Holocene temperatures in southwestern Greenland controlled by topography, ice sheet proximity and oceanic conditions

Acharya, Sudip; Cluett, Allison A.; Grogan, Amy L.; Briner, Jason P.; Castañeda, Isla S.; Thomas, Elizabeth K.

doi:10.5194/egusphere-2025-3113

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https://doi.org/10.5194/egusphere-2025-3113

Preprints

31 Jul 2025

| 31 Jul 2025

Holocene temperatures in southwestern Greenland controlled by topography, ice sheet proximity and oceanic conditions

Sudip Acharya, Allison A. Cluett, Amy L. Grogan, Jason P. Briner, Isla S. Castañeda, and Elizabeth K. Thomas

Abstract. The Holocene thermal maximum (HTM), a period during the early and middle-Holocene when Greenland likely experienced warmer than pre-industrial climate, provides an ideal opportunity to test the sensitivity of the Greenland Ice Sheet to prolonged warmer-than-preindustrial conditions. However, available climate reconstructions from the region provide a controversial picture of the HTM—several reconstructions show an earlier HTM between the early- to middle-Holocene, while others show a delayed HTM between the middle to late Holocene. This discrepancy may be due to either the seasonal sensitivity of the proxies or to spatio-temporal climate variations. Here we generate five new Holocene branched glycerol dialkyl glycerol tetraether (brGDGT)-inferred ice-free season lake water temperature timeseries from lakes along a latitudinal transect in southwestern Greenland, yielding a total of seven Holocene brGDGT timeseries in this region. Lake model simulations suggest minimal intra-lake variation in both the seasonal production window of brGDGTs and the sensitivity of studied lakes to air temperature changes, suggesting regional climate as a primary mechanism influencing these timeseries. Five of the brGDGT timeseries suggest a thermal maximum between approx. 7 and 5 ka, following the peak summer solar insolation and in agreement with many regional reconstructions. A coastal site that is influenced by ocean-atmosphere heat exchange experienced a thermal maximum between approx. 5 to 3 ka, coinciding with nearby sea surface temperature reconstructions. A site far from both the coast and the Greenland Ice Sheet suggests peak warmth in the early Holocene. This suggests that local variations in temperature, influenced by the proximity to the ice sheet and ocean, caused the discrepancies in the Holocene temperature reconstructions in proxy timeseries in southwestern Greenland. Further investigations quantifying seasonal sensitivity and local effects (e.g., site-specific systematics, and proximity to ice sheet and ocean) may reveal similarities among proxy timeseries.

Received: 02 Jul 2025 – Discussion started: 31 Jul 2025

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29 Jul 2026

Holocene temperatures in southwestern Greenland controlled by topography, ice sheet proximity, and oceanic conditions

Sudip Acharya, Allison A. Cluett, Amy L. Grogan, Jason P. Briner, Isla S. Castañeda, and Elizabeth K. Thomas

Clim. Past, 22, 1401–1421, https://doi.org/10.5194/cp-22-1401-2026,https://doi.org/10.5194/cp-22-1401-2026, 2026

Short summary

Sudip Acharya, Allison A. Cluett, Amy L. Grogan, Jason P. Briner, Isla S. Castañeda, and Elizabeth K. Thomas

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2025-3113', Anonymous Referee #1, 28 Aug 2025
Scientific significance
The manuscript by Acharya et al. presents a compilation of 7 brGDGT-based temperature records from west, southwest and south Greenland (5 new, 2 published) and interprets these data as changes in lake water temperature during the ice-free season (IFS LWT). These trends are used to assess spatiotemporal patterns of Holocene temperature change in this sector of Greenland, with particular attention on the regional timing of Holocene Thermal Maximum. There is obvious heterogeneity across the records and the authors attribute the disparities to differences in lake location and proximity to the coast and/or Greenland Ice Sheet. It is a thoughtful study design and an interesting network of sites that, unlike many lakes from Greenland generally, also capture some or most of the early Holocene (10-8 ka). The sites presented have the potential to fill in important spatial context for the extent and pattern of insolation-driven Holocene warming and subsequent cooling across Greenland.
Scientific quality
The dataset presented here is interesting and an important contribution to the body of evidence documenting the past environment from Greenlandic lake sediments. However, the manuscript presents with several major issues that result in a poorly supported interpretation of the data.
The use of brGDGT distributions to estimate temperature is extensively calibrated and commonly used, but the proxy is also widely documented to respond to other environmental gradients beyond temperature. In particular, there is a growing body of work showing that local lake conditions including redox status can overwhelm or skew temperature (Raberg et al., 2025; Yao et al., 2020; Zander et al., 2024) and evidence that Holocene brGDGT temperature reconstructions at Arctic sites are impacted (de Wet et al., 2019; Kusch et al., 2019; Lattaud et al., 2021). The authors acknowledge this as a potential confounding factor and their data show periods of elevated concentrations of isoGDGT0 along with extremely high isoGDGT0/Cren (“Cald/Cren”) ratios (>200) that indicate methanogen production and thus anoxia is indeed heightened at some sites through parts of the Holocene (e.g., Figs. S6-S10). However, they quickly rule out the likelihood of brGDGT distributions being impacted by site-specific redox conditions, reflected in isoGDGTs, based on 1) A lake modeling exercise that indicates all sites are invulnerable to summer stratification, and thus 2) that isoGDGTs have a different production seasonality (winter, with anoxia driven by prolonged ice cover) than brGDGTs (summer). However, there are obvious problems with the lake model, and the second point lacks any additional data to support it independently, as described below.
Lake Model
The presented lake model output for the suite of lakes demonstrates every lake in the dataset is invulnerable to changes in summer mixing regime, even at summer air temperature perturbations as high as +10 degrees. Supplemental Fig. S16 indicates that +10 deg of JJA air temperature will yield just +2 degrees of IFS surface LWT change at every lake despite morphological and catchment type differences. This same model also shows invariant ice phenology regimes (Fig. S15) between the lakes, despite large differences in both elevation and latitude. These model outputs are contradicted by observational data at sites across Greenland and the Arctic broadly, which demonstrate A) lake water and air temperature are much more closely matched at most sites (Carrea et al., 2025; Kettle et al., 2004; Piccolroaz et al., 2020; Tong et al., 2023), B) Arctic lakes can be vulnerable to summer stratification at even modern warming levels (Antoniades et al., 2024) and with a temperature difference between the epi and hypolimnion as little as 0.5 deg C (Klanten et al., 2024), and there are comparable lakes in this sector of Greenland that are summer-stratified today (Saros et al., 2016), and C) ice phenology (i.e., timing and length of the ice free season) is almost certainly variant at these sites based on the elevation range (Posch et al., 2024).
Additionally, this model indicates that Holocene-scale air temperature changes across Greenland (~ +0-4 deg C) should result in changes that are barely detectable in brGDGT distributions (IFS LWT <1 deg C, as demonstrated in Fig S16). However, the reconstructed brGDGT IFS LWT presented here show anomalies on the order of +5-15 degrees, which would lead to highly unreasonable air temperature estimates even at the low end of those estimates given the relationship between air and water temperatures expressed by the model.
It is therefore very unlikely this lake model is accurately capturing thermal dynamics in these lakes and the subsequent logic that these lakes are invulnerable to summer stratification, and thus anoxia is restricted to the winter and brGDGT production is not impacted, is not supported. At the very least, the model needs to be validated by observational data on temperature and mixing status from these or several similar Arctic lakes that have documented summer temperatures and mixing regimes (e.g., Carrea et al., 2025 and references therein) to see if it captures known conditions.
Production Seasonality of archaeal vs. bacterial GDGTs
It is unclear what data exists to support that the production seasonality of archaeal vs. bacterial GDGT production would be so substantially disconnected. As the authors identified, there is data that supports higher production of brGDGTs in the warm season (Raberg et al., 2021; Shanahan et al., 2013), although the reasoning for this is not always clear (Cao et al., 2020), and this observation isn’t necessarily different from the production seasonality of isoGDGTs (Blaga et al., 2011; Li et al., 2025; Zander et al., 2024). There is also relevant data that shows strong increases in production of brGDGTs occurs in anoxic conditions (Raberg et al., 2025; Weber et al., 2018), suggesting brGDGTs could also shift towards dominant production in the winter given development of appropriate conditions like water column anoxia, which may not be widely captured in modern observations if most lakes in the datasets are oxygenated in the winter today (Klanten et al., 2023; Raberg et al., 2025). In absence of other independent data on lake mixing regime, the hypothesis that one signal is winter and the other is summer is interesting and may motivate future work that tests this further but is currently weakly supported by external observations in the existing literature. Furthermore, concentration trends presented by the authors of both isoGDGTs and brGDGTs at the lake sites appear strongly correlated, suggesting production of both groups is responding to similar environmental forcings (Figs. S6-10). Trends in the concentration of isoGDGT0 also appear related to reconstructed IFS temperature. What mechanisms exist to drive this relationship, and can the same production window be excluded? If they are produced during the same season, then within-lake changes can’t be ruled out from interpretation of brGDGT distributions. Nevertheless, the authors could test this hypothesis further by presenting data on the structures specifically within the brGDGTs that are recognized to also respond to redox status: fractional percent of IIIa (e.g., %IIIa, HP5 index) and IIIa’’ (Weber et al., 2015; Yao et al., 2020). The former indices are readily calculated from the data already presented and the latter should be recorded in their HPLC-MS data, given that they used the Hopmans et al. (2016) method.
Summary
A more thorough consideration that lake-specific parameters, including mixing status and oxygen, contribute to brGDGT trends is warranted. Given that the key assumptions that lead to the conclusion that brGDGT distributions are entirely driven by IFS LWT are poorly supported, the discussion of climatic forcings that can explain the heterogeneous pattern of warming is somewhat moot and therefore not extensively evaluated at this stage of review. From this data, can we really be sure that the HTM occurs from ~7-5ka in this sector of Greenland with leads/lags around this timing related to continental position (with even this inconsistent across their dataset), or is it equally or more plausible that higher seasonality and warmer summers in the early Holocene led to mixing regime changes at some of these sites (reflected currently in isoGDGT0 concentration and 0/cren ratios) and consequently increased production of e.g., brGDGT IIIa, creating a cold-biased temperature reconstruction in the early-middle Holocene and catchment-scale heterogeneity across the Holocene.
Other points of consideration:
The cut-off of the IR_6ME ratio at 0.3 to exclude data is arbitrary and substantially lower than the datasets that provide the reasoning for cut-off (i.e., 0.5, 0.4; Bauersachs et al., 2024; Novak et al., 2025). All data, including those flagged by IR ratio, should be included in the main figure(s), even if distinct symbols/colors are used to flag those datapoints, and a thorough discussion related to the IR ratio needs to be included. How does the data interpretation change if a cut-off of 0.4 or 0.5 is applied? Is this cut-off even still applicable when not using the modified MBT5Me calibration that excludes data above the cut-off?

The authors compare IFS LWT directly to estimates of air temperature (e.g., from ice cores, chironomid, pollen), which based on their own model, aren’t directly comparable. The GISP2 record that is presented is not corrected for elevation change or seasonal bias (see Axford et al., 2021). The magnitude of warming in these data is much higher compared to existing estimates of temperature change, and this discrepancy warrants discussion and reconciliation with both existing temperature reconstructions and the model that suggests lake water response should be dampened compared to air temperature if these data are interpreted as temperature.

More justification is needed for the selection of a site-specific calibration dataset from one lake in south Greenland (Zhao et al., 2021) vs. calibration datasets that incorporate more extensive data and many additional Arctic sites (e.g., Raberg et al., 2021) that have greater potential to more adequately cover the range of environmental conditions that occur in these 7 lakes through time.

Is the same screening for soil-derived brGDGTs (<30% hexa-methylated) used in Cluett et al. for the Lake Gus temperature reconstruction also applied to all other lake brGDGT data presented here?

Why does the lake model for Lake Gus in Cluett et al. have such different sensitivity between air and lake water temperature compared to the model for the other lakes here? It could be valuable to remodel Lake Gus and model Lake 578 here as well, using the same modeling decisions applied to the other lakes.

An internal C46 standard is mentioned as added but it is not elaborated on if or how this standard was used in data processing

Presentation Quality
The structure of this manuscript overall flows well. At times the presentation is a little odd though, for example, the supplemental figures are referenced well-before and more often than most of the main figures. It seems like at least some of these data should be moved into the main text (e.g., Figs. S6-10). Some of the background/discussion is not internally consistent. There are minor issues with typos (e.g., surface areas in Table 1 are different from surface areas given in the in-line text; Comarum Sø is spelled incorrectly in parts of the text, Caldarchaeol is spelled incorrectly in some of the figure captions and I did wonder why it’s presented as “Cald” as opposed to the more common presentation of isoGDGT0, etc.). The scaling of deg C on the y-axes on Figures 2, 3 are confusingly unique by each row and make it hard to compare temperature change site to site and record to record; I noted a similar issue with the scaling of cald/cren ratios across Figs. S6-10.

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Citation: https://doi.org/10.5194/egusphere-2025-3113-RC1
- AC1: 'Reply on RC1', Sudip Acharya, 23 Oct 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3113/egusphere-2025-3113-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2025-3113-AC1
RC2:
'Comment on egusphere-2025-3113', Anonymous Referee #2, 04 Sep 2025

This is a well-written and well-illustrated manuscript. Holocene temperature changes in ice-free Greenland were first reconstructed from marine bivalves from raised marine deposits and later by pollen analyses of lake and mire deposits. The former method is problematical because it is difficult to find continuous records and the latter is problematical because it is time-consuming, because of delayed immigration of many plant species and because of long-distance transport of pollen grains from the south. Later studies of lake sediments have used stable isotopes, chironomids, biomarkers and other proxies, but each method has its own problems. However, we still do not have a good picture of the timing of the Holocene Thermal Maximum. Did it vary from area to area? Did it end gradually or more abrupt? And how warm was the HTM in SW Greenland?
I am impressed to see that the authors have generated five new brGDGT-inferred ice-free season lake water temperature series from Holocene lake deposits in southwestern Greenland, yielding a total of seven Holocene brGDGT timeseries in this region. Most proxy studies of lake sediments from Greenland have only dealt with a single or a few lakes.
I am not an expert on brGDGT but I note that Kusch et al. (2019) tried to use brGDGT on lake sediments from North Greenland and concluded that the method did not work in the far north. From the discussion about calibrations, I get the feeling that more work is needed to better infer past temperatures from data on brGDGT in SW Greenland. I am surprised to learn that the authors reconstructed temperatures up to 21.8 °C – I think this are high temperatures for a lake in Greenland. Even more surprisingly, this high temperature was found for Marshall at an elevation of 862 m.
The authors conclude that five of the seven timeseries from South and Southwest Greenland indicate that the Holocene Thermal Maximum occurred between approx. 7000 and 5000 years BP. I note that Fredskild 1983 suggested that the warmest period in SW Greenland occurred from 7500 BP and the following millennia (The Holocene vegetational development of the Godthåbsfjord area, West Greenland. Meddelelser om Grønland, Geoscience 10, https://doi.org/10.7146/moggeosci.v10i.140322). I also note that Bennike et. al. 2010 suggested peak Holocene temperatures from c. 7000 to 6500 cal. years BP based on the occurrence of a warmth-demanding ostracode in lake sediments at the head of Kangerlussuaq (Holocene palaeoecology of southwest Greenland inferred from macrofossils in sediments of an oligosaline lake. Journal of Paleolimnology 43, 787–798
Specific comments:
Line 11, 41. early and middle-Holocene – these are formal units, I suggest to write Early and Middle Holocene
Line 11. Delete likely – it has been demonstrated in numerous studies.
Line 51. defined herein the region – change to: defined herein as the region
Line 51. I would change Nugaatsiaq (spelled Nuugaatsiaq on Fig. 1) to Nuussuaq. Nugaatsiaq is a small abandoned settlement, whereas Nuussuaq is a large, well-known peninsula.
Line 63-64: “reveals a Holocene thermal maximum (HTM) at ~7.9 ka which is temperature ~2.9 ± 1.4 °C warmer than the recent”. Rewrite
Also, strictly speaking, temperatures cannot be warm or cold – they can be high or low.
The high temperatures were recorded at 7960 ± 30 years B.P. – during a short-lived period. The period from 8000 to 6000 years BP shows declining temperatures – you may argue that the HTM is dated to 8000–7000 at Summit.
Line 65. change between ~6 to 4 ka to: between ~6 and 4 ka
Line 98 etc. I would expect some more notes on the setting in this chapter. Including some notes on ocean currents, air temperatures in the region and notes on the strong temperature gradient from the cold outer coast to the warm inland near the margin of the ice sheet. It would also be great if you can provide some data about measured lake water temperatures.
Line 363. katabatic winds are usually warm
Line 364 etc. Here you discuss the distance to the Greenland Ice Sheet. It should be distance to the margin of the ice sheet.
Line 433. The similarity between the GISP2 and Lake Marshall records is not great.
Line 444. both Comarum Sø and Kløft Sø are mis-spelled.
Line 448. The pollen-based temperature reconstruction from Qipisarqo lake is mainly based on Alnus pollen from Labrador.
Line 463. Not sure what you mean by this: due to low temporal resolution of the time series between 2 to 4 ka, anomaly period.
Fig. 1. You can argue that the East Greenland Current continues around Cape Farewell and a little up the coast of West Greenland. The region of locality 13 to 18 is strongly influenced in late summer by sea ice from the Arctic Ocean.
Fig. 3. The temperature record from GISP2 is “upside-down”, so that the 8.2 event appears visually as a warm period (temperatures ~ –34°C) and the HTM appears as a cold period.

Citation: https://doi.org/10.5194/egusphere-2025-3113-RC2
- AC2: 'Reply on RC2', Sudip Acharya, 23 Oct 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3113/egusphere-2025-3113-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2025-3113-AC2

Peer review completion

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

ED: Reconsider after major revisions (29 Oct 2025) by Francesco Muschitiello

AR by Sudip Acharya on behalf of the Authors (25 Nov 2025) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (27 Nov 2025) by Francesco Muschitiello

RR by Anonymous Referee #2 (15 Dec 2025)

RR by Anonymous Referee #1 (21 Jan 2026)

ED: Reconsider after major revisions (30 Jan 2026) by Francesco Muschitiello

ED: Reconsider after major revisions (03 Feb 2026) by Francesco Muschitiello

Dear Authors,

Thank you for addressing the reviewers’ comments and submitting a revised version of the manuscript. In light of the latest reviews, I am unable to accept the manuscript in its current form and must request a further revision that fully addresses the points raised by Reviewer 1.

In particular, R1 deems that the results do not yet convincingly support the conclusions, and that the interpretation of the GDGT data requires more careful evaluation, ideally supported by additional empirical evidence and a more balanced/honest engagement with the literature material.

I include R1’s comments below, which I hope will be helpful for preparing your revision. Please note that, given the extent of the changes required, I will have to send the revised manuscript out for another round of review.

All the best,
FM

Anonymous referee #1

Dear Editor and Authors,
It is my assessment that this paper should receive a recommendation of major revisions or a rejection. They have provided minimal to moderate updates from the initial submission, and do not adequately address the major points raised in the first round of review. As such, my review remains largely unchanged. The paper provides an irresponsible representation of the GDGT proxy literature, which is presented in a way to facilitate a climatic interpretation but not grounded in data. The interpretation additionally leans heavily on a lake model but the study provides no demonstration of how well that model performs for lakes similar to these small, high-arctic lakes, particularly for stratification dynamics. As such, it is difficult to conclude that the data fully support their interpretation of climate dynamics in southern and south western Greenland during the Holocene. The data they have prepared will be a meaningful contribution to the literature and an interesting comparison to other lake data points in the region, but like all proxy inferences is subject to the limitations of the proxy, and needs to be more thoughtfully/carefully evaluated before publication.

I will highlight the key points made in the first round of review and how the revisions failed to address them.

1) “At the very least, the model needs to be validated by observational data on temperature and mixing status from these or several similar Arctic lakes that have documented summer temperatures and mixing regimes”

The authors did not try to do this:

They make the case that the model captures warming accurately, in terms of LSWT sensitivity to air temperature anomalies, and is therefore robust. However, the literature they point to (i.e. Piccolroaz et al, 2020) records observations on lakes that are many orders of magnitude larger than the lakes modelled here (~50-82,000 km2 area, median ~270km2, vs <1 km2 surface area), containing data from just 19 polar lakes with a median (mean) area of 30km2 (500km2). Other datasets show lots of site-to-site variability with tons of heterogeneity in the trends dependent on lake size, elevation, morphometry, etc. (e.g., Dokulil et al, 2021; Zhang 2024 and references therein). But, even if this model is capturing LSWT correctly, this still doesn’t provide validation of the stratification dynamics expressed by the model.

Dokulil: https://doi.org/10.1007/s10584-021-03085-1
Zhang: https://doi.org/10.33265/polar.v43.9580

The authors need to validate this model against real data from a few lakes of comparable size in comparable regions. It is the most basic test of model validation to ask that the authors show that the model can accurately replicate real data in real lakes, similar in size and location to those here, before accepting the model output for these lakes (and the interpretations that rely on it). It is otherwise an assertion that this model is adequate for these lakes, and one major assumption used in the interpretation of their brGDGT data (i.e., that these lakes do not summer-stratify) hinges on this assertion. Yes, Carrera et al documents larger lakes than those in this study, but testing the model against these lakes is better than nothing. I agree with them that smaller lakes more similar to their sites would be even better.

2) “It is unclear what data exists to support that the production seasonality of archaeal vs. bacterial GDGT production would be so substantially disconnected”

This point was raised in the first round of review and the authors continue to present this in the manuscript as though there is an established and well-documented literature to support it. E.g., “Based on the evidence for seasonal production and the contrasting trends in these lake time series, we interpret the br-and isoGDGTs to be predominantly produced during different seasons: brGDGTs in ice-free season and isoGDGTs in ice covered season (Baxter et al., 2021; Blaga et al., 2011; van Bree et al., 2020; Loomis et al., 2014b; Shanahan et al., 2013)”

This point is important because it provides the rationale to rule out biogeochemical impacts on brGDGT distributions based on what is a hypothesis that one group is synthesized in the summer and the other the winter. In their rebuttal, the authors state, “The activity of these archaeal communities is higher during winter in ice-covered lakes” and point to Blaga et al (2011), Masse et al (2019) and Sinnghe-Damste (2022) as evidence for that activity to support winter-biased production of isoGDGTs. Blaga et al (2011) present on a very large, stratified (oligomictic) lake with no ice cover and show highest flux of isoGDGTs overall in late summer and fall (Figs 2, 5); Masse et al (2019) is a study on ammonia oxidation rates with no clear link to isoGDGT production, nevermind that it implicates ammonia-oxidizing bacteria more than archaea in the winter and that ammonia oxidation requires the presence of oxygen under ice; and Sinnghe-Damste et al (2022) present data also on a very large, permanently stratified lake but nevertheless show the highest flux rates of isoGDGTs in the spring-summer months (Fig. 8).

I restate that this is an interesting hypothesis that I hope is tested in future work but there is not independent data that shows isoGDGT production seasonality is clearly winter and brGDGT is clearly summer. There is evidence across the literature, however, to support substantial site-to-site variation in timing/depth/conditions of production dependent on the physical properties of the lake and surrounding watershed.

I note that their brGDGT-related tests for assessing competing gradients (e.g., HP5, %IIIa’’) are interesting and provide some support for differential seasonality, albeit not strongly. There is some moderate correlation or anti-correlation in three out of six lakes (N3, Pluto, Rosaea) and the authors did not also include concentration data in these tests [see prior review, “is it equally or more plausible that higher seasonality and warmer summers in the early Holocene led to mixing regime changes at some of these sites (reflected currently in isoGDGT0 concentration and 0/cren ratios)…”]. Further, the HP5/%IIIa and IIIa’’ trends themselves also suggest there is influence from oxygen in some of the lakes at different points in time (e.g., Bullet Lake). Correlation tests were conducted against MBT’5Me, which is not the temperature index used here. (I would also like to see how strongly their explanatory variables for the climate interpretation correlate to their reconstructions, e.g., SST reconstructions tested against brGDGT-temperatures.)

Overall, it is my position that the authors still do not consider that lake-to-lake variability likely plays a key role in the expression of brGDGTs in these lakes. Ultimately, I don’t think this would be as much of a limitation for the paper if the authors had presented their interpretation as one plausible hypothesis, emphasizing that it is a hypothesis, for explaining the data along with the strong possibility that the spatial variance could also be explained by lake specific conditions, AND that their favored hypothesis is built on major assumptions (e.g., differential seasonality of iso vs. brGDGTs, an unvalidated model that suggests lakes don’t stratify in the summer even under strong warming despite literature that suggests they can stratify at much lower temperature thresholds, clear evidence for anoxia developing in different lakes at different times that shows up in both types of GDGTs, signals that largely are not outside of brGDGT-temp calibration error). My suggestion to the authors would be to take a step back and instead look at what is consistent across the sites (e.g., approximately 1-2 deg of anomalous MAF warmth in the early-middle Holocene), which is more likely to be explained by broad climate than lake-to-lake variability.

Echoing my last review, the discussion of specific climatic forcings that can explain the heterogeneous pattern of warming is somewhat moot and therefore not extensively evaluated at this stage of review.

I note that the authors did address the IR ratio adequately by including all data and noting where it is below their flagged ratio, and that they have changed text to appropriately update e.g., Greenland ice sheet GISP2 records as impacted by elevation. I appreciate that they added new tests to address some of the prior review (e.g., HP5, %IIIa), that they updated the calibration approach, and that they recognized the major discrepancy with air temps if brGDGT IFSLWT followed their model output. I suggest more support in the next iteration for the averaging of values output from different calibrations, what the implications are for different calibrations showing varying trends in the same lake, as well as how they delt with compounded error from averaging.

Other comments:
I suggest the authors double-check they’ve processed all their indices correctly. It seems odd that the HP5 and %IIIa would not predict major changes in brGDGT-inferred temp but I observe that there are places in different lake records where one or the other (abundances or temp) change substantially, but not both (e.g., ~4500 years at N3).

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AR by Sudip Acharya on behalf of the Authors (30 Mar 2026) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (15 Apr 2026) by Francesco Muschitiello

RR by Anonymous Referee #1 (27 May 2026)

Suggestions for revision or reasons for rejection

Dear Editor and Authors,

I have now completed a third review of this paper following major revisions by the authors. The authors have conducted validation work of the lake model against Lake 578 in southern Greenland and some validation work using the available temperature data from N3. They have also removed language that described differential seasonality of production between iso- and brGDGTs.
I suggest accepting with minor revisions.
Some key suggestions include:
• The authors should review and revise the abstract. Although the authors have significantly changed the text, they have not really updated the abstract to reflect these changes, including reconsidering the broad statement that cald/cren is decoupled from their temperature reconstructions (see e.g. Table S4).
• It seems pertinent to include Lake Gus in Figure 5 and given that the data for the lake was produced by the same research group is likely to be available to them. They present Lake Gus as an outlier in temperature trends in terms of timing but do not give the GDGTs the same depth of examination that the other lakes receive.
• I request that the authors make a point in the main text recognizing that the temperature data from N3 indicate that it is likely summer-stratified today and the model supports this stratification persists for most of the IFS. This is somewhat buried in the supplemental (Figure S9) but would be appropriate to include in section 3.3.4. The muted extension of the stratification period in the model may be explained by the observation that there aren’t that many additional days in the IFS during which N3 isn’t already stratified. It is a little hard to consolidate e.g., lines 365-375 which insinuates these lakes should all be well-mixed during most of the IFS with Figures S8, S9 which show the only lakes they have observational data from both have extended periods of summer-stratification during the IFS today under what I think of as relatively weak summer forcing, relative to the early-middle Holocene.
• The authors appear to have removed the temperature calibration uncertainty from the temperature estimates in figures—please add this back into the figures. I do think that the error on these measurements deserves a bit more recognition throughout the text as well but recognize that it likely wouldn’t fundamentally change the interpretation.
• Correlation coefficients being low/non-significant between cald/cren and temperature reconstructions doesn’t necessarily indicate no influence on brGDGT distributions and thus temperature estimates, as outlined in section 3.3.4. That the 0/cren ratios are persistently (very) high overall through periods of the records, especially in the early-middle Holocene at N3 and Pluto, still provides evidence of conditions that can and likely do affect the temperature reconstruction. These are complex and intertwined gradients, and it reads as ‘missing the forest for the trees’ in the treatment.
• Are there no brGDGT-inferred temperature estimates from surface sediments at these sites to compare against modern climatologic data? That seems like a first-order test of whether site-specific parameters compete with the regional geographic temperature trends driven by elevation and coastal/inland positioning.
Line Items
• Line 13: Refers to ‘from the region’ without stating what the region is first
• Line 46: is it really accurate to say “patterns of Holocene climate change in Greenland are still poorly resolved” at this point? There are two reviews on this topic and dozens of reconstructions from the island
• Line 50: I recommend checking this regional definition against other sources. This broad area is elsewhere considered to be multiple sectors of Greenland (see Danish meteorological institute technical reports on Greenland, for e.g.)
• Lines 124-133: meteorological observations should be attributed to primary sources that contain the original observations like precipitation amounts
• Line 164: I am guessing you used BEH HILIC columns and suggest including the phase information details here
• Line 167: Suggest elaborating on what it means here to determine GDGT concentrations relative to the C46 internal standard. Were peaks normalized to this somehow? Was a linearity dilution series performed?
• Line 211: Figure S9 appears to have a sizeable mismatch between modelled bottom water temps and observed bottom water temps starting ~10ish m water depth, despite the text here stating ‘all agree well’. Can you provide somewhere, perhaps here, the range of offset between estimate and model temps?
• Line 232: concentrations peak in the early Holocene but maximum temperatures occur later? Consider adding a discussion point on why peak microbial productivity precedes peak temperature estimates.
• Line 256: Which Otiniano et al. 2024 calibration equation is used? Are decimals on temp estimates meaningful given an uncertainty of +/- 1 degree?
• Line 265: In earlier review, these points were requested to be included in the figures of temperature reconstructions but ‘flagged’ and identified as being excluded from consideration as temperature in the discussion for the reasons provided.
• Lines 324-340: The authors state above the parameterization is somewhat homogenized to reduce computational intensity. How much similarity across the lakes in the model is owed to this?
• Line 557: where does 0.2 as the uncertainty on this estimate derive from? The calibration error is stated above as 1.0 deg C.

Ultimately, I fundamentally disagree with aspects of the interpretation and find some of the reasoning circular, but the authors have certainly addressed the major problems in earlier drafts and are in their right to present this interpretation as a plausible hypothesis and let the reader/community decide. In my opinion, a stronger manuscript would have acknowledged that geochemical sources of noise (e.g., anoxia imperfectly and non-linearly recorded by cald/cren) in addition to regional climate factors and lake attributes could explain the site-to-site differences. However, the authors clearly are eager to make the case these data are explained entirely by regional differences in air temperature and thus climate and so they should.

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ED: Publish subject to minor revisions (review by editor) (09 Jun 2026) by Francesco Muschitiello

AR by Sudip Acharya on behalf of the Authors (12 Jun 2026) Author's tracked changes Manuscript

EF by Svenja Lange (16 Jun 2026) Author's response

ED: Publish as is (01 Jul 2026) by Francesco Muschitiello

AR by Sudip Acharya on behalf of the Authors (09 Jul 2026) Manuscript

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2025-3113', Anonymous Referee #1, 28 Aug 2025
Scientific significance
The manuscript by Acharya et al. presents a compilation of 7 brGDGT-based temperature records from west, southwest and south Greenland (5 new, 2 published) and interprets these data as changes in lake water temperature during the ice-free season (IFS LWT). These trends are used to assess spatiotemporal patterns of Holocene temperature change in this sector of Greenland, with particular attention on the regional timing of Holocene Thermal Maximum. There is obvious heterogeneity across the records and the authors attribute the disparities to differences in lake location and proximity to the coast and/or Greenland Ice Sheet. It is a thoughtful study design and an interesting network of sites that, unlike many lakes from Greenland generally, also capture some or most of the early Holocene (10-8 ka). The sites presented have the potential to fill in important spatial context for the extent and pattern of insolation-driven Holocene warming and subsequent cooling across Greenland.
Scientific quality
The dataset presented here is interesting and an important contribution to the body of evidence documenting the past environment from Greenlandic lake sediments. However, the manuscript presents with several major issues that result in a poorly supported interpretation of the data.
The use of brGDGT distributions to estimate temperature is extensively calibrated and commonly used, but the proxy is also widely documented to respond to other environmental gradients beyond temperature. In particular, there is a growing body of work showing that local lake conditions including redox status can overwhelm or skew temperature (Raberg et al., 2025; Yao et al., 2020; Zander et al., 2024) and evidence that Holocene brGDGT temperature reconstructions at Arctic sites are impacted (de Wet et al., 2019; Kusch et al., 2019; Lattaud et al., 2021). The authors acknowledge this as a potential confounding factor and their data show periods of elevated concentrations of isoGDGT0 along with extremely high isoGDGT0/Cren (“Cald/Cren”) ratios (>200) that indicate methanogen production and thus anoxia is indeed heightened at some sites through parts of the Holocene (e.g., Figs. S6-S10). However, they quickly rule out the likelihood of brGDGT distributions being impacted by site-specific redox conditions, reflected in isoGDGTs, based on 1) A lake modeling exercise that indicates all sites are invulnerable to summer stratification, and thus 2) that isoGDGTs have a different production seasonality (winter, with anoxia driven by prolonged ice cover) than brGDGTs (summer). However, there are obvious problems with the lake model, and the second point lacks any additional data to support it independently, as described below.
Lake Model
The presented lake model output for the suite of lakes demonstrates every lake in the dataset is invulnerable to changes in summer mixing regime, even at summer air temperature perturbations as high as +10 degrees. Supplemental Fig. S16 indicates that +10 deg of JJA air temperature will yield just +2 degrees of IFS surface LWT change at every lake despite morphological and catchment type differences. This same model also shows invariant ice phenology regimes (Fig. S15) between the lakes, despite large differences in both elevation and latitude. These model outputs are contradicted by observational data at sites across Greenland and the Arctic broadly, which demonstrate A) lake water and air temperature are much more closely matched at most sites (Carrea et al., 2025; Kettle et al., 2004; Piccolroaz et al., 2020; Tong et al., 2023), B) Arctic lakes can be vulnerable to summer stratification at even modern warming levels (Antoniades et al., 2024) and with a temperature difference between the epi and hypolimnion as little as 0.5 deg C (Klanten et al., 2024), and there are comparable lakes in this sector of Greenland that are summer-stratified today (Saros et al., 2016), and C) ice phenology (i.e., timing and length of the ice free season) is almost certainly variant at these sites based on the elevation range (Posch et al., 2024).
Additionally, this model indicates that Holocene-scale air temperature changes across Greenland (~ +0-4 deg C) should result in changes that are barely detectable in brGDGT distributions (IFS LWT <1 deg C, as demonstrated in Fig S16). However, the reconstructed brGDGT IFS LWT presented here show anomalies on the order of +5-15 degrees, which would lead to highly unreasonable air temperature estimates even at the low end of those estimates given the relationship between air and water temperatures expressed by the model.
It is therefore very unlikely this lake model is accurately capturing thermal dynamics in these lakes and the subsequent logic that these lakes are invulnerable to summer stratification, and thus anoxia is restricted to the winter and brGDGT production is not impacted, is not supported. At the very least, the model needs to be validated by observational data on temperature and mixing status from these or several similar Arctic lakes that have documented summer temperatures and mixing regimes (e.g., Carrea et al., 2025 and references therein) to see if it captures known conditions.
Production Seasonality of archaeal vs. bacterial GDGTs
It is unclear what data exists to support that the production seasonality of archaeal vs. bacterial GDGT production would be so substantially disconnected. As the authors identified, there is data that supports higher production of brGDGTs in the warm season (Raberg et al., 2021; Shanahan et al., 2013), although the reasoning for this is not always clear (Cao et al., 2020), and this observation isn’t necessarily different from the production seasonality of isoGDGTs (Blaga et al., 2011; Li et al., 2025; Zander et al., 2024). There is also relevant data that shows strong increases in production of brGDGTs occurs in anoxic conditions (Raberg et al., 2025; Weber et al., 2018), suggesting brGDGTs could also shift towards dominant production in the winter given development of appropriate conditions like water column anoxia, which may not be widely captured in modern observations if most lakes in the datasets are oxygenated in the winter today (Klanten et al., 2023; Raberg et al., 2025). In absence of other independent data on lake mixing regime, the hypothesis that one signal is winter and the other is summer is interesting and may motivate future work that tests this further but is currently weakly supported by external observations in the existing literature. Furthermore, concentration trends presented by the authors of both isoGDGTs and brGDGTs at the lake sites appear strongly correlated, suggesting production of both groups is responding to similar environmental forcings (Figs. S6-10). Trends in the concentration of isoGDGT0 also appear related to reconstructed IFS temperature. What mechanisms exist to drive this relationship, and can the same production window be excluded? If they are produced during the same season, then within-lake changes can’t be ruled out from interpretation of brGDGT distributions. Nevertheless, the authors could test this hypothesis further by presenting data on the structures specifically within the brGDGTs that are recognized to also respond to redox status: fractional percent of IIIa (e.g., %IIIa, HP5 index) and IIIa’’ (Weber et al., 2015; Yao et al., 2020). The former indices are readily calculated from the data already presented and the latter should be recorded in their HPLC-MS data, given that they used the Hopmans et al. (2016) method.
Summary
A more thorough consideration that lake-specific parameters, including mixing status and oxygen, contribute to brGDGT trends is warranted. Given that the key assumptions that lead to the conclusion that brGDGT distributions are entirely driven by IFS LWT are poorly supported, the discussion of climatic forcings that can explain the heterogeneous pattern of warming is somewhat moot and therefore not extensively evaluated at this stage of review. From this data, can we really be sure that the HTM occurs from ~7-5ka in this sector of Greenland with leads/lags around this timing related to continental position (with even this inconsistent across their dataset), or is it equally or more plausible that higher seasonality and warmer summers in the early Holocene led to mixing regime changes at some of these sites (reflected currently in isoGDGT0 concentration and 0/cren ratios) and consequently increased production of e.g., brGDGT IIIa, creating a cold-biased temperature reconstruction in the early-middle Holocene and catchment-scale heterogeneity across the Holocene.
Other points of consideration:
The cut-off of the IR_6ME ratio at 0.3 to exclude data is arbitrary and substantially lower than the datasets that provide the reasoning for cut-off (i.e., 0.5, 0.4; Bauersachs et al., 2024; Novak et al., 2025). All data, including those flagged by IR ratio, should be included in the main figure(s), even if distinct symbols/colors are used to flag those datapoints, and a thorough discussion related to the IR ratio needs to be included. How does the data interpretation change if a cut-off of 0.4 or 0.5 is applied? Is this cut-off even still applicable when not using the modified MBT5Me calibration that excludes data above the cut-off?

The authors compare IFS LWT directly to estimates of air temperature (e.g., from ice cores, chironomid, pollen), which based on their own model, aren’t directly comparable. The GISP2 record that is presented is not corrected for elevation change or seasonal bias (see Axford et al., 2021). The magnitude of warming in these data is much higher compared to existing estimates of temperature change, and this discrepancy warrants discussion and reconciliation with both existing temperature reconstructions and the model that suggests lake water response should be dampened compared to air temperature if these data are interpreted as temperature.

More justification is needed for the selection of a site-specific calibration dataset from one lake in south Greenland (Zhao et al., 2021) vs. calibration datasets that incorporate more extensive data and many additional Arctic sites (e.g., Raberg et al., 2021) that have greater potential to more adequately cover the range of environmental conditions that occur in these 7 lakes through time.

Is the same screening for soil-derived brGDGTs (<30% hexa-methylated) used in Cluett et al. for the Lake Gus temperature reconstruction also applied to all other lake brGDGT data presented here?

Why does the lake model for Lake Gus in Cluett et al. have such different sensitivity between air and lake water temperature compared to the model for the other lakes here? It could be valuable to remodel Lake Gus and model Lake 578 here as well, using the same modeling decisions applied to the other lakes.

An internal C46 standard is mentioned as added but it is not elaborated on if or how this standard was used in data processing

Presentation Quality
The structure of this manuscript overall flows well. At times the presentation is a little odd though, for example, the supplemental figures are referenced well-before and more often than most of the main figures. It seems like at least some of these data should be moved into the main text (e.g., Figs. S6-10). Some of the background/discussion is not internally consistent. There are minor issues with typos (e.g., surface areas in Table 1 are different from surface areas given in the in-line text; Comarum Sø is spelled incorrectly in parts of the text, Caldarchaeol is spelled incorrectly in some of the figure captions and I did wonder why it’s presented as “Cald” as opposed to the more common presentation of isoGDGT0, etc.). The scaling of deg C on the y-axes on Figures 2, 3 are confusingly unique by each row and make it hard to compare temperature change site to site and record to record; I noted a similar issue with the scaling of cald/cren ratios across Figs. S6-10.

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Zhao, B., Castañeda, I.S., Bradley, R.S., Salacup, J.M., de Wet, G.A., Daniels, W.C., Schneider, T., 2021. Development of an in situ branched GDGT calibration in Lake 578, southern Greenland. Org Geochem 152, 104168. https://doi.org/10.1016/j.orggeochem.2020.104168
Citation: https://doi.org/10.5194/egusphere-2025-3113-RC1
- AC1: 'Reply on RC1', Sudip Acharya, 23 Oct 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3113/egusphere-2025-3113-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2025-3113-AC1
RC2:
'Comment on egusphere-2025-3113', Anonymous Referee #2, 04 Sep 2025

This is a well-written and well-illustrated manuscript. Holocene temperature changes in ice-free Greenland were first reconstructed from marine bivalves from raised marine deposits and later by pollen analyses of lake and mire deposits. The former method is problematical because it is difficult to find continuous records and the latter is problematical because it is time-consuming, because of delayed immigration of many plant species and because of long-distance transport of pollen grains from the south. Later studies of lake sediments have used stable isotopes, chironomids, biomarkers and other proxies, but each method has its own problems. However, we still do not have a good picture of the timing of the Holocene Thermal Maximum. Did it vary from area to area? Did it end gradually or more abrupt? And how warm was the HTM in SW Greenland?
I am impressed to see that the authors have generated five new brGDGT-inferred ice-free season lake water temperature series from Holocene lake deposits in southwestern Greenland, yielding a total of seven Holocene brGDGT timeseries in this region. Most proxy studies of lake sediments from Greenland have only dealt with a single or a few lakes.
I am not an expert on brGDGT but I note that Kusch et al. (2019) tried to use brGDGT on lake sediments from North Greenland and concluded that the method did not work in the far north. From the discussion about calibrations, I get the feeling that more work is needed to better infer past temperatures from data on brGDGT in SW Greenland. I am surprised to learn that the authors reconstructed temperatures up to 21.8 °C – I think this are high temperatures for a lake in Greenland. Even more surprisingly, this high temperature was found for Marshall at an elevation of 862 m.
The authors conclude that five of the seven timeseries from South and Southwest Greenland indicate that the Holocene Thermal Maximum occurred between approx. 7000 and 5000 years BP. I note that Fredskild 1983 suggested that the warmest period in SW Greenland occurred from 7500 BP and the following millennia (The Holocene vegetational development of the Godthåbsfjord area, West Greenland. Meddelelser om Grønland, Geoscience 10, https://doi.org/10.7146/moggeosci.v10i.140322). I also note that Bennike et. al. 2010 suggested peak Holocene temperatures from c. 7000 to 6500 cal. years BP based on the occurrence of a warmth-demanding ostracode in lake sediments at the head of Kangerlussuaq (Holocene palaeoecology of southwest Greenland inferred from macrofossils in sediments of an oligosaline lake. Journal of Paleolimnology 43, 787–798
Specific comments:
Line 11, 41. early and middle-Holocene – these are formal units, I suggest to write Early and Middle Holocene
Line 11. Delete likely – it has been demonstrated in numerous studies.
Line 51. defined herein the region – change to: defined herein as the region
Line 51. I would change Nugaatsiaq (spelled Nuugaatsiaq on Fig. 1) to Nuussuaq. Nugaatsiaq is a small abandoned settlement, whereas Nuussuaq is a large, well-known peninsula.
Line 63-64: “reveals a Holocene thermal maximum (HTM) at ~7.9 ka which is temperature ~2.9 ± 1.4 °C warmer than the recent”. Rewrite
Also, strictly speaking, temperatures cannot be warm or cold – they can be high or low.
The high temperatures were recorded at 7960 ± 30 years B.P. – during a short-lived period. The period from 8000 to 6000 years BP shows declining temperatures – you may argue that the HTM is dated to 8000–7000 at Summit.
Line 65. change between ~6 to 4 ka to: between ~6 and 4 ka
Line 98 etc. I would expect some more notes on the setting in this chapter. Including some notes on ocean currents, air temperatures in the region and notes on the strong temperature gradient from the cold outer coast to the warm inland near the margin of the ice sheet. It would also be great if you can provide some data about measured lake water temperatures.
Line 363. katabatic winds are usually warm
Line 364 etc. Here you discuss the distance to the Greenland Ice Sheet. It should be distance to the margin of the ice sheet.
Line 433. The similarity between the GISP2 and Lake Marshall records is not great.
Line 444. both Comarum Sø and Kløft Sø are mis-spelled.
Line 448. The pollen-based temperature reconstruction from Qipisarqo lake is mainly based on Alnus pollen from Labrador.
Line 463. Not sure what you mean by this: due to low temporal resolution of the time series between 2 to 4 ka, anomaly period.
Fig. 1. You can argue that the East Greenland Current continues around Cape Farewell and a little up the coast of West Greenland. The region of locality 13 to 18 is strongly influenced in late summer by sea ice from the Arctic Ocean.
Fig. 3. The temperature record from GISP2 is “upside-down”, so that the 8.2 event appears visually as a warm period (temperatures ~ –34°C) and the HTM appears as a cold period.

Citation: https://doi.org/10.5194/egusphere-2025-3113-RC2
- AC2: 'Reply on RC2', Sudip Acharya, 23 Oct 2025
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3113/egusphere-2025-3113-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2025-3113-AC2

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

ED: Reconsider after major revisions (29 Oct 2025) by Francesco Muschitiello

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ED: Reconsider after major revisions (30 Jan 2026) by Francesco Muschitiello

ED: Reconsider after major revisions (03 Feb 2026) by Francesco Muschitiello

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Journal article(s) based on this preprint

29 Jul 2026

Holocene temperatures in southwestern Greenland controlled by topography, ice sheet proximity, and oceanic conditions

Sudip Acharya, Allison A. Cluett, Amy L. Grogan, Jason P. Briner, Isla S. Castañeda, and Elizabeth K. Thomas

Clim. Past, 22, 1401–1421, https://doi.org/10.5194/cp-22-1401-2026,https://doi.org/10.5194/cp-22-1401-2026, 2026

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Sudip Acharya, Allison A. Cluett, Amy L. Grogan, Jason P. Briner, Isla S. Castañeda, and Elizabeth K. Thomas

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https://doi.org/10.5194/egusphere-2025-3113-supplement

Sudip Acharya, Allison A. Cluett, Amy L. Grogan, Jason P. Briner, Isla S. Castañeda, and Elizabeth K. Thomas

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The study analyzed temperature-sensitive bacterial membrane lipids in Holocene Lake sediments from southwestern Greenland. Temperature maxima in five lakes occurred between 7000–5000 years ago, at a coastal site between 5000–3000 years ago, and at an inland site, far from the coast and the Greenland Ice Sheet, between 9000–7000 years ago. Local temperature variations, influenced by the ice sheet and ocean, likely caused discrepancies in the temperature time series.


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