the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 13 Dec 2024
Impacts of CICE sea ice model and ERA atmosphere on an Antarctic MetROMS ocean model, MetROMS-UHel-v1.0
Abstract. In recent years, the Antarctic sea ice has experienced major changes, which are neither well understood nor adequately reproduced by earth system models. To support model development with an aim to improve Antarctic sea ice and upper ocean predictions, the impacts of updating the sea ice model and the atmospheric forcing are investigated. In the new MetROMS-UHel-v1.0 (henceforth MetROMS-UHel) ocean-sea ice model, the sea ice component has been updated from CICE5 to CICE6, and the forcing has been updated from ERA-Interim to ERA5 reanalyses. Both CICE sea ice models were coupled with the regional ROMS ocean model. We find that the update of CICE and ERA reduced the negative bias of the sea ice area in summer. However, the sea ice volume decreases after the CICE update but increase when the atmospheric forcing is updated. As a net result after both updates, the modelled sea ice becomes thinner and more deformed, particularly near the coast. The ROMS ocean model usually yielded a deeper ocean mix layer compared to observations. Using ERA5, the situation was slightly improved. The update from CICE5 to CICE6 resulted in a fresher coastal ocean due to a smaller salt flux from sea ice to the ocean. In the ice shelf cavities, the modelled melt rates are underestimated compared with observations, which could be attributed to missing tides and inadequate model resolution. These identified sea ice and oceanic changes vary seasonally and regionally. By determining sea ice and oceanic changes after the model and forcing updates, and evaluating them against observations, this study informs modellers on improvements and aspects requiring attention with potential model adjustments.
- Preprint
(35074 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 07 Feb 2025)
-
RC1: 'Comment on gmd-2024-213', Anonymous Referee #1, 20 Dec 2024
reply
“Impacts of CICE sea ice model and ERA atmosphere on an Antarctic MetROMS ocean model, MetROMS-UHel-v1.0” by Ӓijälä and colleagues evaluates a circumpolar Southern Ocean model including sea ice and ice shelf cavities. Compared to a previously published version of the model, both the atmospheric forcing and sea ice component have been updated. The impacts of each change in isolation are evaluated, as well as both changes together. Evaluation focuses on sea ice properties, with ocean hydrography and ice shelf melting given a secondary focus. In general the updates to the model are beneficial for the representation of sea ice, but problematic for ocean hydrography, particularly a freshening of the continental shelves.
General comments:
In general this is a solid and thorough evaluation paper including some clever analysis of sea ice model performance. I believe it is suitable for GMD after moderate revisions.
In particular, there are a few missing pieces which would help to fill in the oceanographic gaps in the story:
- Some quantification of ACC strength, ideally a figure showing transport through Drake Passage. The text mentions it slows down, which is concerning, but does not quantify either the initial bias or the degree of drift.
- A figure of the overturning streamfunction in each model configuration. I suspect that the coastal freshening induced by the update to CICE6 is shutting down dense water export from the shelf. Quantifying the strength of the lower cell would confirm this.
- Some analysis of the sea ice formation rates in each experiment, as this process is crucial for setting the shelf water masses.
- A figure (bar chart?) showing ice shelf mass loss integrated over each main ice shelf or region, compared to observations. This would make it much easier to gauge the regional dependence in model bias. From the existing figures it is very difficult to parse the magnitude of the bias or model sensitivity in the small, high-melt cavities in the Amundsen Sea, as well as the large, cold cavities which experience both melting and refreezing.
The manuscript also errs too much on the side of simple description, with some missed opportunities for attribution (i.e. which physical processes are behind the model bias visualised?) Of course it would be excessive to fully analyse the causes of all model biases in one manuscript, but at least some discussion of the likely possibilities is warranted. In my specific comments below I have highlighted examples where this is particularly needed.
Specific comments:
Line 5: It’s worth mentioning more explicitly in the abstract that ice shelf cavities are included, as this is not generally true of Southern Ocean models.
Line 37: You could make the argument that modelling Antarctic sea ice is also challenging because historically, most development and tuning has been focused on Arctic conditions, which are not entirely transferable to Antarctica.
Line 68: What specific changes have been made to the CICE physics parameterisations? If we knew which processes in particular had been updated or added, it could make attribution of the model behaviour easier later. Were any of the bug fixes critical?
Line 71: Naughten et al. 2018, which the baseline MetROMS-Iceshelf simulation seems to follow, used elastic-anisotropic-plastic rheology rather than EVP. What was the rationale for changing this and what was the impact? Are there any other major changes from the original model? I note that the total ice shelf basal mass loss was higher in Naughten et al. than any of the four simulations presented here, and I’m curious as to why.
Figure 1b: The two different blue shadings are hard to distinguish, could you use two more different colours?
Line 128: As with CICE6, the improvements made in ERA5 are summarised as “development in model physics”, which could mean any number of things. Which specific processes have been improved?
Line 134: Note that this salinity restoration is only at the surface.
Line 139: Why is the salinity restoring necessary? It’s an unfortunate limitation on the model and the sort of experiments for which it is suitable. Given the updates to ERA and CICE, have you tried switching it off?
Line 139: ABW should be AABW.
Line 141: Why is there zero zonal velocity at the northern boundary? This seems equivalent to a no-slip condition, i.e. treating 30S as a solid wall. I wonder if this is contributing to slowing down the ACC, as noted later. Or, is it sufficiently clear of the northern front of the ACC?
Line 185: Are the biases in spring (too much ice offshore and too little close to the coast) linked to the strong sea ice drift shown later (i.e. excessive export of ice)? Or are they the beginnings of the summertime low bias, driven by thermodynamic melting?
Line 198: Why might the Pacific and Indian Ocean sectors show the largest underestimation? They are quite a different regime to the other sectors, oceanographically.
Figure 4: It would be interesting to fit linear trends to the observations and models, perhaps piecewise breaking around 2014.
Line 310: Do the CICE6 simulations generally have younger sea ice (there should be an age tracer to analyse)? This would make sense, together with less ridging, thinner coastal ice, stronger export, and possibly stronger sea ice formation (see my general comment).
Figure 7: It’s really hard to see the differences between simulations. Could you plot anomalies of the ice speed without the vectors, perhaps in supplementary?
Line 338: I don’t understand what is meant by “simple ocean boundary”. Do you mean the sea ice-ocean interface? What is simple about it?
Line 358: How appropriate is a comparison to EN4 on the continental shelf (let alone the missing ice shelf cavities)? Does it include enough reliable observations on the shelf?
Figure 9: This figure is uncomfortably similar to Figure 4 of Naughten et al. 2018, down to the placement of the labels and the nonlinear colour bar. Was the same code used? If so, no attribution is given. I am not sure of the journal’s policies on this.
Line 370: The freshening of HSSW in CICE6 is concerning. Hopefully some further tuning of the new sea ice model parameters could alleviate this. Why do you think it occurred? Presumably there’s been a decrease in ice formation and/or a local increase in melting - either way, what could cause this? I don’t understand how this agrees with the other sea ice variables suggesting higher formation (see my above comment on line 310) or deeper mixed layers in the key formation regions (analysed later).
Line 384: The deep waters offshore will basically just be initial conditions so early in the simulation; this should be made more explicit in the note of caution.
Line 398: How is the model surface more saline than EN4 when surface salinity is nudged to observations? Is the nudging really weak, or do the two datasets (WOA and EN4) disagree?
Line 407: A better way to mitigate the freshening problem would be to tune up the CICE6 sea ice formation rates. Salinity restoration should be a last resort, especially on the continental shelves.
Figure 13: Presumably the colour scale is saturated, as observed melt rates in the Amundsen and Bellingshausen sectors are much higher than 4 m/y. The colour scale should indicate this with triangle caps.
Line 464: The wording implies that the biases in the BellAm sector are secondary, but I suspect they are the main driver of the low total mass loss. The cavities are small, so hard to see in Figure 13, but their mass loss is huge. This would be easier to see in the bar chart I suggested.
Line 367: Does the Amundsen Sea have the highest melt increase in percentage terms, or only absolute terms? An extra 2 m/y is not a big change for warm cavities like these, compared to cold cavities with much lower initial melt rates.
Line 471: It looks like there is also a loss of refreezing beneath the Ross and Filchner-Ronne Ice Shelves. This would make sense if fresher HSSW is dampening the magnitude of the ice pump.
Line 473: I disagree that tides and spatial resolution are the main drivers of low simulated melt rates. I strongly suspect the main driver is the cold bias in the Amundsen Sea (Figure A4), and it’s arguable whether or not spatial resolution contributes to this. It’s definitely possible to simulate enough CDW transport onshore in a quarter-degree C-grid model; see for example Mathiot et al. 2017 (doi:10.5194/gmd-10-2849-2017). The Nakayama study about topographic flow used a model equivalent to an Arakawa A-grid, whereas a C-grid as used for ROMS is a lot more forgiving. But even if the topography is adequately resolved, the heat from CDW could be wiped out if there is convection on the Amundsen Sea continental shelf, as sometimes happens with ERA forcing even at much higher resolution (eg Bett et al. 2020, doi:10.1029/2020JC016305). Tides could matter for the Filchner-Ronne Ice Shelf, but this is not a big contributor to the Antarctic total.
Line 523: It’s a bit of a red flag that ChatGPT was used to write some of the code. Was this just for things like figure layout, or did it actually handle the data analysis? If so, was there sufficient human oversight to make sure it didn’t introduce any bugs? I am not sure of the journal’s policies on this matter.
Citation: https://doi.org/10.5194/gmd-2024-213-RC1
Data sets
MetROMS evaluation scripts Cecilia Äijälä and Yafei Nie https://doi.org/10.5281/zenodo.14186139
Model code and software
MetROMS-UHel Cecilia Äijälä and Petteri Uotila https://zenodo.org/records/14185734
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 121 | 32 | 8 | 161 | 2 | 3 |
- HTML: 121
- PDF: 32
- XML: 8
- Total: 161
- BibTeX: 2
- EndNote: 3
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1