Seasonal Evolution of the Sea Ice Floe Size Distribution from Two Decades of MODIS Data

Buckley, Ellen Margaret; Cañuelas, Leela; Timmermans, Mary-Louise; Wilhelmus, Monica Martinez

doi:https://doi.org/10.5194/egusphere-2024-89

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https://doi.org/10.5194/egusphere-2024-89

Preprints

19 Jan 2024

| 19 Jan 2024

Seasonal Evolution of the Sea Ice Floe Size Distribution from Two Decades of MODIS Data

Ellen Margaret Buckley, Leela Cañuelas, Mary-Louise Timmermans, and Monica Martinez Wilhelmus

Abstract. The Arctic sea ice cover seasonally evolves from large plates separated by long, linear leads in the winter to a mosaic of smaller sea ice floes in the summer. The interplay between physical and thermodynamic mechanisms during this process ultimately sets the observed sea ice floe size distribution (FSD), an important metric for characterizing the sea ice cover and assessing model performance. Historically, FSDs have been studied at fixed locations over short periods, leaving a gap in our understanding of the spatial and temporal evolution of the FSD at large scales. Here, we present a new framework for image segmentation, allowing the identification and labeling of individual ice floes in Moderate Resolution Imaging Spectroradiometer (MODIS) data. Using this algorithm, we automatically process and segment 4,861 images, identifying more than 9.4 million floes over 23 years. The extracted characteristics of the floes–including area, perimeter, and orientation–evolve throughout the spring and summer in the Beaufort Sea. We find seasonal patterns of decreasing mean floe area, increasing FSD power law slope, and more variability in the floe orientation as the summer progresses.

Received: 10 Jan 2024 – Discussion started: 19 Jan 2024

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Journal article(s) based on this preprint

06 Nov 2024

Seasonal evolution of the sea ice floe size distribution in the Beaufort Sea from 2 decades of MODIS data

Ellen M. Buckley, Leela Cañuelas, Mary-Louise Timmermans, and Monica M. Wilhelmus

The Cryosphere, 18, 5031–5043, https://doi.org/10.5194/tc-18-5031-2024,https://doi.org/10.5194/tc-18-5031-2024, 2024

Short summary

Ellen Margaret Buckley, Leela Cañuelas, Mary-Louise Timmermans, and Monica Martinez Wilhelmus

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-89', Anonymous Referee #1, 13 Mar 2024

The authors processed 4861 MODIS images of sea ice in the Beaufort Sea spanning the months of March through September in the years 2000 through 2022, identifying more than 9 million ice floes. They then constructed and analyzed the sea-ice floe size distribution (FSD). They found that the FSD follows a power law with an exponent that varies seasonally. They also calculated the mean floe size and the orientation of floes.
Previous studies of the FSD have typically been based on the analysis of a handful of images, or at most a few hundred. The amount of imagery analyzed in this work exceeds all previous studies by a factor of 15 or more, and for that reason alone it is worthy of publication. But regarding the seasonal evolution of the FSD, the authors did not make a careful comparison of their results with previous studies, and there are some mathematical issues to resolve.
Specific Comments
Lines 89-90. "The dynamic threshold value is the weighted mean for the 400-pixel (100 km) neighborhood of a pixel subtracted by a constant." A few questions:

1. A neighborhood is an area. Is the neighborhood 400 x 400 pixels (100 x 100 km), or is it 20 x 20 pixels (400 total, 10 x 10 km)?

2. Is the neighborhood a square or some other shape?

3. What does "subtracted by a constant" mean? What constant?
Lines 161-167. I do not understand the bootstrapping procedure. Samples of (what?) are drawn from (what?).
Lines 178-182. These sentences discuss the mean and median floe areas as shown in Figure 5(a). It should be noted that for a power-law distribution, the mean and the median are directly proportional to the minimum floe area, Amin, which is 5 km^2 in the present work. The power-law pdf with exponent -alpha is:

f(A) = ((alpha-1)/Amin) * (A/Amin)^(-alpha)

The integral of f(A) from Amin to infinity is 1.

The mean floe area is:

Amean = Amin * (alpha-1)/(alpha-2)

The median floe area is:

Amed = Amin * (2^(1/(alpha-1)))

The point is this: The mean and median floe areas are completely dependent upon the resolution of the measuring device. If the resolution of the sensor were to allow the detection of floes 10 times smaller, the mean and median floe areas would be 10 times smaller (provided the data continued to follow the same power law). The mean and median floe areas reported here do not reflect any kind of objective reality but rather the limitations of the sensor. They cannot be meaningfully compared to the mean and median floe areas detected by sensors with different resolutions. It's fine to calculate and plot the mean and median floe areas, and to note their variation over time, but their direct proportionality to the resolution (Amin) of the detection mechanism should be noted, if in fact the floe areas are power-law distributed.
The previous comment raises a further difficulty. For a power-law distribution with exponent -alpha, the mean does not exist when alpha LE 2. In other words, the integral of A*f(A)dA from Amin to infinity is infinite when alpha LE 2. Now look at Figure 5(b). It shows that alpha is LE 2 quite often, and yet Figure 5(a) shows a finite mean floe area. It is not mathematically possible for a power-law distribution with the reported values of alpha to have a finite mean floe area. Fortunately, this is easily fixed by postulating that a maximum floe area (Amax) exists such that the distribution of floe areas follows a power law only for the finite range Amin LE A LE Amax. If this approach is taken, the authors should estimate Amax. If this approach is not taken, the authors should explain how to reconcile the mathematical contradiction.
Line 188. "The power law alpha is inversely correlated to the mean floe area". This finding is based on the data. It could also be checked analytically for a power-law distribution. As noted above, if alpha GT 2 then Amean = Amin * (alpha-1)/(alpha-2). As alpha becomes larger, Amean does indeed become smaller, although not linearly. But most of the values of alpha in this paper are LE 2. If the power law is defined on the finite interval [Amin,Amax] then Amean is a more complicated function of Amin, Amax, and alpha, but Amean still decreases as alpha increases, although not linearly. Whether the authors wish to include such an analytical comparison to the data is up to them, I am only pointing out the possibility to do so.
Lines 210-218. This paragraph compares the power-law exponents of the present study to those found by Stern et al (2018a), but the comparison is not done correctly. The present study uses floe area as the measure of floe size, while Stern et al (2018a) used floe diameter. Assuming that floe area (A) is proportional to the square of floe diameter (x^2), a power-law distribution in A with exponent -alpha is equivalent to a power-law distribution in x with exponent -2*alpha+1. With this conversion, the authors should make a quantitative month-by-month comparison of their results with those of Perovich and Jones (2014), Hwang et al (2017), and Stern et al (2018a), all of which looked at the seasonal evolution of the FSD in the Beaufort Sea.
Regarding floe orientation (section 4.3), a couple of comments:

(1) It's possible that nearly circular floes could have a more variable orientation than elongated floes, because small changes in their perimeter could trigger large changes in their orientation. Therefore, as floe orientation becomes more variable (as in Figure 5(c) in June), how do we know whether it's due to floes becoming more randomly oriented or floes becoming more circular?

(2) Lines 227-231 discusses the orientation of large rectilinear floes, concluding that their orientation is less variable in the early season compared to the full data set, but increasingly variable into the summer. It's not clear what the point of this comparison is. The reader is left hanging, with no figures or numbers or explanation of the significance of the result.
Minor Comments
First line of the Introduction. Consider changing "from the atmosphere to the ocean" to "between the atmosphere and the ocean" because the fluxes go both ways -- atm to ocean and ocean to atm.
Lines 52-53. "The older and thicker multiyear ice is now melting out" -- but the loss of older and thicker multiyear ice has been going on for a long time. It was first noted in 2007:

Maslanik, J. A., C. Fowler, J. Stroeve, S. Drobot, J. Zwally, D. Yi, and W. Emery (2007), A younger, thinner Arctic ice cover: Increased potential for rapid, extensive sea-ice loss, Geophys. Res. Lett., 34, L24501, doi:10.1029/2007GL032043.
Lines 95-102. This same segmentation procedure was also used by Stern et al (2018a) -- see their section 3.2.
Lines 95-96. "where where"
Lines 110-111. "from from" should be "range from"
Line 119. "This quality assurance steps" -- singular or plural?
Line 130. "The standard error of the fitted distribution" -- is this supposed to say the standard error of alpha?
Line 150. "a correlation of 0.99" -- is this supposed to be a squared correlation? Figure 4 says "R^2 = 0.99"
Line 166. "The the"
Line 167. "values increases" -- singular or plural?
Figure 3 caption:

Line 3. "imaeg"

Line 4. Either write "captured" or delete the word "capture"
Figure 5(b). The caption refers to "the slope anomaly" but the figure shows the actual slope, not the anomaly.
Figure 5(c). The caption refers to "low circularity floes" in green but I don't see a green curve.
Figure 5(d). The caption refers to "land (magenta)" but I don't see any magenta color.
Figure 5(d). Is it really necessary to show all that gray area (clouds)? That makes it harder to see the green and blue areas, which are really the quantities of interest.
Lines 203-204. "the standard deviation calculated as in Equation 3." Is this supposed to say "standard error" or "standard deviation"? Does Equation 3 give the standard error or the standard deviation? See line 130.
Line 204. "Fig. 5b, shaded" -- I don't see any shaded part of Figure 5b.
Line 211. 59400 should be 594
Line 225. "that are can be"
Line 239. "increasing power law slopes" -- does this mean steeper or shallower? When alpha increases, the slope decreases (becomes more negative). When alpha decreases, the slope increases (becomes less negative). That's why it might be clearer to say steeper or shallower.
Lines 241-242. This is the first mention of "discrete element models" in the paper. I would suggest that on line 37 the words "discrete element" be added just before the word "models".
Line 245. "new segmentation algorithm presented here" -- the segmentation algorithm is not new. See the comment above for lines 95-102.
There are other minor typos not noted here.

Citation: https://doi.org/10.5194/egusphere-2024-89-RC1
- AC1: 'Reply on RC1', Ellen Buckley, 08 May 2024
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-89/egusphere-2024-89-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2024-89-AC1
RC2:
'Comment on egusphere-2024-89', Anonymous Referee #2, 26 Mar 2024

The comment was upload in the form of the supplement.

Citation: https://doi.org/10.5194/egusphere-2024-89-RC2
- AC2: 'Reply on RC2', Ellen Buckley, 13 May 2024
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-89/egusphere-2024-89-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2024-89-AC2

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2024-89', Anonymous Referee #1, 13 Mar 2024

The authors processed 4861 MODIS images of sea ice in the Beaufort Sea spanning the months of March through September in the years 2000 through 2022, identifying more than 9 million ice floes. They then constructed and analyzed the sea-ice floe size distribution (FSD). They found that the FSD follows a power law with an exponent that varies seasonally. They also calculated the mean floe size and the orientation of floes.
Previous studies of the FSD have typically been based on the analysis of a handful of images, or at most a few hundred. The amount of imagery analyzed in this work exceeds all previous studies by a factor of 15 or more, and for that reason alone it is worthy of publication. But regarding the seasonal evolution of the FSD, the authors did not make a careful comparison of their results with previous studies, and there are some mathematical issues to resolve.
Specific Comments
Lines 89-90. "The dynamic threshold value is the weighted mean for the 400-pixel (100 km) neighborhood of a pixel subtracted by a constant." A few questions:

1. A neighborhood is an area. Is the neighborhood 400 x 400 pixels (100 x 100 km), or is it 20 x 20 pixels (400 total, 10 x 10 km)?

2. Is the neighborhood a square or some other shape?

3. What does "subtracted by a constant" mean? What constant?
Lines 161-167. I do not understand the bootstrapping procedure. Samples of (what?) are drawn from (what?).
Lines 178-182. These sentences discuss the mean and median floe areas as shown in Figure 5(a). It should be noted that for a power-law distribution, the mean and the median are directly proportional to the minimum floe area, Amin, which is 5 km^2 in the present work. The power-law pdf with exponent -alpha is:

f(A) = ((alpha-1)/Amin) * (A/Amin)^(-alpha)

The integral of f(A) from Amin to infinity is 1.

The mean floe area is:

Amean = Amin * (alpha-1)/(alpha-2)

The median floe area is:

Amed = Amin * (2^(1/(alpha-1)))

The point is this: The mean and median floe areas are completely dependent upon the resolution of the measuring device. If the resolution of the sensor were to allow the detection of floes 10 times smaller, the mean and median floe areas would be 10 times smaller (provided the data continued to follow the same power law). The mean and median floe areas reported here do not reflect any kind of objective reality but rather the limitations of the sensor. They cannot be meaningfully compared to the mean and median floe areas detected by sensors with different resolutions. It's fine to calculate and plot the mean and median floe areas, and to note their variation over time, but their direct proportionality to the resolution (Amin) of the detection mechanism should be noted, if in fact the floe areas are power-law distributed.
The previous comment raises a further difficulty. For a power-law distribution with exponent -alpha, the mean does not exist when alpha LE 2. In other words, the integral of A*f(A)dA from Amin to infinity is infinite when alpha LE 2. Now look at Figure 5(b). It shows that alpha is LE 2 quite often, and yet Figure 5(a) shows a finite mean floe area. It is not mathematically possible for a power-law distribution with the reported values of alpha to have a finite mean floe area. Fortunately, this is easily fixed by postulating that a maximum floe area (Amax) exists such that the distribution of floe areas follows a power law only for the finite range Amin LE A LE Amax. If this approach is taken, the authors should estimate Amax. If this approach is not taken, the authors should explain how to reconcile the mathematical contradiction.
Line 188. "The power law alpha is inversely correlated to the mean floe area". This finding is based on the data. It could also be checked analytically for a power-law distribution. As noted above, if alpha GT 2 then Amean = Amin * (alpha-1)/(alpha-2). As alpha becomes larger, Amean does indeed become smaller, although not linearly. But most of the values of alpha in this paper are LE 2. If the power law is defined on the finite interval [Amin,Amax] then Amean is a more complicated function of Amin, Amax, and alpha, but Amean still decreases as alpha increases, although not linearly. Whether the authors wish to include such an analytical comparison to the data is up to them, I am only pointing out the possibility to do so.
Lines 210-218. This paragraph compares the power-law exponents of the present study to those found by Stern et al (2018a), but the comparison is not done correctly. The present study uses floe area as the measure of floe size, while Stern et al (2018a) used floe diameter. Assuming that floe area (A) is proportional to the square of floe diameter (x^2), a power-law distribution in A with exponent -alpha is equivalent to a power-law distribution in x with exponent -2*alpha+1. With this conversion, the authors should make a quantitative month-by-month comparison of their results with those of Perovich and Jones (2014), Hwang et al (2017), and Stern et al (2018a), all of which looked at the seasonal evolution of the FSD in the Beaufort Sea.
Regarding floe orientation (section 4.3), a couple of comments:

(1) It's possible that nearly circular floes could have a more variable orientation than elongated floes, because small changes in their perimeter could trigger large changes in their orientation. Therefore, as floe orientation becomes more variable (as in Figure 5(c) in June), how do we know whether it's due to floes becoming more randomly oriented or floes becoming more circular?

(2) Lines 227-231 discusses the orientation of large rectilinear floes, concluding that their orientation is less variable in the early season compared to the full data set, but increasingly variable into the summer. It's not clear what the point of this comparison is. The reader is left hanging, with no figures or numbers or explanation of the significance of the result.
Minor Comments
First line of the Introduction. Consider changing "from the atmosphere to the ocean" to "between the atmosphere and the ocean" because the fluxes go both ways -- atm to ocean and ocean to atm.
Lines 52-53. "The older and thicker multiyear ice is now melting out" -- but the loss of older and thicker multiyear ice has been going on for a long time. It was first noted in 2007:

Maslanik, J. A., C. Fowler, J. Stroeve, S. Drobot, J. Zwally, D. Yi, and W. Emery (2007), A younger, thinner Arctic ice cover: Increased potential for rapid, extensive sea-ice loss, Geophys. Res. Lett., 34, L24501, doi:10.1029/2007GL032043.
Lines 95-102. This same segmentation procedure was also used by Stern et al (2018a) -- see their section 3.2.
Lines 95-96. "where where"
Lines 110-111. "from from" should be "range from"
Line 119. "This quality assurance steps" -- singular or plural?
Line 130. "The standard error of the fitted distribution" -- is this supposed to say the standard error of alpha?
Line 150. "a correlation of 0.99" -- is this supposed to be a squared correlation? Figure 4 says "R^2 = 0.99"
Line 166. "The the"
Line 167. "values increases" -- singular or plural?
Figure 3 caption:

Line 3. "imaeg"

Line 4. Either write "captured" or delete the word "capture"
Figure 5(b). The caption refers to "the slope anomaly" but the figure shows the actual slope, not the anomaly.
Figure 5(c). The caption refers to "low circularity floes" in green but I don't see a green curve.
Figure 5(d). The caption refers to "land (magenta)" but I don't see any magenta color.
Figure 5(d). Is it really necessary to show all that gray area (clouds)? That makes it harder to see the green and blue areas, which are really the quantities of interest.
Lines 203-204. "the standard deviation calculated as in Equation 3." Is this supposed to say "standard error" or "standard deviation"? Does Equation 3 give the standard error or the standard deviation? See line 130.
Line 204. "Fig. 5b, shaded" -- I don't see any shaded part of Figure 5b.
Line 211. 59400 should be 594
Line 225. "that are can be"
Line 239. "increasing power law slopes" -- does this mean steeper or shallower? When alpha increases, the slope decreases (becomes more negative). When alpha decreases, the slope increases (becomes less negative). That's why it might be clearer to say steeper or shallower.
Lines 241-242. This is the first mention of "discrete element models" in the paper. I would suggest that on line 37 the words "discrete element" be added just before the word "models".
Line 245. "new segmentation algorithm presented here" -- the segmentation algorithm is not new. See the comment above for lines 95-102.
There are other minor typos not noted here.

Citation: https://doi.org/10.5194/egusphere-2024-89-RC1
- AC1: 'Reply on RC1', Ellen Buckley, 08 May 2024
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-89/egusphere-2024-89-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2024-89-AC1
RC2:
'Comment on egusphere-2024-89', Anonymous Referee #2, 26 Mar 2024

The comment was upload in the form of the supplement.

Citation: https://doi.org/10.5194/egusphere-2024-89-RC2
- AC2: 'Reply on RC2', Ellen Buckley, 13 May 2024
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-89/egusphere-2024-89-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2024-89-AC2

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

ED: Reconsider after major revisions (further review by editor and referees) (22 May 2024) by Lars Kaleschke

AR by Ellen Buckley on behalf of the Authors (30 May 2024) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (04 Jun 2024) by Lars Kaleschke

RR by Anonymous Referee #1 (09 Jun 2024)

Suggestions for revision or reasons for rejection

This is from Reviewer #1. The authors have addressed all of my comments. I have a few further comments about the revised manuscript.

Line 87. "on average 58% of an image is covered in opaque clouds..." -- The first draft of this paper said 71%. Why did it change to 58%?

Line 142. The floe areas considered in this work range from 5 km^2 to 300 km^2. That's only a factor of 60, and the range of floe diameters is only sqrt(60) < 8. This is a VERY narrow range of values for fitting a power law -- less than one order of magnitude -- and is necessarily accompanied by a high degree of uncertainty as to whether a power law is indeed the best-fitting function. The authors should acknowledge that the range of floe sizes is very narrow for fitting a power law.

Equation 3 and following -- is alpha required to be greater than 1? It seems that equation 3 only requires alpha not equal to 1, but equation 4 does apparently require alpha greater than 1, otherwise the uncertainty would be negative.

Line 173. "The difference in alpha values ranges from 0.03 to 0.21" -- When I look at Figure 3(c,f,i) I see differences of 0.06 (3c), 0.25 (3f), and 0.17 (3i). Where does "0.03 to 0.21" come from?

Line 191. "bootstrap with replacement" should be "sampling with replacement"

Lines 183-194. About the bootstrapping procedure, my understanding is as follows. Start with a randomly selected image that contains N floes. From that collection of floes, select N floes WITH replacement. If the sampling had been WITHOUT replacement, then there would be no difference between the original set of floes and the bootstrapped set. The only randomization in this bootstrapping procedure is the "with replacement" sampling scheme. That hardly seems like a proper bootstrap to me. Furthermore, if the intention is to assess the uncertainty in the exponent alpha, that should come from the fitting procedure itself (most packages include an uncertainty estimate for the estimated parameters) or from a goodness-of-fit test. Why is bootstrapping even needed?

Lines 231-232. "The mean and median OF THE FITTED POWER LAW can be expressed analytically."

Line 239. "Fig 6b" should be "Fig 6c"

Line 254. "50 m to 5 km^2" -- Is this supposed to say 50 m^2? Are the units supposed to be diameter or area?

Line 268. "Fig 6c, shaded" -- I don't see shading in Fig 6c.

Appendix A. In A1, does alpha have to be greater than 1?
In A2, I think it would be useful to plug in the expression for c from A1 and write E as
((1-a)/(2-a))*((xmax^(2-a)-xmin^(2-a))/(xmax^(1-a)-xmin^(1-a)))
where a=alpha. Note than alpha cannot equal 1 or 2. Those are special cases.
In A3, I think it would be useful to plug in the expression for c from A1 and write x0 as
((1/2)*(xmax^(1-a)+xmin^(1-a)))^(1/(1-a))
Again alpha=1 is a special case.

Hide

RR by Anonymous Referee #2 (01 Jul 2024)

ED: Reconsider after major revisions (further review by editor and referees) (09 Jul 2024) by Lars Kaleschke

Dear author,

The manuscript was revised once after the first review and the reviewers looked at it again. Some questions remain unanswered and new ones have been added. I myself still have some questions (see below). Reviewer 1 describes the level of revision required as minor, and reviewer 2 as major. I personally tend towards the middle. I therefore ask for a reply to all questions and a new revision.

Best regards,

Lars Kaleschke

My questions and comments:

Reviewer 1 emphasized the very narrow range of values for fitting a power law. I share these concerns and point to other methods to determine the fit, which represents further uncertainty (Muchow et al., 2021).

Muchow, M., Schmitt, A. U., and Kaleschke, L.: A lead-width distribution for Antarctic sea ice: a case study for the Weddell Sea with high-resolution Sentinel-2 images, The Cryosphere, 15, 4527–4537, https://doi.org/10.5194/tc-15-4527-2021, 2021.

I find the description of the illustration of the segmentation results not sufficient. Especially the fact that large ice floes are sometimes not separated by the segmentation and form larger objects of the same color. What does this mean for the resulting FSD?

Where does the number of 9.4 million floes come from? Are any of them counted multiple times?

How is the ice floe tracker IFT used in this study? It was mentioned in the introduction and I expected that it is used for some purpose, e.g. to avoid double counting. Please clarify.

What information is stored in the “floe library”? Please describe this library in more detail. Is this a data set? See https://www.the-cryosphere.net/policies/data_policy.html

Section 3.5: 97% of the floes fall in this size range. Where does this number come from? Does this percentage mean by area coverage? Or by the number of floes? Is this the same for MODIS and S2?

Section 5: the imagery largest record of Earth to date. Really? What about Landsat? Maybe a question of definition?

Most references are incomplete, the DOIs are missing. This would result in a long list of complaints for copy editing.

Figure 3cfi: Better plot data points (with error bars) instead connected lines

You can upload your code+data already now on Zenodo with restricted access.

Hide

AR by Ellen Buckley on behalf of the Authors (20 Aug 2024) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (22 Aug 2024) by Lars Kaleschke

RR by Anonymous Referee #1 (03 Sep 2024)

ED: Publish subject to technical corrections (05 Sep 2024) by Lars Kaleschke

AR by Ellen Buckley on behalf of the Authors (06 Sep 2024) Manuscript

Journal article(s) based on this preprint

06 Nov 2024

Seasonal evolution of the sea ice floe size distribution in the Beaufort Sea from 2 decades of MODIS data

Ellen M. Buckley, Leela Cañuelas, Mary-Louise Timmermans, and Monica M. Wilhelmus

The Cryosphere, 18, 5031–5043, https://doi.org/10.5194/tc-18-5031-2024,https://doi.org/10.5194/tc-18-5031-2024, 2024

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Ellen Margaret Buckley, Leela Cañuelas, Mary-Louise Timmermans, and Monica Martinez Wilhelmus

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The Arctic sea ice cover seasonally evolves from large plates separated by long, linear leads in the winter to a mosaic of smaller sea ice floes in the summer. Here, we present a new image segmentation algorithm applied to thousands of images and identifying over 9 million individual pieces of ice. We observe the characteristics of the floes and how they evolve throughout the summer as the ice breaks up.


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