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    Review of 'Improved bathymetry leads to 4000 new seamount predictions in the global ocean'

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    Improved bathymetry leads to 4000 new seamount predictions in the global oceanCrossref
    The paper uses published bathymetry grids to search for seamount. These found some sounding errors.
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        Rated 3.5 of 5.
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        Rated 4 of 5.
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        Rated 3 of 5.
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        Rated 3 of 5.
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        Rated 3 of 5.
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    Improved bathymetry leads to 4000 new seamount predictions in the global ocean

     Chris Yesson (corresponding) ,  Tom B. Letessier,  Alex Nimmo-Smith (2020)
    Seamounts are important marine habitats that are hotpots of species diversity. Relatively shallow peaks, increasedproductivity and offshore locations make seamounts vulnerable to human impact and difficult to protect. Present estimates ofseamount numbers vary from barely 10000 to more than 60000), because locating and identifying them remotely can bedifficult. Seamount locations can be estimated by extracting conical shaped features from bathymetry grids. These predictedseamounts are a useful reference for marine researchers and can help direct exploratory surveys. However, these predictionsare dependent on the quality of the surveys underpinning the bathymetry. Historically, quality has been patchy, but isimproving as mapping efforts step up towards the target of complete seabed coverage by 2030.This study presents an update of seamount predictions based on the most recent SRTM30 global bathymetry. This updatewas prompted by a seamount survey in the British Indian Ocean Territory, where locations of two putative seamounts, basedon several previous global seamount predictions, were visited, but no such features were detected during echosoundersurveys. An examination of Admiralty charts for the area showed that the summits of these putative features had soundingsreporting no bottom detected at this depth where this depth was similar to the seabed reported from the bathymetrygrids: we suspect that these features likely resulted from an initial misreading of the charts. We show that perhaps 15phantom seamount features, derived from a misinterpretation of no-bottom sounding data, persist in current globalbathymetry grids and updated seamount predictions. Overall, we predict 37,889 seamounts, an increase of 4,437 from theprevious prediction derived from an older global bathymetry grid. This increase is due to greater detail in newer bathymetrygrids as acoustic mapping of the seabed expands
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      Review information

      10.14293/S2199-1006.1.SOR-GEO.AMRD2Q.v1.RMVCQF

      This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

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      Review text

      We discussed this paper as a group in our weekly lab meeting on March 8, 2021.  Three of us have provided comments below.

      David Sandwell 

      This is an interesting paper that has two main conclusions.  The first is that some data were incorrectly harvested from old Admiralty charts and then used in global grids.  The second is an improved analysis of global seamounts from the SRTM30 V11 global grid which is based on predicted depth and measured depth.  For each of these grids there is a matching source identification (SID) grid that enables one to determine the source of every sounding.

      I have a few comments about versions of SRTM and GEBCO grids.  First the, latest SRTM and GEBCO grids have moved to 15 arcseconds.  The latest SRTM 15 V2.1 grid is described in a recent publication (Tozer, B., Sandwell, D.T., Smith, W.H., Olson, C., Beale, J.R. and Wessel, P., 2019. Global bathymetry and topography at 15 arc sec: SRTM15+. Earth and Space Science, 6(10), pp.1847-1864).  Table 1 of that paper explains that the GEBCO grids are a copy of the SRTM grids with soundings added.  It is interesting that the GEBCO 2014 grid has two false seamounts while the SRTM V11 has only one.  Seamount A is in all versions of SRTM30 V7, 8, 9, 10, and 11.  However Seamount B is not in any of these versions.  The archive of all the old versions is at ftp://topex.ucsd.edu/pub/archive/srtm30 . Look in the topo30 folder for the SID grid in netcdf format.  Therefore, this B data point was somehow added to the GEBCO 2014.  I also see the B-pont it is not in the latest GEBCO 2020 grid which is mostly a copy of SRTM15_V2.0.  

      This incorrect sounding at location A came from the following source.  This is a dataset from the NGA which was harvested from digital nautical charts (DNC).  It has a depth of -140 m.  

      16393 shallow7.cm private DNC https://www1.nga.mil/ProductsServices/NauticalHydrographicBathymetricProduct/Pages/default.aspx YEAR NGA

      Basically I completely agree with this part of the paper and the analysis of the phantom seamounts.  The authors should add the locations of the 14 additional “phantom seamounts” so they can be removed from the next versions of the SRTM and then the GEBCO data sets.

      Regarding the claim of the discovery of 4000 new seamounts, this is probably also correct although I think the better way to locate seamounts is to use the vertical gravity gradient data following the Kim and Wessel 2011 study.   I see that none of the phantom seamounts described in this paper on Figure 4 were identified in the VGG by Kim and Wessel (2011).

      Here are some general comments:  

      1. The data file on the locations and characteristics of the old and new seamounts needs to be available.

      2. There should be a more complete discussion about the overlaps of the various seamount data sets.  Also in areas of rough topography, associated with abyssal hills and fracture zones, how do the authors discriminate between features created by seafloor spreading and off-axis volcanoes.

      3. The quality of Figures 1, 3, and 4 is very poor.  The latitude/longitude labels on Figure 1 should be decimal degrees to match the text.

       

      #20210308: From Katherine -- I mainly read this with an eye for editorial stuff, so I will just list some of the issues I had (I want to underline David’s point #3 above about the figures being quite poor too). Please feel free to rewrite/include whatever though!

      Line 12 - 13: Delete “barely”, change to  “...vary from anywhere between 10000…”; Also, delete extraneous parentheses after “60000”

      Line 13 - 14: If they are going to say “can be difficult” say/explain why (e.g. locating them can be difficult because of x, y, z reasons..)

      Line 18 - 21: The second sentence of this paragraph needs a little help -- it’s very choppy/confusing. Why not instead say, from sentence one of that paragraph: “based on the most recent SRTM30 (is that the most recent?) global bathymetry, which was prompted by a recent (what year?) survey in the …. Two of the seamounts visited did not display any echosounder readings, despite having been previously identified as seamounts in earlier seamount maps/databases.”

      Line 21: I’m not in this field and do not know what Admiralty charts are -- but maybe the audience of this paper does know what they are?

      Line 23: “perhaps 15” features? Did they not just do an analysis to identify these? Maybe clarify, or don’t use the word perhaps (are they sure or not sure about their analysis?)

      Line 26: Specify which “older bathymetry grid” they are comparing to.

      Line 44 - 45: Does this not contradict the sentence in the abstract where they specify a seamount number estimate of 10000 - 60000 ?

      Line 49 - 50: Probably should define those acronyms for completeness sake (GEBCO and SRTM)

      Line 104 - 105: I feel like this sentence should have been stated earlier than now. This is the clearest thing I have read so far that describes what they are doing/trying to do, and I like it.

      Line 108: First time telling the reader what SRTM is, but they don’t mention the acronym (stay consistent if possible)

      Line 141 - 143: They mention that datasets vary, in particular with how they identify any seamounts along ridges, but the authors don’t appear to specify what they do when it comes to ridges and possible seamount features there?

      Line 162: I think they mean “invalid” instead of “in-valid”?

       

      Julie Gevorgian Review: I mostly looked for grammatical errors and the overall flow of the paper. 

      Line 50: Remove “themselves”

      Line 51: Remove the dash between “Satellite- altimetry”

      Line 54: Change to “these are utilized to constrain” - the word “used” is used twice in the same sentence, might be better to avoid repetition. 

      Line 59: remove “so”

      Line 59-60: Might be worth rewording this sentence to make it flow better: “Since sounding data is limited, it is valuable to make use of all available data. Historical soundings based on weighted lines have been extracted from nautical charts to expand the data (Becker et al.,2009).”

      Line 72: change “were” to “was” - important to be consistent with past/present tense 

      Line 115: change to “can and oftentimes do encompass”

      Line 163: change to “phantom seamounts.” - the period always goes inside the quotation


       

      Comments

      We thank the reviewers for their constructive and positive comments.

      We have made minor edits following the recommendations, although we have chosen not to go into the prediction method (point 2), as this is a repeat of previously published methodology.

      We have made all the line-by-line edits suggested and we have uploaded 600dpi versions of the figures.

      2021-03-31 13:33 UTC
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