Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var

Abstract

Abstract. This study analyses data assimilative numerical simulations in an eddy-dominated western boundary current: the East Auckland Current (EAuC). The goal is to assess the impact of assimilating surface and subsurface data into a model of the EAuC. We used the Regional Ocean Modelling System (ROMS) in conjunction with the 4-dimensional variational (4D-Var) data assimilation scheme to incorporate sea surface height (SSH) and temperature (SST), and subsurface temperature, salinity, and velocities from three moorings located at the upper, mid and lower continental slope using a 7-day assimilation window. Assimilation of surface fields (SSH and SST) reduced SSH root mean square deviation (rmsd) in relation to the non-assimilative (NoDA) run. The inclusion of velocity subsurface data reduced SSH rmsd up- and downstream of the moorings. By improving the representation of the mesoscale eddy field, data assimilation increased complex correlation between modelled and observed velocity in all experiments. However, the inclusion of temperature and salinity slightly decreased the velocity complex correlation. The assimilative experiments had smaller SST rmsd in comparison to the NoDA run. The lack of sub-surface temperature for assimilation led to larger errors (>1 °C) around 100 m in relation to the NoDA run. Comparisons to independent Argo data showed similar results. Withholding subsurface temperature forces near-surface average negative temperature increments that are corrected by increased net heat flux at the surface which does not affect waters at 100 m depth. Assimilation of mooring temperature generates increments to the initial conditions that reduces 100 m water temperature rmsd. Larger positive wind stress curl was generated in experiments that assimilated subsurface temperature data. Positive wind stress curl generates convergence and downwelling which is another way of correcting the upper thermocline cold bias. The larger positive wind stress curl might also be responsible for decreased velocity correlation in the experiments that assimilated temperature and salinity. The few moored CTDs (8) had little impact in correcting salinity, however, using doubled decorrelation length scales of tracers and a 2-day assimilation window improved model salinity in comparison to independent Argo data. In addition, the results were similar to the global reanalysis HYCOM-NCODA which assimilates Argo profiles and was used as boundary condition. HYCOM-NCODA had near zero velocity complex correlation on the mid-slope, whereas all reanalyses showed improved results which highlights the benefit of downscaling to a regional model of the EAuC.

Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system

“…Each system was tuned by its developers (Australian Bureau of Meteorology for EnOI and UNSW for 4D-Var). We note that the degree of fit between an analysis and the assimilated observations of a specific DA system is sensitive to the prior choice of various parameters, such as the observation and background error covariances, and that the system performance is influenced by the DA system configuration, such as size of the ensemble for ensemble methods and the assimilation window length for 4D-Var Santana et al, 2023). For example, the EnOI system presented here could be further tuned to provide an improved fit to SSH observations (Fig.…”