Moninya Roughan⁴, Dr Colette Kerry¹

¹UNSW Australia, Sydney, Australia

To optimise ocean forecast skill, it is important to understand which observation types and locations are most effective at constraining model state estimates and improving predictions.  Here we use three different methods to assess observation impact in Australia’s dynamic Western Boundary Current (WBC), the East Australian Current (EAC), with consistent results. Combining a high-resolution (2.5-6km) ocean model with an unprecedented observational data set, using 4-dimensional variational data assimilation, we assess the impact of various observations on the prediction of EAC transport and eddies. In addition to the traditional data streams (satellite derived SSH and SST, Argo profiling floats and XBT lines) we exploit novel observations collected as part of Australia’s Integrated Marine Observing System. These include observations from a deep-water mooring array and shelf moorings, a high-frequency (HF) radar array and a suite of ocean glider missions. Firstly, a comparison of experiments with and without the novel observations allows us to assess their value in prediction of current transport and eddy structure. Secondly, variational methods allow us to quantify directly how each observation contributes to the state-estimate solution. Thirdly, a series of Observing System Simulation Experiments are designed to assess the impact of subsurface temperature observations and the impact of sampling the (upstream) coherent jet versus the (downstream) eddy field.  We show that observation impact is far-reaching; both up and downstream. We find that observations taken in regions with greater natural variability contribute most to constraining the model estimates, and subsurface observations have a high impact relative to the number of observations. The challenge of correctly representing the depth structure of the current and its eddies upon data assimilation is discussed. This work provides new information on the value of specific observation platforms for prediction of the EAC and motivates further work into improving WBC prediction.

Biography:

Colette worked as a coastal and ocean engineer before moving to academia, where she has revolutionised high-resolution modelling, state estimation and the understanding of observation impact in the EAC system. She leads the UNSW Coastal and Regional Ocean modelling and data assimilation team, where she and her colleagues use regional ocean models to understand WBC dynamics, heat content and ocean warming, observation impact, and predictability. Colette’s research interests include:

Regional and coastal ocean modelling
Data assimilation and adjoint methods
Mesoscale and submesoscale predictability
Western Boundary Current dynamics
Observation impact and optimising observation system design
Predictability of ocean temperature extremes