This article describes the implementation of an incremental first guess at an appropriate time three‐dimensional variational (3DVAR) data assimilation scheme, NEMOVAR, in the Met Office's operational 1/4 degree global ocean model. NEMOVAR assimilates observations of sea‐surface temperature (SST), sea‐surface height (SSH), in situ temperature and salinity profiles and sea ice concentration. The Met Office is the first centre to implement NEMOVAR at 1/4 degree and the required developments are discussed, with particular focus on the specification of the background‐error covariances. Background‐error correlations in NEMOVAR are modelled using a diffusion operator. The horizontal background‐error correlations for temperature, salinity and sea ice concentration are parametrized using the Rossby radius, which produces relatively short correlation length‐scales at mid to high latitudes, while a flow‐dependent mixed‐layer depth parametrization is used to define the vertical length‐scales for the 3D variables. Results from a one‐year reanalysis with NEMOVAR are presented and compared with the preceding operational data assimilation scheme at the Met Office. NEMOVAR is shown to provide significant improvements to SST, SSH and sea ice concentration fields, with the largest improvements seen in regions of high variability such as eddy shedding and frontal regions and the marginal ice zone. This improvement is associated with shorter correlation length‐scales in the extratropics and an improved fit to observations in NEMOVAR. Some degradation to subsurface temperature and salinity fields where data are sparse is identified and this will be the focus of future improvements to the system.

Abstract. The Forecast Ocean Assimilation Model (FOAM) is an operational ocean analysis and forecast system run daily at the Met Office. FOAM provides modelling capability in both deep ocean and coastal shelf sea regimes using the NEMO (Nucleus for European Modelling of the Ocean) ocean model as its dynamical core. The FOAM Deep Ocean suite produces analyses and 7-day forecasts of ocean tracers, currents and sea ice for the global ocean at 1/4° resolution. Satellite and in situ observations of temperature, salinity, sea level anomaly and sea ice concentration are assimilated by FOAM each day over a 48 h observation window. The FOAM Deep Ocean configurations have recently undergone a major upgrade which has involved the implementation of a new variational, first guess at appropriate time (FGAT) 3D-Var, assimilation scheme (NEMOVAR); coupling to a different, multi-thickness-category, sea ice model (CICE); the use of coordinated ocean-ice reference experiment (CORE) bulk formulae to specify the surface boundary condition; and an increased vertical resolution for the global model. In this paper the new FOAM Deep Ocean system is introduced and details of the recent changes are provided. Results are presented from 2-year reanalysis integrations of the Global FOAM configuration including an assessment of short-range ocean forecast accuracy. Comparisons are made with both the previous FOAM system and a non-assimilative FOAM system. Assessments reveal considerable improvements in the new system to the near-surface ocean and sea ice fields. However there is some degradation to sub-surface tracer fields and in equatorial regions which highlights specific areas upon which to focus future improvements.

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A new coupled data assimilation (DA) system developed with the aim of improving the initialization of coupled forecasts for various time ranges from short range out to seasonal is introduced. The implementation here is based on a “weakly” coupled data assimilation approach whereby the coupled model is used to provide background information for separate ocean–sea ice and atmosphere–land analyses. The increments generated from these separate analyses are then added back into the coupled model. This is different from the existing Met Office system for initializing coupled forecasts, which uses ocean and atmosphere analyses that have been generated independently using the FOAM ocean data assimilation system and NWP atmosphere assimilation systems, respectively. A set of trials has been run to investigate the impact of the weakly coupled data assimilation on the analysis, and on the coupled forecast skill out to 5–10 days. The analyses and forecasts have been assessed by comparing them to observations and by examining differences in the model fields. Encouragingly for this new system, both ocean and atmospheric assessments show the analyses and coupled forecasts produced using coupled DA to be very similar to those produced using separate ocean–atmosphere data assimilation. This work has the benefit of highlighting some aspects on which to focus to improve the coupled DA results. In particular, improving the modeling and data assimilation of the diurnal SST variation and the river runoff should be examined.