the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Global seamless tidal simulation using a 3D unstructured-grid model
- 1Center for Coastal Resource Management, Virginia Institute of Marine Science, College of William & Mary, Gloucester Point, 23062, USA
- 2Universidad de Cádiz, 11003, Spain
- 3Environmental Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA
- 4NOAA National Ocean Service, Silver Spring, MD, 20910, USA
- 1Center for Coastal Resource Management, Virginia Institute of Marine Science, College of William & Mary, Gloucester Point, 23062, USA
- 2Universidad de Cádiz, 11003, Spain
- 3Environmental Science Division, Argonne National Laboratory, Lemont, IL, 60439, USA
- 4NOAA National Ocean Service, Silver Spring, MD, 20910, USA
Abstract. We present a new 3D unstructured-grid global ocean model to study both tidal and non-tidal processes, with a focus on the total water elevation. Unlike existing global ocean models, the new model resolves estuaries and rivers down to ~8m without the need for grid nesting. The model is validated with both satellite and in-situ observations for elevation, temperature, and salinity. Tidal elevation solutions have a mean complex RMSE of 4.2 cm for M2 and 5.4 cm for combined 5 other major frequencies in the deep ocean. The non-tidal residual assessed by a tide gauge dataset (GESLA) has a mean RMSE of 7 cm. For the first time ever, we demonstrate the potential for seamless simulation, on a single mesh, from the global ocean into a few estuaries along the US west coast. The model is able to accurately capture the total elevation, and qualitatively capture the challenging salinity intrusion processes in the Columbia River. The model can therefore potentially serve as the backbone in a global tide-surge and compound flooding forecasting framework.
Yinglong Joseph Zhang et al.
Status: open (extended)
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CEC1: 'Comment on gmd-2022-165', Astrid Kerkweg, 15 Aug 2022
reply
Dear authors,
in my role as Executive editor of GMD, I would like to bring to your attention our Editorial version 1.2: https://www.geosci-model-dev.net/12/2215/2019/
This highlights some requirements of papers published in GMD, which is also available on the GMD website in the ‘Manuscript Types’ section: http://www.geoscientific-model-development.net/submission/manuscript_types.html
In particular, please note that for your paper, the following requirements have not been met in the Discussions paper:
- "The main paper must give the model name and version number (or other unique identifier) in the title."
- “If the model development relates to a single model then the model name and the version number must be included in the title of the paper. If the main intention of an article is to make a general (i.e. model independent) statement about the usefulness of a new development, but the usefulness is shown with the help of one specific model, the model name and version number must be stated in the title. The title could have a form such as, “Title outlining amazing generic advance: a case study with Model XXX (version Y)”.''
In order to simplify reference to your developments, please add a model name (and/or its acronym) and a version number in the title of your article in your revised submission to GMD.
Yours, Astrid Kerkweg
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AC1: 'Reply on CEC1', Y. Joseph Zhang, 15 Aug 2022
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Dear Editor:
Your request on title change is noted. How shall I do this? Shall I reload the revised manuscript? Also can I make other minor editorial changes? Thank you.
Joseph Zhang
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CEC2: 'Reply on AC1', Astrid Kerkweg, 15 Aug 2022
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Dear Joseph Zhang,
for the title change it is sufficient, if you do this, when you submit the revised manuscript after the end of the discussion phase. However, if you like to make changes, you want to apply to your article anyhow, already available / visible to the readers, you are free to upload a new (unofficial) manuscript version here in the discussion forum.
But note, that the referees are reviewing the official discussion version and that they are free to take your intermediate, new uploaded article version into account or not.
Best wishes,
Astrid Kerkweg
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CEC2: 'Reply on AC1', Astrid Kerkweg, 15 Aug 2022
reply
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RC1: 'Comment on gmd-2022-165', Anonymous Referee #1, 16 Sep 2022
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In this paper, authors present a new 3D unstructured-grid global ocean model to study both tidal and non-tidal processes, with a focus on the total water elevation. Unlike existing global ocean models, the new model resolves estuaries and rivers down to ~8m without the need for grid nesting. The model is validated with both satellite and in-situ observations for elevation, temperature and salinity. The authors demonstrate the potential for seamless simulation, on a single mesh, from the global ocean into several estuaries along the US west coast. The model is able to accurately capture the total elevation, and qualitatively capture the challenging salinity intrusion processes in the Columbia River. The model May be potentially serve as the backbone in a global tide-surge and compound flooding forecasting framework. There is no doubt about the importance, innovation and value of this work. However, in the writing and presentation, some places still need further explanation. I think this paper satisfies the scope and standard of Geoscientific Model Development, but I also have some concerns. Therefore, I recommend a major revision.
Major concerns:
- The usual numerical simulation of multi-constituents oftides basically considers four major diurnal and semi-diurnal tides, or eight major diurnal and semi-diurnal tides. Six of the eight main sub-tides are considered. In fact, Q1 is weaker than K2 and P1 tides. The author considers Q1 tides in the study, but does not consider K2 and P1 tides, which gives a strange feeling. Of course, the authors may have made this trade-off from a computational standpoint. The reviewer still insisted that either four major diurnal and semi-diurnal sub-tides or eight major diurnal and semi-diurnal sub-tides should be considered. In view of the fact that the author did not display and analyze the results of N2 and Q1 tides, it is suggested that the author remove these two tides.
- In Page 3, Line 89-91, These features has allowed a single model to be used for challenging compound flooding studies that involve coastal transition zones between hydrodynamic and hydrologic regimes, forced by ocean, precipitation and watershed rivers (Ye et al. 2020; Zhang et al. 2020; Huang et al. 2021; Ye et al. 2021).Necessary modifications are required. Whereocean, precipitation and watershed rivers are not a juxtaposition.
3.In the reviewer's opinion, it is very difficult to understand that the bottom friction coefficient is set to 0 in deep water. Please confirm and give a clear explanation. The following is the corresponding expression in the original text, the reviewer really difficult to understand the bold part of the expression.
Page 4, Line 110, As a result, the near-bottom vertical layers can be as thick as 1km in the deep ocean; in other words, the logarithmic layer there is not well resolved and therefore, we apply zero friction in the deep depths.
Page 4, Line 111-113, To ensure adequate energy dissipation toward shallows, we use a simple depth-dependent bottom friction coefficient (used in the quadratic drag formulation) that linearly increases from 0 at depth 200m to 0.0025 at 50m.
- Page 4, Line 106-107, The number of sigma layers varies from a maximum of 34 to 1 (i.e. 2DH configuration), with an average of 32 layers.What does average mean? How it's calculated?
- In Page 5, Line 138-139, Relaxation of temperature and salinity near the ocean surface, which is commonly utilized in many global ocean models (Ringler et al. 2013), was not applied here due to the relatively short duration of the simulation. This is an awkward statement.What does the author mean by this expression? Ask the authors to give an explanation.
- In Page 8, Line 196-199, The averaged complex RMSE for M2 is 4.2cm for depths greater than 1km, and 14.3cm for shallower depths. The averaged RMSE for the remaining frequencies (S2, N2, K1, O1, Q1) is 5.4cm / 16.6cm or depths greater/less than 1km. These results are slightly better than the previous best 3D model results without data assimilation (Schindelegger et al. 2018) but worse than those in Pringle et al. (2021).Here the reviewer thinks it must be pointed out that in the numerical simulation of multi-tidal, the evaluation indexes of all sub-tidal should be given in detail. In this paper, the author gives the index of M2 sub-tide alone, and the other five sub-tide indicators are combined.
- Page 8, Line 203-206, Compared to other global 3D models, our model seems to be able to obtain satisfactory results without the need for some elaborate drag formulations described in A18, which might be attributed to the fact that the higher resolution used in the coastal ocean has provided adequate energy dissipation. I don't agree with the author here, the higher resolution used in the coastal ocean is not a panacea. Ask the authors to give an explanation.
- Page 10, Line 245, Table 1. Summary of model performance to reproduce the main semi-diurnal tidal component for SCHISM and FES2012 models against GESLA. Are the indicators here consistent with those in lines 196-199?I think this table currently lacks a clear interpretation.
Minor concers:
Abstract, Line 14-15, Tidal elevation solutions have a mean complex RMSE of 4.2 cm for M2 and 5.4 cm for combined 5 other major frequencies in the deep ocean. I think the evaluation indexes of all sub-tidal should be given in detail. Where frequencies should be constituents
Page 8, Line 197ï¼the remaining frequencies should be the remaining constituents
Page 16, Line 326, ssytems should be systems
Page 17, Line 356, The large stratification should be The strong stratification
Page 20, Line 391-392, The simulated tide showed good skill, with a mean complex RMSE of 4.2cm for M2 and 5.4cm for the 5 other major frequencies in deeper depths. What is deeper depths mean?
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AC2: 'Reply on RC1', Y. Joseph Zhang, 19 Sep 2022
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My response is shown in bold italic texts below. Thank you so much for your constructive comments.
Major concerns:
- The usual numerical simulation of multi-constituents oftides basically considers four major diurnal and semi-diurnal tides, or eight major diurnal and semi-diurnal tides. Six of the eight main sub-tides are considered. In fact, Q1 is weaker than K2 and P1 tides. The author considers Q1 tides in the study, but does not consider K2 and P1 tides, which gives a strange feeling. Of course, the authors may have made this trade-off from a computational standpoint. The reviewer still insisted that either four major diurnal and semi-diurnal sub-tides or eight major diurnal and semi-diurnal sub-tides should be considered. In view of the fact that the author did not display and analyze the results of N2 and Q1 tides, it is suggested that the author remove these two tides.
>> We have actually tested including 8 constituents but decided to follow Pringle et al. to include only 6 of them in the text. The difference for M2 is negligible. We will add the results with 8 constitutents and also for each constituent in the revision.
- In Page 3, Line 89-91, These features has allowed a single model to be used for challenging compound flooding studies that involve coastal transition zones between hydrodynamic and hydrologic regimes, forced by ocean, precipitation and watershed rivers (Ye et al. 2020; Zhang et al. 2020; Huang et al. 2021; Ye et al. 2021).Necessary modifications are required. Where ocean, precipitation and watershed rivers are not a juxtaposition.
>> We agree and will revise the texts. Compound flooding will be future development.
3.In the reviewer's opinion, it is very difficult to understand that the bottom friction coefficient is set to 0 in deep water. Please confirm and give a clear explanation. The following is the corresponding expression in the original text, the reviewer really difficult to understand the bold part of the expression.
Page 4, Line 110, As a result, the near-bottom vertical layers can be as thick as 1km in the deep ocean; in other words, the logarithmic layer there is not well resolved and therefore, we apply zero friction in the deep depths.
Page 4, Line 111-113, To ensure adequate energy dissipation toward shallows, we use a simple depth-dependent bottom friction coefficient (used in the quadratic drag formulation) that linearly increases from 0 at depth 200m to 0.0025 at 50m.
>> To save computatuional cost the vertical grid coarsely resolves the deeper depths such that some bottom layer has thickness of ~1km. Therefore, the assumption of a logarithmic velocity profile in the bottom boundary layer is not appropriate. We could use a very small drag coefficient in lieu of 0 but the effect is similar: the velocity profile inside the bottom layer should not be strongly affected by the friction when the layer is 1km thick.
- Page 4, Line 106-107, The number of sigma layers varies from a maximum of 34 to 1 (i.e. 2DH configuration), with an average of 32 layers.What does average mean? How it's calculated?
>> The LSC2 vertical grid system in SCHISM allows different numbers of layers to be applied at different horizontal locations, and the average number of layers is simply the arithmetic mean of the number of layers at each node.
- In Page 5, Line 138-139, Relaxation of temperature and salinity near the ocean surface, which is commonly utilized in many global ocean models (Ringler et al. 2013), was not applied here due to the relatively short duration of the simulation. This is an awkward statement.What does the author mean by this expression? Ask the authors to give an explanation.
>> In climate models it's a common practice to relax near-surface T,S to climatological values in order to prevent drift of simulation over a long time. This is not used here. We'll add some explanation in the manuscript.
- In Page 8, Line 196-199, The averaged complex RMSE for M2 is 4.2cm for depths greater than 1km, and 14.3cm for shallower depths. The averaged RMSE for the remaining frequencies (S2, N2, K1, O1, Q1) is 5.4cm / 16.6cm or depths greater/less than 1km. These results are slightly better than the previous best 3D model results without data assimilation (Schindelegger et al. 2018) but worse than those in Pringle et al. (2021).Here the reviewer thinks it must be pointed out that in the numerical simulation of multi-tidal, the evaluation indexes of all sub-tidal should be given in detail. In this paper, the author gives the index of M2 sub-tide alone, and the other five sub-tide indicators are combined.
>> We have those numbers and will add them.
- Page 8, Line 203-206, Compared to other global 3D models, our model seems to be able to obtain satisfactory results without the need for some elaborate drag formulations described in A18, which might be attributed to the fact that the higher resolution used in the coastal ocean has provided adequate energy dissipation. I don't agree with the author here, the higher resolution used in the coastal ocean is not a panacea. Ask the authors to give an explanation.
>> Indeed this is speculative and that's why we used 'might'. Will revised.
- Page 10, Line 245, Table 1. Summary of model performance to reproduce the main semi-diurnal tidal component for SCHISM and FES2012 models against GESLA. Are the indicators here consistent with those in lines 196-199?I think this table currently lacks a clear interpretation.
>> The GESLA comparison is complementary to the co-tidal chart because it's focused on nearshore. We will add more explanations for the table. Thank you.
Minor concerns: >> Will correct those issues.
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RC2: 'Comment on gmd-2022-165', Anonymous Referee #1, 27 Sep 2022
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I need to see the revised paper.
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AC3: 'Reply on RC2', Y. Joseph Zhang, 27 Sep 2022
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We are waiting for comments from the other reviewer before revising the manuscript. Thank you for yout patience.
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AC3: 'Reply on RC2', Y. Joseph Zhang, 27 Sep 2022
reply
Yinglong Joseph Zhang et al.
Yinglong Joseph Zhang et al.
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