Articles | Volume 11, issue 2
https://doi.org/10.5194/gmd-11-681-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/gmd-11-681-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
22 Feb 2018
Model description paper |
| 22 Feb 2018
AMM15: a new high-resolution NEMO configuration for operational simulation of the European north-west shelf
Jennifer A. Graham
CORRESPONDING AUTHOR
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
now at: Centre for Environment, Fisheries and Aquaculture Science, Pakefield Road, Lowestoft, NR33 0HT, UK
Enda O'Dea
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Jason Holt
National Oceanography Centre, Liverpool, L3 5DA, UK
Jeff Polton
National Oceanography Centre, Liverpool, L3 5DA, UK
Helene T. Hewitt
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Rachel Furner
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Karen Guihou
National Oceanography Centre, Liverpool, L3 5DA, UK
Departamento Oceanografía, Servicio de Hidrografía Naval, Buenos Aires, Argentina
Ashley Brereton
National Oceanography Centre, Liverpool, L3 5DA, UK
Alex Arnold
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
Sarah Wakelin
National Oceanography Centre, Liverpool, L3 5DA, UK
Juan Manuel Castillo Sanchez
Met Office, FitzRoy Road, Exeter, EX1 3PB, UK
C. Gabriela Mayorga Adame
National Oceanography Centre, Liverpool, L3 5DA, UK
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Preprint withdrawn
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Rachel Furner, Peter Haynes, Dave Munday, Brooks Paige, Daniel C. Jones, and Emily Shuckburgh
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Revised manuscript not accepted
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Traditional weather & climate models are built from physics-based equations, while data-driven models are built from patterns found in datasets using Machine Learning or statistics. There is growing interest in using data-driven models for weather & climate prediction, but confidence in their use depends on understanding the patterns they're finding. We look at this with a simple regression model of ocean temperature and see the patterns found by the regression model are similar to the physics.
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Short summary
This paper describes the next-generation ocean forecast model for the European NW shelf, AMM15 (Atlantic Margin Model, 1.5 km resolution). The current forecast system has a resolution of 7 km. While this is sufficient to represent large-scale circulation, many dynamical features (such as eddies, frontal jets, and internal tides) can only begin to be resolved at 0–1 km resolution. Here we introduce AMM15 and demonstrate its ability to represent the mean state and variability of the region.
This paper describes the next-generation ocean forecast model for the European NW shelf, AMM15...
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