Articles | Volume 18, issue 5
https://doi.org/10.5194/bg-18-1803-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-18-1803-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Mar 2021
Research article |
| 16 Mar 2021
| 16 Mar 2021
An observation-based evaluation and ranking of historical Earth system model simulations in the northwest North Atlantic Ocean
Department of Oceanography, Dalhousie University, Halifax, Nova Scotia, Canada
Katja Fennel
Department of Oceanography, Dalhousie University, Halifax, Nova Scotia, Canada
Angela Kuhn
Scripps Institution of Oceanography, UC San Diego, La Jolla, CA, USA
Related authors
Arnaud Laurent, Bin Wang, Dariia Atamanchuk, Subhadeep Rakshit, Kumiko Azetsu-Scott, Chris Algar, and Katja Fennel
EGUsphere, https://doi.org/10.5194/egusphere-2025-3361, https://doi.org/10.5194/egusphere-2025-3361, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
Surface ocean alkalinity enhancement, through the release of alkaline materials, is a technology that could increase the storage of anthropogenic carbon in the ocean. Halifax Harbour (Canada) is a current test site for operational alkalinity addition. Here, we present a model of Halifax Harbour that simulates alkalinity addition at various locations of the harbour and quantifies the resulting net CO2 uptake. The model can be relocated to study alkalinity addition in other coastal systems.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024, https://doi.org/10.5194/gmd-17-8697-2024, 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 ocean 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.
Katja Fennel, Matthew C. Long, Christopher Algar, Brendan Carter, David Keller, Arnaud Laurent, Jann Paul Mattern, Ruth Musgrave, Andreas Oschlies, Josiane Ostiguy, Jaime B. Palter, and Daniel B. Whitt
State Planet, 2-oae2023, 9, https://doi.org/10.5194/sp-2-oae2023-9-2023, https://doi.org/10.5194/sp-2-oae2023-9-2023, 2023
Short summary
Short summary
This paper describes biogeochemical models and modelling techniques for applications related to ocean alkalinity enhancement (OAE) research. Many of the most pressing OAE-related research questions cannot be addressed by observation alone but will require a combination of skilful models and observations. We present illustrative examples with references to further information; describe limitations, caveats, and future research needs; and provide practical recommendations.
Arnaud Laurent, Haiyan Zhang, and Katja Fennel
Biogeosciences, 19, 5893–5910, https://doi.org/10.5194/bg-19-5893-2022, https://doi.org/10.5194/bg-19-5893-2022, 2022
Short summary
Short summary
The Changjiang is the main terrestrial source of nutrients to the East China Sea (ECS). Nutrient delivery to the ECS has been increasing since the 1960s, resulting in low oxygen (hypoxia) during phytoplankton decomposition in summer. River phosphorus (P) has increased less than nitrogen, and therefore, despite the large nutrient delivery, phytoplankton growth can be limited by the lack of P. Here, we investigate this link between P limitation, phytoplankton production/decomposition, and hypoxia.
Haiyan Zhang, Katja Fennel, Arnaud Laurent, and Changwei Bian
Biogeosciences, 17, 5745–5761, https://doi.org/10.5194/bg-17-5745-2020, https://doi.org/10.5194/bg-17-5745-2020, 2020
Short summary
Short summary
In coastal seas, low oxygen, which is detrimental to coastal ecosystems, is increasingly caused by man-made nutrients from land. This is especially so near mouths of major rivers, including the Changjiang in the East China Sea. Here a simulation model is used to identify the main factors determining low-oxygen conditions in the region. High river discharge is identified as the prime cause, while wind and intrusions of open-ocean water modulate the severity and extent of low-oxygen conditions.
Arnaud Laurent, Bin Wang, Dariia Atamanchuk, Subhadeep Rakshit, Kumiko Azetsu-Scott, Chris Algar, and Katja Fennel
EGUsphere, https://doi.org/10.5194/egusphere-2025-3361, https://doi.org/10.5194/egusphere-2025-3361, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
Surface ocean alkalinity enhancement, through the release of alkaline materials, is a technology that could increase the storage of anthropogenic carbon in the ocean. Halifax Harbour (Canada) is a current test site for operational alkalinity addition. Here, we present a model of Halifax Harbour that simulates alkalinity addition at various locations of the harbour and quantifies the resulting net CO2 uptake. The model can be relocated to study alkalinity addition in other coastal systems.
Lina Garcia-Suarez, Katja Fennel, Neha Mehendale, Tronje Peer Kemena, and David Peter Keller
EGUsphere, https://doi.org/10.22541/essoar.173758192.24328151/v2, https://doi.org/10.22541/essoar.173758192.24328151/v2, 2025
This preprint is open for discussion and under review for Ocean Science (OS).
Short summary
Short summary
This study shows that regional ocean warming can make the Gulf Stream appear to shift north, even when its path remains stable in a changing climate. Temperature-based proxies, like the Gulf Stream North Wall, overestimate changes in its position. Methods based on sea surface height provide a more accurate view. These results help improve how we track changes in ocean currents and avoid misinterpreting signs of climate-related shifts.
Gianpiero Cossarini, Andrew Moore, Stefano Ciavatta, and Katja Fennel
State Planet, 5-opsr, 12, https://doi.org/10.5194/sp-5-opsr-12-2025, https://doi.org/10.5194/sp-5-opsr-12-2025, 2025
Short summary
Short summary
Marine biogeochemistry refers to the cycling of chemical elements resulting from physical transport, chemical reaction, uptake, and processing by living organisms. Biogeochemical models can have a wide range of complexity, from a single nutrient to fully explicit representations of multiple nutrients, trophic levels, and functional groups. Uncertainty sources are the lack of knowledge about the parameterizations, the initial and boundary conditions, and the lack of observations.
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024, https://doi.org/10.5194/gmd-17-8697-2024, 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 ocean 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.
Krysten Rutherford, Katja Fennel, Lina Garcia Suarez, and Jasmin G. John
Biogeosciences, 21, 301–314, https://doi.org/10.5194/bg-21-301-2024, https://doi.org/10.5194/bg-21-301-2024, 2024
Short summary
Short summary
We downscaled two mid-century (~2075) ocean model projections to a high-resolution regional ocean model of the northwest North Atlantic (NA) shelf. In one projection, the NA shelf break current practically disappears; in the other it remains almost unchanged. This leads to a wide range of possible future shelf properties. More accurate projections of coastal circulation features would narrow the range of possible outcomes of biogeochemical projections for shelf regions.
Robert W. Izett, Katja Fennel, Adam C. Stoer, and David P. Nicholson
Biogeosciences, 21, 13–47, https://doi.org/10.5194/bg-21-13-2024, https://doi.org/10.5194/bg-21-13-2024, 2024
Short summary
Short summary
This paper provides an overview of the capacity to expand the global coverage of marine primary production estimates using autonomous ocean-going instruments, called Biogeochemical-Argo floats. We review existing approaches to quantifying primary production using floats, provide examples of the current implementation of the methods, and offer insights into how they can be better exploited. This paper is timely, given the ongoing expansion of the Biogeochemical-Argo array.
Li-Qing Jiang, Adam V. Subhas, Daniela Basso, Katja Fennel, and Jean-Pierre Gattuso
State Planet, 2-oae2023, 13, https://doi.org/10.5194/sp-2-oae2023-13-2023, https://doi.org/10.5194/sp-2-oae2023-13-2023, 2023
Short summary
Short summary
This paper provides comprehensive guidelines for ocean alkalinity enhancement (OAE) researchers on archiving their metadata and data. It includes data standards for various OAE studies and a universal metadata template. Controlled vocabularies for terms like alkalinization methods are included. These guidelines also apply to ocean acidification data.
Katja Fennel, Matthew C. Long, Christopher Algar, Brendan Carter, David Keller, Arnaud Laurent, Jann Paul Mattern, Ruth Musgrave, Andreas Oschlies, Josiane Ostiguy, Jaime B. Palter, and Daniel B. Whitt
State Planet, 2-oae2023, 9, https://doi.org/10.5194/sp-2-oae2023-9-2023, https://doi.org/10.5194/sp-2-oae2023-9-2023, 2023
Short summary
Short summary
This paper describes biogeochemical models and modelling techniques for applications related to ocean alkalinity enhancement (OAE) research. Many of the most pressing OAE-related research questions cannot be addressed by observation alone but will require a combination of skilful models and observations. We present illustrative examples with references to further information; describe limitations, caveats, and future research needs; and provide practical recommendations.
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
Benjamin Richaud, Katja Fennel, Eric C. J. Oliver, Michael D. DeGrandpre, Timothée Bourgeois, Xianmin Hu, and Youyu Lu
The Cryosphere, 17, 2665–2680, https://doi.org/10.5194/tc-17-2665-2023, https://doi.org/10.5194/tc-17-2665-2023, 2023
Short summary
Short summary
Sea ice is a dynamic carbon reservoir. Its seasonal growth and melt modify the carbonate chemistry in the upper ocean, with consequences for the Arctic Ocean carbon sink. Yet, the importance of this process is poorly quantified. Using two independent approaches, this study provides new methods to evaluate the error in air–sea carbon flux estimates due to the lack of biogeochemistry in ice in earth system models. Those errors range from 5 % to 30 %, depending on the model and climate projection.
Arnaud Laurent, Haiyan Zhang, and Katja Fennel
Biogeosciences, 19, 5893–5910, https://doi.org/10.5194/bg-19-5893-2022, https://doi.org/10.5194/bg-19-5893-2022, 2022
Short summary
Short summary
The Changjiang is the main terrestrial source of nutrients to the East China Sea (ECS). Nutrient delivery to the ECS has been increasing since the 1960s, resulting in low oxygen (hypoxia) during phytoplankton decomposition in summer. River phosphorus (P) has increased less than nitrogen, and therefore, despite the large nutrient delivery, phytoplankton growth can be limited by the lack of P. Here, we investigate this link between P limitation, phytoplankton production/decomposition, and hypoxia.
Krysten Rutherford, Katja Fennel, Dariia Atamanchuk, Douglas Wallace, and Helmuth Thomas
Biogeosciences, 18, 6271–6286, https://doi.org/10.5194/bg-18-6271-2021, https://doi.org/10.5194/bg-18-6271-2021, 2021
Short summary
Short summary
Using a regional model of the northwestern North Atlantic shelves in combination with a surface water time series and repeat transect observations, we investigate surface CO2 variability on the Scotian Shelf. The study highlights a strong seasonal cycle in shelf-wide pCO2 and spatial variability throughout the summer months driven by physical events. The simulated net flux of CO2 on the Scotian Shelf is out of the ocean, deviating from the global air–sea CO2 flux trend in continental shelves.
Bin Wang, Katja Fennel, and Liuqian Yu
Ocean Sci., 17, 1141–1156, https://doi.org/10.5194/os-17-1141-2021, https://doi.org/10.5194/os-17-1141-2021, 2021
Short summary
Short summary
We demonstrate that even sparse BGC-Argo profiles can substantially improve biogeochemical prediction via a priori model tuning. By assimilating satellite surface chlorophyll and physical observations, subsurface distributions of physical properties and nutrients were improved immediately. The improvement of subsurface chlorophyll was modest initially but was greatly enhanced after adjusting the parameterization for light attenuation through further a priori tuning.
Thomas S. Bianchi, Madhur Anand, Chris T. Bauch, Donald E. Canfield, Luc De Meester, Katja Fennel, Peter M. Groffman, Michael L. Pace, Mak Saito, and Myrna J. Simpson
Biogeosciences, 18, 3005–3013, https://doi.org/10.5194/bg-18-3005-2021, https://doi.org/10.5194/bg-18-3005-2021, 2021
Short summary
Short summary
Better development of interdisciplinary ties between biology, geology, and chemistry advances biogeochemistry through (1) better integration of contemporary (or rapid) evolutionary adaptation to predict changing biogeochemical cycles and (2) universal integration of data from long-term monitoring sites in terrestrial, aquatic, and human systems that span broad geographical regions for use in modeling.
Haiyan Zhang, Katja Fennel, Arnaud Laurent, and Changwei Bian
Biogeosciences, 17, 5745–5761, https://doi.org/10.5194/bg-17-5745-2020, https://doi.org/10.5194/bg-17-5745-2020, 2020
Short summary
Short summary
In coastal seas, low oxygen, which is detrimental to coastal ecosystems, is increasingly caused by man-made nutrients from land. This is especially so near mouths of major rivers, including the Changjiang in the East China Sea. Here a simulation model is used to identify the main factors determining low-oxygen conditions in the region. High river discharge is identified as the prime cause, while wind and intrusions of open-ocean water modulate the severity and extent of low-oxygen conditions.
Cited articles
Adachi, Y., Yukimoto, S., Deushi, M., Obata, A., Nakano, H., Tanaka, T. Y.,
Hosaka, M., Sakami, T., Yoshimura, H., Hirabara, M., Shindo, E., Tsujino, H.,
Mizuta, R., Yabu, S., Koshiro, T., Ose, T., and Kitoh, A.: Basic performance
of a new earth system model of the Meteorological Research Institute
(MRI-ESM1), Papers Meteorol. Geophys., 64, 1–19,
https://doi.org/10.2467/mripapers.64.1, 2013. a
Anav, A., Friedlingstein, P., Kidston, M., Bopp, L., Ciais, P., Cox, P., Jones, C., Jung, M., Myneni, R., and Zhu, Z.: Evaluating the Land and Ocean
Components of the Global Carbon Cycle in the CMIP5 Earth System Models,
J. Climate, 26, 6801–6843, https://doi.org/10.1175/JCLI-D-12-00417.1, 2013. a
Arora, V. K., Scinocca, J. F., Boer, G. J., Christian, J. R., Denman, K. L.,
Flato, G. M., Kharin, V. V., Lee, W. G., and Merryfield, W. J.: Carbon
emission limits required to satisfy future representative concentration
pathways of greenhouse gases, Geophys. Res. Lett., 38, L05805,
https://doi.org/10.1029/2010GL046270, 2011. a
Aumont, O. and Bopp, L.: Globalizing results from ocean in situ iron
fertilization studies, Global Biogeochem. Cy., 20, GB2017,
https://doi.org/10.1029/2005GB002591, 2006. a, b
Aumont, O., Ethé, C., Tagliabue, A., Bopp, L., and Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies, Geosci. Model Dev., 8, 2465–2513, https://doi.org/10.5194/gmd-8-2465-2015, 2015. a, b, c
Bianucci, L., Fennel, K., Chabot, D., Shackell, N., and Lavoie, D.: Ocean
biogeochemical models as management tools: a case study for Atlantic wolffish and declining oxygen, ICES J. Mar. Sci.,
73, 263–274, https://doi.org/10.1093/icesjms/fsv220, 2016. a, b
Bonan, G. B. and Doney, S. C.: Climate, ecosystems, and planetary futures: The challenge to predict life in Earth system models, Science, 359, eaam8328, https://doi.org/10.1126/science.aam8328, 2018. a
Bopp, L., Resplandy, L., Orr, J. C., Doney, S. C., Dunne, J. P., Gehlen, M., Halloran, P., Heinze, C., Ilyina, T., Séférian, R., Tjiputra, J., and Vichi, M.: Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models, Biogeosciences, 10, 6225–6245, https://doi.org/10.5194/bg-10-6225-2013, 2013. a, b
Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y.,
Bastrikov, V., Bekki, S., Bonnet, R., Bony, S., Bopp, L., Braconnot, P.,
Brockmann, P., Cadule, P., Caubel, A., Cheruy, F., Codron, F., Cozic, A.,
Cugnet, D., D'Andrea, F., Davini, P., Lavergne, C., Denvil, S., Deshayes, J.,
Devilliers, M., Ducharne, A., Dufresne, J., Dupont, E., Éthé, C.,
Fairhead, L., Falletti, L., Flavoni, S., Foujols, M., Gardoll, S., Gastineau,
G., Ghattas, J., Grandpeix, J., Guenet, B., Guez, L., Guilyardi, É.,
Guimberteau, M., Hauglustaine, D., Hourdin, F., Idelkadi, A., Joussaume, S.,
Kageyama, M., Khodri, M., Krinner, G., Lebas, N., Levavasseur, G.,
Lévy, C., Li, L., Lott, F., Lurton, T., Luyssaert, S., Madec, G.,
Madeleine, J., Maignan, F., Marchand, M., Marti, O., Mellul, L., Meurdesoif,
Y., Mignot, J., Musat, I., Ottlé, C., Peylin, P., Planton, Y., Polcher,
J., Rio, C., Rochetin, N., Rousset, C., Sepulchre, P., Sima, A., Swingedouw,
D., Thiéblemont, R., Traore, A. K., Vancoppenolle, M., Vial, J.,
Vialard, J., Viovy, N., and Vuichard, N.: Presentation and evaluation of the
IPSL‐CM6A‐LR climate model, J. Adv. Model. Earth
Syst., https://doi.org/10.1029/2019MS002010, 2020. a
Bourgeois, T., Orr, J. C., Resplandy, L., Terhaar, J., Ethé, C., Gehlen, M., and Bopp, L.: Coastal-ocean uptake of anthropogenic carbon, Biogeosciences, 13, 4167–4185, https://doi.org/10.5194/bg-13-4167-2016, 2016. a
Brennan, C. E., Bianucci, L., and Fennel, K.: Sensitivity of Northwest North
Atlantic shelf circulation to surface and boundary forcing: a regional model assessment, Atmos.-Ocean, 54, 230–247,
https://doi.org/10.1080/07055900.2016.1147416, 2016. a, b, c
Bryndum-Buchholz, A., Boyce, D., Tittensor, D., Christensen, V., Bianchi, D.,
and Lotze, H.: Climate-change impacts and fisheries management challenges in the North Atlantic Ocean, Mar. Ecol. Progr. Ser., 648, 1–17,
https://doi.org/10.3354/meps13438, 2020a. a
Bryndum-Buchholz, A., Prentice, F., Tittensor, D. P., Blanchard, J. L., Cheung,
W. W., Christensen, V., Galbraith, E. D., Maury, O., and Lotze, H. K.:
Differing marine animal biomass shifts under 21st century climate change
between Canada's three oceans, Facets, 5, 105–122,
https://doi.org/10.1139/facets-2019-0035, 2020b. a
Cai, W.-J., Dai, M., and Wang, Y.: Air-sea exchange of carbon dioxide in ocean margins: A province-based synthesis, Geophys. Res. Lett., 33,
L12603, https://doi.org/10.1029/2006GL026219, 2006. a
Chen, C.-T. A., Huang, T.-H., Chen, Y.-C., Bai, Y., He, X., and Kang, Y.: Air–sea exchanges of CO2 in the world's coastal seas, Biogeosciences, 10, 6509–6544, https://doi.org/10.5194/bg-10-6509-2013, 2013. a
Christian, J. R., Arora, V. K., Boer, G. J., Curry, C. L., Zahariev, K.,
Denman, K. L., Flato, G. M., Lee, W. G., Merryfield, W. J., Roulet, N. T.,
and Scinocca, J. F.: The global carbon cycle in the Canadian Earth system
model (CanESM1): Preindustrial control simulation, J. Geophys.
Res., 115, G03014, https://doi.org/10.1029/2008JG000920, 2010. a
Claret, M., Galbraith, E. D., Palter, J. B., Bianchi, D., Fennel, K., Gilbert, D., and Dunne, J. P.: Rapid coastal deoxygenation due to ocean circulation shift in the northwest Atlantic, Nat. Clim. Change, 8, 868–872, https://doi.org/10.1038/s41558-018-0263-1, 2018. a
Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran, P.,
Hinton, T., Hughes, J., Jones, C. D., Joshi, M., Liddicoat, S., Martin, G.,
O'Connor, F., Rae, J., Senior, C., Sitch, S., Totterdell, I., Wiltshire, A.,
and Woodward, S.: Development and evaluation of an Earth-System model –
HadGEM2, Geosci. Model Dev., 4, 1051–1075,
https://doi.org/10.5194/gmd-4-1051-2011, 2011. a
Danabasoglu, G., Lamarque, J., Bacmeister, J., Bailey, D. A., DuVivier, A. K.,
Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., Hannay,
C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M.,
Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R.,
Oleson, K. W., Otto‐Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S.,
Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer,
C., Fox‐Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson,
V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L.,
Rasch, P. J., and Strand, W. G.: The Community Earth System Model Version 2
(CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020. a, b
Donlon, C. J., Martin, M., Stark, J., Roberts-Jones, J., Fiedler, E., and
Wimmer, W.: The Operational Sea Surface Temperature and Sea Ice Analysis
(OSTIA) system, Remote Sens. Environ., 116, 140–158,
https://doi.org/10.1016/j.rse.2010.10.017, 2012. a
Ducklow, H. and McCallister, S.: The biogeochemistry of carbon dioxide in the coastal oceans, in: The Sea, Vol 13: The global coastal ocean. Multiscale interdisciplinary processes, edited by: Robinson, A. R. and Brink, K. H., John Wiley & Sons, New York, 269–315, 2004. a
Dufresne, J. L., Foujols, M. a., Denvil, S., Caubel, a., Marti, O., Aumont, O.,
Balkanski, Y., Bekki, S., Bellenger, H., Benshila, R., Bony, S., Bopp, L.,
Braconnot, P., Brockmann, P., Cadule, P., Cheruy, F., Codron, F., Cozic, a.,
Cugnet, D., de Noblet, N., Duvel, J. P., Ethé, C., Fairhead, L.,
Fichefet, T., Flavoni, S., Friedlingstein, P., Grandpeix, J. Y., Guez, L.,
Guilyardi, E., Hauglustaine, D., Hourdin, F., Idelkadi, a., Ghattas, J.,
Joussaume, S., Kageyama, M., Krinner, G., Labetoulle, S., Lahellec, a.,
Lefebvre, M. P., Lefevre, F., Levy, C., Li, Z. X., Lloyd, J., Lott, F.,
Madec, G., Mancip, M., Marchand, M., Masson, S., Meurdesoif, Y., Mignot, J.,
Musat, I., Parouty, S., Polcher, J., Rio, C., Schulz, M., Swingedouw, D.,
Szopa, S., Talandier, C., Terray, P., Viovy, N., and Vuichard, N.: Climate
change projections using the IPSL-CM5 Earth System Model: From CMIP3 to
CMIP5, Vol. 40, https://doi.org/10.1007/s00382-012-1636-1, 2013. a
Dunne, J. P.: Technical description of Tracers of Ocean Phytoplankton with
Allometric Zooplankton version 2 (TOPAZ2) used in GFDL's ESM2M and ESM2G
submitted as part of the coupled model intercomparison project phase 5,
Tech. rep., https://doi.org/10.1175/JCLI-D-12-00150.s1, 2013. a
Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W.,
Shevliakova, E., Stouffer, R. J., Cooke, W., Dunne, K. A., Harrison, M. J.,
Krasting, J. P., Malyshev, S. L., Milly, P. C. D., Phillipps, P. J., Sentman,
L. T., Samuels, B. L., Spelman, M. J., Winton, M., Wittenberg, A. T., and
Zadeh, N.: GFDL's ESM2 Global Coupled Climate–Carbon Earth System Models.
Part I: Physical Formulation and Baseline Simulation Characteristics,
J. Climate, 25, 6646–6665, https://doi.org/10.1175/JCLI-D-11-00560.1, 2012. a
Dunne, J. P., John, J. G., Shevliakova, E., Stouffer, R. J., Krasting, J. P.,
Malyshev, S. L., Milly, P. C. D., Sentman, L. T., Adcroft, A. J., Cooke, W.,
Dunne, K. A., Griffies, S. M., Hallberg, R. W., Harrison, M. J., Levy, H.,
Wittenberg, A. T., Phillips, P. J., and Zadeh, N.: GFDL's ESM2 Global
Coupled Climate–Carbon Earth System Models, Part II: Carbon System
Formulation and Baseline Simulation Characteristics*, J. Climate,
26, 2247–2267, https://doi.org/10.1175/JCLI-D-12-00150.1, 2013. a
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. a, b
Fennel, K., Wilkin, J., Levin, J., Moisan, J., O'Reilly, J., and Haidvogel, D.: Nitrogen cycling in the Middle Atlantic Bight: Results from a
three-dimensional model and implications for the North Atlantic nitrogen
budget, Global Biogeochem. Cy., 20, GB3007,
https://doi.org/10.1029/2005GB002456, 2006. a, b, c, d
Fennel, K., Wilkin, J., Previdi, M., and Najjar, R.: Denitrification effects
on air-sea 2 flux in the coastal ocean: Simulations for the
northwest North Atlantic, Geophys. Res. Lett., 35, L24608,
https://doi.org/10.1029/2008GL036147, 2008. a
Fennel, K., Hu, J., Laurent, A., Marta-Almeida, M., and Hetland, R.:
Sensitivity of hypoxia predictions for the northern Gulf of Mexico to
sediment oxygen consumption and model nesting, J. Geophys.
Res.-Oceans, 118, 990–1002, https://doi.org/10.1002/jgrc.20077, 2013. a
Fennel, K., Alin, S., Barbero, L., Evans, W., Bourgeois, T., Cooley, S., Dunne, J., Feely, R. A., Hernandez-Ayon, J. M., Hu, X., Lohrenz, S., Muller-Karger, F., Najjar, R., Robbins, L., Shadwick, E., Siedlecki, S., Steiner, N., Sutton, A., Turk, D., Vlahos, P., and Wang, Z. A.: Carbon cycling in the North American coastal ocean: a synthesis, Biogeosciences, 16, 1281–1304, https://doi.org/10.5194/bg-16-1281-2019, 2019. a
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Zweng, M. M.,
Baranova, O. K., and Johnson, D. R.: World Ocean Atlas 2009, Volume 4:
Nutrients (phosphate, nitrate, silicate), U.S. Government Printing Office,
Washington, D.C., NOAA Atlas edn., 2010. a
Garcia, H. E., Locarnini, R. A., Boyer, T. P., Antonov, J. I., Baranova, O. K., Zweng, M. M., Reagan, J. R., and Johnson, D.: World Ocean Atlas 2013, Volume 4: Dissolved Inorganic Nutrients (phosphate, nitrate, silicate), edited by: Levitus, S. and Mishonov, A., NOAA Atlas NESDIS 76, 2014. a
Gilbert, D., Sundby, B., Gobeil, C., Mucci, A., and Tremblay, G.-H.: A
seventy-two-year record of diminishing deep-water oxygen in the St. Lawrence estuary: The northwest Atlantic connection, Limnol. Oceanogr., 50, 1654–1666, https://doi.org/10.4319/lo.2005.50.5.1654, 2005. a
Gilbert, D., Rabalais, N. N., Díaz, R. J., and Zhang, J.: Evidence for greater oxygen decline rates in the coastal ocean than in the open ocean, Biogeosciences, 7, 2283–2296, https://doi.org/10.5194/bg-7-2283-2010, 2010. a
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J.,
Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak,
K., Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh,
L., Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D.,
Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H.,
Schnur, R., Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C.,
Wegner, J., Widmann, H., Wieners, K.-H., Claussen, M., Marotzke, J., and
Stevens, B.: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM
simulations for the Coupled Model Intercomparison Project phase 5, J. Adv. Model. Earth Syst., 5, 572–597, https://doi.org/10.1002/jame.20038,
2013. a
Greenan, B., Petrie, B., Harrison, W., and Oakey, N.: Are the spring and fall blooms on the Scotian Shelf related to short-term physical events?,
Continental Shelf Res., 24, 603–625, https://doi.org/10.1016/j.csr.2003.11.006,
2004. a
Greenan, B. J. W., Petrie, B. D., Harrison, W. G., and Strain, P. M.: The
onset and evolution of a spring bloom on the Scotian Shelf, 53, 1759–1775, 2008. a
Greenan, B. J. W., Shackell, N. L., Ferguson, K., Greyson, P., Cogswell, A.,
Brickman, D., Wang, Z., Cook, A., Brennan, C. E., and Saba, V. S.: Climate
Change Vulnerability of American Lobster Fishing Communities in Atlantic
Canada, Front. Mar. Sci., 6, 579, https://doi.org/10.3389/fmars.2019.00579,
2019. a
Gruber, N., Hauri, C., Lachkar, Z., Loher, D., Frolicher, T. L., and Plattner, G.-K.: Rapid Progression of Ocean Acidification in the California Current System, Science, 337, 220–223, https://doi.org/10.1126/science.1216773, 2012. a
Haidvogel, D. B., Arango, H., Budgell, W. P., Cornuelle, B. D., Curchitser, E.,
Lorenzo, E. D., Fennel, K., Geyer, W. R., Hermann, A. J., Lanerolle, L.,
Levin, J., McWilliams, J. C., Miller, A. J., Moore, A. M., Powell, T. M.,
Shchepetkin, A. F., Sherwood, C. R., Signell, R. P., Warner, J. C., and
Wilkin, J.: Ocean forecasting in terrain-following coordinates: Formulation and skill assessment of the Regional Ocean Modeling System, J. Comput. Phys., 227, 3595–3624, https://doi.org/10.1016/j.jcp.2007.06.016, 2008. a
Hajima, T., Watanabe, M., Yamamoto, A., Tatebe, H., Noguchi, M. A., Abe, M.,
Ohgaito, R., Ito, A., Yamazaki, D., Okajima, H., Ito, A., Takata, K., Ogochi,
K., Watanabe, S., and Kawamiya, M.: Development of the MIROC-ES2L Earth
system model and the evaluation of biogeochemical processes and feedbacks,
Geosci. Model Dev., 13, 2197–2244,
https://doi.org/10.5194/gmd-13-2197-2020, 2020. a
Hermann, A. J., Gibson, G. A., Bond, N. A., Curchitser, E. N., Hedstrom, K.,
Cheng, W., Wang, M., Cokelet, E. D., Stabeno, P. J., and Aydin, K.:
Projected future biophysical states of the Bering Sea, Deep Sea Research
Pt. II, 134, 30–47, https://doi.org/10.1016/j.dsr2.2015.11.001, 2016. a
Hermann, A. J., Gibson, G. A., Cheng, W., Ortiz, I., Aydin, K., Wang, M.,
Hollowed, A. B., and Holsman, K. K.: Projected biophysical conditions of the Bering Sea to 2100 under multiple emission scenarios, ICES J. Mar. Sci., 76, 1937–1937, https://doi.org/10.1093/icesjms/fsz111, 2019. a
Holt, J., Harle, J., Proctor, R., Michel, S., Ashworth, M., Batstone, C.,
Allen, I., Holmes, R., Smyth, T., Haines, K., Bretherton, D., and Smith, G.: Modelling the global coastal ocean, Philos. T. Roy. Soc. A, 367, 939–951, https://doi.org/10.1098/rsta.2008.0210, 2009. a
Holt, J., Schrum, C., Cannaby, H., Daewel, U., Allen, I., Artioli, Y., Bopp,
L., Butenschon, M., Fach, B. A., Harle, J., Pushpadas, D., Salihoglu, B., and Wakelin, S.: Potential impacts of climate change on the primary production of regional seas: A comparative analysis of five European seas, Prog. Oceanogr., 140, 91–115, https://doi.org/10.1016/j.pocean.2015.11.004, 2016. a, b
Holt, J., Hyder, P., Ashworth, M., Harle, J., Hewitt, H. T., Liu, H., New, A. L., Pickles, S., Porter, A., Popova, E., Allen, J. I., Siddorn, J., and Wood, R.: Prospects for improving the representation of coastal and shelf seas in global ocean models, Geosci. Model Dev., 10, 499–523, https://doi.org/10.5194/gmd-10-499-2017, 2017. a, b, c, d
Ilyina, T., Six, K. D., Segschneider, J., Maier-Reimer, E., Li, H., and
Núñez-Riboni, I.: Global ocean biogeochemistry model HAMOCC:
Model architecture and performance as component of the MPI-Earth system model
in different CMIP5 experimental realizations, J. Adv.
Model. Earth Syst., 5, 287–315, https://doi.org/10.1029/2012MS000178, 2013. a
Kuhn, A. M. and Fennel, K.: Evaluating ecosystem model complexity for the
northwest North Atlantic through surrogate-based optimization, Ocean
Model., 142, 101437, https://doi.org/10.1016/j.ocemod.2019.101437, 2019. a, b
Kwiatkowski, L., Torres, O., Bopp, L., Aumont, O., Chamberlain, M., Christian, J. R., Dunne, J. P., Gehlen, M., Ilyina, T., John, J. G., Lenton, A., Li, H., Lovenduski, N. S., Orr, J. C., Palmieri, J., Santana-Falcón, Y., Schwinger, J., Séférian, R., Stock, C. A., Tagliabue, A., Takano, Y., Tjiputra, J., Toyama, K., Tsujino, H., Watanabe, M., Yamamoto, A., Yool, A., and Ziehn, T.: Twenty-first century ocean warming, acidification, deoxygenation, and upper-ocean nutrient and primary production decline from CMIP6 model projections, Biogeosciences, 17, 3439–3470, https://doi.org/10.5194/bg-17-3439-2020, 2020. a
Lachkar, Z. and Gruber, N.: What controls biological production in coastal upwelling systems? Insights from a comparative modeling study, Biogeosciences, 8, 2961–2976, https://doi.org/10.5194/bg-8-2961-2011, 2011. a
Laruelle, G. G., Cai, W.-J., Hu, X., Gruber, N., Mackenzie, F. T., and Regnier, P.: Continental shelves as a variable but increasing global sink for atmospheric carbon dioxide, Nat. Commun., 9, 454,
https://doi.org/10.1038/s41467-017-02738-z, 2018. a
Laurent, A. and Fennel, K.: Regional model (ACM) data used for the evaluation and ranking of historical Earth System Model simulations in the northwest North Atlantic Ocean (Laurent et al., 2021, Biogeosciences), Zenodo, https://doi.org/10.5281/zenodo.4562357, 2021. a
Laurent, A., Fennel, K., Ko, D. S., and Lehrter, J.: Climate Change Projected to Exacerbate Impacts of Coastal Eutrophication in the Northern Gulf of Mexico, J. Geophys. Res.-Oceans, 123, 3408–3426,
https://doi.org/10.1002/2017JC013583, 2018. a, b
Lavoie, D., Lambert, N., Rousseau, S., Dumas, J., Chassé, J., Long, Z.,
Perrie, W., Starr, M., Brickman, D., and Azetsu-Scott, K.: Projections of
future physical and biogeochemical conditions in the Gulf of St. Lawrence,
on the Scotian Shelf and in the Gulf of Maine, Can. Tech. Rep. Hydrogr.
Ocean Sci., 334, available at: https://science-catalogue.canada.ca/record=b4019914~S6, 2020. a, b
Lindsay, K., Bonan, G. B., Doney, S. C., Hoffman, F. M., Lawrence, D. M., Long,
M. C., Mahowald, N. M., Keith Moore, J., Randerson, J. T., and Thornton,
P. E.: Preindustrial-Control and Twentieth-Century Carbon Cycle Experiments
with the Earth System Model CESM1(BGC), J. Climate, 27, 8981–9005,
https://doi.org/10.1175/JCLI-D-12-00565.1, 2014. a
Loder, J. W., van der Baaren, A., and Yashayaev, I.: Climate Comparisons and
Change Projections for the Northwest Atlantic from Six CMIP5 Models,
Atmos.-Ocean, 53, 529–555, https://doi.org/10.1080/07055900.2015.1087836, 2015. a, b, c, d
Mattern, J. P. and Edwards, C. A.: Simple parameter estimation for complex
models — Testing evolutionary techniques on 3-dimensional biogeochemical
ocean models, J. Marine Syst., 165, 139–152,
https://doi.org/10.1016/j.jmarsys.2016.10.012, 2017. a
McKiver, W. J., Vichi, M., Lovato, T., Storto, A., and Masina, S.: Impact of
increased grid resolution on global marine biogeochemistry, J.
Marine Syst., 147, 153–168, https://doi.org/10.1016/j.jmarsys.2014.10.003, 2015. a
Moore, J. K., Lindsay, K., Doney, S. C., Long, M. C., and Misumi, K.: Marine
Ecosystem Dynamics and Biogeochemical Cycling in the Community Earth System
Model [CESM1(BGC)]: Comparison of the 1990s with the 2090s under the RCP4.5
and RCP8.5 Scenarios, J. Climate, 26, 9291–9312,
https://doi.org/10.1175/JCLI-D-12-00566.1, 2013. a
Müller, W. A., Jungclaus, J. H., Mauritsen, T., Baehr, J., Bittner, M.,
Budich, R., Bunzel, F., Esch, M., Ghosh, R., Haak, H., Ilyina, T., Kleine,
T., Kornblueh, L., Li, H., Modali, K., Notz, D., Pohlmann, H., Roeckner, E.,
Stemmler, I., Tian, F., and Marotzke, J.: A Higher-resolution Version of the
Max Planck Institute Earth System Model (MPI-ESM1.2-HR), J. Adv. in Model. Earth Sy., 10, 1383–1413, https://doi.org/10.1029/2017MS001217, 2018. a, b, c
Muller-Karger, F. E.: The importance of continental margins in the global
carbon cycle, Geophys. Res. Lett., 32, L01602,
https://doi.org/10.1029/2004GL021346, 2005. a
Palmer, J. and Totterdell, I.: Production and export in a global ocean
ecosystem model, Deep-Sea Res. P.t I,
48, 1169–1198, https://doi.org/10.1016/S0967-0637(00)00080-7, 2001. a
Peña, M. A., Fine, I., and Callendar, W.: Interannual variability in
primary production and shelf-offshore transport of nutrients along the
northeast Pacific Ocean margin, Deep Sea Research Pt. II, 169–170, 104637, https://doi.org/10.1016/j.dsr2.2019.104637, 2019. a
Romanou, A., Gregg, W., Romanski, J., Kelley, M., Bleck, R., Healy, R.,
Nazarenko, L., Russell, G., Schmidt, G., Sun, S., and Tausnev, N.: Natural
air–sea flux of 2 in simulations of the NASA-GISS climate
model: Sensitivity to the physical ocean model formulation, Ocean Model.,
66, 26–44, https://doi.org/10.1016/j.ocemod.2013.01.008, 2013. a
Ross, T., Craig, S. E., Comeau, A., Davis, R., Dever, M., and Beck, M.: Blooms and subsurface phytoplankton layers on the Scotian Shelf: Insights from profiling gliders, J. Marine Syst., 172, 118–127,
https://doi.org/10.1016/j.jmarsys.2017.03.007, 2017. a
Rousseaux, C. S. and Gregg, W. W.: Recent decadal trends in global
phytoplankton composition, Global Biogeochem. Cy., 29, 1674–1688,
https://doi.org/10.1002/2015GB005139, 2015. a
Rutherford, K. and Fennel, K.: Diagnosing transit times on the northwestern North Atlantic continental shelf, Ocean Sci., 14, 1207–1221, https://doi.org/10.5194/os-14-1207-2018, 2018. a, b, c, d
Saba, V. S., Griffies, S. M., Anderson, W. G., Winton, M., Alexander, M. A.,
Delworth, T. L., Hare, J. A., Harrison, M. J., Rosati, A., Vecchi, G. A., and
Zhang, R.: Enhanced warming of the Northwest Atlantic Ocean under climate
change, J. Geophys. Res.-Oceans, 121, 118–132,
https://doi.org/10.1002/2015JC011346, 2016. a, b, c, d
Schmidt, G. A., Kelley, M., Nazarenko, L., Ruedy, R., Russell, G. L., Aleinov,
I., Bauer, M., Bauer, S. E., Bhat, M. K., Bleck, R., Canuto, V., Chen, Y.-H.,
Cheng, Y., Clune, T. L., Del Genio, A., de Fainchtein, R., Faluvegi, G.,
Hansen, J. E., Healy, R. J., Kiang, N. Y., Koch, D., Lacis, A. A., LeGrande,
A. N., Lerner, J., Lo, K. K., Matthews, E. E., Menon, S., Miller, R. L.,
Oinas, V., Oloso, A. O., Perlwitz, J. P., Puma, M. J., Putman, W. M., Rind,
D., Romanou, A., Sato, M., Shindell, D. T., Sun, S., Syed, R. A., Tausnev,
N., Tsigaridis, K., Unger, N., Voulgarakis, A., Yao, M.-S., and Zhang, J.:
Configuration and assessment of the GISS ModelE2 contributions to the CMIP5
archive, J. Adv. Model. Earth Syst., 6, 141–184,
https://doi.org/10.1002/2013MS000265, 2014. a
Schneider, B., Bopp, L., Gehlen, M., Segschneider, J., Frölicher, T. L., Cadule, P., Friedlingstein, P., Doney, S. C., Behrenfeld, M. J., and Joos, F.: Climate-induced interannual variability of marine primary and export production in three global coupled climate carbon cycle models, Biogeosciences, 5, 597–614, https://doi.org/10.5194/bg-5-597-2008, 2008. a, b
SeaWiFS 2018: NASA Goddard Space Flight Center, Ocean Ecology Laboratory,
Ocean Biology Processing Group. Sea-viewing Wide Field-of-view Sensor
(SeaWiFS) Chlorophyll Data; 2018 Reprocessing, NASA OB, DAAC, Greenbelt, MD, USA, https://doi.org/10.5067/ORBVIEW-2/SEAWIFS/L3M/CHL/2018. a
Séférian, R., Nabat, P., Michou, M., Saint‐Martin, D., Voldoire,
A., Colin, J., Decharme, B., Delire, C., Berthet, S., Chevallier, M.,
Sénési, S., Franchisteguy, L., Vial, J., Mallet, M., Joetzjer,
E., Geoffroy, O., Guérémy, J., Moine, M., Msadek, R., Ribes, A., Rocher, M., Roehrig, R., Salas‐y‐Mélia, D., Sanchez, E., Terray,
L., Valcke, S., Waldman, R., Aumont, O., Bopp, L., Deshayes, J.,
Éthé, C., and Madec, G.: Evaluation of CNRM Earth System Model, CNRM‐ESM2‐1: Role of Earth System Processes in Present‐Day and Future
Climate, J. Adv. Model. Earth Sy., 11, 2019MS001791,
https://doi.org/10.1029/2019MS001791, 2019. a, b
Seitzinger, S. P. and Giblin, A. E.: Estimating denitrification in North
Atlantic continental shelf sediments, Biogeochemistry, 35, 235–260,
https://doi.org/10.1007/BF02179829, 1996. a
Sellar, A. A., Jones, C. G., Mulcahy, J., Tang, Y., Yool, A., Wiltshire, A.,
O'Connor, F. M., Stringer, M., Hill, R., Palmieri, J., Woodward, S., Mora,
L., Kuhlbrodt, T., Rumbold, S., Kelley, D. I., Ellis, R., Johnson, C. E.,
Walton, J., Abraham, N. L., Andrews, M. B., Andrews, T., Archibald, A. T.,
Berthou, S., Burke, E., Blockley, E., Carslaw, K., Dalvi, M., Edwards, J.,
Folberth, G. A., Gedney, N., Griffiths, P. T., Harper, A. B., Hendry, M. A.,
Hewitt, A. J., Johnson, B., Jones, A., Jones, C. D., Keeble, J., Liddicoat,
S., Morgenstern, O., Parker, R. J., Predoi, V., Robertson, E., Siahaan, A.,
Smith, R. S., Swaminathan, R., Woodhouse, M. T., Zeng, G., and Zerroukat, M.:
UKESM1: Description and evaluation of the UK Earth System Model, J.
Adv. Model. Earth Syst., p. 2019MS001739,
https://doi.org/10.1029/2019MS001739, 2019. a
Siedlecki, S. A., Banas, N. S., Davis, K. A., Giddings, S., Hickey, B. M.,
MacCready, P., Connolly, T., and Geier, S.: Seasonal and interannual oxygen variability on the Washington and Oregon continental shelves, J.
Geophys. Res.-Oceans, 120, 608–633, https://doi.org/10.1002/2014JC010254,
2015. a
Stock, C. A., Dunne, J. P., Fan, S., Ginoux, P., John, J., Krasting, J. P.,
Laufkötter, C., Paulot, F., and Zadeh, N.: Ocean Biogeochemistry in
GFDL's Earth System Model 4.1 and Its Response to Increasing Atmospheric2, J. Adv. Model. Earth Syst., 12,
https://doi.org/10.1029/2019MS002043, 2020. a
Stortini, C. H., Shackell, N. L., Tyedmers, P., and Beazley, K.: Assessing
marine species vulnerability to projected warming on the Scotian Shelf,
Canada, ICES J. Mar. Sci., 72, 1731–1743,
https://doi.org/10.1093/icesjms/fsv022, 2015. a, b
Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Hanna, S., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Sigmond, M., Solheim, L., von Salzen, K., Yang, D., and Winter, B.: The Canadian Earth System Model version 5 (CanESM5.0.3), Geosci. Model Dev., 12, 4823–4873, https://doi.org/10.5194/gmd-12-4823-2019, 2019. a
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and the Experiment Design, B. Am. Meteor. Soc., 93,
485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012. a, b
Tjiputra, J. F., Roelandt, C., Bentsen, M., Lawrence, D. M., Lorentzen, T.,
Schwinger, J., Seland, Ø., and Heinze, C.: Evaluation of the carbon cycle
components in the Norwegian Earth System Model (NorESM), Geosci. Model
Dev., 6, 301–325, https://doi.org/10.5194/gmd-6-301-2013, 2013. a
UK Met Office 2005: OSTIA L4 SST Analysis, Ver. 1.0. PO. DAAC, CA, USA,
https://doi.org/10.5067/GHOST-4FK01, 2005. a
Urrego-Blanco, J. and Sheng, J.: Interannual Variability of the Circulation
over the Eastern Canadian Shelf, Atmos.-Ocean, 50, 277–300,
https://doi.org/10.1080/07055900.2012.680430, 2012. a
Vichi, M., Masina, S., and Navarra, a.: A generalized model of pelagic
biogeochemistry for the global ocean ecosystem. Part II: Numerical
simulations, J. Mar. Syst., 64, 110–134,
https://doi.org/10.1016/j.jmarsys.2006.03.014, 2007a. a
Vichi, M., Pinardi, N., and Masina, S.: A generalized model of pelagic
biogeochemistry for the global ocean ecosystem, Part I: Theory, J.
Mar. Syst., 64, 89–109, https://doi.org/10.1016/j.jmarsys.2006.03.006,
2007b.
a
Vichi, M., Manzini, E., Fogli, P. G., Alessandri, A., Patara, L., Scoccimarro,
E., Masina, S., and Navarra, A.: Global and regional ocean carbon uptake and
climate change: sensitivity to a substantial mitigation scenario, Clim.
Dynam., 37, 1929–1947, https://doi.org/10.1007/s00382-011-1079-0, 2011. a
Voldoire, A., Sanchez-Gomez, E., Salas y Mélia, D., Decharme, B.,
Cassou, C., Sénési, S., Valcke, S., Beau, I., Alias, A.,
Chevallier, M., Déqué, M., Deshayes, J., Douville, H., Fernandez,
E., Madec, G., Maisonnave, E., Moine, M.-P., Planton, S., Saint-Martin, D.,
Szopa, S., Tyteca, S., Alkama, R., Belamari, S., Braun, A., Coquart, L., and
Chauvin, F.: The CNRM-CM5.1 global climate model: description and basic
evaluation, Clim. Dynam., 40, 2091–2121,
https://doi.org/10.1007/s00382-011-1259-y, 2013. a
Walsh, J. J.: Importance of continental margins in the marine biogeochemical
cycling of carbon and nitrogen, Nature, 350, 53–55, 1991. a
Wilson, K. and Lotze, H.: Climate change projections reveal range shifts of
eelgrass Zostera marina in the Northwest Atlantic, Mar. Ecol. Prog.
Ser., 620, 47–62, https://doi.org/10.3354/meps12973, 2019. a
Wilson, K. L., Skinner, M. A., and Lotze, H. K.: Projected 21st‐century
distribution of canopy‐forming seaweeds in the Northwest Atlantic with
climate change, Divers. Distrib., 25, 582–602,
https://doi.org/10.1111/ddi.12897, 2019. a
Yool, A., Popova, E. E., and Anderson, T. R.: MEDUSA-2.0: an intermediate
complexity biogeochemical model of the marine carbon cycle for climate change
and ocean acidification studies, Geosci. Model Dev., 6,
1767–1811, https://doi.org/10.5194/gmd-6-1767-2013, 2013. a
Zhang, H., Fennel, K., Laurent, A., and Bian, C.: A numerical model study of the main factors contributing to hypoxia and its interannual and short-term variability in the East China Sea, Biogeosciences, 17, 5745–5761, https://doi.org/10.5194/bg-17-5745-2020, 2020. a
Zweng, M. M., Reagan, J. R., Antonov, J. I., Locarnini, R. A., Mishonov, A. V., Boyer, T. P., Garcia, H. E., Baranova, O. K., Johnson, D. R., Seidov, D., and Biddle, M. M.: World Ocean Atlas 2013, Volume 2: Salinity, edited by: Levitus, S. and Mishonov, A., NOAA Atlas NESDIS 74, USA, 2013. a
Short summary
CMIP5 and CMIP6 models, and a high-resolution regional model, were evaluated by comparing historical simulations with observations in the northwest North Atlantic, a climate-sensitive and biologically productive ocean margin region. Many of the CMIP models performed poorly for biological properties. There is no clear link between model resolution and skill in the global models, but there is an overall improvement in performance in CMIP6 from CMIP5. The regional model performed best.
CMIP5 and CMIP6 models, and a high-resolution regional model, were evaluated by comparing...
Altmetrics
Final-revised paper
Preprint