Multiscale data assimilation in the Bluelink ocean reanalysis (BRAN)

Forecast errors of subsurface temperature and salinity are substantially reduced with an efficient, two-step, multiscale Ensemble Optimal Interpolation (EnOI) system, applied to a near-global eddy-resolving ocean model. A critical element of any data assimilation system is the background error covariance, which for EnOI is typically a static ensemble of anomalies from a long model run. Here, we construct two ensembles — one based on intraseasonal anomalies from a free run of the same eddy-resolving ocean model used to underpin the forecasts, and a second ensemble of climatogical anomalies calculated using a relatively coarse, 1-degree global ocean model. For each assimilation cycle, the coarse-resolution ensemble is used to “correct” the broad-scales, and the high-resolution ensemble is used to “correct” the eddy-scales. Corrections from the coarse steps are more effective at reducing systematic errors in the subsurface ocean whereas the high-resolution steps typically produce vertically coherent corrections associated with mesoscale eddies. We compare two configurations of multiscale data assimilation with different localisation radii in the coarse data assimilation step. The best performance and slowest error growth was found with localisation that was large enough to encompass neighbouring profiles in each assimilation cycle. The efficacy of the approach is demonstrated in ocean reanalyses over 2017-8 that assimilate data every 3 days. We demonstrate clear improvements in the representation of temperature and salinity at all depths around Australia. Model-observation differences are particularly improved in and below the thermocline. The corrections to the ocean state with multiscale data assimilation follow water mass structures. The increased computational cost of this multiscale approach is modest (about double the analysis step), but the performance improvement is significant, making this approach suitable for research and operational applications.