the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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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Status: open (until 16 Sep 2026)
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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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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.