Thank you, Eric, for your comments. I will take these into account when revising the manuscript. A few remarks to your comments are found below.

Best regards and thank you for your efforts editing the GICC papers,

Sune

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Major comment: Dye 3 ECM. Somehow the number of significant figures in both depth and acidity have been reduced to the point where the data are unuseable (depths given only as metres so that many data have the same depth). Please revise this dataset.

Thanks for spotting this. I have contacted PANGAEA and will sort this out as soon as I get a reply. It is likely a file conversion error.

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Additional comment on data: The file providing the annual layer depths is done for GICC05, but for GICC21 we are simply referred to the supplement to Sinnl et al (2022). This is OK but it leaves the reader who has found the GICC05 layers unaware that for the last 3.8 kyr they have been superceded. I realise this may be hard to do but wouldn’t it be valuable to add a column giving the corresponding depths (even if only for 1 site) for GICC21 until 3.8 ka b2k, so that the reader knows they are better to use?  This is just a question of copying some columns from that supplement and would have the added value of making the GICC21 data available in a more regular database.

GICC21 applies to more cores than GICC05, and I fear that the data file will be very unhandy to use if we merge GICC05 with GICC21 layer positions plus the other supporting material that comes with GICC21. I suggest that we make a clear reference in the metadata of the GICC05 annual layer to the location of the corresponding GICC21 spreadsheet which has both the annual layer positions and a GICC05-GICC21 transfer table. Then all users will know that a newer time scale is available.

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Line 195. … I do wonder why ECM data are supplied as H+ (which the paper admits is uncalibrated) rather than as what was measured, ie current. Possibly this is simply a question of what level of product has been stored but maybe it is worth a comment?

Yes, this is indeed the reason: The data files available to us (and used for GICC05) were the tentatively calibrated H+ records, not the original measurments. I will add a comment.

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Line 268. I appreciate that the abstract to the dataset warns that CPH ammonium and STO lithium may be unreliable, but by the time one has downloaded the tab file as an Excel, that warning is lost. I feel it should be clearly mentioned in the metadata within the file; I also question the value of publishing data you believe to be wrong.

We do not think that the data are wrong, but as described in section 3.4, they may be subject to larger bias than for other species due to the analytical setup. The warning also appears on the PANGAEA data page and will this accompany the data in the downloaded Excel file.

Reply to review comments by "RC3, Anonymous Referee #2".

On behalf of all co-authors, I thank the reviewer for their kind and constructive remarks. 

I provide a few comments and clarifying remarks below. RC3's comments are in italics.

An important output derived from the timescale are snow accumulation rates. For NEEM, these have been published in Rasmussen et al. 2013, but for GRIP and NGRIP Seierstadt et al. 2014 presented them in their paper, but did not provide them in their supplementary. When releasing such a large dataset of impurities measured in ice, many people may want to calculate fluxes etc. Hence, I would ask the authors to also provide the accumulation data from Seierstadt et al. This could also be done by just providing the thinning function for each core.

In Seierstad et al., 2014, we mainly discussed annual layer thicknesses as they come directly out of the time scale transfer. However, we mention accumulation rates in the paper in the context of the construction of the gas time scales for GRIP and GISP2, sections 2.5.1 and 2.5.2. I have contacted the co-authors who did the gas time-scale modelling to see if we can locate the thinning functions obtained back then and/or newer and potentially better estimates. If this is the case, I will make these available at https://www.iceandclimate.nbi.ku.dk/data next to the rest of the data from the Seierstad paper. 

For NGRIP, Kindler et al. (Clim. Past, 10, 887–902, 2014, www.clim-past.net/10/887/2014/) provides an accumulation estimate in the supplement.

In both cases, I think it is beyond the scope of the current manuscript to provide details about thinning function modelling, but I’ll be happy to add a paragraph to section 3.7 with the links to the relevant papers.

L187: I am not sure the name of the laboratory technician is of relevance here? If this is an cknowledgement of her work, and she is fine with being named this is ok, but I suppose many other people could be named throughout the paper too.

You are absolutely right that many people deserve acknowledgement for their work in the laboratories. The reason why we decided to explicitly mention Anita Boas is that we want to acknowledge that she played a particularly important role in the isotope measurements in Copenhagen, measuring several hundred thousand samples over decades with a never-failing eye for getting things right.

L230-232: Nice anecdote, but I guess “yeah, well, that’s just, like, your opinion, man”? Please remove the reference to Dill & Janke.

I abide. 

L258: what do you consider to be “reasonably good”?

The uncertainty of the counting is variable and published together with the GICC05 and GICC21 time scales. The point we are trying to make here is that the resolution of the IC data (3-4 samples per year, although a bit better in the top) would normally be at least marginal for annual layer detection, but that having several parallel series with different seasonality makes it possible. I have removed “with reasonably good accuracy” as this is a vague statement.

Data-table: The linescan (greyscale) data is for NGRIP2, right? If so, please indicate this in the 2nd column of the table (just says “NGRIP”).

Correct, thank you. Fixed.

Many thanks, and again thanks for your time and effort.

Sune O. Rasmussen

I have now talked to Christo Buizert who made the delta-age modelling for Seierstad et al., 2014. For GRIP and GISP2, the accumulation rate results were not thoroughly optimized to give the best estimate of accumulation rates, and we do not think that these can be releases in their current form. 

As mentioned in the review, Kindler et al. (Clim. Past, 10, 887–902, 2014, www.clim-past.net/10/887/2014/) provides an accumulation estimate for NGRIP in their supplement, but note that Gkinis et al. (EPSL, 405, 132–141, https://doi.org/10.1016/j.epsl.2014.08.022) find from diffusion-based estimates that the accumulation is ~10% lower. 

Differences of up to 30% between accumulation estimates derived from different methods were found for NEEM (Clim. Past, 9, 2713–2730, 2013, www.clim-past.net/9/2713/2013/), illustrating that these reconstructions must be considered rather uncertain, and that comparing accumulation reconstructions made in different ways is recommended in order to properly estimate the uncertainty.

I think it is beyond the scope of the current manuscript to make new accumulation reconstructions for GRIP and GISP2. I am aware of ongoing work that will provide consistently estimated accumulation rates for many Greenland ice cores, so hopefully, a solution is not too far away.

I kindly ask the editor to make a recommendation about whether a section referring to existing accumulation reconstructions (mainly for NGRIP and NEEM) should be added as outline in the first reply to the review.