Development and evaluation of a high-resolution reanalysis of the East Australian Current region using the Regional Ocean Modelling System (ROMS 3.4) and Incremental Strong-Constraint 4-Dimensional Variational data assimilation (IS4D-Var)

Abstract

Abstract. As with other western boundary currents globally, the East Australian Current (EAC) is inherently dynamic making it a challenge to model and predict. For the EAC region, we combine a high-resolution state-of-the-art numerical ocean model with a variety of traditional and newly available observations using an advanced variational data assimilation scheme. The numerical model is configured using the Regional Ocean Modelling System (ROMS 3.4) and takes boundary forcing from the BlueLink ReANalysis (BRAN3). For the data assimilation we use an Incremental Strong-Constraint 4-Dimensional Variational (IS4D-Var) scheme. This paper describes the data assimilative model configuration that achieves an optimised minimisation of the difference between the modelled solution and the observations to give a dynamically-consistent `best-estimate' of the ocean state over a 2-year period. The reanalysis is shown to represent both assimilated and non-assimilated observations well. It achieves mean spatially-averaged RMS residuals with the observations of 7 cm for SSH and 0.4 °C for SST over the assimilation period. The time-mean RMS residual for subsurface temperature measured by Argo floats is a maximum of 1 °C between water depths of 100–300 m and smaller throughout the rest of the water column. Velocities at several offshore and continental shelf moorings are well represented in the reanalysis with complex correlations between 0.8–1 for all observations in the upper 500 m. Surface radial velocities from a high-frequency radar array are assimilated and the reanalysis provides surface velocity estimates with complex correlations with observed velocities of 0.8–1 across the radar footprint. Comparison with independent (non-assimilated) shipboard CTD cast observations shows a marked improvement in the representation of the subsurface ocean in the reanalysis, with the RMS residual in potential density reduced to about half of the residual with the free-running model in the upper eddy-influenced part of the water column. This shows that information is successfully propagated from observed variables to unobserved regions as the assimilation system uses the model dynamics to determine covariance, such that the ocean state better fits and is in balance with the observations. This is the first study to generate a reanalysis of the region at such a high resolution, making use of an unprecedented observational data set and using an assimilation method that uses the time-evolving model physics to adjust the model in a dynamically consistent way. As such, the reanalysis potentially represents a marked improvement in our ability to capture important circulation dynamics in the EAC. The reanalysis is being used to study EAC dynamics, observation impact in state-estimation and as forcing for a variety of downscaling studies.

Multiple spawning events promote increased larval dispersal of a predatory fish in a western boundary current

“…Comparisons of volume transported by the EAC were also made with estimates from full‐depth moorings (Sloyan et al, 2016) and a combination of XBT, Argo and altimetry data (Zilberman, Roemmich, Gille, & Gilson, 2018). The simulated hydrodynamics were found to be consistent with the observations providing confidence in the model as it provides a very good representation of the currents in the EAC separation region and accurately represents the spatial patterns of mesoscale SSH variability driven by the dynamic mesoscale eddy field, the EAC separation and the seasonal SST cycle over the 22‐year simulation period (Kerry et al, 2016; Kerry & Roughan, 2020b).…”

“…Symbols show the release location for the forwards (triangles) and backwards (circles) simulations. The dotted line represents the boundaries of the regional oceanographic model which provided the velocity estimates used in the simulations (Kerry et al, 2016), and the solid black line shows the 200m isobath, b) a visualisation of the observed January 2016 (summer) ocean currents (black arrows) and sea surface temperature (colour) of the region. The SST observations are taken from MODIS‐Aqua using NASA's OceanColor Web.…”

“…The model is a free‐running simulation covering a 22‐year period (1994–2016; Kerry & Roughan, 2020a). It is a temporal extension of the 10‐year free‐running simulation described in Kerry, Powell, Roughan, and Oke (2016) and Rocha, Edwards, Roughan, Cetina‐Heredia, and Kerry (2019). Model output is saved as daily averages.…”

Retention and Leakage of Water by Mesoscale Eddies in the East Australian Current System

“…The regions where we detect water parcel entrainment into and leakage out of mesoscale eddies (Figure 4) correspond to an area where sea surface height variability is large (Mata et al, 2006), and that has been associated with high eddy kinetic energy (Kerry et al, 2016;O'Kane et al, 2011;Schiller et al, 2008). Eddies are often aligned with the continental shelf break along the EAC and EAC extension, and over a quasi-zonal band into the Tasman Sea at~31°S where the EAC separates frequently and gives rise to the Tasman Front (Figure 4).…”

Observation Impact in a Regional Reanalysis of the East Australian Current System

“…We have developed a numerical model of the southeastern Australia oceanic region that extends from north of where the EAC is most coherent and encompasses the eddy field in the Tasman Sea (Figure a). We use 4D‐Var data assimilation to assimilate observations from a variety of platforms over a 2‐year period (2012–2013; Kerry et al, ) and, in this paper, quantify the impact of specific data streams on estimates of the EAC. The EAC and its associated eddy field dominate the circulation along the east coast of Australia.…”