the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at km-scale
- 1Met Office, Exeter, EX1 3PB, UK
- 2National Centre for Medium Range Weather Forecasting (NCMRWF), India
- 3National Oceanography Centre, Liverpool, UK
- 4UK Centre of Ecology & Hydrology (UKCEH), UK
- 5University of Leeds, UK
- 6India Meteorological Department (IMD), India
- 7University of Reading, UK
- 8INCOIS, India
- 1Met Office, Exeter, EX1 3PB, UK
- 2National Centre for Medium Range Weather Forecasting (NCMRWF), India
- 3National Oceanography Centre, Liverpool, UK
- 4UK Centre of Ecology & Hydrology (UKCEH), UK
- 5University of Leeds, UK
- 6India Meteorological Department (IMD), India
- 7University of Reading, UK
- 8INCOIS, India
Abstract. A new regional coupled modelling framework is introduced – the Regional Coupled Suite (RCS). This provides a flexible research capability with which to study the interactions between atmosphere, land, ocean and wave processes resolved at km-scale, and the effect of environmental feedbacks on the evolution and impacts of multi-hazard weather events. A configuration of the RCS focussed on the Indian region, termed RCS-IND1, is introduced. RCS-IND1 includes a regional configuration of the Unified Model (UM) atmosphere, directly coupled to the JULES land surface model, on a grid with horizontal spacing of 4.4 km, enabling convection to be explicitly simulated. These are coupled through OASIS3-MCT libraries to 2.2 km grid NEMO ocean and WAVEWATCH III wave model configurations. To examine a potential approach to reduce computation cost, and simplify ocean initialisation, the RCS includes an alternative approach to couple the atmosphere to a lower resolution Multi-Column K Profile Parameterization (KPP) for the ocean. Through development of a flexible modelling framework, a variety of fully and partially coupled experiments can be defined, along with traceable uncoupled simulations and options to use external input forcing in place of missing coupled components. This offers a wide scope to researchers designing sensitivity and case study assessments. Case study results are presented and assessed to demonstrate the application of RCS-IND1 to simulate two tropical cyclone cases which developed in the Bay of Bengal, namely Titli in October 2018 and Fani in April 2019. Results show realistic cyclone simulations, and that coupling can improve the cyclone track and produces more realistic intensification than uncoupled simulations for Titli but prevents sufficient intensification for Fani. Atmosphere-only UM regional simulations omit the influence of frictional heating on the boundary layer to prevent cyclone over-intensification. However, it is shown that this term can improve coupled simulations, enabling a more rigorous treatment of the near-surface energy budget to be represented. For these cases, a 1D mixed layer scheme shows similar first-order SST cooling and feedback on the cyclones as a 3D ocean. Nevertheless, the 3D ocean generally shows stronger localised cooling than the 1D ocean. Coupling with the waves have limited feedback on the atmosphere for these cases. Priorities for future model development are discussed.
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Juan Manuel Castillo et al.
Status: closed
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RC1: 'Comment on gmd-2022-7', Anonymous Referee #1, 06 Feb 2022
Generally, this paper is well written and is important to the regional coupled model community. Therefore, I recommend publication in the Geoscientific Model Development after minor revisions.
Please read the enclosed pdf for details. [gmd-2022-7_comment_R1.pdf]
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RC3: 'Reply on RC1', Anonymous Referee #3, 21 Feb 2022
Review of the paper “The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at km scale”
General Comments
In the paper entitled “The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at km scale” by Castillo et al., the Authors introduces and describes a new high resolution coupled modeling tool for the Indian region. Using different modeling configurations its performances are investigated using two case studies related to tropical cyclone activity in area. The manuscript is well written and clear and I suggest its publication after some minor revisions.
Specific comment
Line 46-56: I would move this part at the end of the introduction.
Line 85- Chlorophyll-a
Line 113 where, required,..
Line 123-125 I do not understand very well this statement. Do you mean that Jules behaves as a library of the UM? Please explain better
Section 2.1, section 2.3 and section 2.4 : I would merge these sections in just one. In this way a potential Reader would not need to jump from section 2.1 to section 2.3 to get information about the vertical resolution of the ocean model NEMO (as I did)
Fig.1 the two colorbars share some colors (for example the blue). This could lead to some confusion in reading the Figure 1. I would suggest to redraw the figure 1 with different colorbars.
Line 276 What do you mean with “multi-annual”…please specify.
Figure 3-4 Maybe using oC would make the maps and graphs more readable. I would also use different markers and colors for the location of the buoys. Did you test if the differences observed in the maps are statistically significant or not? This question holds also for other figures where you compare observations and simulated fields.
Line 465-466. Could you please describe better how you detect and track tropical cyclone.
I find really interesting the discussion and conclusions paragraph. Probably I missed the point but I do not understand if there exists a better configuration with respect to other tested in your experiments or which is able to balance different factors such as biases, computational time... Could you please infer a little bit more about?
-
RC3: 'Reply on RC1', Anonymous Referee #3, 21 Feb 2022
-
RC2: 'Comment on gmd-2022-7', Anonymous Referee #2, 18 Feb 2022
General comments
This paper presents a new regional coupled modelling framework focussed on the Indian region, termed RCS-IND1. The framework includes the Unified Model (UM) as atmospheric component, directly coupled to the JULES land surface model, on a grid with horizontal spacing of 4.4 km, enabling convection to be explicitly simulated. These models are coupled through the OASIS3-MCT coupler to the NEMO ocean circulation model and the WAVEWATCH III wave model configured on a grid with horizontal spacing of 2.2 km. The coupled system was tested in two tropical cyclone cases in the Indian region, namely Titli in October 2018 and Fani in April 2019, using five different coupling strategies. It is a very good work carefully written with very interesting findings supporting the research in air-sea coupled modeling systems and tropical cyclones. However, I can suggest it for publication after minor revisions.
Specific Comments
Line 63: “focussed” is used in the rest of manuscript
Lines 189-191: I am trying to understand this advantage. Please give an example and provide more details, because the air-sea momentum transfer is a very important factor in cyclones.
Line 210: Does the time step refer to the atmospheric model or to the land surface model? For a resolution of 4.4 km, an atmospheric time step of 120 s sounds large. Please clarify it.
Line 227: Improve -> Improvement of
Section 2.6: Please provide information about the bathymetry used in the wave model.
Line 315: How did you choose the upper limit of 0.32 for Charnock?
Lines 373-374: I suppose that with the term “frictional heating” you mean dissipative heating. It is usually considered as a term that added in sensible heat flux calculation in surface layer parameterizations of atmospheric models. How do you estimate it in your model? E.g., provide an equation.
486-487: MSLP differences of 30-36 hPa seem very large. I think that the SST cooling presented in this study may hardly result in such large pressure differences? Do they agree with MSLP differences reported by other studies using coupled systems for tropical cyclones?
Line 498: Why does AOW result in slightly earlier intensification? The increased wave-induced sea surface roughness in AOW is expected to delay the intensification due to the kinetic energy loss in the surface layer. Please explain your finding.
Line 510: is however -> are however
Line 535: “having increased MSLP”. Maybe, do you mean “decreased”?
Line 554-557: How is this inconsistency in MSLP and maximum wind speed explained?
Lines 555 & 557, Table 8 and Figures 7 & 8: m/s is preferable than knots to be consistent with Figures 5, 6 and 9.
Line 575: You mention that the impact of wave coupling on wind speeds is relatively small. However, according to relative studies using coupled systems, wave coupling seems to have strong effects on momentum exchange and, subsequently, on wind speed because it changes the roughness length and the drag coefficient. I appreciate your discussion in L581-592 about sea surface drag and the decrease of drag coefficient in high intensities, but please further explain the finding presented in L575. Also, write in the text a range of wind speed differences between the simulations because the color palette does not help the readers to quantify the differences.
Lines 595-628: It is a little unclear for me which simulation has the best overall performance. Putting it another way, which coupled configuration would you choose to better predict rainfall during TCs in the India region? An approach using contingency table and respective statistics for discrete variables could support the evaluation.
Lines 672-674: Do you use a drag formulation including saturation in very high wind speeds? Such formulation could impact not only momentum exchange but also heat exchange through the change of Ck (bulk air-sea enthalpy transfer coefficient). Please provide more information about these important processes in the surface layer.
Table 9: Please check output/day values, they seem inconsistent. For example, AOW resulted to 109 Gb/day, but summing a, o and w gives 42 Gb/day.
Figures 12 & 13: Although the spatially accumulated precipitation expressed in mm can be used for the comparison of simulations results, it is dependent on horizontal spacing used and, thus, it does not have robust physical meaning. For example, if you used 2 times higher resolution you would have 4 times higher spatially accumulated precipitation values, given the same area. So, it would be better to express the spatially accumulated precipitation as kg (or tons) per total area instead of mm. Another approach would be the estimation of areal precipitation which is the average precipitation depth over the area.
-
AC1: 'Comment on gmd-2022-7', Huw Lewis, 22 Apr 2022
We are grateful to the 3 anonymous reviewers who gave their time to consider the submitted manuscript and for their insightful comments and positive responses. We kindly acknowledge that all reviewers commended the paper content and relevance and agreed that the manuscript should be accepted for publication following minor revisions. The specific comments received will be addressed in a revised manuscript with tracked changes that will be submitted on finalising this author response.
A detailed summary of responses to all review comments is provided in the supplement pdf response, including references to amendments that are included in the revised manuscript. Original review comments are shown in red for clarity, with author comments in black.
Status: closed
-
RC1: 'Comment on gmd-2022-7', Anonymous Referee #1, 06 Feb 2022
Generally, this paper is well written and is important to the regional coupled model community. Therefore, I recommend publication in the Geoscientific Model Development after minor revisions.
Please read the enclosed pdf for details. [gmd-2022-7_comment_R1.pdf]
-
RC3: 'Reply on RC1', Anonymous Referee #3, 21 Feb 2022
Review of the paper “The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at km scale”
General Comments
In the paper entitled “The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at km scale” by Castillo et al., the Authors introduces and describes a new high resolution coupled modeling tool for the Indian region. Using different modeling configurations its performances are investigated using two case studies related to tropical cyclone activity in area. The manuscript is well written and clear and I suggest its publication after some minor revisions.
Specific comment
Line 46-56: I would move this part at the end of the introduction.
Line 85- Chlorophyll-a
Line 113 where, required,..
Line 123-125 I do not understand very well this statement. Do you mean that Jules behaves as a library of the UM? Please explain better
Section 2.1, section 2.3 and section 2.4 : I would merge these sections in just one. In this way a potential Reader would not need to jump from section 2.1 to section 2.3 to get information about the vertical resolution of the ocean model NEMO (as I did)
Fig.1 the two colorbars share some colors (for example the blue). This could lead to some confusion in reading the Figure 1. I would suggest to redraw the figure 1 with different colorbars.
Line 276 What do you mean with “multi-annual”…please specify.
Figure 3-4 Maybe using oC would make the maps and graphs more readable. I would also use different markers and colors for the location of the buoys. Did you test if the differences observed in the maps are statistically significant or not? This question holds also for other figures where you compare observations and simulated fields.
Line 465-466. Could you please describe better how you detect and track tropical cyclone.
I find really interesting the discussion and conclusions paragraph. Probably I missed the point but I do not understand if there exists a better configuration with respect to other tested in your experiments or which is able to balance different factors such as biases, computational time... Could you please infer a little bit more about?
-
RC3: 'Reply on RC1', Anonymous Referee #3, 21 Feb 2022
-
RC2: 'Comment on gmd-2022-7', Anonymous Referee #2, 18 Feb 2022
General comments
This paper presents a new regional coupled modelling framework focussed on the Indian region, termed RCS-IND1. The framework includes the Unified Model (UM) as atmospheric component, directly coupled to the JULES land surface model, on a grid with horizontal spacing of 4.4 km, enabling convection to be explicitly simulated. These models are coupled through the OASIS3-MCT coupler to the NEMO ocean circulation model and the WAVEWATCH III wave model configured on a grid with horizontal spacing of 2.2 km. The coupled system was tested in two tropical cyclone cases in the Indian region, namely Titli in October 2018 and Fani in April 2019, using five different coupling strategies. It is a very good work carefully written with very interesting findings supporting the research in air-sea coupled modeling systems and tropical cyclones. However, I can suggest it for publication after minor revisions.
Specific Comments
Line 63: “focussed” is used in the rest of manuscript
Lines 189-191: I am trying to understand this advantage. Please give an example and provide more details, because the air-sea momentum transfer is a very important factor in cyclones.
Line 210: Does the time step refer to the atmospheric model or to the land surface model? For a resolution of 4.4 km, an atmospheric time step of 120 s sounds large. Please clarify it.
Line 227: Improve -> Improvement of
Section 2.6: Please provide information about the bathymetry used in the wave model.
Line 315: How did you choose the upper limit of 0.32 for Charnock?
Lines 373-374: I suppose that with the term “frictional heating” you mean dissipative heating. It is usually considered as a term that added in sensible heat flux calculation in surface layer parameterizations of atmospheric models. How do you estimate it in your model? E.g., provide an equation.
486-487: MSLP differences of 30-36 hPa seem very large. I think that the SST cooling presented in this study may hardly result in such large pressure differences? Do they agree with MSLP differences reported by other studies using coupled systems for tropical cyclones?
Line 498: Why does AOW result in slightly earlier intensification? The increased wave-induced sea surface roughness in AOW is expected to delay the intensification due to the kinetic energy loss in the surface layer. Please explain your finding.
Line 510: is however -> are however
Line 535: “having increased MSLP”. Maybe, do you mean “decreased”?
Line 554-557: How is this inconsistency in MSLP and maximum wind speed explained?
Lines 555 & 557, Table 8 and Figures 7 & 8: m/s is preferable than knots to be consistent with Figures 5, 6 and 9.
Line 575: You mention that the impact of wave coupling on wind speeds is relatively small. However, according to relative studies using coupled systems, wave coupling seems to have strong effects on momentum exchange and, subsequently, on wind speed because it changes the roughness length and the drag coefficient. I appreciate your discussion in L581-592 about sea surface drag and the decrease of drag coefficient in high intensities, but please further explain the finding presented in L575. Also, write in the text a range of wind speed differences between the simulations because the color palette does not help the readers to quantify the differences.
Lines 595-628: It is a little unclear for me which simulation has the best overall performance. Putting it another way, which coupled configuration would you choose to better predict rainfall during TCs in the India region? An approach using contingency table and respective statistics for discrete variables could support the evaluation.
Lines 672-674: Do you use a drag formulation including saturation in very high wind speeds? Such formulation could impact not only momentum exchange but also heat exchange through the change of Ck (bulk air-sea enthalpy transfer coefficient). Please provide more information about these important processes in the surface layer.
Table 9: Please check output/day values, they seem inconsistent. For example, AOW resulted to 109 Gb/day, but summing a, o and w gives 42 Gb/day.
Figures 12 & 13: Although the spatially accumulated precipitation expressed in mm can be used for the comparison of simulations results, it is dependent on horizontal spacing used and, thus, it does not have robust physical meaning. For example, if you used 2 times higher resolution you would have 4 times higher spatially accumulated precipitation values, given the same area. So, it would be better to express the spatially accumulated precipitation as kg (or tons) per total area instead of mm. Another approach would be the estimation of areal precipitation which is the average precipitation depth over the area.
-
AC1: 'Comment on gmd-2022-7', Huw Lewis, 22 Apr 2022
We are grateful to the 3 anonymous reviewers who gave their time to consider the submitted manuscript and for their insightful comments and positive responses. We kindly acknowledge that all reviewers commended the paper content and relevance and agreed that the manuscript should be accepted for publication following minor revisions. The specific comments received will be addressed in a revised manuscript with tracked changes that will be submitted on finalising this author response.
A detailed summary of responses to all review comments is provided in the supplement pdf response, including references to amendments that are included in the revised manuscript. Original review comments are shown in red for clarity, with author comments in black.
Juan Manuel Castillo et al.
Data sets
Data used in preparation of manuscript figures Castillo, J. M. et al. https://doi.org/10.5281/zenodo.5831574
Juan Manuel Castillo et al.
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