The Met Office Forecast Ocean Assimilation Model (FOAM) using a 1/12‐degree grid for global forecasts

Barbosa Aguiar, Ana; Bell, Michael J.; Blockley, Edward; Calvert, Daley; Crocker, Richard; Inverarity, Gordon; King, Robert; Lea, Daniel J.; Maksymczuk, Jan; Martin, Matthew J.; Price, Martin R.; Siddorn, John ORCID: https://orcid.org/0000-0003-3848-8868; Smout‐Day, Kerry; Waters, Jennifer; While, James. 2024 The Met Office Forecast Ocean Assimilation Model (FOAM) using a 1/12‐degree grid for global forecasts. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.4798

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Official URL: http://dx.doi.org/10.1002/qj.4798

Abstract/Summary

The Met Office Forecast Ocean Assimilation Model (FOAM) ocean–sea-ice analysis and forecasting operational system has been using an ORCA tripolar grid with 1/4° horizontal grid spacing since December 2008. Surface boundary forcing is provided by numerical weather prediction fields from the operational global atmosphere Met Office Unified Model. We present results from a 2-year simulation using a 1/12° global ocean–sea-ice model configuration while keeping a 1/4° data assimilation (DA) set-up. We also describe recent operational data assimilation enhancements that are included in our 1/4° control and 1/12° simulations: a new bias-correction term for sea-level anomaly assimilation and a revised pressure correction algorithm. The primary effect of the first is to decrease the mean and variability of sea-level anomaly increments at high latitudes, whereas the second significantly reduces the vertical velocity standard deviation in the tropical Pacific. The level of improvement achieved with the higher resolution configuration is moderate but consistently satisfactory when measured using neighbourhood verification metrics that provide fairer quantitative comparisons between gridded model fields at different spatial resolutions than traditional root-mean-square metrics. A comparison of the eddy kinetic energy from each configuration and an observation-based product highlights the regions where further system developments are most needed.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1002/qj.4798
ISSN:	0035-9009
Additional Keywords:	1/12 degree grid, data assimilation, eddy kinetic energy, forecast, global, neighbourhood verification, ocean
Date made live:	24 Jul 2024 12:14 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/537760

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1002/qj.4798

ISSN:

0035-9009

Additional Keywords:

1/12 degree grid, data assimilation, eddy kinetic energy, forecast, global, neighbourhood verification, ocean

Date made live:

24 Jul 2024 12:14 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/537760