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

• Published in: Quarterly Journal of the Royal Meteorological Society
• Main Authors: 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, Smout‐Day, Kerry, Waters, Jennifer, While, James
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2024
• Subjects: Orca; Sea ice
• Online Access: http://nora.nerc.ac.uk/id/eprint/537760/; https://nora.nerc.ac.uk/id/eprint/537760/1/Quart%20J%20Royal%20Meteoro%20Soc%20-%202024%20-%20Barbosa%20Aguiar%20-%20The%20Met%20Office%20Forecast%20Ocean%20Assimilation%20Model%20%20FOAM%20%20using%20a%201.pdf; https://doi.org/10.1002/qj.4798

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.