the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 Sep 2024
Numerical Models for Monitoring and Forecasting Sea Ice: a short description of present status
Abstract. The severe changes in climate resulting in the polar oceans getting warmer – with drastic consequences to their physical, biogeochemical and biological state – require forecasting systems that can accurately simulate and skilfully predict the state of the ice cover and its temporal evolution. Sea-ice processes significantly impact ocean circulation, water mass formation and modifications, and air-sea fluxes. They comprise vertical processes, mainly related to thermodynamics, and horizontal ones, due to internal sea ice mechanics and motion. We provide an overview on how these processes can be modelled and how operational systems are working, in combination with data assimilation techniques, to enhance accuracy and reliability. We also emphasize the need for advancing research on improving such numerical techniques by highlighting currents limits and ways forward.
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RC1: 'Comment on sp-2024-24', Anonymous Referee #1, 19 Oct 2024
General comments:
This paper provides an overview of sea ice process, modeling, and short-term forecast by referring to previous literature including the most recent papers. It would be very helpful for general readers who are not familiar with the sea ice modeling and forecast but are interested in their product. Since this paper focuses on the general description of the past studies, there are no new values to be added in the sea ice research community. Overall, the paper is well written and organized with some evidence, but there are a few more things to be added in the paper which would help further improve the understanding of the sea ice process, modeling, and forecast. Below are major and more specific comments on this paper.
1. Biogeochemistry (L65-68)
The authors mentioned only about the sea animals and algae around the sea ice, but the sea ice also plays an important role in the exchange of natural and anthropogenic gases such as carbon dioxides and aerosols that are crucial sources of nutrients for the phytoplankton and other sea life below the sea ice. Could the authors expand the section a bit more by adding a few more sentences on the sea ice role in the biogeochemical cycle (e.g., carbon and nutrients)?
2. Model bias and further improvement (L107-L114)
At the end of this paper, the authors discussed the model bias in forecasting the sea ice edge and boundary between the first and multi-year ice, but what are the underlying causes of these model biases (e.g., model physics, resolutions, ensemble members, data assimilation techniques, and/or observation)? Also, what measures can the sea ice modeling community undertake the most to reduce the forecast errors? The authors suggested two research thrusts in the end, but I could not find the link to these errors, wondering how these suggestions can help resolve the model biases.
Specific comments:
L20: To meet this goal,
L39, 41: “birthday party” is a bit narrative. Is it a well-accepted expression in the scientific community?
L40: This process is called “brine rejection”, so you may add this word in the sentence.
L60: I am a bit confused. Does it mean a positive feedback, because the waves get amplified with smaller ice floes and generate more ice floes with smaller scales.
Figure 1: Do you have any satellite observation map to validate the model simulation? This would help readers to understand how reasonably the model reproduces the sea ice thickness.
Table 1: “SIUV motions” should be “SIUV velocities”. What is “SID”? Also, remove “**” in the area of the IcePOM in the table.
Citation: https://doi.org/10.5194/sp-2024-24-RC1 -
AC1: 'Reply on RC1', Laurent Bertino, 29 Nov 2024
We would like to thank the reviewer for his careful review.
1. Biogeochemistry:
Thanks for bringing more issues to our attention. The following points will be added:
- Sea ice holds nutrients, some airborne, others having ocean cycles only (silicates). Nutrients are flushed to the surface ocean through brine channels, like salt. A very recent reference to Lund-Hansen et al. (2024) has been added.
- Sea ice carries sediments, nutrients, various biological material and pollutants from the shallow shelf seas to the central Arctic (Krumpen et al. 2019).
- Sea ice acts as a lid preventing exchange of greenhouse gases fluxes between ocean and atmosphere, but the sea ice also holds its own carbon pump accounting for 30% of the Carbon uptake in the Arctic (Richaud et al. 2023).
2. Model bias and further improvement
Thanks for keeping our feet on the ground, we have tried to improve the logic and make this section more conclusive by introducing this text:
"Biases in sea ice area coverage arise from multiple sources, primarily from biased ocean and atmospheric boundary conditions, but also intrinsic biases of the sea ice model itself. These biases interact with each other in complex ways (feedback loops or cancellation of errors).
The main avenues towards reducing these biases are the following:- Advocating for optimal observing networks, using data assimilation techniques.
- Improving atmospheric and ocean models, in particular the representation of their boundary layers.
- Improving sea ice models.
- In the meantime, post-processing techniques, now aided by machine learning, are a novelty in sea ice forecasting (Parleme et al. 2021, 2023). "
Specific comments:
L20: To meet this goal,
OK.
L39, 41: “birthday party” is a bit narrative. Is it a well-accepted expression in the scientific community?
It is not, this is an original attempt to catch the readers’ attention. We aim at readers outside of the sea ice community and hope that some light humour will stimulate their long-term memory. There are other basic emotions such as sadness, fear or anger that can help forming long-term memories, but we will rather choose joy.
L40: This process is called “brine rejection”, so you may add this word in the sentence.
Thanks, added.
L60: I am a bit confused. Does it mean a positive feedback, because the waves get amplified with smaller ice floes and generate more ice floes with smaller scales.
No, it is a negative feedback: the waves are scattered by more numerous ice-ocean edges of smaller floes and are attenuated. Clarified in the text.
Figure 1: Do you have any satellite observation map to validate the model simulation? This would help readers to understand how reasonably the model reproduces the sea ice thickness.
OK, adding CS2SMOS for the same date.Table 1: “SIUV motions” should be “SIUV velocities”. What is “SID”? Also, remove “**” in the area of the IcePOM in the table.
Thanks for the corrections. SID is Sea ice Drift, replaced by SIUV in the new text.
Stars are footnotes to the captions.Citation: https://doi.org/10.5194/sp-2024-24-AC1
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AC1: 'Reply on RC1', Laurent Bertino, 29 Nov 2024
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RC2: 'Comment on sp-2024-24', Anonymous Referee #2, 24 Oct 2024
General comments:
This manuscript provides a brief overview of recent developments in numerical models for sea-ice. It covers fundamental physical processes, modelling approaches, and operational systems with data assimilation techniques, and provides a summary of modern numerical models and operational system for sea ice. The manuscript also draws attention to the challenges and concerns in developing sea ice modeling, numerical solvers, and machine learning applications. The manuscript is concise and informative, thus suitable for publication.
Specific comments:
Line 60: "Smaller ice floes offer more reflecting edges and are more efficient at attenuating waves." This statement is incomprehensive as it only mentions reflection or scattering, but not dissipation through multiple energy non-conservative processes in the ice effects on waves, which is also mentioned in Squire (2020).
Technical corrections:
Regarding Chapter 2's organization: The "Overview of processes in sea ice" currently includes sections that aren't strictly processes (numerical models and data assimilation). I would recommend that the author consider restructuring the technical sections into a new chapter regarding the current modeling approaches.
In Table 1, it mentions "*Output interpolated to 9 km" in the caption, but the corresponding entry isn't shown in the table. Moreover, the links for GIOPS and RIOPS are not precise, and Met Office FOAM may also need a relevant link.
Citation: https://doi.org/10.5194/sp-2024-24-RC2 -
AC2: 'Reply on RC2', Laurent Bertino, 29 Nov 2024
We would like to thank the reviewer for the constructive remarks.
Specific comments:
Line 60: "Smaller ice floes offer more reflecting edges and are more efficient at attenuating waves." This statement is incomprehensive as it only mentions reflection or scattering, but not dissipation through multiple energy non-conservative processes in the ice effects on waves, which is also mentioned in Squire (2020).
Thanks for the insightful remark, dissipation has been added.Technical corrections:
Regarding Chapter 2's organization: The "Overview of processes in sea ice" currently includes sections that aren't strictly processes (numerical models and data assimilation). I would recommend that the author consider restructuring the technical sections into a new chapter regarding the current modeling approaches.
Correct, all these subsections have been turned into sections.In Table 1, it mentions "*Output interpolated to 9 km" in the caption, but the corresponding entry isn't shown in the table. Moreover, the links for GIOPS and RIOPS are not precise, and Met Office FOAM may also need a relevant link.
Thanks, the missing asterisk has been added to the ECMWF line in the table.
The links for GIOPS and RIOPS were provided by ECCC.
The FOAM high-resolution forecast system is distributed to selected users and has been removed from the table.Citation: https://doi.org/10.5194/sp-2024-24-AC2
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AC2: 'Reply on RC2', Laurent Bertino, 29 Nov 2024
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