the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 25 Oct 2022
The effects of assimilating a sub-grid scale sea ice thickness distribution in a new Arctic sea ice data assimilation system
Nicholas Williams
Nicholas Byrne
Daniel Feltham
Peter Jan Van Leeuwen
Ross Bannister
David Schroeder
Andrew Ridout
Lars Nerger
Abstract. In the past decade groundbreaking new satellite observations of the Arctic sea ice cover have been made, allowing researchers to understand the state of the Arctic sea ice system in greater detail than before. The derived estimates of sea ice thickness are useful but limited in time and space. In this study the first results of a new sea ice data assimilation system are presented. Observations assimilated (in various combinations) are monthly mean sea ice thickness and monthly mean sea ice thickness distribution from Cryosat-2, and NASA daily Bootstrap sea ice concentration. This system couples the Centre for Polar Observation and Modelling's (CPOM) version of the Los Alamos Sea Ice Model (CICE) to the Localised Ensemble Transform Kalman Filter (LETKF) from the Parallel Data Assimilation Framework (PDAF) library. The impact of assimilating a sub-grid scale sea ice thickness distribution is of particular novelty. The sub-grid scale sea ice thickness distribution is a fundamental component of sea ice models, playing a vital role in the dynamical and thermodynamical processes, yet very little is known of its true state in the Arctic.
This study finds that assimilating Cryosat-2 products for the mean thickness and the sub-grid scale thickness distribution can have significant consequences on the modelled distribution of the ice thickness across the Arctic and particularly in regions of thick multi-year ice. The assimilation of sea ice concentration, mean sea ice thickness and sub-grid scale sea ice thickness distribution together performed best when compared to a subset of Cryosat-2 observations held back for validation. Regional model biases are reduced: the thickness of the thickest ice in the Canadian Archipelago is decreased, but the thickness of the ice in the Central Arctic is increased. When comparing the assimilation of mean thickness with the assimilation of sub-grid scale thickness distribution, it is found that the latter leads to a significant change in the volume of ice in each category. Estimates of the thickest ice improve significantly with the assimilation of sub-grid scale thickness distribution alongside mean thickness.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(6155 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(6155 KB) - BibTeX
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- Final revised paper
Journal article(s) based on this preprint
Nicholas Williams et al.
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2022-982', Anonymous Referee #1, 14 Nov 2022
Cryosphere Review for egusphere-2022-982
The effects of assimilating a sub-grid scale sea ice thickness distribution in a new Arctic sea ice data assimilation system. Williams et al.
Summary
A standalone sea ice model (CICE5.1.2) is used to investigate the impact of incorporating a sub-grid scale sea ice thickness distribution by coupling to the LETKF using the latest version of PDAF. The source of the ice thickness data is from monthly means of CryoSat-2. Multiple experiments are performed consisting of a control run (no assimilation), assimilation of ice concentration only (NASA Bootstrap), assimilation of ice concentration and mean ice thickness, and assimilation of ice concentration, mean ice thickness, and a monthly sea ice thickness distribution. Experiments with 100 ensemble members were performed in which ensemble spread was generated by perturbing the NCEP-2 atmospheric forcing. They find that a forgetting factor of 0.995, amplification factor of 1.5 and localization radius of 100km worked best in these studies. The authors state that this is the first time that a sub-grid scale thickness distribution product has been assimilated. The authors find that the experiment assimilating concentration, mean ice thickness and sub-grid scale thickness distribution performed best in the four thinnest sea ice categories. Comparisons were made against unassimilated CryoSat-2 observations.
I find this to be a well written paper with a thorough description of the techniques and analysis methods used. The graphics and tables are well laid out. I find that this research will be valuable to the community. I recommend publication with minor revisions noted below. General and specific comments are below.
General Comments:
Use CryoSat-2 (not Cryosat-2) throughout the paper.
In the section with lines 55-60; please add these additional references for model forecast systems assimilating sea ice concentration:
Smith GC, Roy F, Rezka M, Surcel Colan D, He Z, Deacu D, Bélanger J-M, Skachko S, Liu Y, Dupont F, Lemieux J-F, Beaudoin C, Tranchant B, Drévillon M, Garric G, Testut C-E, Lellouche J-M, Pellerin P, Ritchie H, Lu Y, Davidson F, Buehner M, Caya A, Lajoie M. 2014. Sea ice forecast verification in the Canadian Global Ice Ocean Prediction System. Q. J. R. Meteorol. Soc., https://doi.org/10.1002/qj.2555
Hebert, D. A., R. A. Allard, E. J. Metzger,P. G. Posey, R. H. Preller, A. J. Wallcraft,M. W. Phelps, and O. M. Smedstad(2015), Short-term sea ice forecasting:An assessment of ice concentrationand ice drift forecasts using the U.S.Navy’s Arctic Cap Nowcast/ForecastSystem, J. Geophys. Res. Oceans, 120,8327–8345, doi:10.1002/2015JC011283.
Papers by Massonnet et al. (2011) and Smith et al. (2022) examined the impact of a 15-category ice thickness distribution on seasonal and climate modeling studies. Please speculate on the potential impact of increasing the number of ice categories (ignoring the additional computational cost) in your study.
Massonnet, F., Fichefet, T., Goosse, H., Vancoppenolle, M., Mathiot, P., & K.nig Beatty, C. (2011). On the influence of model physics on simulations of Arctic and Antarctic sea ice. The Cryosphere, 5(3), 687–699. https://doi.org/10.5194/tc-5-687-2011
Smith, M. M., Holland, M. M., Petty, A. A., Light, B., & Bailey, D. A. (2022). Effects of increasing the category resolution of the sea ice thickness distribution in a coupled climate model on Arctic and Antarctic sea ice mean state. Journal of Geophysical Research: Oceans, 127, e2022JC019044. https://doi.org/10.1029/
In lines 365-370 you state that using a forgetting factor of 0.995 (Fig. 1) does not lead to any model crashing. What is the cause of spikes seen in January – May, and Oct-Dec, evident in all runs except for the control?
In lines 430-432 you state: “for the assimilation runs that the decrease in concentration in late August in the Fram Strait leads to a remarkable increase in the sea ice thickness at the same time in these runs.” I do not see any “remarkable increase”. Please clarify, reword, or delete this sentence.
Lines 537-538: I disagree that all runs with assimilation of sea ice concentration showed very similar results. I agree they are similar to Bootstrap for any given year, but not amongst themselves. Please reword this section or provide additional details to me on what I seem to be missing.
Specific Comments:
Line 26: “rise at roughly twice this” amount.
Line 63: A comparison of fourteen ocean-sea ice reanalyzes (provide reference)
Line 95: Somewhere in this section, please provide the horizontal resolution of the CICE model used in this study.
Line 163: (Gaspari and Cohn, 1999) do not appear in references. Please add.
Line 170: Is a reference missing where I see a “?” ?
Line 238: Reword phrase “Grid cells In CICE-PDAF we use…” awkward
Line 333: “and CS2 thickness observations are assimilated monthly”. Please clarify as there are not CS2 observations available for May – September.
Figure 2: label on top and bottom for “c” and “h” I assume should be “assim_conc_hi_loc100?
Figure 2 caption should be “Columns show CryoSat-2 and 4 CICE-PDAF runs…”
Figure 3: Legend should be “assim_conc_hi_amp2” The “amp2” is missing.
Line 450: I do not see a gold line in the legend.
Figure 6: With the exception of the control run (green), the 3 other experiments are difficult to see except for the assim_conc_hi_4hd. They must be very similar. Can assim_conc_h1_4hd be drawn first? Maybe assim_conc and assim_conc_hi will be easier to see.
Line 468: Table 2 shows value of “0.62”. Which is correct?
Lines 507-508: The assimilation of only concentration does not show an increase versus the control in the first year. Please modify sentence.
Line 511: I do not see a gold line in Fig 10. Please clarify.
Line 795: Hollinger et al. reference not cited.
Line 878: Zhang and Krishnamurti (1999) not cited.
Citation: https://doi.org/10.5194/egusphere-2022-982-RC1 -
AC1: 'Reply on RC1', Nicholas Williams, 25 Jan 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-982/egusphere-2022-982-AC1-supplement.pdf
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AC1: 'Reply on RC1', Nicholas Williams, 25 Jan 2023
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RC2: 'Comment on egusphere-2022-982', Anonymous Referee #2, 15 Nov 2022
The paper describes assimilation of monthly mean sea ice thickness, monthly mean sea ice thickness distribution from Cryosat-2 and sea ice concentration from passive microwave observations in CICE Arctic sea ice model. The best result was achieved when all three data sources are assimilated. For the first time, a sub-grid scale sea ice thickness distribution was assimilated. This led to a significant improvement in estimation of the thickness of the thickest ice category. The paper can be published once the following comments are addressed.
General Comment:
My major concern is that the only data source used for model verification was Cryosat-2 ice thicknesses that were not assimilated. In general, the fact that the modelled ice thickness becomes closer to Cryosat-2 observations indicate that the assimilation of Cryosat-2 ice thicknesses has been performed correctly. However, in order to further assess if the data assimilation brings the model closer to the reality, it is important to do a comparison against additional sea ice thickness observations. I suggest that the authors conduct verification of the model results against the available independent sea ice thickness observations including (1) NASA’s IceBridge, (2) Beaufort Gyre Exploration Project upper-looking sonars (ULS), and (3) Airborne EM observations (“EM-bird”). I think that such additional verification analysis will substantially increase the quality of the paper.
Specific Minor Comments:
I noticed some minor inaccuracies throughout the paper:
Line 16 and throughout the paper. “Canadian Archipelago” à “Canadian Arctic Archipelago”. Abbreviation “CAA” can be also used.
Fig. 1 In Y-axis title please add “)”. X-axis title should be “Month”?
Line 58. Term “Optimal Interpolation” has been already introduced above.
Line 170. Please define “(?)”.
Line 190-191. Words “using”, ”use”, ”using” are part of the same sentence. Please rephrase.
Line 214. Word “key” could be removed.
Line 217. “MYI”, “FYI” were not defined.
Line 218. “radiances” -> “brightness temperatures”.
Line 226. “team” -> “Team”.
Line 279. Please rephrase “Ice thinner than 0.5 is not assimilated…” ->“Ice thicknesses lower than 0.5 are not assimilated…”
Lines 399-401. “because” is used twice in the sentence.
Legend font on Fig. 5 is very small.
Table 3. Add dimension to RMSE.
Figure 8, y-axis title. Add dimension.
Line 513. Should it be Fig. 13 instead of Fig. 12?
Citation: https://doi.org/10.5194/egusphere-2022-982-RC2 -
AC2: 'Reply on RC2', Nicholas Williams, 25 Jan 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-982/egusphere-2022-982-AC2-supplement.pdf
- AC3: 'Reply on RC2', Nicholas Williams, 25 Jan 2023
-
AC2: 'Reply on RC2', Nicholas Williams, 25 Jan 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2022-982', Anonymous Referee #1, 14 Nov 2022
Cryosphere Review for egusphere-2022-982
The effects of assimilating a sub-grid scale sea ice thickness distribution in a new Arctic sea ice data assimilation system. Williams et al.
Summary
A standalone sea ice model (CICE5.1.2) is used to investigate the impact of incorporating a sub-grid scale sea ice thickness distribution by coupling to the LETKF using the latest version of PDAF. The source of the ice thickness data is from monthly means of CryoSat-2. Multiple experiments are performed consisting of a control run (no assimilation), assimilation of ice concentration only (NASA Bootstrap), assimilation of ice concentration and mean ice thickness, and assimilation of ice concentration, mean ice thickness, and a monthly sea ice thickness distribution. Experiments with 100 ensemble members were performed in which ensemble spread was generated by perturbing the NCEP-2 atmospheric forcing. They find that a forgetting factor of 0.995, amplification factor of 1.5 and localization radius of 100km worked best in these studies. The authors state that this is the first time that a sub-grid scale thickness distribution product has been assimilated. The authors find that the experiment assimilating concentration, mean ice thickness and sub-grid scale thickness distribution performed best in the four thinnest sea ice categories. Comparisons were made against unassimilated CryoSat-2 observations.
I find this to be a well written paper with a thorough description of the techniques and analysis methods used. The graphics and tables are well laid out. I find that this research will be valuable to the community. I recommend publication with minor revisions noted below. General and specific comments are below.
General Comments:
Use CryoSat-2 (not Cryosat-2) throughout the paper.
In the section with lines 55-60; please add these additional references for model forecast systems assimilating sea ice concentration:
Smith GC, Roy F, Rezka M, Surcel Colan D, He Z, Deacu D, Bélanger J-M, Skachko S, Liu Y, Dupont F, Lemieux J-F, Beaudoin C, Tranchant B, Drévillon M, Garric G, Testut C-E, Lellouche J-M, Pellerin P, Ritchie H, Lu Y, Davidson F, Buehner M, Caya A, Lajoie M. 2014. Sea ice forecast verification in the Canadian Global Ice Ocean Prediction System. Q. J. R. Meteorol. Soc., https://doi.org/10.1002/qj.2555
Hebert, D. A., R. A. Allard, E. J. Metzger,P. G. Posey, R. H. Preller, A. J. Wallcraft,M. W. Phelps, and O. M. Smedstad(2015), Short-term sea ice forecasting:An assessment of ice concentrationand ice drift forecasts using the U.S.Navy’s Arctic Cap Nowcast/ForecastSystem, J. Geophys. Res. Oceans, 120,8327–8345, doi:10.1002/2015JC011283.
Papers by Massonnet et al. (2011) and Smith et al. (2022) examined the impact of a 15-category ice thickness distribution on seasonal and climate modeling studies. Please speculate on the potential impact of increasing the number of ice categories (ignoring the additional computational cost) in your study.
Massonnet, F., Fichefet, T., Goosse, H., Vancoppenolle, M., Mathiot, P., & K.nig Beatty, C. (2011). On the influence of model physics on simulations of Arctic and Antarctic sea ice. The Cryosphere, 5(3), 687–699. https://doi.org/10.5194/tc-5-687-2011
Smith, M. M., Holland, M. M., Petty, A. A., Light, B., & Bailey, D. A. (2022). Effects of increasing the category resolution of the sea ice thickness distribution in a coupled climate model on Arctic and Antarctic sea ice mean state. Journal of Geophysical Research: Oceans, 127, e2022JC019044. https://doi.org/10.1029/
In lines 365-370 you state that using a forgetting factor of 0.995 (Fig. 1) does not lead to any model crashing. What is the cause of spikes seen in January – May, and Oct-Dec, evident in all runs except for the control?
In lines 430-432 you state: “for the assimilation runs that the decrease in concentration in late August in the Fram Strait leads to a remarkable increase in the sea ice thickness at the same time in these runs.” I do not see any “remarkable increase”. Please clarify, reword, or delete this sentence.
Lines 537-538: I disagree that all runs with assimilation of sea ice concentration showed very similar results. I agree they are similar to Bootstrap for any given year, but not amongst themselves. Please reword this section or provide additional details to me on what I seem to be missing.
Specific Comments:
Line 26: “rise at roughly twice this” amount.
Line 63: A comparison of fourteen ocean-sea ice reanalyzes (provide reference)
Line 95: Somewhere in this section, please provide the horizontal resolution of the CICE model used in this study.
Line 163: (Gaspari and Cohn, 1999) do not appear in references. Please add.
Line 170: Is a reference missing where I see a “?” ?
Line 238: Reword phrase “Grid cells In CICE-PDAF we use…” awkward
Line 333: “and CS2 thickness observations are assimilated monthly”. Please clarify as there are not CS2 observations available for May – September.
Figure 2: label on top and bottom for “c” and “h” I assume should be “assim_conc_hi_loc100?
Figure 2 caption should be “Columns show CryoSat-2 and 4 CICE-PDAF runs…”
Figure 3: Legend should be “assim_conc_hi_amp2” The “amp2” is missing.
Line 450: I do not see a gold line in the legend.
Figure 6: With the exception of the control run (green), the 3 other experiments are difficult to see except for the assim_conc_hi_4hd. They must be very similar. Can assim_conc_h1_4hd be drawn first? Maybe assim_conc and assim_conc_hi will be easier to see.
Line 468: Table 2 shows value of “0.62”. Which is correct?
Lines 507-508: The assimilation of only concentration does not show an increase versus the control in the first year. Please modify sentence.
Line 511: I do not see a gold line in Fig 10. Please clarify.
Line 795: Hollinger et al. reference not cited.
Line 878: Zhang and Krishnamurti (1999) not cited.
Citation: https://doi.org/10.5194/egusphere-2022-982-RC1 -
AC1: 'Reply on RC1', Nicholas Williams, 25 Jan 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-982/egusphere-2022-982-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Nicholas Williams, 25 Jan 2023
-
RC2: 'Comment on egusphere-2022-982', Anonymous Referee #2, 15 Nov 2022
The paper describes assimilation of monthly mean sea ice thickness, monthly mean sea ice thickness distribution from Cryosat-2 and sea ice concentration from passive microwave observations in CICE Arctic sea ice model. The best result was achieved when all three data sources are assimilated. For the first time, a sub-grid scale sea ice thickness distribution was assimilated. This led to a significant improvement in estimation of the thickness of the thickest ice category. The paper can be published once the following comments are addressed.
General Comment:
My major concern is that the only data source used for model verification was Cryosat-2 ice thicknesses that were not assimilated. In general, the fact that the modelled ice thickness becomes closer to Cryosat-2 observations indicate that the assimilation of Cryosat-2 ice thicknesses has been performed correctly. However, in order to further assess if the data assimilation brings the model closer to the reality, it is important to do a comparison against additional sea ice thickness observations. I suggest that the authors conduct verification of the model results against the available independent sea ice thickness observations including (1) NASA’s IceBridge, (2) Beaufort Gyre Exploration Project upper-looking sonars (ULS), and (3) Airborne EM observations (“EM-bird”). I think that such additional verification analysis will substantially increase the quality of the paper.
Specific Minor Comments:
I noticed some minor inaccuracies throughout the paper:
Line 16 and throughout the paper. “Canadian Archipelago” à “Canadian Arctic Archipelago”. Abbreviation “CAA” can be also used.
Fig. 1 In Y-axis title please add “)”. X-axis title should be “Month”?
Line 58. Term “Optimal Interpolation” has been already introduced above.
Line 170. Please define “(?)”.
Line 190-191. Words “using”, ”use”, ”using” are part of the same sentence. Please rephrase.
Line 214. Word “key” could be removed.
Line 217. “MYI”, “FYI” were not defined.
Line 218. “radiances” -> “brightness temperatures”.
Line 226. “team” -> “Team”.
Line 279. Please rephrase “Ice thinner than 0.5 is not assimilated…” ->“Ice thicknesses lower than 0.5 are not assimilated…”
Lines 399-401. “because” is used twice in the sentence.
Legend font on Fig. 5 is very small.
Table 3. Add dimension to RMSE.
Figure 8, y-axis title. Add dimension.
Line 513. Should it be Fig. 13 instead of Fig. 12?
Citation: https://doi.org/10.5194/egusphere-2022-982-RC2 -
AC2: 'Reply on RC2', Nicholas Williams, 25 Jan 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-982/egusphere-2022-982-AC2-supplement.pdf
- AC3: 'Reply on RC2', Nicholas Williams, 25 Jan 2023
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AC2: 'Reply on RC2', Nicholas Williams, 25 Jan 2023
Peer review completion
Journal article(s) based on this preprint
Nicholas Williams et al.
Model code and software
PDAF v2.0 Lars Nerger https://pdaf.awi.de/trac/wiki
CICE v5.1.2 Elizabeth Hunke, David Bailey, Adrian Turner, William Lipscomb, Alice DuVivier, Nicole Jeffery, Daniela Flocco https://github.com/CICE-Consortium/CICE-svn-trunk/tree/cice-5.1.2
Nicholas Williams et al.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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