the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Jul 2026
Wide-swath satellite altimetry and novel subsurface temperature observations improve predictions in a dynamic western boundary current: System optimization and performance
Abstract. Understanding and predicting regional and coastal ocean dynamics requires the effective combination of numerical models and observations that resolve key processes at suitable time and space scales. Fine-scale oceanic features and the ocean's complex subsurface structure remain a significant source of uncertainty in coastal and regional models due to lack of observations at necessary scales. Recently available observation platforms provide an unprecedented view of the ocean's fine-scale structure both at the surface (the Surface Water and Ocean Topography satellite mission, SWOT) and below the surface (using data from the Fishing Vessel Observation Network, FVON). Here we use advanced data assimilation to demonstrate the impact of these novel observation types on dynamic ocean state estimates in an eddy-dominated western boundary current region, the East Australian Current. First we show that these newly available observations benefit from an updated data assimilation configuration. Using this improved configuration, we show that the inclusion of SWOT data improves model representation of both the ocean surface across scales and of subsurface temperature (as observed by FVON). Assimilating FVON data, which drastically increases subsurface information in the coastal and shelf region, significantly improves subsurface temperature representation. Using novel observations from SWOT and FVON in a realistic ocean model, we show enhanced representation of ocean structure, particularly below the surface, essential for improved ocean forecasts and projections.
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CC1: 'Comment on egusphere-2026-2467', David Griffin, 05 Aug 2026
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AC1: 'Reply on CC1', Colette Kerry, 06 Aug 2026
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The reviewer’s first major comment is around SWOT being an experimental mission.
“Being an experimental mission, there is just one SWOT satellite presently in orbit. Its objective is to find out how accurately it can measure swaths of sea level. A single SWOT satellite, with a repeat time of 21 days, is not expected to sample the ocean frequently enough to successfully constrain a model to simulate the evolution of the small-scale features that each overpass can see. Several SWOT satellites would need to be in orbit to achieve that. So, our objective here is to measure the impact of assimilating data from just one SWOT satellite, noting the above considerations.”We completely agree with this comment. SWOT is an experimental mission, not an operational system. However, we find the results of the study nevertheless useful in that there is considerable improvement in model state estimates across scales. The satellite did not intend to improve forecasts of small scales features (and while we show that it doesn’t, we do show improvements in small scale feature representation). We aim to show the value of SWOT and will make note of the above comment in the revised paper. Indeed, a set of OSSEs would be useful to ascertain how many SWOT satellites would be required to successfully constrain a model to simulate the evolution of the small-scale features (potential future work).
The other major comment refers to the issue of assimilating gridded SLA vs assimilating along track SLA. We highlight the advantages of assimilating observations where and when they were taken with 4D-Var; however, the daily gridded DUACS product is used to constrain SSH (6 fields per 6 day window), rather than the along-track altimetry. This is necessary to ensure that the constraint is projected into the baroclinic ocean state solution. The use of along track SSH data successfully with 4D-Var relies on the prescription of balanced terms in the background error covariance matrix to describe the covariance between SSH and the subsurface ocean. This is a topic of further research. A ‘work around’ to force projection into the baroclinic ocean is to repeat the tracks a certain (short) time (say +/- 2 hours) either side of the actual track; however, we are yet to implement this successfully in EAC-ROMS. We prefer to focus our future research on a DA system that incorporates the balanced terms, through improved specification of the background error covariance matrix (e.g. En-Var methods, future work).That said, the gridded product used in this and previous work (since Kerry et al. 2016) produces good results in terms of mesoscale prediction (improving on other available reanalyses in the region). We ensure that the observation uncertainty allows for imbalances between the statistical fit to along-track SSH data provides by the DUACS fields and a dynamically balanced SSH field required by the model. The error in the DUACS delayed-time global SLA product due to noise for the region is estimated at 2 cm (CNES, 2015). We include a further 4 cm of uncertainty both to account for the fact that we use the DUACS fields and because, in this case, the model resolves far more structure at smaller spatial scales than is capable in the observations.
This caveat will be noted in the revised manuscript and we hope that future advances in the DA system (by the authors) will allow the use of along track SSH in the region in future studies.
All other minor comments are much appreciated and will be addressed in the revised manuscript. This will be provided at the end of the Preprint discussion period.
Citation: https://doi.org/10.5194/egusphere-2026-2467-AC1
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AC1: 'Reply on CC1', Colette Kerry, 06 Aug 2026
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RC1: 'Comment on egusphere-2026-2467', Anonymous Referee #1, 28 Sep 2026
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Preprint “Wide-swath satellite altimetry and novel subsurface temperature observations improve predictions in a dynamic western boundary current: System optimization and performance” by Colette G. Kerry et al is a new addition to a set of papers describing performance of an assimilative ROMS-4dVar model of East Australian Current. This preprint is focused on improvements resulting from adding SWOT and FVON observations to ROMS-4dVAR. A thorough description of adjustments to observation and model error hypothesis is presented. Of particular interest are a set of comparison of impacts of using different de-correlation scales.
My only suggestion would be to have a little more oceanography in the paper. Addition of several sentences and a schematic showing major flow patterns (in addition or in place of MKE in Figure 1) would be useful. Figures 2-7 show very useful and impressive statistical comparisons between different reanalyses, but it would make the paper more interesting if we could see an impact of assimilation of SWOT and FVON not only in terms of statistics, but also in terms of actual oceanographic features. Do you see an improvement in a representation of an eddy, or a strength of a current, etc., which could illustrate benefits from assimilation of SWOT and FVON?
The preprint is very well written. My only suggestion with regards to the language is to modify a sentence at line 5: "Recently available observation platforms provide an unprecedented view of the ocean’s fine-scale structure both at the surface (the Surface Water and Ocean Topography satellite mission, SWOT) and below surface ..." SSHA from SWOT changes barotropic fine scale stracture, not only surface structure.
Citation: https://doi.org/10.5194/egusphere-2026-2467-RC1 -
AC2: 'Reply on RC1', Colette Kerry, 02 Oct 2026
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We thank the referee for taking the time to review the paper. The referee suggested that the paper would benefit from more oceanography, specifically description of the major flow patterns and a schematic showing them.
In our paper revision we will include a schematic describing the flow patterns at Figure 1a and will also add some additional description in Section 2.1 Study Region, as below:
“The EAC is the WBC of the South Pacific subtropical gyre (Figure 1a), advecting warm water along the southeastern coast of Australia (Oke et al., 2019b). The current is most coherent off 27◦ S (Sloyan et al., 2016) and intensifies at around 31◦ S (Kerry and Roughan, 2020). The current typically separates from the coast between 31◦ S and 32.5◦ S (Cetina Heredia et al., 2014) and turns eastward to form the EAC eastern extension (Oke et al., 2019a). The position of the EAC jet and its associated eddies are responsible for the significant ocean variability experienced off southeastern Australia (Cetina Heredia et al., 2014; Sloyan et al., 2016; Kerry and Roughan, 2020) and the non-uniform warming trends (Malan et al., 2021). Along the extent of the EAC system, eddies can directly influence shelf circulation (Roughan et al., 2011; Schaeffer et al., 2014; Schaeffer and Roughan, 2015; Malan et al., 2023). When the current jet separates from the coast, large warm-core eddies are shed with cold-core eddies between them (Cetina Heredia et al., 2014; Oke et al., 2019b). These eddies propagate and evolve (Pilo et al., 2015a, b) and often exhibit complex vertical structure including tilting and stacking (Oke and Griffin, 2011; Macdonald et al., 2013; Roughan et al., 2017; Pilo et al., 2018; Rykova and Oke, 2022).”
We completely agree with the referee’s comment that “it would make the paper more interesting if we could see an impact of assimilation of SWOT and FVON not only in terms of statistics, but also in terms of actual oceanographic features. Do you see an improvement in a representation of an eddy, or a strength of a current, etc., which could illustrate benefits from assimilation of SWOT and FVON?” This is why we have written a companion paper that does just that.
This paper titled “Wide-swath satellite altimetry and novel subsurface temperature observations improve predictions in a dynamic western boundary current: System optimization and performance” presents the statistical comparisons between the different reanalyses. In our companion paper (titled “ Wide-swath satellite altimetry and novel subsurface observations improve predictions in a dynamic western boundary current: Resolving complex fine-scale structures”, also now available for interactive review) we present several case studies that display the specific impact of SWOT and FVON data in resolving complex oceanographic features. We present 4 case studies where we look in detail at eddy surface and subsurface structure and how it differs across the different reanalyses, using both assimilated and independent observations (from a research cruise and ocean gliders). We discuss oceanographic features such as mixed layer depth, a sharp temperature front, eddy over washing, and eddy shape, evolution and subsurface structure.In our revisions of this paper (Part 1) we will refer to Part 2 in the conclusions, such that the reader is aware that this paper presents the overall statistical analysis, while the companion paper contains specific oceanographic context. The revised last paragraph will read:
“Overall, we have presented a data assimilation system that is carefully configured and draws value from novel SWOT and FVON / FishSOOP observations to improve model state estimates of the EAC System across spatial scales and below the surface. Here we have compared the different reanalyses using temporally and spatially averaged statistics to describe model performance. In our companion paper (Wide-swath satellite altimetry and novel subsurface observations improve predictions in a dynamic western boundary current: Resolving complex fine-scale structures, Kerry et al, 2026c) we exploit a set of independent observations to present several case studies to elucidate the impact of SWOT and FVON observations in revealing complex oceanographic features. The case studies reveal details of specific flow-dependent observation impacts, and how they are projected in space and time to improve model predictions. The results presented in both papers motivate the sustained collection of novel observations and their integration into regional ocean models to provide advances in prediction. Our work also demonstrates the benefit of tight collaboration between observational data collection (e.g FishSOOP) and ocean data assimilation (e.g. SEA-COFS) for continued improvement of both fields of research.”
If the referee has the time and interest, we would really appreciate comments on the companion paper (https://egusphere.copernicus.org/preprints/2026/egusphere-2026-4125/).Citation: https://doi.org/10.5194/egusphere-2026-2467-AC2
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AC2: 'Reply on RC1', Colette Kerry, 02 Oct 2026
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I apologise in advance that I have only had a fairly quick look at the paper, so the comments I've inserted into the attached PDF range from trivial to important but probably just requiring a little explanation. It is a very detailed paper with lots of good results to think about so I hope to have time for a deeper read later on.