Articles | Volume 11, issue 2
https://doi.org/10.5194/gmd-11-681-2018
https://doi.org/10.5194/gmd-11-681-2018
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, Enda O'Dea, Jason Holt, Jeff Polton, Helene T. Hewitt, Rachel Furner, Karen Guihou, Ashley Brereton, Alex Arnold, Sarah Wakelin, Juan Manuel Castillo Sanchez, and C. Gabriela Mayorga Adame

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Cited articles

Aslam, T., Hall, R. A., and Dye, S. R.: Internal tides in a dendritic submarine canyon, Prog. Oceanogr., https://doi.org/10.1016/j.pocean.2017.10.005, in press, 2017.
Badin, G., Williams, R. G., Holt, J. T., and Fernand, L. J.: Are mesoscale eddies in shelf seas formed by baroclinic instability of tidal fronts?, J. Geophys. Res., 114, C10021, https://doi.org/10.1029/2009JC005340, 2009.
Batstone, C., Lawless, M., Tawn, J., Horsburgh, K., Blackman, D., McMillan, A., Worth, D., Laeger, S., and Hunt, T.: A UK best-practice approach for extreme sea level analysis along complex topographic coastlines, Ocean Eng., 71, 28–39, https://doi.org/10.1016/j.oceaneng.2013.02.003i, 2013.
Beckmann, A. C. and Döscher, R.: A Method for Improved Representation of Dense Water Spreading over Topography in Geopotential-Coordinate Models, J. Phys. Oceanogr., 27, 581–591, 1997.
Belcher, S., Grant, A., Hanley, K., Fox-Kemper, B., Van Roekel, L., Sullivan, P., Large, W., Brown, A., Hines, A., Calvert, D., Rutgersson, A., Pettersson, H., Bidlot, J.-R., Janssen, P., and Polton, J.: A global perspective on Langmuir turbulence in the ocean surface boundary layer, Geophys. Res. Lett., 39, L18605, https://doi.org/10.1029/2012gl052932, 2012.
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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.