Evaluating the 11-year solar cycle and short-term <sup>10</sup>Be deposition events with novel excess water samples from the EGRIP project

Paleari, Chiara I.; Mekhaldi, Florian; Erhardt, Tobias; Zheng, Minjie; Christl, Marcus; Adolphi, Florian; Hörhold, Maria; Muscheler, Raimund

doi:https://doi.org/10.5194/cp-2022-94

Preprints

https://doi.org/10.5194/cp-2022-94

Preprints

19 Dec 2022

| 19 Dec 2022

Status: a revised version of this preprint was accepted for the journal CP and is expected to appear here in due course.

Evaluating the 11-year solar cycle and short-term ¹⁰Be deposition events with novel excess water samples from the EGRIP project

Chiara I. Paleari, Florian Mekhaldi, Tobias Erhardt, Minjie Zheng, Marcus Christl, Florian Adolphi, Maria Hörhold, and Raimund Muscheler

Abstract. ¹⁰Be is produced by the interaction between galactic cosmic rays (GCR) and solar energetic particles (SEP) with the Earth’s atmospheric constituents. The flux of GCR is modulated by the varying strength of the magnetic fields of the Earth and the Sun. Measurement of ¹⁰Be concentrations from polar ice cores is thus a valuable tool to reconstruct the variations of the geomagnetic field and solar activity levels. The interpretation of ¹⁰Be records is, however, complicated by non-production related effects on the ¹⁰Be deposition rate caused by climate/weather induced noise. Furthermore, volcanic eruptions have been proposed to lead to short-term ¹⁰Be deposition enhancements. In this study, we test the use of excess meltwater from continuous flow analysis (CFA) to measure ¹⁰Be, allowing less time-consuming and more cost-effective sample preparation. We compare two records obtained from CFA and discrete samples from the EGRIP S6 firn core, reaching back to 1900 CE. We find that the two records agree well and that the ¹⁰Be record from CFA samples agrees as well as the discrete samples with other records from Greenland. Furthermore, by subtracting the theoretically expected GCR-induced signal, we investigate the high-frequency variability of the ¹⁰Be records from Greenland and Antarctica after 1951 CE, with focus on SEP events and volcanic eruptions. Finally, we use the ¹⁰Be records from Greenland and Antarctica to study the 11-year solar cycles, allowing us to assess the suitability of the CFA samples for the reconstruction of solar activity. This result opens new opportunities for the collection of continuous ¹⁰Be records with less time-consuming sample preparation while saving an important portion of the ice cores for other measurements.

Received: 13 Dec 2022 – Discussion started: 19 Dec 2022

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Chiara I. Paleari et al.

Status: closed

RC1:
'Comment on cp-2022-94', Anonymous Referee #1, 16 Jan 2023
General Comments

Paleari et al. present a new way of measuring ¹⁰Be in polar snow/ice by using the excess of meltwater from continuous flow analysis (CFA) instead of discrete snow samples in EGRIP S6 firn core. The authors investigate the agreement with other ¹⁰Be records from Greenland measured in a “traditional” way. They also use this record to study the 11-year solar cycles as well as the short-term SEP events and stratospheric volcanic eruptions. This new way of measuring ¹⁰Be opens new opportunities for the collection of continuous records with less time-consuming sample preparation while saving an important portion of the ice cores for other measurements.

The paper is an introduction study to advertise the opportunities of using ¹⁰Be measured by CFA technic to investigate solar cycles and short-term ¹⁰Be deposition events. The analyses on the ¹⁰Be record are not very deep. On the other hand, the new measurements technic is promising. So, my two main comments, among others, are about the CFA technic that should be more highlighted and the (non-)detection of ¹⁰Be short-term events related to SEP or volcanic eruptions. I recommend major revisions before acceptance for publication in CP.

Specific comments:

The preparation of the CFA samples is described in section 2.1. In addition, I think it would be beneficial to add the schematic figure summarizing this preparation. Moreover, it would be interesting to know how much time is effectively won when using this technic instead of the classical extraction from ice or snow samples, as well as the quantity of ice.

I am not completely convinced that ¹⁰Be from CFA can be used to detect SEP or volcanic eruptions. As the authors said, “one of the main complications of dealing with CFA systems is the possible smoothing of the signal locked in the ice” (see grey and green curves in figure 3). Moreover, is the temporal resolution of the EGRIP S6 core (yearly) enough for such detection? It should be discussed in the manuscript. Finally, the analysis can be misleading in its present form. The authors just state the years when the residual is more than 1-sigma, and it is difficult to know if these years correspond to some events or if they are due to local effects. To improve the way how are presented the analyses, I suggest replacing the histogram figures (figures 6, 7 and 8), which are not really used in the manuscript, by the standard score records shown in Supplementary Material. In these graphs, the authors could add colored dashed vertical lines corresponding to major volcanic eruptions and SEP events. In this way, it would facilitate the analyses and it would be easier for the readers to see if the standard score peaks correspond or not to these events. I would also suggest coloring the curves if the standard score curve is higher to 1-sigma, 2-sigma…, like for climatological indices.

The comparison of EGRIP S6 with other Greenland ice cores is quite convincing (figures 3 and 4), while it is not so much the case for Antarctica. I would rephrase the sentence “our results indicate that the signal measured in the CFA samples is reproducing the common radionuclide signal in Greenland and Antarctica as well as the discrete firn samples” at lines 218-219. Moreover, how the correlation is improved if instead of “global stack – no EGRIP”, a Greenland stack – no EGRIP is used in Figure 5? Do the ¹⁰Be normalized records correspond to ¹⁰Be concentrations records (and not flux) for both Greenland and Antarctica? Please precise.

Minor comments and corrections:

1^st sentence of the abstract: “¹⁰Be is produced by the interaction of galactic cosmic rays (GCR) or solar energetic particles (SEP) with the Earth’s atmospheric constituents.”

Section 2.3: The authors adopted the timescale by Zheng et al., submitted. Because this paper is under review, the readers have no complete information about the timescale of EGRIP.

Table 1: highlight in color the years corresponding to SEP or volcanic events.

11-year cycle: I suggest doing some spectral analyses, too.

Figures in Supplementary Material are not referenced in the main manuscript while they are useful. I suggest replacing the histograms by these figures (see general comment). The histograms can go in supplementary material if the authors want to keep them.
Citation: https://doi.org/10.5194/cp-2022-94-RC1
- AC1: 'Reply on RC1', Chiara Ileana Paleari, 07 Jun 2023
  
  We thank Referee 1 for the useful comments and suggestions. Please find our replies in the attached PDF file.
  Kind regards,
  Paleari et al.
  
  Citation: https://doi.org/10.5194/cp-2022-94-AC1
RC2:
'Comment on cp-2022-94', Anonymous Referee #2, 20 Mar 2023
General comments:
Paleari et al. present a new method, continuous flow analysis (CGA), for the extraction of beryllium-10 from ice that greatly reduces the labour and sample size associated with discrete sampling. Through this study of a Greenland firn core, the authors show that the CFA method is capable of reconstructing galactic cosmic ray (GCR) variation during the 20^th century and 11-year solar cycles that compares well to previous studies using discrete sampling.
As this is an initial study, I would like to see a better estimate of the associated depth errors when compared to discrete sampling to ascertain the inherent bias introduced by the CFA method. Also, filtering the background noise and extracting the 11-year cycle could provide a better way to compare between sites in Greenland and Antarctica. These revisions should be relatively minor.
Specific comments:
The CFA method combines samples to obtain enough ¹⁰Be for measurement. This essentially “smooths” the data when compared to discrete sampling. A rough estimate of the depth attribution is provided in section 2.2, but more statistical approaches are available. I recommend using a Bayesian approach for samples with inherent depth uncertainty to determine the age model under both the discrete (Zheng et al.) and CFA (this study) sampling. They can then be directly compared to constrain the additional depth uncertainty introduced by your CFA method. The freely available software Undatable (Lougheed and Obrochta, 2019) has been developed for radiocarbon dating but can be adjusted for the tie points, i.e., ash layers and annual bands, used here. Other Bayesian approaches are available e.g., Parnell et al., 2008.

Sampling and environmental factors introduce background noise that obscures GCR variability in the Greenland and Antarctic records presented in Fig. 3. This leads to relatively low, albeit statistically significant, correlation between EGRIP and other cores. If the main purpose of ¹⁰Be analysis in ice cores is to reconstruct the 11-year solar cycles, would it not be better to first filter out the background noise to isolate the 11-year cycles and then compare? A simple bandpass or high pass filter, provided by MATLAB, R, python etc., could achieve this. The cycles can then be directly compared using coherency and cross-phase spectral analysis (although this part is not essential). This can also help assess the nature of odd and even cycles.

Minor comments:
Line 109: Please provide more details of your chosen carrier e.g., brand, concentration etc.
Line 110: Are the samples filtered for dust? This could also influence your results due to scavenging and deposition of 10Be. This can be easily done using a syringe and 20-30 µm mesh.
Line 139: It is hard to access the age model as it is not published so it might be good to present the CFA and discrete sampling age models here for comparison. This can be done using Undatable.
Line 171: It would be good to see this relationship visually (scatter plot) and compared to the relationship between the two data sets before interpolation.
Line 173 and 185: There is also less variability in the discrete samples between 4 and 8 m which will therefore provide a better correlation to the smoothed CFA. In other words, there is less variability to smooth.
Line 292: Space between no. and number e.g., no. 05. Please apply throughout the manuscript.
Line 300: relative, not relatively.
Reference:
Lougheed, B.C. and Obrochta, S.P., 2019. A rapid, deterministic age‐depth modelling routine for geological sequences with inherent depth uncertainty. Paleoceanography and Paleoclimatology, 34(1), pp.122-133.
Parnell, A.C., Haslett, J., Allen, J.R., Buck, C.E. and Huntley, B., 2008. A flexible approach to assessing synchroneity of past events using Bayesian reconstructions of sedimentation history. Quaternary Science Reviews, 27(19-20), pp.1872-1885.
Citation: https://doi.org/10.5194/cp-2022-94-RC2
- AC2: 'Reply on RC2', Chiara Ileana Paleari, 07 Jun 2023
  
  We thank Referee 2 for the useful comments and suggestions. Please find our replies in the attached PDF file.
  Kind regards,
  Paleari et al.
  
  Citation: https://doi.org/10.5194/cp-2022-94-AC2
RC3:
'Comment on cp-2022-94', Anonymous Referee #3, 20 Apr 2023

General Comments:
This paper from Paleari et al. details a new beryllium-10 sampling technique and assesses the suitability of the technique for making high-resolution measurements for investigating short term signals from Solar Energetic Proton Events, the 11-year solar cycle and possible 10Be signals linked to volcanic activity. The authors compare results obtained from ice core continuous flow analysis (CFA) and traditional sampling methods, and compare their results with other published records. Using the CFA waste stream makes good and efficient use of limited ice core resources, and their results indicate that the technique works quite well and delivers a reproducible record. The paper is a valuable contribution to the field for this reason.
Overall, I believe their work to be sound, however, there are sections that are lacking in detail, or require a higher level of assumed knowledge to properly understand. In my view the paper may be suitable for publication in CP after clarifications/corrections to address the points raised below.
Major Comments:
The derivation of the depth scale should be explained in more detail. The authors discuss the uncertainty induced by crossover between 1 m ice sections, but they should state clearly how sample depth is attributed and how the depth uncertainty is estimated.
I would like to see a proper explanation of how the S6 timescale was developed and its associated errors. I see there is a submitted paper, but I think it is important for this paper dealing with annual timings of SEPs, volcanics and comparisons with other records that any uncertainty in dating be acknowledged and its implications for interpretations be addressed.
As the S6 discrete analytical method is not currently published, can you give details about the discrete sampling (e.g. sample sizes etc.) so the readers can appreciate the value of this method in time and ice material savings?
How much does site accumulation rate affect the interpretation of the record? What resolution is required for CFA to produce a record capable of detecting SEP events? Does the smoothed nature of CFA signals present a problem in determining rapid events compared to discrete methods?
I see the primary value of the paper is its convincing demonstration of the veracity of a CFA sampled 10Be record. As such the paper is primarily a methods paper and the methods therefore should be presented with some more detail. The current methods sections are extremely brief, some points where more detail would help are noted further below.
Specific Comments:
Line 81: The authors state it was “not possible to analyze in depth and ultimately quantify the uncertainties related to this method”. Could the authors clarify what is meant by this comment?
Line 109: What carrier was used? How was the sample water captured in the centrifuge tubes? E.g. by fraction collector, or manually? What was the length and type of the tubing between the melthead and the centrifuge tube – this is relevant given the potential risks of adsorption of 10Be to surfaces prior to the centrifuge tube. Please clarify with answers in the main text.
Section 2.2: This is difficult to follow. For starters, specify in the text the target resolution you were aiming for. It is not clear from this section if it was 1 sample per core or a much larger number of samples per core. I see the answer comes later around L161, but bring that information also into Sect 2.2 to help the reader.
Line 171: Two sided or one sided t test?
Line 178: Also on STE cite Heikkilä et al., 2013 (doi:10.1002/jgrd.50217) and Pedro et al., 2011 (doi:10.1029/2011JD016530).
Line 180: Hence give more detail on the materials and lengths that were used.
Figure 3: Congratulations, the CFA S6 versus discrete S6 plot is convincing.
Figure 3. The reference for DSS should be Pedro et al., 2012.
Lines 221-223: Das2 written instead of Das 2 as in the rest of the manuscript.
Line 260: For clarity, it may be worth stating the 1951 start date is determined by Mekhaldi et al., not just a time period you chose.
Figure 6. Consider moving this figure to supplementary material.
Line 275: These two paragraphs in particular are difficult to follow. Table 1 already summarises much of this information in a more concise and easier to comprehend way. Rather than list every 1 sigma or greater year, the authors might consider revising Table 1 with colors or bold font to indicate volcanics and GLEs, or create a table specifically to highlight where these intersect with above average 10Be concentrations.
Line 404: formatting of 10Be.
Conclusions: The paper is overly shy in drawing a conclusion on detection of SEPs/GLEs and volcanic events. A clearer statement would be that volcanic and SEP/GLE events are not clearly distinguishable from the level of internal variability in annually-resolved 10Be signals.

Citation: https://doi.org/10.5194/cp-2022-94-RC3
- AC3: 'Reply on RC3', Chiara Ileana Paleari, 07 Jun 2023
  
  We thank Referee 3 for the useful comments and suggestions. Please find our replies in the attached PDF file.
  Kind regards,
  Paleari et al.
  
  Citation: https://doi.org/10.5194/cp-2022-94-AC3

Status: closed

RC1:
'Comment on cp-2022-94', Anonymous Referee #1, 16 Jan 2023
General Comments

Paleari et al. present a new way of measuring ¹⁰Be in polar snow/ice by using the excess of meltwater from continuous flow analysis (CFA) instead of discrete snow samples in EGRIP S6 firn core. The authors investigate the agreement with other ¹⁰Be records from Greenland measured in a “traditional” way. They also use this record to study the 11-year solar cycles as well as the short-term SEP events and stratospheric volcanic eruptions. This new way of measuring ¹⁰Be opens new opportunities for the collection of continuous records with less time-consuming sample preparation while saving an important portion of the ice cores for other measurements.

The paper is an introduction study to advertise the opportunities of using ¹⁰Be measured by CFA technic to investigate solar cycles and short-term ¹⁰Be deposition events. The analyses on the ¹⁰Be record are not very deep. On the other hand, the new measurements technic is promising. So, my two main comments, among others, are about the CFA technic that should be more highlighted and the (non-)detection of ¹⁰Be short-term events related to SEP or volcanic eruptions. I recommend major revisions before acceptance for publication in CP.

Specific comments:

The preparation of the CFA samples is described in section 2.1. In addition, I think it would be beneficial to add the schematic figure summarizing this preparation. Moreover, it would be interesting to know how much time is effectively won when using this technic instead of the classical extraction from ice or snow samples, as well as the quantity of ice.

I am not completely convinced that ¹⁰Be from CFA can be used to detect SEP or volcanic eruptions. As the authors said, “one of the main complications of dealing with CFA systems is the possible smoothing of the signal locked in the ice” (see grey and green curves in figure 3). Moreover, is the temporal resolution of the EGRIP S6 core (yearly) enough for such detection? It should be discussed in the manuscript. Finally, the analysis can be misleading in its present form. The authors just state the years when the residual is more than 1-sigma, and it is difficult to know if these years correspond to some events or if they are due to local effects. To improve the way how are presented the analyses, I suggest replacing the histogram figures (figures 6, 7 and 8), which are not really used in the manuscript, by the standard score records shown in Supplementary Material. In these graphs, the authors could add colored dashed vertical lines corresponding to major volcanic eruptions and SEP events. In this way, it would facilitate the analyses and it would be easier for the readers to see if the standard score peaks correspond or not to these events. I would also suggest coloring the curves if the standard score curve is higher to 1-sigma, 2-sigma…, like for climatological indices.

The comparison of EGRIP S6 with other Greenland ice cores is quite convincing (figures 3 and 4), while it is not so much the case for Antarctica. I would rephrase the sentence “our results indicate that the signal measured in the CFA samples is reproducing the common radionuclide signal in Greenland and Antarctica as well as the discrete firn samples” at lines 218-219. Moreover, how the correlation is improved if instead of “global stack – no EGRIP”, a Greenland stack – no EGRIP is used in Figure 5? Do the ¹⁰Be normalized records correspond to ¹⁰Be concentrations records (and not flux) for both Greenland and Antarctica? Please precise.

Minor comments and corrections:

1^st sentence of the abstract: “¹⁰Be is produced by the interaction of galactic cosmic rays (GCR) or solar energetic particles (SEP) with the Earth’s atmospheric constituents.”

Section 2.3: The authors adopted the timescale by Zheng et al., submitted. Because this paper is under review, the readers have no complete information about the timescale of EGRIP.

Table 1: highlight in color the years corresponding to SEP or volcanic events.

11-year cycle: I suggest doing some spectral analyses, too.

Figures in Supplementary Material are not referenced in the main manuscript while they are useful. I suggest replacing the histograms by these figures (see general comment). The histograms can go in supplementary material if the authors want to keep them.
Citation: https://doi.org/10.5194/cp-2022-94-RC1
- AC1: 'Reply on RC1', Chiara Ileana Paleari, 07 Jun 2023
  
  We thank Referee 1 for the useful comments and suggestions. Please find our replies in the attached PDF file.
  Kind regards,
  Paleari et al.
  
  Citation: https://doi.org/10.5194/cp-2022-94-AC1
RC2:
'Comment on cp-2022-94', Anonymous Referee #2, 20 Mar 2023
General comments:
Paleari et al. present a new method, continuous flow analysis (CGA), for the extraction of beryllium-10 from ice that greatly reduces the labour and sample size associated with discrete sampling. Through this study of a Greenland firn core, the authors show that the CFA method is capable of reconstructing galactic cosmic ray (GCR) variation during the 20^th century and 11-year solar cycles that compares well to previous studies using discrete sampling.
As this is an initial study, I would like to see a better estimate of the associated depth errors when compared to discrete sampling to ascertain the inherent bias introduced by the CFA method. Also, filtering the background noise and extracting the 11-year cycle could provide a better way to compare between sites in Greenland and Antarctica. These revisions should be relatively minor.
Specific comments:
The CFA method combines samples to obtain enough ¹⁰Be for measurement. This essentially “smooths” the data when compared to discrete sampling. A rough estimate of the depth attribution is provided in section 2.2, but more statistical approaches are available. I recommend using a Bayesian approach for samples with inherent depth uncertainty to determine the age model under both the discrete (Zheng et al.) and CFA (this study) sampling. They can then be directly compared to constrain the additional depth uncertainty introduced by your CFA method. The freely available software Undatable (Lougheed and Obrochta, 2019) has been developed for radiocarbon dating but can be adjusted for the tie points, i.e., ash layers and annual bands, used here. Other Bayesian approaches are available e.g., Parnell et al., 2008.

Sampling and environmental factors introduce background noise that obscures GCR variability in the Greenland and Antarctic records presented in Fig. 3. This leads to relatively low, albeit statistically significant, correlation between EGRIP and other cores. If the main purpose of ¹⁰Be analysis in ice cores is to reconstruct the 11-year solar cycles, would it not be better to first filter out the background noise to isolate the 11-year cycles and then compare? A simple bandpass or high pass filter, provided by MATLAB, R, python etc., could achieve this. The cycles can then be directly compared using coherency and cross-phase spectral analysis (although this part is not essential). This can also help assess the nature of odd and even cycles.

Minor comments:
Line 109: Please provide more details of your chosen carrier e.g., brand, concentration etc.
Line 110: Are the samples filtered for dust? This could also influence your results due to scavenging and deposition of 10Be. This can be easily done using a syringe and 20-30 µm mesh.
Line 139: It is hard to access the age model as it is not published so it might be good to present the CFA and discrete sampling age models here for comparison. This can be done using Undatable.
Line 171: It would be good to see this relationship visually (scatter plot) and compared to the relationship between the two data sets before interpolation.
Line 173 and 185: There is also less variability in the discrete samples between 4 and 8 m which will therefore provide a better correlation to the smoothed CFA. In other words, there is less variability to smooth.
Line 292: Space between no. and number e.g., no. 05. Please apply throughout the manuscript.
Line 300: relative, not relatively.
Reference:
Lougheed, B.C. and Obrochta, S.P., 2019. A rapid, deterministic age‐depth modelling routine for geological sequences with inherent depth uncertainty. Paleoceanography and Paleoclimatology, 34(1), pp.122-133.
Parnell, A.C., Haslett, J., Allen, J.R., Buck, C.E. and Huntley, B., 2008. A flexible approach to assessing synchroneity of past events using Bayesian reconstructions of sedimentation history. Quaternary Science Reviews, 27(19-20), pp.1872-1885.
Citation: https://doi.org/10.5194/cp-2022-94-RC2
- AC2: 'Reply on RC2', Chiara Ileana Paleari, 07 Jun 2023
  
  We thank Referee 2 for the useful comments and suggestions. Please find our replies in the attached PDF file.
  Kind regards,
  Paleari et al.
  
  Citation: https://doi.org/10.5194/cp-2022-94-AC2
RC3:
'Comment on cp-2022-94', Anonymous Referee #3, 20 Apr 2023

General Comments:
This paper from Paleari et al. details a new beryllium-10 sampling technique and assesses the suitability of the technique for making high-resolution measurements for investigating short term signals from Solar Energetic Proton Events, the 11-year solar cycle and possible 10Be signals linked to volcanic activity. The authors compare results obtained from ice core continuous flow analysis (CFA) and traditional sampling methods, and compare their results with other published records. Using the CFA waste stream makes good and efficient use of limited ice core resources, and their results indicate that the technique works quite well and delivers a reproducible record. The paper is a valuable contribution to the field for this reason.
Overall, I believe their work to be sound, however, there are sections that are lacking in detail, or require a higher level of assumed knowledge to properly understand. In my view the paper may be suitable for publication in CP after clarifications/corrections to address the points raised below.
Major Comments:
The derivation of the depth scale should be explained in more detail. The authors discuss the uncertainty induced by crossover between 1 m ice sections, but they should state clearly how sample depth is attributed and how the depth uncertainty is estimated.
I would like to see a proper explanation of how the S6 timescale was developed and its associated errors. I see there is a submitted paper, but I think it is important for this paper dealing with annual timings of SEPs, volcanics and comparisons with other records that any uncertainty in dating be acknowledged and its implications for interpretations be addressed.
As the S6 discrete analytical method is not currently published, can you give details about the discrete sampling (e.g. sample sizes etc.) so the readers can appreciate the value of this method in time and ice material savings?
How much does site accumulation rate affect the interpretation of the record? What resolution is required for CFA to produce a record capable of detecting SEP events? Does the smoothed nature of CFA signals present a problem in determining rapid events compared to discrete methods?
I see the primary value of the paper is its convincing demonstration of the veracity of a CFA sampled 10Be record. As such the paper is primarily a methods paper and the methods therefore should be presented with some more detail. The current methods sections are extremely brief, some points where more detail would help are noted further below.
Specific Comments:
Line 81: The authors state it was “not possible to analyze in depth and ultimately quantify the uncertainties related to this method”. Could the authors clarify what is meant by this comment?
Line 109: What carrier was used? How was the sample water captured in the centrifuge tubes? E.g. by fraction collector, or manually? What was the length and type of the tubing between the melthead and the centrifuge tube – this is relevant given the potential risks of adsorption of 10Be to surfaces prior to the centrifuge tube. Please clarify with answers in the main text.
Section 2.2: This is difficult to follow. For starters, specify in the text the target resolution you were aiming for. It is not clear from this section if it was 1 sample per core or a much larger number of samples per core. I see the answer comes later around L161, but bring that information also into Sect 2.2 to help the reader.
Line 171: Two sided or one sided t test?
Line 178: Also on STE cite Heikkilä et al., 2013 (doi:10.1002/jgrd.50217) and Pedro et al., 2011 (doi:10.1029/2011JD016530).
Line 180: Hence give more detail on the materials and lengths that were used.
Figure 3: Congratulations, the CFA S6 versus discrete S6 plot is convincing.
Figure 3. The reference for DSS should be Pedro et al., 2012.
Lines 221-223: Das2 written instead of Das 2 as in the rest of the manuscript.
Line 260: For clarity, it may be worth stating the 1951 start date is determined by Mekhaldi et al., not just a time period you chose.
Figure 6. Consider moving this figure to supplementary material.
Line 275: These two paragraphs in particular are difficult to follow. Table 1 already summarises much of this information in a more concise and easier to comprehend way. Rather than list every 1 sigma or greater year, the authors might consider revising Table 1 with colors or bold font to indicate volcanics and GLEs, or create a table specifically to highlight where these intersect with above average 10Be concentrations.
Line 404: formatting of 10Be.
Conclusions: The paper is overly shy in drawing a conclusion on detection of SEPs/GLEs and volcanic events. A clearer statement would be that volcanic and SEP/GLE events are not clearly distinguishable from the level of internal variability in annually-resolved 10Be signals.

Citation: https://doi.org/10.5194/cp-2022-94-RC3
- AC3: 'Reply on RC3', Chiara Ileana Paleari, 07 Jun 2023
  
  We thank Referee 3 for the useful comments and suggestions. Please find our replies in the attached PDF file.
  Kind regards,
  Paleari et al.
  
  Citation: https://doi.org/10.5194/cp-2022-94-AC3

Chiara I. Paleari et al.

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Short summary

In this study we test the use of excess meltwater from continuous flow analysis from a firn core from Greenland for the measurement of ¹⁰Be for solar activity reconstructions. We show that the quality of results is similar to the measurements on clean firn which opens the possibility to obtain continuous ¹⁰Be records without requiring large amounts of clean ice. Furthermore, we investigate the possibility to identify solar storm signals in ¹⁰Be records from Greenland and Antarctica.


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Evaluating the 11-year solar cycle and short-term 10Be deposition events with novel excess water samples from the EGRIP project

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Evaluating the 11-year solar cycle and short-term ¹⁰Be deposition events with novel excess water samples from the EGRIP project