Assessing the Impact of Nontraditional Ocean Observations for Prediction of the East Australian Current

Siripatana, Adil; Kerry, Colette; Roughan, Moninya; Souza, Joao Marcos Azevedo Correia de; Keating, Shane R.

doi:10.1029/2020jc016580

Cited by 8 publications

(17 citation statements)

References 63 publications

(118 reference statements)

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“…This data assimilating configuration has also been used in previous studies (e.g. Kerry et al, 2016;Kerry et al, 2018;Siripatana et al, 2020) including for OSSEs (Gwyther et al, 2022;Gwyther et al, 2023). The lateral forcing conditions are from BRAN2020, while atmospheric conditions are sourced from the Australian Bureau of Meteorology's ACCESS reanalysis (Puri et al, 2013).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Impact of assimilating repeated subsurface temperature transects on state estimates of a western boundary current

Gwyther

Roughan²,

Kerry³

et al. 2023

Front. Mar. Sci.

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Western Boundary Currents and the eddies they shed are high priorities for numerical estimation and forecasting due to their economic, ecological and dynamical importance. However, the rapid evolution, complex dynamics and baroclinic structure that is typical of eddies and the relatively sparse sampling in western boundary currents leads to significant challenges in understanding the 3-dimensional structure of these boundary currents and mesoscale eddies. Here, we use Observing System Simulation Experiments (OSSEs) to explore the impact of assimilating synthetic subsurface temperature observations at a range of temporal resolutions, to emulate expendable bathythermograph transects with different repeat frequencies (weekly to quarterly). We explore the improvement in the representation of mesoscale eddies and subsurface conditions in a dynamic western boundary current system, the East Australian Current, with a data-assimilating regional ocean model. A characterisation of the spatial and temporal ocean variability spectrum demonstrates the potential for undersampling and aliasing by a lower sampling frequency. We find that assimilating subsurface temperature data with at least a weekly repeat time best improves subsurface representation of this dynamic, eddy-rich region. However, systemic biases introduced by the data assimilation system hinder the ability of the model to produce more accurate subsurface representation with fortnightly or monthly sampling. Removal of this bias may improve subsurface representation in eddy-rich regions with fortnightly or even less frequent observations. These results highlight the value of both increased subsurface observation density in regions of dynamic oceanography as well as continued development of data assimilation techniques in order to optimise the impact of existing observations.

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Section: Methodsmentioning

confidence: 99%

“…In contrast, hindcast reanalyses with a research focus (e.g. Kerry et al, 2016;Siripatana et al, 2020), can augment these traditional observation types with more novel, often delayedmode observations, e.g. high frequency radar-inferred surface currents, hydrography from autonomous gliders, and measurements from subsurface moorings.…”

Section: Introductionmentioning

confidence: 99%

Impact of assimilating repeated subsurface temperature transects on state estimates of a western boundary current

Gwyther

Roughan²,

Kerry³

et al. 2023

Front. Mar. Sci.

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“…In particular, we focus on two manifestations of this impact: firstly how the model represents the instability that generates eddies and secondly the cascade of energy through the vertical (baroclinic) modes (e.g. Smith and Vallis, 2001). In Sect.…”

Section: Introductionmentioning

confidence: 99%

How does 4DVar data assimilation affect the vertical representation of mesoscale eddies? A case study with observing system simulation experiments (OSSEs) using ROMS v3.9

Gwyther

Keating²,

Kerry³

et al. 2023

Geosci. Model Dev.

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Abstract. Accurate estimates and forecasts of ocean eddies in key regions such as western boundary currents are important for weather and climate, biology, navigation, and search and rescue. The dynamic nature of mesoscale eddies requires data assimilation to produce accurate eddy timings and locations in ocean model simulations. However, data assimilating models are rarely assessed below the surface due to a paucity of observations; hence it is not clear how data assimilation impacts the subsurface eddy structure. Here, we use a suite of observing system simulation experiments to show how the subsurface representation of eddies is changed within data assimilating simulations even when assimilating nearby observations. We examine in detail two possible manifestations of how the data assimilation process impacts three-dimensional eddy structure, namely, by producing overly active baroclinic instability and through inaccurate vertical mode structure. Therefore, in DA simulations, subsurface temperature structures can be too deep and too warm, particularly in dynamic eddy features. Our analyses demonstrate the need for further basic research in ocean data assimilation methodologies to improve the representation of the subsurface ocean structure.

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“…The 4-dimensional variational data assimilation (4D-Var) method reduces model errors over a finite time interval using all observations available while preserving dynamical consistency. 4D-Var has notable applications in oceanography, such as: Weaver et al (2003); Powell et al (2008); Mazloff et al (2010); Matthews et al (2012); Zavala-Garay et al (2012); de Souza et al (2015); Osafune et al (2015); Kerry et al (2016); Powell (2017); Phillipson and Toumi (2017); ; Janeković et al (2020); Siripatana et al (2020); Levin et al (2020); López et al (2020); de Paula et al (2021); Moore et al (2021)). Some of those are realistic 4D-Var applications using the Regional Ocean Modelling system (ROMS), from which different values of time-window length, observational errors, and decorrelation length scales were used for the tests presented in the current study.…”

Section: Introductionmentioning

confidence: 99%

“…stated that assimilation of temperature and salinity from ocean gliders should be accompanied by surface measurements to prevent the generation of unrealistic instabilities. Siripatana et al (2020) compared two reanalysis: (i) assimilated traditional observations only (satellite SSH and SST, and temperature and salinity from Argo floats) and (ii) assimilated traditional observations and data from moorings, gliders and high-frequency radar; and found improved subsurface results in the latter experiment.…”

Section: Introductionmentioning

confidence: 99%

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

Santana

Macdonald

O'Callaghan

et al. 2022

Preprint

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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.

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Assessing the Impact of Nontraditional Ocean Observations for Prediction of the East Australian Current

Cited by 8 publications

References 63 publications

Impact of assimilating repeated subsurface temperature transects on state estimates of a western boundary current

Impact of assimilating repeated subsurface temperature transects on state estimates of a western boundary current

How does 4DVar data assimilation affect the vertical representation of mesoscale eddies? A case study with observing system simulation experiments (OSSEs) using ROMS v3.9

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

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