, H.: Projection of physical conditions in the North Sea for the 21st century, Clim. Res., 61, 1–17, https://doi.org/10.3354/cr01232, 2014.
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.
MCCIP: Futureproofing our ocean though climate-smart spatial management of UK fisheries, aquaculture and conservation, edited by: Frost, M., Buckley, P., Queirós, A., and Talbot, L., Summary Report, MCCIP, Lowestoft, https://doi.org/10.14465/2023.msp01.spm, 2023.
Menary, M. B. and Wood, R.: An anatomy of the projected North Atlantic warming hole in CMIP5 models, Clim. Dynam., 50, 3063–3080, https://doi.org/10.1007/s00382-017-3793-8, 2018.
Morice, C. P., Kennedy, J. J., Rayner, N. A., and Jones, P. D.: Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set, J. Geophys. Res.-Atmos., 117, https://doi.org/10.1029/2011JD017187, 2012.
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., https://doi.org/10.5194/os-17-789-2021, 2021.
Murphy, J. M., Harris, G. R., Sexton, D. M. H., Kendon, E. J., Bett, P. E., Clark, R. T., Eagle, K. E., Fosser, G., Fung, F., Lowe, J. A., McDonald, R. E., McInnes, R. N., McSweeney, C. F., Mitchell, J. F. B., Rostron, J. W., Thornton, H. E., Tucker, S., and Yamazaki, K.: UKCP18 Land Projections: Science Report, Met Office Hadley Centre, https://www.metoffice.gov.uk/pub/data/weather/uk/ukcp18/science-reports/UKCP18-Land-report.pdf (last access: 28 May 2024), 2018.
Murphy, J. M., Booth, B. B. B., Harris, G. R., McSweeney, C. F., Palmer, T. E., Sexton, D. M. H., and Yamazaki, K.: Hadley Centre Technical Note 109: Comparison between climate change projections from the UKCP land scenarios and CMIP6 models, Met Office, Exeter, EX1 3PB, UK, 64 pp., https://digital.nmla.metoffice.gov.uk/IO_ef5ce3b5-33ac-4ac4-a8ea-c77ff90a2ebc/ (last access: 28 May 2024), 2023.
Nakicenovic, N., Alcamo, J., Davis, G., de Vries, B., Fenhann, J., Gaffin, S., Gregory, K., Grubler, A., Jung, T., Kram, T., La Rovere, E., Michaelis, L., Mori, S., Morita, T., Pepper, W., Pitcher, H. M., Price, L., Riahi, K., Roehrl, A., Rogner, H.-H., Sankovski, A., Schlesinger, M., Shukla, P., Smith, S. J., Swart, R., van Rooijen, S., Victor, N., Dadi, Z., and Press, C. U.: Special Report on Emissions Scenarios: A special report of Working Group III of the Intergovernmental Panel on Climate Change, IPCC, ISBN 0 521 80081 1, 2000.
NOSCCA: North Sea Region Climate Change Assessment, edited by: Quante, M. and Colijn, F., Springer International Publishing, 528 pp., https://doi.org/10.1007/978-3-319-39745-0, 2016.
O'Dea, E., Arnold, A. K., Edwards, K. P., Furner, R., Hyder, P., Martin, M. J., Siddorn, J., Storkey, D., While, J., Holt, J., and Lui, H.: An operational ocean forecast system incorporating NEMO and SST data assimilation for the tidally driven European North-West shelf, J. Oper. Oceanogr., 5, 3–17, https://doi.org/10.1080/1755876X.2012.11020128, 2012.
O'Dea, E., Furner, R., Wakelin, S., Siddorn, J., While, J., Sykes, P., King, R., Holt, J., and Hewitt, H.: The CO5 configuration of the 7 km Atlantic Margin Model: large-scale biases and sensitivity to forcing, physics options and vertical resolution, Geosci. Model Dev., 10, 2947–2969, https://doi.org/10.5194/gmd-10-2947-2017, 2017.
Olbert, A. I., Dabrowski, T., Nash, S., and Hartnett, M.: Regional modelling of the 21st century climate changes in the Irish Sea, Cont. Shelf Res., 41, 48–60, https://doi.org/10.1016/j.csr.2012.04.003, 2012.
OSPAR: OSPAR Convention for the Protection of the Marine Environment of the Northeast Atlantic, Meeting of the OSPAR Commission, Bremen, 23–27 June 2003, OSPAR Recommendation 2003/3 adopted by OSPAR 2003 (OSPAR 03/17/1, Annex 9), amended by OSPAR Recommendation 2010/2 (OSPAR 10/23/1, Annex 7), 2010.
Palmer, M. D., Howard, T. P., Tinker, J., Lowe, J., Bricheno, L., Calvert, D., Edwards, T., Gregory, J. M., Harris, G., Krijnen, J., Roberts, C. D., and Wolf, J.: UKCP18 Marine Report, Met Office Hadley Centre, Exeter, UK, 133 pp., 2018.
Palmer, M. D., Gregory, J. M., Bagge, M., Calvert, D., Hagedoorn, J. M., Howard, T., Klemann, V., Lowe, J. A., Roberts, C. D., Slangen, A. B. A., and Spada, G.: Exploring the Drivers of Global and Local Sea-Level Change Over the 21st Century and Beyond, Earths Future, 8, e2019EF001413, https://doi.org/10.1029/2019EF001413, 2020.
Perez, F. F., Fontela, M., García-Ibáñez, M. I., Mercier, H., Velo, A., Lherminier, P., Zunino, P., De La Paz, M., Alonso-Pérez, F., Guallart, E. F., and Padin, X. A.: Meridional overturning circulation conveys fast acidification to the deep Atlantic Ocean, Nature, 554, 515–518, https://doi.org/10.1038/nature25493, 2018.
Petch, J. C., Short, C. J., Best, M. J., McCarthy, M., Lewis, H. W., Vosper, S. B., and Weeks, M.: Sensitivity of the 2018 UK summer heatwave to local sea temperatures and soil moisture, Atmos. Sci. Lett., 21, e948, https://doi.org/10.1002/asl.948, 2020.
Pingree, R. D. and Griffiths, D. K.: Sand transport paths around the British Isles resulting from M2 and M4 tidal interactions, J. Mar. Biol. Assoc. UK, 59, 497–513, https://doi.org/10.1017/S0025315400042806, 1979.
Pope, V. D., Gallani, P. R., Rowntree, P. R., and Stratton, R. A.: The impact of new physical parametrizations in the Hadley Centre climate model: HadAM3, Clim. Dynam., 16, 123–146, https://doi.org/10.1007/s003820050009, 2000.
Prandle, D., Ballard, G., Flatt, D., Harrison, A. J., Jones, S. E., Knight, P. J., Loch, S., McManus, J. P., Player, R., and Tappin, A.: Combining modelling and monitoring to determine fluxes of water, dissolved and particulate metals through the Dover Strait, Cont. Shelf Res., 16, 237–257, 1996.
Pugh, D.: Tides, Surges and mean sea-level, John Wiley and Sons, Chichester, https://doi.org/10.1111/j.1365-246X.1988.tb06710.x, 1987.
Pugh, D.: Socio-economic indicators of marine-related activities in the UK economy, The Crown Estate, ISBN-10 1906410011, 68 pp., 2008.
Queirós, A. M., Talbot, E., Beaumont, N. J., Somerfield, P. J., Kay, S., Pascoe, C., Dedman, S., Fernandes, J. A., Jueterbock, A., Miller, P. I., Sailley, S. F., Sará, G., Carr, L. M., Austen, M. C., Widdicombe, S., Rilov, G., Levin, L. A., Hull, S. C., Walmsley, S. F., and Nic Aonghusa, C.: Bright spots as climate-smart marine spatial planning tools for conservation and blue growth, Glob. Change Biol., 27, 5514–5531, https://doi.org/10.1111/gcb.15827, 2021.
Renshaw, R., Wakelin, S. L., Mahdon, R., O'Dea, E., and Tinker, J.: Copernicus Marine Environment Monitoring Service Quality Information Document North West European Shelf Production Centre NORTHWESTSHELF_REANALYSIS_PHYS_004_009, Copernicus Marine Service, Exeter, 60 pp., https://doi.org/10.48670/moi-00059, 2019.
Rhein, M., Rintoul, S. R., Aoki, S., Campos, E., Chambers, D., Feely, R. A., Gulev, S., Johnson, G. C., Josey, S. A., Kostianoy, A., Mauritzen, C., Roemmich, D., Talley, L. D., and Wang, F.: Observations: Ocean, 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.
Ridley, J. K., Blockley, E. W., Keen, A. B., Rae, J. G. L., West, A. E., and Schroeder, D.: The sea ice model component of HadGEM3-GC3.1, Geosci. Model Dev., https://doi.org/10.5194/gmd-11-713-2018, 2018.
Rio, M.-H., Mulet, S., and Picot, N.: Beyond GOCE for the ocean circulation estimate: Synergetic use of altimetry, gravimetry, and in situ data provides new insight into geostrophic and Ekman currents, Geophys. Res. Lett., 41, 8918–8925, https://doi.org/10.1002/2014GL061773, 2014.
Roberts-Jones, J., Fiedler, E., and Martin, M. J.: Daily, Global, High-Resolution SST and Sea Ice Reanalysis for 1985–2007 Using the OSTIA System, J. Climate, 25, 6215–6232, https://doi.org/10.1175/JCLI-D-11-00648.1, 2012.
Rostron, J. W., Sexton, D. M. H., McSweeney, C. F., Yamazaki, K., Andrews, T., Furtado, K., Ringer, M. A., and Tsushima, Y.: The impact of performance filtering on climate feedbacks in a perturbed parameter ensemble, Clim. Dynam., 55, 521–551, https://doi.org/10.1007/s00382-020-05281-8, 2020.
Ruan, R., Chen, X., Zhao, J., Perrie, W., Mottram, R., Zhang, M., Diao, Y., Du, L., and Wu, L.: Decelerated Greenland Ice Sheet Melt Driven by Positive Summer North Atlantic Oscillation, J. Geophys. Res.-Atmos., 124, 7633–7646, https://doi.org/10.1029/2019JD030689, 2019.
Schleussner, C.-F., Lissner, T. K., Fischer, E. M., Wohland, J., Perrette, M., Golly, A., Rogelj, J., Childers, K., Schewe, J., Frieler, K., Mengel, M., Hare, W., and Schaeffer, M.: Differential climate impacts for policy-relevant limits to global warming: the case of 1.5 °C and 2 °C, Earth Syst. Dynam., 7, 327–351, https://doi.org/10.5194/esd-7-327-2016, 2016.
Sexton, D. M. H., McSweeney, C. F., Rostron, J. W., Yamazaki, K., Booth, B. B. B., Murphy, J. M., Regayre, L., Johnson, J. S., and Karmalkar, A. V.: A perturbed parameter ensemble of HadGEM3-GC3.05 coupled model projections: part 1: selecting the parameter combinations, Clim. Dynam., 56, 3395–3436, https://doi.org/10.1007/s00382-021-05709-9, 2021.
Siddorn, J. R. R. and Furner, R.: An analytical stretching function that combines the best attributes of geopotential and terrain-following vertical coordinates, Ocean Model., 66, 1–13, https://doi.org/10.1016/j.ocemod.2013.02.001, 2013.
Silva, E., Counillon, F., Brajard, J., Korosov, A., Pettersson, L. H., Samuelsen, A., and Keenlyside, N.: Twenty-One Years of Phytoplankton Bloom Phenology in the Barents, Norwegian, and North Seas, Front. Mar. Sci., 8, 746327, https://doi.org/10.3389/fmars.2021.746327, 2021.
Simpson, J. H. and Bowers, D.: Models of stratification and frontal movement in shelf seas, Deep-Sea Res., 28, 727–738, 1981.
Stigebrandt, A.: A Model for the Vertial Circulation of the Baltic Deep Water, J. Phys. Oceanogr., 17, 1772–1785, https://doi.org/10.1175/1520-0485(1987)017<1772:AMFTVC>2.0.CO;2, 1987.
Svendsen, E., Saetre, R., and Mork, M.: Features of the northern North Sea circulation, Cont. Shelf Res., 11, 493–508, 1991.
Tebaldi, C., Debeire, K., Eyring, V., Fischer, E., Fyfe, J., Friedlingstein, P., Knutti, R., Lowe, J., O'Neill, B., Sanderson, B., van Vuuren, D., Riahi, K., Meinshausen, M., Nicholls, Z., Tokarska, K. B., Hurtt, G., Kriegler, E., Lamarque, J.-F., Meehl, G., Moss, R., Bauer, S. E., Boucher, O., Brovkin, V., Byun, Y.-H., Dix, M., Gualdi, S., Guo, H., John, J. G., Kharin, S., Kim, Y., Koshiro, T., Ma, L., Olivié, D., Panickal, S., Qiao, F., Rong, X., Rosenbloom, N., Schupfner, M., Séférian, R., Sellar, A., Semmler, T., Shi, X., Song, Z., Steger, C., Stouffer, R., Swart, N., Tachiiri, K., Tang, Q., Tatebe, H., Voldoire, A., Volodin, E., Wyser, K., Xin, X., Yang, S., Yu, Y., and Ziehn, T.: Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6, Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, 2021.
Tinker, J.: Physical Marine Climate Projections for the North West European Shelf Seas: EnsStats, NERC EDS Centre for Environmental Data Analysis [data set], https://doi.org/10.5285/bd375134bd8c4990a1e9eb6d199cc723, 2023a.
Tinker, J.: Physical Marine Climate Projections for the North West European Shelf Seas: NWSPPE, NERC EDS Centre for Environmental Data Analysis [data set], https://doi.org/10.5285/edf66239c70c426e9e9f19da1ac8ba87, 2023b.
Tinker, J.: sical Marine Climate Projections for the North West European Shelf Seas: PDCtrl, NERC EDS Centre for Environmental Data Analysis [data set], https://doi.org/10.5285/66e39885a60e4b6386752b1a295f268a, 2023c.
Tinker, J.: Physical Marine Climate Projections for the North West European Shelf Seas based on the UKCP18 Perturbed Parameter Ensemble, NERC EDS Centre for Environmental Data Analysis [data set], http://catalogue.ceda.ac.uk/uuid/832677618370457f9e0a85da021c1312, 2023d.
Tinker, J. and Hermanson, L.: Towards winter seasonal predictability on the North West European Shelf Seas, Front. Mar. Sci., 8, 698997, https://doi.org/10.3389/fmars.2021.698997, 2021.
Tinker, J. and Howes, E. L.: The impacts of climate change on temperature (air and sea), relevant to the coastal and marine environment around the UK, Lowestoft, 30 pp., MCCIP, https://doi.org/10.14465/2020.arc01.tem, 2020.
Tinker, J. and Polton, J. A.: hadjt/CurrUncertEllipses: Ensemble Statistics, Zenodo [code], https://doi.org/10.5281/zenodo.11370979, 2024.
Tinker, J., Lowe, J., Holt, J., Pardaens, A., and Wiltshire, A.: Validation of an ensemble modelling system for climate projections for the northwest European shelf seas, Prog. Oceanogr., 138, 211–237, https://doi.org/10.1016/j.pocean.2015.07.002, 2015.
Tinker, J., Lowe, J., Pardaens, A., Holt, J., and Barciela, R.: Uncertainty in climate projections for the 21st century northwest European shelf seas, Prog. Oceanogr., 148, 56–73, https://doi.org/10.1016/j.pocean.2016.09.003, 2016.
Tinker, J., Krijnen, J., Wood, R., Barciela, R., and Dye, S. R.: What are the prospects for seasonal prediction of the marine environment of the North-west European Shelf?, Ocean Sci., 14, 887–909, https://doi.org/10.5194/os-14-887-2018, 2018.
Tinker, J., Renshaw, R., Barciela, R., and Wood, R.: Regional mean time series for the Northwest European Shelf seas, in: Copernicus Marine Service Ocean State Report, Issue 3, J. Oper. Oceanogr., 12, s26–s30, https://doi.org/10.1080/1755876X.2019.1633075, 2019.
Tinker, J., Palmer, M. D., Copsey, D., Howard, T. P., Lowe, J., and Hermans, T. H. J.: Dynamical downscaling of unforced interannual sea-level variability in the North-West European shelf seas, Clim. Dynam., https://doi.org/10.1007/s00382-020-05378-0, 2020.
Tinker, J., Polton, J. A., Robins, P. E., Lewis, M. J., and O'Neill, C. K.: The influence of tides on the North West European shelf winter residual circulation, Front. Mar. Sci., 9, 847138, https://doi.org/10.3389/fmars.2022.847138, 2022.
Tonani, M., Sykes, P., King, R. R., McConnell, N., Péquignet, A.-C., O'Dea, E., Graham, J. A., Polton, J., and Siddorn, J.: The impact of a new high-resolution ocean model on the Met Office North-West European Shelf forecasting system, Ocean Sci., 15, 1133–1158, https://doi.org/10.5194/os-15-1133-2019, 2019.
Turrell, W. R., Henderson, E. W., Slesser, G., Payne, R., and Adams, R. D.: Seasonal changes in the circulation of the northern North Sea, Cont. Shelf Res., 12, 257–286, 1992.
UNESCO: Algorithms for computation of fundamental property of sea water, Techn. Paper in Mar. Sci, 44, UNESCO, https://doi.org/10.25607/OBP-1450, 1983.
UNFCCC: United Nations Framework Convention on Climate Change, 9 May 1992, S. Treaty Doc No. 102-38, 1771 U. N. T., https://treaties.un.org/pages/ViewDetailsIII.aspx?src=TREATY&mtdsg_no=XXVII-7&chapter=27&Temp=mtdsg3&clang=_en (last access: 4 June 2024), 1992.
Van Leeuwen, S., Tett, P., Mills, D., and Van Der Molen, J.: Stratified and nonstratified areas in the North Sea: Long-term variability and biological and policy implications, J. Geophys. Res.-Oceans, 120, 4670–4686, https://doi.org/10.1002/2014JC010485, 2015.
Vautard, R., Gobiet, A., Jacob, D., Belda, M., Colette, A., Déqué, M., Fernández, J., García-Díez, M., Goergen, K., Güttler, I., Halenka, T., Karacostas, T., Katragkou, E., Keuler, K., Kotlarski, S., Mayer, S., van Meijgaard, E., Nikulin, G., Patarèiæ, M., Scinocca, J., Sobolowski, S., Suklitsch, M., Teichmann, C., Warrach-Sagi, K., Wulfmeyer, V., and Yiou, P.: The simulation of European heat waves from an ensemble of regional climate models within the EURO-CORDEX project, Clim. Dynam., 41, 2555–2575, https://doi.org/10.1007/s00382-013-1714-z, 2013.
Wakelin, S. L., Holt, J. T., and Proctor, R.: The influence of initial conditions and open boundary conditions on shelf circulation in a 3D ocean-shelf model of the North East Atlantic, Ocean Dynam., 59, 67–81, https://doi.org/10.1007/s10236-008-0164-3, 2009.
Wakelin, S. L., Holt, J., Blackford, J., Allen, I., Butenschön, M., and Artioli, Y.: Modeling the carbon fluxes of the northwest European continental shelf: Validation and budgets, J. Geophys. Res.-Oceans, 117, C05020, https://doi.org/10.1029/2011JC007402, 2012.
Walters, D., Baran, A. J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Carslaw, K., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Jones, C., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and Zerroukat, M.: The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations, Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, 2019.
Weeks, J. H., Fung, F., Harrison, B. J., and Palmer, M. D.: The evolution of UK sea-level projections, Environ. Res. Commun., 5, 032001, https://doi.org/10.1088/2515-7620/acc020, 2023.
Williams, K. D., Copsey, D., Blockley, E., Bodas-Salcedo, A., Calvert, D., Comer, R. E., Davis, P., Graham, T., Hewitt, H. T., Hill, R., Hyder, P., Ineson, S., Johns, T. C., Keen, A. B., Lee, R. W., Megann, A., Milton, S. F., Rae, J. G. L., Roberts, M. J., Scaife, A., Schiemann, R., Storkey, D., Thorpe, L., Watterson, I. G., Walters, D. N., West, A., Wood, R. A., Woollings, T., and Xavier, P. K.: The Met Office Global Coupled model 3.0 and 3.1 (GC3 & GC3.1) configurations, J. Adv. Model. Earth Sy., 10, 357–380, https://doi.org/10.1002/2017MS001115, 2018.
Wise, A., Harle, J., Bruciaferri, D., O'Dea, E., and Polton, J.: The effect of vertical coordinates on the accuracy of a shelf sea model, Ocean Model., 170, 101935, https://doi.org/10.1016/j.ocemod.2021.101935, 2022.
Wise, A., Calafat, F. M., Hughes, C. W., Jevrejeva, S., Katsman, C. A., Oelsmann, J., Piecuch, C., Polton, J., and Richter, K.: Using Shelf‐Edge Transport Composition and Sensitivity Experiments to Understand Processes Driving Sea Level on the Northwest European Shelf, J. Geophys. Res.-Oceans 129, e2023JC020587, https://doi.org/10.1029/2023JC020587, 2024.
Yamazaki, K., Sexton, D. M. H., Rostron, J. W., McSweeney, C. F., Murphy, J. M., and Harris, G. R.: A perturbed parameter ensemble of HadGEM3-GC3.05 coupled model projections: part 2: global performance and future changes, Clim. Dynam., 56, 3437–3471, https://doi.org/10.1007/s00382-020-05608-5, 2021.
Zhu, C. and Liu, Z.: Weakening Atlantic overturning circulation causes South Atlantic salinity pile-up, Nat. Clim. Change, 10, 998–1003, https://doi.org/10.1038/s41558-020-0897-7, 2020.
Zika, J. D., Skliris, N., Blaker, A. T., Marsh, R., Nurser, A. J. G., and Josey, S. A.: Improved estimates of water cycle change from ocean salinity: The key role of ocean warming, Environ. Res. Lett., 13, 074036, https://doi.org/10.1088/1748-9326/aace42, 2018.
Short summary
The northwest European shelf (NWS) seas are economically and environmentally important but poorly represented in global climate models (GCMs). We combine use of a shelf sea model with GCM output to provide improved 21st century projections of the NWS. We project a NWS warming of 3.11 °C and freshening of −1.01, and we provide uncertainty estimates. We calculate the climate signal emergence and consider warming levels. We have released our data for the UK's Climate Change Risk Assessment.
The northwest European shelf (NWS) seas are economically and environmentally important but...
