Articles | Volume 9, issue 2
https://doi.org/10.5194/os-9-377-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-9-377-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
The effect of various vertical discretization schemes and horizontal diffusion parameterization on the performance of a 3-D ocean model: the Black Sea case study
G. Shapiro
University of Plymouth, School of Marine Science and Engineering, Drake Circus, Plymouth, PL4 8AA, UK
M. Luneva
National Oceanography Centre Liverpool, Joseph Proudman Building, 6 Brownlow Street, Liverpool, L3 5DA, UK
J. Pickering
University of Plymouth, School of Marine Science and Engineering, Drake Circus, Plymouth, PL4 8AA, UK
D. Storkey
Met Office, Fitzroy Road, Exeter, Devon, EX1 3PB ,UK
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EGUsphere, https://doi.org/10.5194/egusphere-2024-1737, https://doi.org/10.5194/egusphere-2024-1737, 2024
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In this paper we review marine data assimilation (MDA) in the UK, its stakeholders, needs, past and present developments in different areas of UK MDA, and offer a vision for their longer future. The specific areas covered are ocean physics and sea ice, marine biogeochemistry, coupled MDA, MDA informing observing network design and MDA theory. We also discuss future vision for MDA resources: observations, software, hardware and people skills.
Georgy I. Shapiro and Jose M. Gonzalez-Ondina
Ocean Sci. Discuss., https://doi.org/10.5194/os-2021-77, https://doi.org/10.5194/os-2021-77, 2021
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An effective method is developed for data assimilation in a high-resolution (child) ocean model in the case when the output from a coarse-resolution data-assimilating model (parent) is available. The basic idea is to assimilate data from the coarser model instead of actual observations. The method named Data Assimilation with Stochastic-Deterministic Downscaling (SDDA) does not allow the child model to drift away from reality as it is indirectly controlled by observations via the parent model.
Georgy I. Shapiro, Jose M. Gonzalez-Ondina, and Vladimir N. Belokopytov
Ocean Sci., 17, 891–907, https://doi.org/10.5194/os-17-891-2021, https://doi.org/10.5194/os-17-891-2021, 2021
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This paper presents an efficient method for high-resolution ocean modelling based on a combination of the deterministic and stochastic approaches. The method utilises mathematical tools similar to those developed for data assimilation in ocean modelling. The main difference is that instead of assimilating a relatively small number of observations, the SDD method assimilates all the data produced by a parent model. The method is applied to create an operational Stochastic Model of the Red Sea.
F. Wobus, G. I. Shapiro, J. M. Huthnance, M. A. M. Maqueda, and Y. Aksenov
Ocean Sci., 9, 885–899, https://doi.org/10.5194/os-9-885-2013, https://doi.org/10.5194/os-9-885-2013, 2013
Davi Mignac, Jennifer Waters, Daniel J. Lea, Matthew J. Martin, James While, Anthony T. Weaver, Arthur Vidard, Catherine Guiavarc’h, Dave Storkey, David Ford, Edward W. Blockley, Jonathan Baker, Keith Haines, Martin R. Price, Michael J. Bell, and Richard Renshaw
EGUsphere, https://doi.org/10.5194/egusphere-2024-3143, https://doi.org/10.5194/egusphere-2024-3143, 2024
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We describe major improvements of the Met Office's global ocean-sea ice forecasting system. The models and the way observations are used to improve the forecasts were changed, which led to a significant error reduction of 1-day forecasts. The new system performance in past conditions, where sub-surface observations are scarce, was improved with more consistent ocean heat content estimates. The new system will be of better use for climate studies and will provide improved forecasts for end users.
David Storkey, Pierre Mathiot, Michael J. Bell, Dan Copsey, Catherine Guiavarc'h, Helene T. Hewitt, Jeff Ridley, and Malcolm J. Roberts
EGUsphere, https://doi.org/10.5194/egusphere-2024-1414, https://doi.org/10.5194/egusphere-2024-1414, 2024
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The Southern Ocean is a key region of the world ocean in the context of climate change studies. We show that the HadGEM3 coupled model with intermediate ocean resolution struggles to accurately simulate the Southern Ocean. Increasing the frictional drag that the sea floor exerts on ocean currents, and introducing a representation of unresolved ocean eddies both appear to reduce the large-scale biases in this model.
Jozef Skakala, David Ford, Keith Haines, Amos Lawless, Matthew Martin, Philip Browne, Marcin Chrust, Stefano Ciavatta, Alison Fowler, Daniel Lea, Matthew Palmer, Andrea Rochner, Jennifer Waters, Hao Zuo, Mike Bell, Davi Carneiro, Yumeng Chen, Susan Kay, Dale Partridge, Martin Price, Richard Renshaw, Georgy Shapiro, and James While
EGUsphere, https://doi.org/10.5194/egusphere-2024-1737, https://doi.org/10.5194/egusphere-2024-1737, 2024
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In this paper we review marine data assimilation (MDA) in the UK, its stakeholders, needs, past and present developments in different areas of UK MDA, and offer a vision for their longer future. The specific areas covered are ocean physics and sea ice, marine biogeochemistry, coupled MDA, MDA informing observing network design and MDA theory. We also discuss future vision for MDA resources: observations, software, hardware and people skills.
Catherine Guiavarc'h, Dave Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene T. Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
EGUsphere, https://doi.org/10.5194/egusphere-2024-805, https://doi.org/10.5194/egusphere-2024-805, 2024
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GOSI9 is the new UK’s hierarchy of global ocean and sea ice models. Developed as part of a collaboration between several UK research institutes it will be used for various applications such as weather forecast and climate prediction. The models, based on NEMO, are available at three resolutions 1°, ¼° and 1/12°. GOSI9 improves upon previous version by reducing global temperature and salinity biases and enhancing the representation of the Arctic sea ice and of the Antarctic Circumpolar Current.
Georgy I. Shapiro and Jose M. Gonzalez-Ondina
Ocean Sci. Discuss., https://doi.org/10.5194/os-2021-77, https://doi.org/10.5194/os-2021-77, 2021
Preprint withdrawn
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An effective method is developed for data assimilation in a high-resolution (child) ocean model in the case when the output from a coarse-resolution data-assimilating model (parent) is available. The basic idea is to assimilate data from the coarser model instead of actual observations. The method named Data Assimilation with Stochastic-Deterministic Downscaling (SDDA) does not allow the child model to drift away from reality as it is indirectly controlled by observations via the parent model.
Georgy I. Shapiro, Jose M. Gonzalez-Ondina, and Vladimir N. Belokopytov
Ocean Sci., 17, 891–907, https://doi.org/10.5194/os-17-891-2021, https://doi.org/10.5194/os-17-891-2021, 2021
Short summary
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This paper presents an efficient method for high-resolution ocean modelling based on a combination of the deterministic and stochastic approaches. The method utilises mathematical tools similar to those developed for data assimilation in ocean modelling. The main difference is that instead of assimilating a relatively small number of observations, the SDD method assimilates all the data produced by a parent model. The method is applied to create an operational Stochastic Model of the Red Sea.
David Storkey, Adam T. Blaker, Pierre Mathiot, Alex Megann, Yevgeny Aksenov, Edward W. Blockley, Daley Calvert, Tim Graham, Helene T. Hewitt, Patrick Hyder, Till Kuhlbrodt, Jamie G. L. Rae, and Bablu Sinha
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We document the latest version of the shared UK global configuration of the
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models for the UK contribution to the IPCC 6th Assessment Report.
30-year integrations forced with atmospheric forcing show that the new
configurations have an improved simulation in the Southern Ocean with the
near-surface temperatures and salinities and the sea ice all matching the
observations more closely.
Helene T. Hewitt, Malcolm J. Roberts, Pat Hyder, Tim Graham, Jamie Rae, Stephen E. Belcher, Romain Bourdallé-Badie, Dan Copsey, Andrew Coward, Catherine Guiavarch, Chris Harris, Richard Hill, Joël J.-M. Hirschi, Gurvan Madec, Matthew S. Mizielinski, Erica Neininger, Adrian L. New, Jean-Christophe Rioual, Bablu Sinha, David Storkey, Ann Shelly, Livia Thorpe, and Richard A. Wood
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A modelling study of eddy-splitting by an island/seamount
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Influence of frontal cyclone evolution on the 2009 (Ekman) and 2010 (Franklin) Loop Current eddy detachment events
Modelling seasonal circulation and thermohaline structure of the Caspian Sea
Chaotic variability of the meridional overturning circulation on subannual to interannual timescales
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Motivated by eddy-splitting near Dongsha island, the eddy's trajectory and the effect of topography on eddy evolution were explored using the MITgcm. Warm eddies propagate to the southwest while cold eddies propagate to the northwest in open oceans. The results of the model indicate that the eddy would split in a qualitative range, and the location of the eddy split-off is related to the island size. In addition, eddy-splitting is an important way to transform energy between different scales.
C. Irrgang, J. Saynisch, and M. Thomas
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In this study, the influence of a spatio-temporally variable seawater conductivity on ocean-circulation-induced magnetic signals is investigated. To simulate the ocean-circulation-induced magnetic field, a combination of an ocean general circulation model (OMCT) and an electromagnetic induction model is used. It is found that a spatially varying seawater conductivity has a significant impact on the temporal variability of the induced magnetic field.
Y. S. Androulidakis, V. H. Kourafalou, and M. Le Hénaff
Ocean Sci., 10, 947–965, https://doi.org/10.5194/os-10-947-2014, https://doi.org/10.5194/os-10-947-2014, 2014
M. Gunduz and E. Özsoy
Ocean Sci., 10, 459–471, https://doi.org/10.5194/os-10-459-2014, https://doi.org/10.5194/os-10-459-2014, 2014
J. J.-M. Hirschi, A. T. Blaker, B. Sinha, A. Coward, B. de Cuevas, S. Alderson, and G. Madec
Ocean Sci., 9, 805–823, https://doi.org/10.5194/os-9-805-2013, https://doi.org/10.5194/os-9-805-2013, 2013
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