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

• Published in: Quarterly Journal of the Royal Meteorological Society
• Main Authors: Waters, Jennifer, Lea, Daniel J., Martin, Matthew J., Mirouze, Isabelle, Weaver, Anthony, While, James
• Other Authors: Met Office
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2014
• Subjects: Sea ice
• Online Access: http://dx.doi.org/10.1002/qj.2388; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fqj.2388; https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.2388

Abstract This article describes the implementation of an incremental first guess at an appropriate time three‐dimensional variational (3 DVAR ) 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.