Implementing a variational data assimilation system in an operational 1/4 degree global ocean model

Abstract

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.

Observing and modelling phytoplankton community structure in the North Sea

“…There are 51 vertical levels, using a hybrid σ -S coordinate system with the stretching function of Siddorn and Furner (2013). This uses terrain-following coordinates whilst ensuring a fixed surface resolution of 1 m. Remotely sensed and in situ observations of SST were assimilated using a 3D-Var implementation of the NEMOVAR data assimilation scheme (Waters et al, 2015;O'Dea et al, 2012). River inputs were taken from the E-HYPE model (Donnelly et al, 2015) for flow values, and from the same climatology as in Edwards et al (2012) for nutrients and SPM.…”

GODAE OceanView Class 4 forecast verification framework: global ocean inter-comparison

“…The horizontal grid is the 1/4°tri-polar ORCA grid (referred to as ORCA025) ) with a vertical coordinate based on DRAKKAR 75 level set. The assimilation system is a first guess at appropriate time 3D-VAR system developed alongside NEMO, called NEMOVAR (Mogensen et al 2012;Waters et al 2014) The surface boundary condition (SBC) is specified using the CORE bulk formulation of Large and Yeager (2004). On the 17th of January 2013, FOAM underwent a large operational upgrade (from v11 to v12) which affected the assimilation scheme (OCNASM to NEMOVAR), the vertical resolution (50 levels to 75), the sea ice model (LIM2 to CICE), the SBC (upgraded from direct forcing to CORE bulk formulation) and many other changes.…”

A multiple length scale correlation operator for ocean data assimilation

“…The multiple length scale correlation operator has been implemented and tested in the global 1/4 8 NEMOVAR system (Waters et al, 2015) that constitutes the data assimilation component of the current Met Office operational Forecast Ocean Assimilation Model (FOAM) system (Blockley et al, 2014).…”