the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Jul 2025
Climate-related signals in the GV7-C ice core from East Antarctica for 1782–2013 CE: Potential relevance to climate and teleconnections between tropics and Antarctica
Abstract. This study investigates climate-related signals preserved in the GV7-C ice core from East Antarctica (1782–2013 CE), analyzing stable water isotopes (δ¹⁸O and d-excess) and snow accumulation (SA). Annual data were compared with climate indices representing the El Niño–Southern Oscillation (Niño3.4, SOI), Southern Annular Mode (SAM), Indian Ocean Dipole (IOD), and sea surface temperature (SST) anomalies in the southeastern Indian Ocean (SST-SEIO). During 1957–2013 CE, δ¹⁸O correlated intermittently with Pacific Ocean sector indices, while d-excess consistently correlated with SAM, IOD, and SST-SEIO, indicating stable moisture sources from the Indian Ocean. Over the longer period (1872–2013 CE), δ¹⁸O correlations weakened, suggesting shifting climatic influences, whereas d-excess retained correlations, emphasizing its reliability for tracking moisture-source variability. Snow accumulation showed weak and inconsistent correlations with climatic variables, suggesting multiple influencing factors. Spatial correlation analyses revealed that δ¹⁸O and d-excess signals primarily reflect conditions in the Pacific and Indian Ocean sectors, respectively. These findings highlight dynamic teleconnections between Antarctic climate and tropical ocean conditions, underscoring the complexity of interpreting Antarctic ice core records in climate variability studies and emphasizing the importance of considering varying temporal resolutions and climatic contexts.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-2408', Anonymous Referee #1, 05 Dec 2025
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RC2: 'Comment on egusphere-2025-2408', Anonymous Referee #2, 23 Jan 2026
Publisher’s note: this comment was edited on 26 January 2026. The following text is not identical to the original comment, but the adjustments were minor without effect on the scientific meaning.
Dear editor,
The manuscript by Nyamgerel et al. presents a thoughtful investigation of the d18O, dexcess and snow accumulation records preserved in GV7-C ice core layers. Using correlation analyses, they assess how the variability of the GV7-C records may be influenced by climate indices and parameters (e.g. ENSO, SAM, IOD, SST). This manuscript is interesting and relevant and should be considered for publication in Earth System Dynamics. However, some key points need to be reassessed before acceptance for publication in Earth System Dynamics.
Major comments:
- My main concern is the data treatment prior to applying Pearson’s linear correlation. Figure 2 illustrates the annual values for δ¹⁸O, δD, and d-excess. Among the mean annual values shown in the figure, some values appear to significantly exceed the mean plus or minus two standard deviations. Despite these notably higher or lower values, the manuscript does not mention an outlier assessment. Additionally, the manuscript fails to address the assessment of data distribution and the potential need for linearization of the records. Furthermore, there is no discussion on whether detrending of datasets is necessary before applying the Pearson’s linear correlation. All these steps are crucial, as they could substantially influence the results obtained from Pearson's linear correlation. This is particularly relevant since the main findings of the manuscript depend on the results derived from this correlation. Incorporating these steps into the data treatment would enhance the manuscript.
- The results section presents correlation analyses between annual GV7-C records and annual/seasonal climate variables. Section 2.1 states that snow accumulation at the GV7-C site is higher during austral summer and autumn. This increased snow accumulation during these seasons will inevitably bias the GV7-C annual records (δ¹⁸O and SA) and will consequently affect the results derived from correlating GV7-C annual records with ERA5 annual/seasonal climate variables. Failing to account for this seasonal bias in GV7-C records could lead to misleading interpretations of the relationship between these records and climate variables. Therefore, incorporating a seasonal bias assessment for GV7-C records and discussing this bias will improve the manuscript.
- Section 2.2 indicates that “Annual layers were determined based on the seasonal summer maximum δ¹⁸O peaks in the GV7-C ice core.” While there is an explanation of how annual layers were identified, the manuscript lacks information on how the annual averages, which are used to generate most of the results, were calculated. Calculating annual averages from values between summer peaks will capture annual minima during austral winter but may disrupt the continuous representation of annual maxima during austral summer. This is particularly important because annual averages will reflect “better” the "continuous" season and introduce uncertainties regarding the representation of the "discontinuous" season. This approach can lead to some seasons being more prominently represented within the annual average, potentially skewing the correlations. Please provide additional information on how the annual averages were calculated and address the potential effects of divided seasons in both the results analysis and discussion.
- Section 3.2.1 lacks clarity in presenting the data. For instance, lines 188-190 do not explicitly state whether the authors are discussing the 10-m v wind or the 850 hPa v-wind. There also seems to be an inconsistency in reporting the positive or negative correlations between the Pacific Ocean (PO) and Indian Ocean (IO). Similarly, lines 193-194 mention positive correlations between annual d-excess and 2 m/850 hPa temperatures over the western PO and IO sectors. Figure S4 shows positive correlations between annual d-excess and 850 hPa temperatures over the IO sector, but there is no evidence supporting a positive correlation over the western PO sector. It would be very beneficial to include further information about the coverage of the PO and IO sectors, either in Figure 1 or within the text. Section 3.2.1 is complex and difficult to read, and the supporting plots do not provide complete information. For example, Figure S5 presents only the d-excess-SST spatial correlations for DJF and SON. Why are only these presented? Including the entire dataset (annual, DJF, MAM, JJA, and SON) would allow readers to understand how these spatial relationships change throughout the year. The same recommendation applies to all spatial correlations presented. Please reassess the clarity and organization of this section, as it is challenging to follow.
- Section 3.2.2 is quite challenging to read due to the amount of information presented without a clear structure. I recommend that the authors review the organization of this section, focusing on clearly conveying the main information relevant to supporting their arguments.
Minor comments:
Line 25: Please consider specifying…large variations in the “near surface” air temperature….
Line 39: Changes in atmospheric circulation “patterns”
Lines 44-46: This sentence is not clear: “In recent decades, the Southern Annular Mode (SAM), which indicates the modulation of westerly winds towards the Southern Hemisphere (Hall and Visbeck, 2002; Fogt et al., 2012), has become increasingly important for the Southern Hemisphere climate (Russell and McGregor, 2010).”. Does this mean that before the recent decades, SAM had no major relevance in the Southern Hemisphere climate? Please specify.
Line 60: It is mentioned that the study aims to explore the climate-related signals in the GV7-C ice core record (including dD). However, the dD signal is not explored in depth (only included in the manuscript through the d-excess). Please include the dD record on the analyses or remove dD from the list of the records that will be explored in the study.
Line 72: it is mentioned that the site is 95km away from the coastline, however, the coastline is “permanently” covered with perennial sea ice (as seen in Fig 1). It would be useful to know how far is the site from the open water. Please add this info.
Line 76-80: The information in these lines seem to disagree. The first line says that during autumn-winter airmasses primarily originate from WPO and during spring the from the Ross sector. Then, the next line says airmasses (2007-2012) are from the Indian Ocean and Antarctic Plateau with smaller contributions from the Ross Sea and PO. These sentences don’t say much unless the evaluation time period is specified in the first sentence. Please evaluate clarifying the information in these lines.
Line 82-83: Please specify which parameter is the one that exhibits the second maximum in winter. If it is the SA, please specify.
Figure1: Please add a reference to the geographical location of the oates coast
Figure 1: Please add elevation contours to the map
Figure 1: There are grey and green dots in the map, please add a legend stating what they mean
Line 98: how was the electrical conductivity measured? Please, specify.
Line 99-101: The manuscript doesn’t mention about the SA estimation accounting for compression. Please specify why.
Lines 103-107: Please specify why the evaluation period goes back only to 1957, when ERA5 extends from 1950-present.
Line 127: The datasets are presented and evaluated in “periods”. Please specify in the methods section the reason to evaluate the datasets in these particular time periods.
Line 129: It is mentioned six periods, however, Figure 2 shows seven periods and there are seven periods in between brackets in line 130. Please, correct for consistency.
Line 132: Is mentioned that there are four periods with sequential years higher than the average. However, figure 2 only shows three periods. Please, correct for consistency.
Line 132: Periods are reported without a temporal unit (CE), not matching previously reported periods in Line 130.
Line 138-139: The manuscript lists eight periods while Figure 2 only highlights seven. Please, correct for consistency.
Table 1,2 & 3: The evaluation periods have higher “n” values than the annual evaluation. Please specify in the methods section what data is being used when comparing the evaluation “periods”
Line 177: The correlations mentioned in this line cannot be directly traced to the figures in supporting evidence, making it difficult to evaluate the magnitude and spatial distribution of the correlations mentioned in the text. Please, provide figures for the correlations mentioned in the text or remove these statements from the text if the correlations are not relevant.
Table 5: The table intends to summarise the observed correlations, however, it remains unclear the criteria that has to be met for a correlation to be included in the table and the table is not precise on the magnitude or sign of the correlation. Please, clarify.
Line 178-179: the manuscript brings attention to “the correlations”, however, it remains unclear to which correlations the authors are referring (positive? negative?). Please, clarify.
Figure 3: Please add values to each vertical axis for reference.
Line 297: the manuscript states correlations were performed using the running-averaged data. Why not the non-averaged data? Also, it seems that they only used the 5-year running-averaged data. Why not the 3-year running-averaged data? It is not clear from the manuscript why they use some datasets and not all the ones they generated.
Lines 312-324: it is not clear if the authors are reporting results obtained using the 3-year or 5-year running-averaged data. Please specify.
Table 8: I find very difficult to understand this table. What does the number inside the parenthesis mean? The caption says “Pearson’s correlation coeficcients between three- and five-year average (in parenthesis) and…”. According to what is written in the caption, I understand that what it is in parenthesis is the five-year average correlation coefficient. However, the last four rows of the table are exclusively dedicated to presenting the data for the 5-year running-average dataset and it also has numbers in parenthesis. Please consider adding information in the table caption about how to interpret table 8.
Line 347: Please consider adding the word “partly” to “…(decreasing) d18O can be ______ explained by the intrusion…”.
Line 349-350: A correlation is reported over the period 2005-2014 CE. Is this correlation (R=-0.24) statistically significant? If not, please remove it from the manuscript and report that “no statistically significant correlations were found” in that core over that period of time.
Line 351-353: Please add a reference to that line.
Line 369: Please correct “is contrast” for “contrasts”
Lines 372-373: The sentence in these lines reports Southern Ocean warming co-varying with dexcess during 1991-2000 CE. While this statement may support the authors point, it also raises questions about the co-variability of these parameters outside those 10 years. Please, add more information about the Southern Ocean warming vs d-excess relationship outside that 10 year window.
Line 375: The line states “… was consistent with the GV7-C ice core result”. Please specify to which result you are referring to.
Lines 389-390: Please check this sentence for clarity
Lines 396-397: Please add a reference to this line.
Line 411: The line states “It is useful…”. Please specify “what is useful” or reassess the sentence for clarity.
Citation: https://doi.org/10.5194/egusphere-2025-2408-RC2
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- 1
The manuscript by Nyamgerel et al investigates climate related signals in the GV7-C ice core located in East Antarctica, and the potential teleconnections between the tropics and Antarctica. While the manuscript addresses an important question regarding the climate variability signals within the GV7-C ice core in East Antarctica, major revisions are necessary before it can be considered for publication.
My main concerns that need to be addressed before further review are:
(1) Additional detail added to the method. Currently the method lacks sufficient detail to understand and have confidence in the results and interpretation. My key concerns include:
(2) Most of the figures are in the supplementary material. These are referred to in the results and essential to be able to understand the results and interpretation discussed so need to be made more concise to be able to be included in the main text.
(3) Manuscript needs a major restructure. Currently there are a lot of discussion points in the results and it is challenging to determine what the key findings of the manuscript are. These need to be obvious based on the figures and results section, which is currently not the case with multiple figures in the supplementary and no clear structure to the result and discussion section.
(4) Missing key relevant references. One example is around the studies that investigate the link between weather regimes (including atmospheric rivers) and their links to modes of climate variability in the region, and how these influence the interpretation of climate signals in ice cores. Some relevant examples are:
Given the above, I recommend major revisions to strengthen the methodological transparency, clarify results and make the figures more concise and related to the key messages of the paper, and restructure to improve the interpretation and integration of findings within the broader Antarctic climate variability research.