DALROMS-NWA12 v1.0, a coupled circulation-ice-biogeochemistry modelling system for the northwest Atlantic Ocean: Development and validation

Ohashi, Kyoko; Laurent, Arnaud; Renkl, Christoph; Sheng, Jinyu; Fennel, Katja; Oliver, Eric

doi:https://doi.org/10.5194/egusphere-2024-1372

Preprints

https://doi.org/10.5194/egusphere-2024-1372

Preprints

05 Aug 2024

| 05 Aug 2024

DALROMS-NWA12 v1.0, a coupled circulation-ice-biogeochemistry modelling system for the northwest Atlantic Ocean: Development and validation

Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver

Abstract. This study presents DalROMS-NWA12 v1.0, a coupled ocean circulation-sea ice-biogeochemistry modelling system for the northwest Atlantic Ocean (NWA) in which the circulation and biogeochemistry modules are based on ROMS (Regional Ocean Modeling System). The circulation module is coupled to a sea ice module based on the Community Ice CodE (CICE), and the physical ocean state simulated by the circulation module drives the biogeochemical module. Study of the biological carbon pump in the NWA is one of the main intended applications of this model. Global atmospheric and ocean reanalyses are used respectively to force DalROMS-NWA12 at the sea surface and as part of its lateral boundary input. The modelling system is also forced by tides, riverine freshwater input, and continental runoff. The physical ocean state and sea ice from two simulations of the period 2015–2018, with and without nudging of the simulated temperature and salinity towards a blend of observations and reanalysis, are examined in this study. Statistical comparisons between model results and observations or reanalyses show the control (nudged) simulation outperforms the prognostic (un-nudged) simulation in reproducing the paths of the Gulf Stream and the West Greenland Current, as well as propagation of the estuarine plume in the Gulf of St. Lawrence. The prognostic simulation performs better in simulating the sea ice concentration. The biogeochemical module, which is run only in the control simulation, performs reasonably well in reproducing the observed spatiotemporal variations of oxygen, nitrate, alkalinity, and total inorganic carbon. To examine the effects of tides and sea ice on the physical fields in the study area, results of simulations from which either component is absent are compared to results of the prognostic simulation. In the absence of tides, Ungava Bay in summer experiences a simulated surface salinity that is higher by up to ~7 than in the simulation with tides, as well as changes in horizontal distributions of surface temperature and sea ice. Without coupling to the sea ice module, the circulation module produces summertime sea surface temperatures that are higher by up to ~5 °C in Baffin Bay.

Received: 08 May 2024 – Discussion started: 05 Aug 2024

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Journal article(s) based on this preprint

10 Dec 2024

DalROMS-NWA12 v1.0, a coupled circulation–ice–biogeochemistry modelling system for the northwest Atlantic Ocean: development and validation

Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver

Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024,https://doi.org/10.5194/gmd-17-8697-2024, 2024

Short summary

Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-1372', Anonymous Referee #1, 11 Aug 2024
Biogeochemical modeling is increasingly important for both understanding biogeochemical processes and predicting rapidly changing ocean conditions due to ongoing climate change. The authors have developed a fully coupled NWA model that integrates ocean, ice, and biogeochemical components, meeting the needs of many researchers working in this region. Sensitivity analyses enhance understanding of the roles of tides and sea ice in model biases.
This manuscript is well written. The authors use RMSE, RMSD, and other statistical measures to evaluate the performance of the model runs, which is appropriate. While it is known that the Northwest Atlantic Ocean has been undergoing significant changes, temporal changes in the ocean can serve as important indicators of the impact of climate change. Although the short simulation period of 4 years may not be useful for climate research, I suggest the authors select specific locations to demonstrate whether the models can properly simulate the evolution of key variables (monthly mean or annual mean). Numerous observed sea surface temperature data, bottom temperature data (summertime), current meter data, and other types of data are available for this region, which could be used to further investigate model performance. This would enhance the confidence of readers and future users in the model. Additionally, winter convection events in the Labrador Sea are believed to be a significant driver of circulation in the North Atlantic Ocean, impacting water mass properties in this region. It is worth reporting whether the ROMS model can well simulate these winter convection events during the study period.

Below is a list of specific comments.
Line 34 “up to 7”, could “up to 7 psu” be better”?

Lines 153-154. Why are the eddy viscosity and diffusivity set to zero? Given that you employ high-order accuracy schemes (3rd and 4th order), it’s unclear why these values would be zero. Could you provide a rationale for this choice?

Lines 172-174. Are the inter-annually variable GLORYS12 data used at open boundaries or the daily climatological ones? Please specify.

Lines 182-183. I am curious why it is through the bottom. River discharge is through top layers.

Lines 298-299. Glorys12 uses data assimilation (4d var), and in theory, this can eliminate those biases from the non-inclusion of tides.

Lines 310-311. Same as above. You may want to find some literature to support this statement.

Lines 369-378. This seems an indication of numerical scheme issue or the horizontal mixing issue (zero is used).

Lines 409-425. Data from Drinkwater (1988) were for the year of 1982, and the data your model and GLORYS12 are for the recent years. You need to mention the probable existence of decadal or even longer variability for the current in this area.

Figure 13. I cannot see any dots there. Could the quality of the figure need improving?
Citation: https://doi.org/10.5194/egusphere-2024-1372-RC1
- AC1:
  'Reply on RC1', Kyoko Ohashi, 28 Aug 2024
  
  We thank the referee for taking the time to review our manuscript and for providing supportive comments. Please find in the attached file our response to your comments.
  
  Citation: https://doi.org/10.5194/egusphere-2024-1372-AC1
  - RC3: 'Reply on AC1', Anonymous Referee #1, 05 Sep 2024
    
    Thank you to the authors for their comprehensive responses to my questions and comments. The proposed changes are acceptable.
    However, I would like to reiterate my concern regarding the choice of zero for both the eddy viscosity and diffusivity. I believe that further refinement of the model with more appropriate values for these parameters could enhance its accuracy and predictive capabilities
    
    Citation: https://doi.org/10.5194/egusphere-2024-1372-RC3
    
    AC2: 'Reply on RC3', Kyoko Ohashi, 10 Sep 2024
    
    Thank you for your reply. In response to your concern about the horizontal eddy diffusivity and viscosity being zero, we have modified the discussion of possible future research directions (Page 44, Line 742 in the original version) to the following (new part in italics): "In addition to studies of the biological carbon pump and of the downstream effects of changes in the water transported by the Labrador Current, another possible direction of future research is to explore further the effects of model configuration, such as parameterization of deep convection or the choice of advection schemes (including the use of non-zero horizontal eddy diffusivity and viscosity with the third-order upstream scheme). In addition, ...".
    
    Citation: https://doi.org/10.5194/egusphere-2024-1372-AC2
    
    RC4: 'Reply on AC2', Anonymous Referee #2, 11 Sep 2024
    
    Thank you for your response and the additions. I agree with your point about incorporating a small viscosity/diffusivity; this adjustment may enhance the accuracy of future simulations in certain subregions of your model domain. Overall, this is a minor detail compared to the solid work you’ve accomplished in developing and validating DalROMS for the western North Atlantic.
    
    Citation: https://doi.org/10.5194/egusphere-2024-1372-RC4
    
    AC4: 'Reply on RC4', Kyoko Ohashi, 11 Sep 2024
    
    Thank you for the positive comments!
    
    Citation: https://doi.org/10.5194/egusphere-2024-1372-AC4
RC2:
'Comment on egusphere-2024-1372', Anonymous Referee #2, 02 Sep 2024

The manuscript presents results from implementing and validating a coupled ocean-sea ice-biochemical model of the North Atlantic. The authors developed an advanced coupling between the ROMS and CICE ice models. Model results are compared with surface and in situ ocean observations, and the validation encompasses various setups, including model forecasts, simulations constrained by observed temperature and salinity, and scenarios without tides or sea ice.
The manuscript is well-written, and the model validation results are robust. The authors’ conclusions are well-supported by various statistical measures of model error. The model validation demonstrates the model's significant potential for future diagnostic and prognostic climate change simulations in the Western North Atlantic.
However, I recommend adding further discussion on several aspects of the model setup and simulations:
• Lines 55-56: Is deep convection an additional or dominant component of CO₂ removal in the Labrador Sea, as Tian et al. (2004) discussed? Clarifying this point would strengthen the manuscript.
• Line 104: The resolution of "O(km)" is mentioned. Currently, eddy-resolving circulation models of the North Atlantic typically have resolutions between 1 and 10 km. A more specific definition of the model resolution would be helpful for readers.
• Line 119: Is the freshwater flux separated into solid and liquid components? If not, could the authors provide a rationale for this choice?
• Lines 153-154: The model diffusion/viscosity is zero. What boundary condition is used for the tangential velocity component, and does this formulation accurately represent the friction in the lateral boundary Ekman layer?
• Lines 348-350: The salinity model error may be related to boundary conditions in this region of the model domain. Do the GLORYS simulations provide adequate boundary conditions? The higher horizontal resolution of your model suggests that the GLORYS model might underestimate horizontal advective transport through the open boundary of the St. Lawrence Estuary.
• Lines 550-556: The impact of tides on temperature and salinity in the Bay of Fundy appears minimal (Fig. 19). Could the authors discuss why the tidal effect is relatively small in this area? I would expect them to be more significant.
Thank you for considering these suggestions to enhance the manuscript.

Citation: https://doi.org/10.5194/egusphere-2024-1372-RC2
- AC3: 'Reply on RC2', Kyoko Ohashi, 10 Sep 2024
  
  We thank the referee for taking the time to review our manuscript and for providing supportive comments. Please find in the attached file our response to your comments.
  
  Citation: https://doi.org/10.5194/egusphere-2024-1372-AC3

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-1372', Anonymous Referee #1, 11 Aug 2024
Biogeochemical modeling is increasingly important for both understanding biogeochemical processes and predicting rapidly changing ocean conditions due to ongoing climate change. The authors have developed a fully coupled NWA model that integrates ocean, ice, and biogeochemical components, meeting the needs of many researchers working in this region. Sensitivity analyses enhance understanding of the roles of tides and sea ice in model biases.
This manuscript is well written. The authors use RMSE, RMSD, and other statistical measures to evaluate the performance of the model runs, which is appropriate. While it is known that the Northwest Atlantic Ocean has been undergoing significant changes, temporal changes in the ocean can serve as important indicators of the impact of climate change. Although the short simulation period of 4 years may not be useful for climate research, I suggest the authors select specific locations to demonstrate whether the models can properly simulate the evolution of key variables (monthly mean or annual mean). Numerous observed sea surface temperature data, bottom temperature data (summertime), current meter data, and other types of data are available for this region, which could be used to further investigate model performance. This would enhance the confidence of readers and future users in the model. Additionally, winter convection events in the Labrador Sea are believed to be a significant driver of circulation in the North Atlantic Ocean, impacting water mass properties in this region. It is worth reporting whether the ROMS model can well simulate these winter convection events during the study period.

Below is a list of specific comments.
Line 34 “up to 7”, could “up to 7 psu” be better”?

Lines 153-154. Why are the eddy viscosity and diffusivity set to zero? Given that you employ high-order accuracy schemes (3rd and 4th order), it’s unclear why these values would be zero. Could you provide a rationale for this choice?

Lines 172-174. Are the inter-annually variable GLORYS12 data used at open boundaries or the daily climatological ones? Please specify.

Lines 182-183. I am curious why it is through the bottom. River discharge is through top layers.

Lines 298-299. Glorys12 uses data assimilation (4d var), and in theory, this can eliminate those biases from the non-inclusion of tides.

Lines 310-311. Same as above. You may want to find some literature to support this statement.

Lines 369-378. This seems an indication of numerical scheme issue or the horizontal mixing issue (zero is used).

Lines 409-425. Data from Drinkwater (1988) were for the year of 1982, and the data your model and GLORYS12 are for the recent years. You need to mention the probable existence of decadal or even longer variability for the current in this area.

Figure 13. I cannot see any dots there. Could the quality of the figure need improving?
Citation: https://doi.org/10.5194/egusphere-2024-1372-RC1
- AC1:
  'Reply on RC1', Kyoko Ohashi, 28 Aug 2024
  
  We thank the referee for taking the time to review our manuscript and for providing supportive comments. Please find in the attached file our response to your comments.
  
  Citation: https://doi.org/10.5194/egusphere-2024-1372-AC1
  - RC3: 'Reply on AC1', Anonymous Referee #1, 05 Sep 2024
    
    Thank you to the authors for their comprehensive responses to my questions and comments. The proposed changes are acceptable.
    However, I would like to reiterate my concern regarding the choice of zero for both the eddy viscosity and diffusivity. I believe that further refinement of the model with more appropriate values for these parameters could enhance its accuracy and predictive capabilities
    
    Citation: https://doi.org/10.5194/egusphere-2024-1372-RC3
    
    AC2: 'Reply on RC3', Kyoko Ohashi, 10 Sep 2024
    
    Thank you for your reply. In response to your concern about the horizontal eddy diffusivity and viscosity being zero, we have modified the discussion of possible future research directions (Page 44, Line 742 in the original version) to the following (new part in italics): "In addition to studies of the biological carbon pump and of the downstream effects of changes in the water transported by the Labrador Current, another possible direction of future research is to explore further the effects of model configuration, such as parameterization of deep convection or the choice of advection schemes (including the use of non-zero horizontal eddy diffusivity and viscosity with the third-order upstream scheme). In addition, ...".
    
    Citation: https://doi.org/10.5194/egusphere-2024-1372-AC2
    
    RC4: 'Reply on AC2', Anonymous Referee #2, 11 Sep 2024
    
    Thank you for your response and the additions. I agree with your point about incorporating a small viscosity/diffusivity; this adjustment may enhance the accuracy of future simulations in certain subregions of your model domain. Overall, this is a minor detail compared to the solid work you’ve accomplished in developing and validating DalROMS for the western North Atlantic.
    
    Citation: https://doi.org/10.5194/egusphere-2024-1372-RC4
    
    AC4: 'Reply on RC4', Kyoko Ohashi, 11 Sep 2024
    
    Thank you for the positive comments!
    
    Citation: https://doi.org/10.5194/egusphere-2024-1372-AC4
RC2:
'Comment on egusphere-2024-1372', Anonymous Referee #2, 02 Sep 2024

The manuscript presents results from implementing and validating a coupled ocean-sea ice-biochemical model of the North Atlantic. The authors developed an advanced coupling between the ROMS and CICE ice models. Model results are compared with surface and in situ ocean observations, and the validation encompasses various setups, including model forecasts, simulations constrained by observed temperature and salinity, and scenarios without tides or sea ice.
The manuscript is well-written, and the model validation results are robust. The authors’ conclusions are well-supported by various statistical measures of model error. The model validation demonstrates the model's significant potential for future diagnostic and prognostic climate change simulations in the Western North Atlantic.
However, I recommend adding further discussion on several aspects of the model setup and simulations:
• Lines 55-56: Is deep convection an additional or dominant component of CO₂ removal in the Labrador Sea, as Tian et al. (2004) discussed? Clarifying this point would strengthen the manuscript.
• Line 104: The resolution of "O(km)" is mentioned. Currently, eddy-resolving circulation models of the North Atlantic typically have resolutions between 1 and 10 km. A more specific definition of the model resolution would be helpful for readers.
• Line 119: Is the freshwater flux separated into solid and liquid components? If not, could the authors provide a rationale for this choice?
• Lines 153-154: The model diffusion/viscosity is zero. What boundary condition is used for the tangential velocity component, and does this formulation accurately represent the friction in the lateral boundary Ekman layer?
• Lines 348-350: The salinity model error may be related to boundary conditions in this region of the model domain. Do the GLORYS simulations provide adequate boundary conditions? The higher horizontal resolution of your model suggests that the GLORYS model might underestimate horizontal advective transport through the open boundary of the St. Lawrence Estuary.
• Lines 550-556: The impact of tides on temperature and salinity in the Bay of Fundy appears minimal (Fig. 19). Could the authors discuss why the tidal effect is relatively small in this area? I would expect them to be more significant.
Thank you for considering these suggestions to enhance the manuscript.

Citation: https://doi.org/10.5194/egusphere-2024-1372-RC2
- AC3: 'Reply on RC2', Kyoko Ohashi, 10 Sep 2024
  
  We thank the referee for taking the time to review our manuscript and for providing supportive comments. Please find in the attached file our response to your comments.
  
  Citation: https://doi.org/10.5194/egusphere-2024-1372-AC3

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Kyoko Ohashi on behalf of the Authors (02 Oct 2024) Author's response Author's tracked changes Manuscript

ED: Publish as is (10 Oct 2024) by Andrew Yool

AR by Kyoko Ohashi on behalf of the Authors (16 Oct 2024)

Journal article(s) based on this preprint

10 Dec 2024

DalROMS-NWA12 v1.0, a coupled circulation–ice–biogeochemistry modelling system for the northwest Atlantic Ocean: development and validation

Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver

Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024,https://doi.org/10.5194/gmd-17-8697-2024, 2024

Short summary

Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver

Data sets

DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: input files (1 of 3) K. Ohashi et al. https://zenodo.org/records/12752190

DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: input files (2 of 3) K. Ohashi et al. https://zenodo.org/records/12734049

DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: input files (3 of 3) K. Ohashi et al. https://zenodo.org/records/12735153

DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: output files (1 of 2) K. Ohashi et al. https://zenodo.org/records/12744506

DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: output files (2 of 2) K. Ohashi et al. https://zenodo.org/records/12746262

Model code and software

DALROMS-NWA12 v1.0, a coupled circulation-sea ice-biogeochemistry model for the northwest North Atlantic: codes and namelists K. Ohashi et al. https://zenodo.org/records/12752091

Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver

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We developed a modelling system of the northwest Atlantic Ocean that simulates the currents, temperature, salinity, and parts of the biochemical cycle of the ocean, as well as sea ice. The system combines advanced, open-source models and can be used to study, for example, the oceans’ capture of atmospheric carbon dioxide which is a key process in the global climate. The system produces realistic results, and we use it to investigate the roles of tides and sea ice in the northwest Atlantic Ocean.


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