Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
- 1The University of Auckland, Department of Physics, Auckland, 1010, New Zealand
- 2National Institute of Water and Atmospheric Research, Wellington, 6021, New Zealand
- 3University of Otago, Department of Mathematics & Statistics, Dunedin, 9016, New Zealand
- 4Department of Oceanography, University of Hawai’i, Honolulu, HI 96822, United States
- 5University of North Carolina Wilmington, Wilmington, NC, 28403, United States
- 1The University of Auckland, Department of Physics, Auckland, 1010, New Zealand
- 2National Institute of Water and Atmospheric Research, Wellington, 6021, New Zealand
- 3University of Otago, Department of Mathematics & Statistics, Dunedin, 9016, New Zealand
- 4Department of Oceanography, University of Hawai’i, Honolulu, HI 96822, United States
- 5University of North Carolina Wilmington, Wilmington, NC, 28403, United States
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.
Rafael Santana et al.
Status: open (until 19 Feb 2023)
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CEC1: 'Comment on gmd-2022-270', Astrid Kerkweg, 28 Nov 2022
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Dear authors,
the GMD editorial states about Model experiment description papers: "The primary purpose of these papers is to enable modelling communities to perform the same experiments. Therefore, everything required to run the experiment must be provided, apart from the model itself." (GMD Editorial main text, see also appendix B4)
I do not see that your article is about a model experiment which is performed by a larger community with different models. Therefore, your paper fits better the "Technical and development paper" type and I will ask the editorial office to apply this manuscript type to your article.
Additionally, please note, that for this type of paper the exact version of the model code used to produce the results needs to be permanently (DOI) archived.
Kind regards,
Astrid Kerkweg (GMD Executive Editor)
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AC1: 'Reply on CEC1', Rafael Santana, 29 Nov 2022
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Dear Astrid Kerkweg,
Thanks for your comments. I have uploaded the model code version to Zenodo and generated a DOI (below). I hope that fulfils your recommendation. Please, let me know if there is anything missing.
https://doi.org/10.5281/zenodo.7378738
Kind regards,
Rafa
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AC1: 'Reply on CEC1', Rafael Santana, 29 Nov 2022
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RC1: 'Comment on gmd-2022-270', Srinivasa Ramanujam Kannan, 22 Dec 2022
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At the outset, the manuscript is very well written and is suitable for publication. The author has raised pertinent issues which are scientifically relevant. The methodology adopted is well suited to solve this problem. The key issues raised by the authors were:
What is the impact of subsurface data assimilation into a forecast model? The authors have considered assimilation with all parameters included, and have also considered subsets of it to study the sensitivity of different parameters using the observing systems experiments approach. There are a few minor concerns that the authors should address, which will make the work reproducible. The following are the minor concerns:
Fig 1 looks cluttered with too many features. The authors can either split them into subplots or make different plots to make it more clear.
Page 3, Section 2.1: Authors should provide additional information about the ROMS model used in the present study, such as various parameterization schemes available and suitable for the considered study. Even though the sensitivity of various parameterization schemes is beyond the scope of the present work, the authors must highlight significant results from the literature. Suitable modifications are also required in Line numbers 41-45 on Page 2.
Page 6, Eq. 1: How is the cost function minimized? The author should briefly explain the algorithm used to minimize the cost function.
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RC2: 'Comment on gmd-2022-270', Anonymous Referee #2, 26 Jan 2023
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Data assimilation sensitivity experiments in the East Auckland Current system using 4D-Var
by Rafael Santana, Helen Macdonald, Joanne O’Callaghan, Brian Powell, Sarah Wakes, and Sutara H. SuandaReferee Comment
General Comment:
The manuscript explores the impacts of assimilating different types (altimetry SSH, satellite SST, mooring-observed T,S,U,&V) of measurements on reconstructing the ocean state near EAuC, using ROMS-4DVAR system and OSEs. The authors conducted six (or seven) experiments to examine the relative importance of different observations on estimating the ocean state. This is the first step towards an operational ocean forecasting system. However, there are still many deficiencies that need to be addressed before publication, especially the comparisons and explanation of the final results. In addition, I would suggest the authors to edit the manuscript by a person with a better command of English.
In the manuscript, the authors didn’t develop (at least didn’t document) the ROMS-4Dvar system. Considering the scope of GMD and the content of this manuscript, I would suggest the authors transfer/resubmit the manuscript to more appropriate Journals such as Ocean Science, Ocean Modelling, QJRMS, MWR, JAMES, if possible.
I have commented the manuscript in the attached pdf files. And below are some general comments on on individual Sections:
Section 1 Introduction:
I suggest the authors to rewrite these paragraphs from 45-60, including the comparisons of different assimilation schemes, motivating the current study. The introduction to OSEs is too much, can be move to before the last paragraph of Introduction. The authors should motivate and highlight the current study better here.
Section 2
Please consider listing all experiments here in a table, showing their names, assimilated observations, number of observation.
Besides, more information about the background terms (covariance patterns) should be provided. If the authors follow previous studies, the authors should also provide some figures about different decorrelation scales, covariance patterns here or in the discussion, since it is likely the background terms play dominating roles in determining the sensitivity rather than the adjoint model part. I feel like the heat flux increments are weird. More details can be found in the attached pdf files.
Figure 1 should be simplified. Please point out regions with high eddy activities (SSH STD) and the model-data differences. Also schematic circulation pattern should be shown here. This could help in the results part.
Section 3:
I would prefer better presentations of the assimilation results.
Here I give a few suggestions, details can be found in the pdf files.
- I feel like results of NoUVTS (or NoUV) is not necessary be shown here. The authors mostly concentrate on the impacts of with/without TS profiles. Maybe one of them is enough.
- What is the radius of meso-eddies in the model domain? I cannot see any mesoscale eddies in Figures 4, 6,7. If the authors want to discuss impacts of assimilation on mesoscale process, I suggest the authors plot the horizontal structure of the eddies in specific time, for instance when there are large errors which are corrected by assimilation. Otherwise, it is not clear at all.
- I also encourage explore more on salinity which was degraded. Since the author want to develop this system into an operation system, the authors need to understand why the degradations occur.
Section 4 discussions
In this part, the authors should explain why 2-d experiment looks better than 7-d experiment? Is it because of background terms? Comparison between background terms, adjoint model terms, even just for a specific assimilation cycle should be shown here to explain the differences.
Section 5 Conclusions
Since the authors want to develop the model to an operational system, the authors should list details of the computational cost here.
Rafael Santana et al.
Rafael Santana et al.
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