Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies

Kaminski, T.; Kauker, F.; Eicken, H.; Karcher, M.

doi:https://doi.org/10.5194/tc-9-1721-2015

Articles | Volume 9, issue 4

The Cryosphere, 9, 1721–1733, 2015

https://doi.org/10.5194/tc-9-1721-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

The Cryosphere, 9, 1721–1733, 2015

https://doi.org/10.5194/tc-9-1721-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 9, issue 4

Research article 27 Aug 2015

Research article | 27 Aug 2015

Exploring the utility of quantitative network design in evaluating Arctic sea ice thickness sampling strategies

T. Kaminski et al.

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Final revised paper (published on 27 Aug 2015)
Preprint (discussion started on 19 Mar 2015)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC C511: 'Review of “Exploring the utility of quantitative network design in evaluating Arctic sea-ice thickness sampling strategies” by Kaminski et al. for publication in The Cryosphere', Anonymous Referee #1, 21 Apr 2015
RC C602: 'Review of TC-2015-54', Anonymous Referee #2, 28 Apr 2015
AC C1001: 'Author Comment', Thomas Kaminski, 09 Jun 2015

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Thomas Kaminski on behalf of the Authors (09 Jun 2015) Author's response

ED: Referee Nomination & Report Request started (01 Jul 2015) by Christian Haas

RR by Christian Haas (02 Jul 2015)

Suggestions for revision or reasons for rejection

Dear authors,

Thank you for the revisions of your manuscript and for addressing most points raised by the reviewers. As one reviewer has requested major revisions I have sent the revised manuscript out for review again.
However, to speed up the processes once that review has been received, I would already like to make a few additional suggestions as the Editor of your manuscript and would be glad if you could consider them in your revisions.
This is an interesting paper and very promising approach, and the material is generally well presented.
However, the text is quite compact and I feel that some aspects are still unclear. In particular, you should still better describe what the uncertainty reduction is and how it can be interpreted, despite the new paragraph on page 11, l7-13. Please could you expand this paragraph and better explain what uncertainty reduction really is and how it relates to the terms in equation 1. Maybe you could also include an example, e.g. that uncertainty reduction of xxx % compared to the initial uncertainty of xxx means that parameter xxx is known better by ??? How does this relate to the parameters in table 1?
Your use of the term observations is also confusing. Particularly with regard to page 7, l14-17, page 11, l20, and p12, l5. Please check that these sentences are consistent and maybe include more explanatory text.
Similarly, it is unclear when and why you have used ice concentration and when not, e.g. p9, l14-16, and p11, l17. Why was ice concentration not used? Or was it not used as input variable, but as predicted variable?
The abstract is very general. Can you include some quantitative results? Also I wonder if NASA OIB needs to be mentioned in the abstract. Aren’t the results likewise applicable to other thickness data from the same transects, e.g. from submarine missions?
The long flight lines raise another question. How would the results be different were the flight tracks much shorter and only focused on the study regions and regions slightly further upstream? Can you comment on that? In contrast to one of the reviewers, I do believe that regional studies with less extensive observational data would be feasible too? At least when relative short prediction times are considered. Wouldn’t only ice conditions be relevant in regions and ice fields which could drift into the study region during the prediction period?

Some minor comments:
P3, l24: what is the name of the satellite mission?
P4, l 14: approach THAT operates…
P4, l24: is the southern boundary the Atlantic? Needs to be clarified.
P5, l11: rephrase “precipitation is added to the snow mass”? What happens anyways when air temperatures are at or above freezing, i.e. during the summer?
Spell out PHC (p5), TAF (p8).
P6, l18: why does this guarantee full consistency?
P7, l22: WAS perfect
P10, l12, and figure 2: Why do you describe 9 regions but only use 2 (or 3?) in the paper?
P12, l7: should the 30 cm in the text not be the same as the value in table 1, i.e. 0.5 m for ice and 0.2 m for snow thickness?
P13, l22: Do you mean LOW impact? Why is it remarkable?
P14, l10: do you mean INCREASES ice concentration?
P15, l4: compare to FIGURE 9, or cf Figure 9.
Table 1: precip, given in m/s?
All table and figure captions. Please spell out the acronyms/abbreviations of variables etc. and just include them in parentheses such that the captions are self-explaining and do not require searching the text for explanation.
Fig 1: BS2PB is light blue? How would results be different if flight tracks were shorter?
Figure 12: add annotation with case description to each panel, such that differences between their contents become immediately obvious.

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RR by Anonymous Referee #2 (15 Jul 2015)

Suggestions for revision or reasons for rejection

I have reviewed the manuscript "Exploring the utility of quantitative network design in evaluating Arctic sea-ice thickness sampling strategies" and now find it acceptable for publication with just a few minor (perhaps even trivial) revisions. The authors have adequately addressed all the issues I had with the earlier version of the paper.

General: Inconsistent use of sea ice versus sea-ice. I favour sea ice (which then makes sea ice - ocean more readable), but up to the authors discretion.

P. 4, l. 20: Acronym (GFDL) is introduced, but never used again.

P. 10, l. 2: In replicating these variables in condensed way -> In replicating these variables in a condensed way

P. 14, l 5: I believe some words were inadvertently left out here:
Original manuscript: For both, region 7 and 8, Fig. 9 shows the direction in which a change of tau yields the largest increase in ice thickness.
Latest revision: For both, region 7 and 8, Fig. 8 a change of tau yields the largest increase in ice thickness.

P. 14, l 4: (cmp 9) -- I assume the authors mean (compared with Fig. 9). The abbreviation does not help readability. Also note that the bracket is not closed -- missing ")".

Open questions (for which I don't necessary expect an answer):

Why is B2F only superior for snow thickness, but C2F for ice thickness and area?

Figure 12: I find the increased sensitivity to perfect forcing and perfect model over perfect forcing intriguing given the almost zero sensitivity to perfect model otherwise seen. Does this indicate that the forcing introduces so much random error as to swamp any model error? Only when forcing error is eliminated, does the model error then show some sensitivity.

Figures:

Figs. 3, 6, 9, and 12: There is a lot of white space. Do the authors really wish to have the sensitivity scale from 0-100% in all cases at the expense of being able to differentiate some of the smaller sensitivities?

Figures 4, 7, and 10: The authors have done their best to improve the readability of these figures. However, I fear all but the most eagle-eyed of readers will be dependent on the (scalable) electronic versions of these figures for all but the most trivial of interpretations.

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ED: Publish subject to minor revisions (Editor review) (16 Jul 2015) by Christian Haas

AR by Thomas Kaminski on behalf of the Authors (24 Jul 2015) Author's response Manuscript

ED: Publish as is (09 Aug 2015) by Christian Haas

Short summary

We present a quantitative network design study of the Arctic sea ice-ocean system. For a demonstration, we evaluate two idealised hypothetical flight transects derived from NASA’s Operation IceBridge airborne ice surveys in terms of their potential to improve 10-day to 5-month sea ice forecasts. Our analysis quantifies the benefits of sampling upstream of the target area and of reducing the sampling uncertainty. It further quantifies the complementarity of combining two flight transects.