the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Jun 2026
Simulating the permafrost thermal regime in the Northwestern Antarctic Peninsula from 1950 to 2100
Abstract. Permafrost underlies most of the Antarctic ice-free areas, being crucial for terrestrial ecosystems, influencing pedogenesis, hydrology, geomorphic dynamics, and the carbon biogeochemical cycle. However, uncertainty in the evolution of permafrost temperature is particularly relevant in the Antarctic Peninsula, a climatic hotspot of the continent where an increase in mean annual air temperature of 3.4 ± 1.2 °C has been recorded, together with a rise in both the frequency and intensity of warm-weather episodes. The impact on permafrost is difficult to foresee, due to a scarce monitoring network implemented following the International Polar Year in 2007–2008, with limited temporal coverage that constrains trends evaluation. In this study, we simulate past and future permafrost temperature evolution in the Northwestern Antarctic Peninsula using the CryoGrid Community Model at five permafrost observatories from the University of Lisbon’s network (PERMANTAR). Simulations forced with ERA5 reanalysis reconstruct ground temperature evolution since 1950, revealing a warming trend at all depths, with mean annual ground surface temperature, temperature at the top of permafrost, and mean annual ground temperature warming at rates between 0.19 and 0.29 °C dec⁻¹. Four distinct periods are identified since 1950: early sustained warming (1950–1975), highly variable warming and cooling (1975–2000), a short cooling period with increased snowfall (2000–2015), and intense warming after 2015 that accelerates permafrost temperature increases at 20 m depth, resulting in mean annual ground temperatures above -2 °C. Future projections using the ACCESS‑CM2 model under SSP1‑2.6, SSP2‑4.5, and SSP5‑8.5 reveal progressive permafrost degradation and a widespread transition to positive mean annual ground temperatures at 20 m depth during the 21st century, with timing and magnitude strongly influenced by elevation, snow cover duration, and local changes in ocean–atmosphere interactions. In the SSP1-2.6, warming rates ranging from 0.21 ± 0.01 to 0.23 ± 0.01 °C dec⁻¹ are predicted for the sites, resulting in extensive permafrost degradation at low altitude. Under SSP2‑4.5, all sites are projected to develop positive mean annual ground temperatures at 20 m between 2049 and 2087, with warming rates ranging from 0.31 ± 0.01 to 0.43 ± 0.01 °C dec⁻¹, implying increased permafrost degradation and increased susceptibility of coastal terrestrial ecosystems in the Northwestern Antarctic Peninsula to climate-driven change. Under the SSP5-8.5, with warming rates between 0.46 ± 0.01 and 0.62 ± 0.01 °C dec⁻¹, the degradation of permafrost is predicted to occur more rapidly, with positive mean annual ground temperature values at 20 m reached between 2045 and 2071. The projected warming and associated permafrost loss will change surface and subsurface hydrology, biochemical fluxes and geomorphological processes, impacting the sensitive terrestrial ecosystems.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-1914', Tomáš Uxa, 28 Jul 2026
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RC2: 'Comment on egusphere-2026-1914', Tomáš Uxa, 28 Jul 2026
Of course, the list of useful references in my review omits Kaplan Pastíriková et al. (2023), so I am adding it separately.
Kaplan Pastíriková, L., Hrbáček, F., Uxa, T., Láska, K., 2023. Permafrost table temperature and active layer thickness variability on James Ross Island, Antarctic Peninsula, in 2004–2021. Science of the Total Environment, 869, 161690. https://doi.org/10.1016/j.scitotenv.2023.161690
All the best,
Tomáš Uxa
Citation: https://doi.org/10.5194/egusphere-2026-1914-RC2 -
RC3: 'Comment on egusphere-2026-1914', Anonymous Referee #2, 30 Jul 2026
This manuscript applies CryoGrid to reconstruct and project ground temperatures at five observatories in the northwestern Antarctic Peninsula. The study is timely, the observational network is valuable, and the comparison among sites could make a useful contribution. However, several aspects of the model evaluation and future projections should be clarified before the main conclusions can be assessed with confidence. I therefore recommend major revision.
1) It appears that the snowfall multipliers and some subsurface parameters were adjusted using the same ground-temperature observations later used to evaluate model performance. If so, Table 3 represents calibration performance rather than independent validation. Please specify the calibration and evaluation periods, observations, and depths used at each site. I would recommend a split-sample or leave-one-year-out evaluation, together with the parameter ranges and selection criterion. Agreement at 0.4 m should not be presented as independent model skill if that depth was used to determine the snowfall multiplier.
2) The projections depend on one CMIP6 model and apparently one random realization of the monthly carrier sequence. ACCESS-CM2 was selected partly because it reproduces the ERA5 trend, although another candidate has smaller MAE and RMSE. This does not necessarily demonstrate that ACCESS-CM2 provides the most credible future regional warming. Please show how model selection and carrier sampling affect the main results. Ideally, the authors should include projections from the other candidate models and several carrier realizations. If this is not feasible, the results should be described as ACCESS-CM2-driven sensitivity experiments, and threshold crossings should be reported by approximate decade or as ranges rather than as exact years.
Section 3.5 also needs clarification. Please verify Equation (2) against the implemented code and explain whether the same sampled month was used for all forcing variables. Otherwise, covariance among temperature, humidity, precipitation, wind, and radiation may not be preserved.
3) The manuscript frequently interprets positive mean annual ground temperature at 20 m as the disappearance of permafrost. I would avoid treating these as equivalent. A positive annual mean at one depth does not establish the thermal state of the full profile or whether permafrost persists above or below that level. Please define the criterion used to diagnose permafrost degradation and distinguish it from the year when MAGT at 20 m becomes positive. If possible, provide active-layer thickness and talik diagnostics from the complete simulated profile. Otherwise, “permafrost loss” should be replaced by the more precise phrase “positive MAGT at 20 m”. Active-layer thickness should also be removed from the title of Section 4.3 unless the corresponding results are presented.
Other comments:
Abstract, lines 14-15: Replace “constrains trends evaluation” with “constrains the evaluation of trends.”
Abstract: Please state clearly that the final projections are based on one CMIP6 model. Also avoid wording that equates positive MAGT at 20 m directly with complete permafrost loss.
Line 50: Remove the unnecessary parentheses around “Obu et al. (2020).”
Lines 58-60: “Recommended Concentration Pathway” should be “Representative Concentration Pathway.” More importantly, CMIP6 scenarios are SSP-based and should not be presented as predictions.
Section 2.1: The heading uses “Western Antarctic Peninsula,” whereas the rest of the manuscript refers to the “northwestern Antarctic Peninsula.” Please standardize the geographical terminology and capitalization.
Line 73: Replace “divided in two” with “divided into two.”
Line 76 and elsewhere: Replace “Thomas e Tetzner 2019” with “Thomas and Tetzner (2019).”
Line 97: “measured at King Sejong Station.”
Table 1: “Measurement height/depth” combines height above the surface and depth below it. Please separate these quantities or use a clear signed convention.
Lines 193-196: Air temperature appears to be missing from the ERA5 variable list. Dew-point temperature is listed, whereas CryoGrid uses specific humidity; please explain the conversion.
Table 2: Please provide units for MAE and RMSE and specify the sampling frequency and evaluation period. The meaning of the reported p-value should also be defined, considering temporal autocorrelation.
Lines 246-250: Please clarify whether monthly CMIP6 data were used and standardize the variable names and units. Specific humidity should be reported in kg kg⁻¹ rather than as dimensionless.
Line 257: The description of the vertical model resolution is unclear. Please state explicitly the grid spacing above and below 5 m depth.
Section 3.5: In addition to the issues raised above, all symbols in Equations (2) and (3) should be defined consistently, and the ERA5 and CMIP6 terms should be distinguishable.
Table 3: Please define whether mineral and water/ice contents are volume fractions and provide units, sample sizes, and evaluation periods for the performance statistics.
Figure 2: The caption should define the box, whisker, and outlier conventions and give the observation period for each site.
Section 4.2 and Figure 3: These give different historical periods. More generally, please check all analysis periods, as the manuscript alternates among 1950–2020, 1950–2022, 2020–2100, and 2022–2100.
Figure 3: Please define the SWE statistic. For example, whether it represents an annual mean, maximum, or another quantity. The caption should also be revised because it groups air temperature and snowfall under “ground temperatures.”
Figure 4: This appears to show five point simulations rather than a spatially continuous estimate. Please revise the figure or caption accordingly. The use of the single year 1950 as a baseline should also be justified, particularly if it was exceptionally cold.
Results and Discussion: Please distinguish clearly between total temperature changes in °C and trends in °C decade⁻¹. Each value should have a clearly defined reference period.
Results, Discussion, and Conclusions: Several threshold years differ among the abstract, Results, Discussion, and Conclusions. I suggest generating all threshold years from one summary table and using them consistently throughout.
Section 4.3: Active-layer thickness should be removed from the section title unless the corresponding results are presented.
Figure 8: Figure 8 is cited, but no Figure 8 is included. Please identify the intended figure.
Table 5: The caption should reflect that the table includes MAAT and MAGST as well as MAGT at 20 m. Please also use uppercase “SSP” consistently.
Figure 5: Please identify the transition from ERA5 to synthesized ACCESS-CM2 forcing and define the line colors in the caption.
Figure 6: Please use the complete scenario names SSP1-2.6, SSP2-4.5, and SSP5-8.5.
Discussion: Some explanations involving the Amundsen Sea Low, sea-ice changes, and snow effects are presented causally without direct supporting analysis. Please provide the relevant diagnostics or present these mechanisms as possible explanations.
Conclusions: Please verify statements such as “most observatories” against the site-specific results. Wider implications involving thermokarst and slope instability should also be presented as possible consequences rather than direct model results, particularly because most sites are represented as bedrock with little ground ice.
Appendix C: The text refers to Table A1, but this appears to be Table C1.
Table C1: Please use the official CMIP6 model identifiers consistently. The IPSL model appears in different forms, including IPSL-CM6A, IPSL-CM6-A, and IPSL-CM6A-LR.
Appendix E: Its title gives 2022–2100, whereas the associated analysis also uses 2020–2100. Please standardize the period.
Code and data availability: Please provide the exact CryoGrid version, release, or commit used. The processed forcing, parameter files, carrier realization or ensemble, and relevant scripts should also be made available in a persistent repository to ensure reproducibility.
Citation: https://doi.org/10.5194/egusphere-2026-1914-RC3 -
RC4: 'Comment on egusphere-2026-1914', Anonymous Referee #3, 05 Aug 2026
General comments
I found this manuscript timely and potentially valuable. It uses the CryoGrid Community Model to reconstruct and project ground thermal conditions at five PERMANTAR observatories in the northwestern Antarctic Peninsula, combining rare borehole observations with ERA5 and ACCESS-CM2 forcing. The observational basis is important for a region where long ground-temperature records remain scarce, and the comparison among sites could make a useful contribution to Antarctic permafrost research.
At the same time, I am not yet persuaded that the present analysis supports the precision and spatial scope of several of the main conclusions. Principal concerns relate to the distinction between calibration and independent model evaluation, the treatment of uncertainty in snow and subsurface parameters, and the reliance on a single CMIP6 model. A positive mean annual ground temperature at 20 m is sometimes discussed as if it demonstrated complete permafrost loss, even though most boreholes are shallower than 20 m and observed permafrost was not reached in three of them. The extent to which five bedrock sites represent the wider range of ice-free coastal terrain also needs to be considered more explicitly.
On this basis, I recommend major revision. In my view, the paper would be considerably stronger if the authors documented the observational and modelling workflow more fully, evaluated the principal sources of uncertainty, and narrowed some of the claims concerning permafrost degradation and regional impacts.
Specific comments
1. I understand the practical reason for selecting relatively deep boreholes in bedrock and thereby reducing site heterogeneity. Nevertheless, this choice also limits the environments represented by the study. I would like the authors to explain how far these five sites can reasonably represent the ice-free areas of the northwestern Antarctic Peninsula. In particular, are unconsolidated marine terraces, glacial deposits, colluvium, or ice-rich sediments largely absent from the selected network? If so, this should be stated clearly before the point simulations are extended to coastal landscapes or used to discuss thermokarst, slope instability, and infrastructure exposure.
2. It’s difficult to reconstruct the observational basis for each simulation from the information distributed between the main text and the appendices. A single site-characteristics table would be helpful. It should include logger type and accuracy, monitored depths, observation periods and gaps, slope aspect and inclination, surface and subsurface material, vegetation or organic cover, and available information on local snow conditions.
It is also unclear which air-temperature observations were used to correct ERA5 at Amsler, where the local air-temperature logger appears to have been installed only in 2023.
3. As I understand the workflow, at least some subsurface parameters and the snowfall multipliers were selected by comparing simulations with the same ground-temperature records that were later used to report model performance. If it is correct, those statistics describe goodness of fit after calibration rather than performance against independent data, and they are likely to be optimistic.
Please separate calibration and validation periods, or apply a suitable temporal cross-validation procedure. Performance metrics should be presented independently for both periods. The duration and number of observations used at each site and depth should also be reported.
4. I could not determine the full parameter space explored during calibration. Please report the tested ranges, increments, and selection criterion for mineral, organic, water, and ice fractions and for thermal conductivity. At line 155, the manuscript states that the sum of water and ice contents remains constant, but the value at which it is held constant is not defined.
It would be useful to distinguish parameters supported by direct observations from parameters inferred through fitting. Were porosity, fracture density, water or ice content, and related properties documented during drilling or measured on cores? If not, the adopted values should be treated as uncertain parameters rather than physically validated site properties. A sensitivity or ensemble analysis is required to assess parameter equifinality.
5. What is the basis for applying the same geothermal heat flux of 50 mW m⁻² at all five sites, and how deep is the lower model boundary? Is this value supported by regional measurements or previous studies? Since the principal results concern temperature at 20 m, sensitivity to geothermal heat flux, domain depth and initial temperature profile should be evaluated.
6. The boreholes are only 4–15 m deep, whereas the main projections concern MAGT at 20 m. At several sites, the calculated temperature at 20 m is therefore well outside the observed depth interval. The associated uncertainty should be explicitly quantified.
Positive MAGT at 20 m should not automatically be equated with complete permafrost loss. Please define the diagnostic criterion used to determine the presence or absence of permafrost. The manuscript should distinguish between: positive MAGT at a specified depth; loss of permafrost at that depth; active-layer deepening; and complete disappearance of the permafrost body.
Regional statements about widespread permafrost loss should be revised accordingly.
7. Snow is interpreted as a major control on differences among sites, but the snowfall multiplier was calibrated indirectly against ground temperature. Are any field observations of snow depth, snow-cover duration, or snow water equivalent available? If not, independent remote-sensing or photographic evidence should be considered.
The assumption of a constant multiplier of 0.3 or 0.5 throughout the future simulation also requires justification. Future changes in precipitation phase, wind redistribution, and snow duration may alter the relationship between large-scale precipitation and local accumulation. At minimum, the sensitivity of the projections to the snowfall multiplier should be shown.
8. The phrase “adequate data to force the CCM” should be defined more precisely. Please state which required variables, temporal resolutions, ensemble members, and experiments were available for each CMIP6 model.
ACCESS-CM2 is selected mainly because its MAAT trend and variability resemble ERA5 at Papagal. The evaluation should include all five sites and the forcing variables most relevant to the surface energy balance, especially precipitation, radiation, and wind.
Projections based on one GCM cannot represent the full climate-model uncertainty.
9. I found the construction of the submonthly forcing difficult to follow. When a historical ERA5 month is sampled as the carrier, are all meteorological variables taken together from the same month and year, or are variables sampled separately? The former is important for retaining covariance among temperature, humidity, precipitation, wind, and radiation.
The random carrier sequence is itself a source of uncertainty. I would expect different admissible sequences to produce some spread in annual ground temperatures and in the estimated timing of threshold crossings. Several realisations should be generated and propagated through the analysis, with the random seed and sampling procedure documented.
10. I could not find a description of the statistical method used to estimate temperature trends or the uncertainty reported after the ± sign. Please state the regression method, confidence level and significance criterion.
The four historical periods appear to have been selected visually. Either apply an objective change-point or segmented-regression method, or describe these intervals explicitly as qualitative periods. Decadal rates calculated for the short 2015–2022 interval should be interpreted cautiously.
11. I agree that elevation, snow persistence, wind exposure, sea-ice decline, and changes in the Amundsen Sea Low are plausible explanations for the simulated contrasts. However, the present experiments do not isolate their individual effects. Unless additional factorial simulations or atmospheric indices are analysed, the language should be changed from causal statements to cautious interpretations such as “may be associated with” or “is consistent with”.
12. Please cross-check the abstract, Results, Discussion, Table 5, and Conclusions. There are inconsistencies in the reported years when MAGT becomes positive and in the use of “warming” versus “warming rate”. For example, values such as 0.59, 2.59, and 5.05 °C appear to represent total changes by 2100 in some places but are described as rates elsewhere.
The statement that positive MAGT occurs at most sites by 2045 under SSP5-8.5 is also not consistent with the site-specific results. The title of Sect. 4.3 refers to active-layer thickness, but active-layer results are not presented.
Technical corrections
At first use, spell out CryoGrid Community Model (CCM), and then use the abbreviation consistently.
The manuscript uses “Recommended Concentration Pathways”; this should be corrected.
Please standardise units and notation, including °C decade⁻¹, W m⁻¹ K⁻¹, and m a.s.l.
TTOP needs a precise definition, including how it is diagnosed from the model output and how it is interpreted at sites without confirmed permafrost within the borehole.
Replace “biochemical fluxes” with “biogeochemical fluxes”.
Increase the font and panel size in Figs. 2, 3, 5, and D1. Several time series and legends are difficult to read.Citation: https://doi.org/10.5194/egusphere-2026-1914-RC4
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- 1
This is an important and timely contribution on the recent past and future ground temperature dynamics in the Northwestern Antarctic Peninsula. Not only is there no similar study to date, but the numerical modelling approach used is novel in Antarctica. However, I have several comments and recommendations that should be addressed before the manuscript can be considered for publication.
(1) The simulation of recent past conditions was based on the bias-corrected ERA5 for 1950–2020 (with 10 spin-up loops in 1940–1949). By contrast, the simulation of future conditions was based on the bias-corrected CMIP6 models for 1850–2100, with 10 spin-up loops in 1850–1860 and bias-corrected ERA5 used in 1940–2022. Why did not you apply the modelling strategy used for future to recent past as well? The 100-year model initialization phase running since 1850 would likely be better than the 10 spin-up loops over 1940–1949. Moreover, this would mean better consistency and less work since you would have single time series covering the whole period 1850–2100 and both recent past and future scenarios.
Additionally, was the CMIP6 bias correction based on the bias-corrected ERA5? This is unclear to me.
(2) Considering that you did the bias correction only in the case of air temperature, while the rest of the variables retained their uncorrected values, is the resulting dataset internally consistent? For instance, if the air temperature was corrected, while the dew point temperature remained uncorrected, this may affect outputs calculated from these two variables. Likewise, precipitation retained its uncorrected value, but solid and liquid precipitation usually occurs at some specific temperatures, which can also be affected if the temperature is corrected. I have no idea how this might affect the simulation outputs, but the issue is here obvious.
(3) In the methods, explain why you modelled ground temperatures specifically at a depth of 20 m. Frequently, you also present ground temperatures from a depth of 10 m, which is much closer to a maximum depth of the boreholes and might therefore have a higher validity. Was this because that is at or below the depth of zero annual amplitude?
(4) For consistency, descriptions of both recent past and future simulations should present the evolution of mean annual air temperatures, mean annual ground surface temperatures, temperatures at the base of the freeze-layer layer (TTOP under permafrost conditions), and mean annual ground temperatures at a depth of 20 m. Some of these temperature metrics are frequently missing, which makes a little sense in terms of consistency and (not only) mutual context. If mean annual ground temperatures at a depth of 10 m are shown as well, I would present them before those from 20 m. Because of heat diffusion, the temperature patterns at 10 m precede those at 20 m, so it would have more logic to proceed in this order.
(5) The discussion is relatively short and in principle deals with results of this study alone, and the context of other studies is provided to a very limited extent. While I am aware that there is currently no analogous study published for Antarctica, there are several studies that assessed short-term trends in permafrost temperatures or active-layer thickness (e.g., Guglielmin and Cannone, 2012; Ramos et al., 2017; Biskaborn et al., 2019; Hrbáček and Uxa, 2020; Hrbáček et al., 2021, 2023, 2025; Baptista et al., 2025) or some several long-term meteorological series (e.g., Oliva et al., 2017). I do not understand why you do not mention your previous study in the discussion (Baptista et al., 2025).
What I also miss in the discussion is a section devoted to the evaluation of the ERA5 and CMIP6 models used as model forcings. Consequently, I would move the Appendix C into the discussion. You may also refer to Baptista et al. (2025) or Kaplan Pastíriková et al. (2025) when evaluating the suitability of ERA5 or reananalyses for permafrost studies in Antarctica in general.
(6) Consider carefully whether the content of the appendices really needs to placed in them. I think that most of the appendices could be involved in the main body of the manuscript without making it fragmented.
Specific comments:
P1L13: State the period over which the mean annual air temperature increase of 3.4±1.2 °C was recorded.
P1L18: Specify the depth for the mean annual ground temperature. Is it 20 m?
P1L20: In contrast to the above, it is unnecessary to specify the depth of 20 m here because it is a general statement.
P2L42–43: Again, state the period over which the mean annual air temperature increase of 3.4±1.2 °C was recorded. Considering that mean annual air temperature can exhibit substantial variations from year to year, is it appropriate to use a single year as a baseline value?
P2L50: Change (Obu et al., 2020) to Obu et al. (2020).
P2L57–58: In the aims of the manuscript, be specific and clearly define the time frames for both the recent past and the future modelling periods.
P3L61–62: This previous study (Babtista et al., 2025) should be briefly described before the aims of the manuscript, so that the objectives follow logically from it. I think that, in this case, it disrupts the structure of the paragraph devoted to the aims.
P3L76: Change (Thomas e Tetzner 2019) to (Thomas and Tetzner 2019).
P4L96: Considering the substantial warming trend, the mean annual air temperature could be reported for a shorter, more recent period to better represent current climatic conditions. Of course, this depends on your intentions.
P5L100–101: Rewrite the sentence “… the highest areas of Hurd Peninsula were deglaciated at 20 ka with most high interfluves becoming ice-free around 14-16 ka …” so that it is clear when these locations were actually deglaciated. Was it at 20 ka or around 16-14 ka?
P5L101: Change 14-16 ka to 16-14 ka.
P5L106: State the period for which the mean annual air temperature and mean annual precipitation are reported.
P5L115–116: State the period for which the mean annual air temperature and mean annual precipitation are reported.
P5L124–125: State the period for which the mean annual air temperature and mean annual precipitation are reported.
P6L127–140: Move the whole section 3.1 to the section 2.2. The details on permafrost temperature and active-layer thickness at individual sites can be presented in the sections 2.2.1 to 2.2.4.
P7L151–152. This sentence on the calibration strategy is difficult to understand. Rewrite it even though it is partly obvious from the following text.
P7L156: What is the geothermal heat flux of 50 mWm^-2 based on? Please cite the source.
P7L157: What does the phrase “With the structure set, …” mean?
P7L160: Is the supplement “… using a probe.” necessary?
P7L164: What do you mean by “relative volume fraction” here?
P7L171: Indicate that Fub(t) is the energy flux into the uppermost grid cell. The rest of the variables (radiation and heat fluxes) would be better to describe after Eq. (1).
P7L175: “The heat conduction based on Fourier’s law is the main mode of heat transport in the subsurface.” is too brief description of the subsurface heat transfer.
P8L183: Change “phenomenologically” to “phenomenological”.
P8L186: State also that you calculated p-value.
P9L219: I guess there should be “SPPs” in “The RCPs are used to represent 4 pathways…”
P10L230: Note that the SPP5-8.5 scenario is now considered an extreme case that is rather implausible. You should point this out in the manuscript (here and in the discussion).
P10L235: Remove the word “models”.
P10L243–245: Place this paragraph at the end of the whole section 3.3.2.
P10L253: I would remove “…in the selected PERMANTAR monitoring sites.” because it is redundant here.
P11L258: The vertical resolution of the model is unclear from this: “… from 0.05 to 0.5 m, below 5 m depth.” Revise it.
P11L259: Specify the depths at which you calculated the mean annual ground temperature.
P11L266–269: Rewrite this so it is more clear that you bias-corrected the period 1850–2100 from CMIP6 using the statistical relationships with ERA5 for the sub-period 1940–2020.
P12L300: Remove the sentence “In the figures, the x-axis spans the period 2000-2100.”
P13L326: In Table 3, you should indicate that the thermal conductivity relates to the rock.
P14L354: In Fig. 2, the range seems to be somewhat smaller than -5 to 5 °C.
P16L364–380: In addition to the trends, present also the temperatures or their ranges. This is only done at three stations for TTOP and at all of them for MAGT. Report also the values and trends from the mean annual air temperature (and maybe snowfall if both are shown in Fig. 3).
P16L381: In Table 4, specify the depth for the mean annual ground temperature.
P17L385: Fig. 3 has a misleading caption because snowfall and air temperature cannot be referred to as ground temperatures.
P18L388: In Fig. 4, I think it is a bit misleading to present the temperature for a single year 1950 because it was exceptionally cold. Is it appropriate to use a single year here, at least for the mean annual ground surface temperature, which has an instantaneous response to air temperature?
P18–19L391–416: Check that it is clearly stated everywhere what temperature the reported trends refer to.
P18L409: Rewrite the sentence “Despite continued interannual air temperature variability, MAGST fluctuated between -4 to -1 °C.” which does not make complete sense.
P19L412: It is unclear what temperature the trend of 2.10±0.60 °C refers to.
P19L423: You should rather write for 2020–2100. Trends should always refer to a period, not a single year. Additionally, it is unclear what the temperature trend of 0.59±0.22 °C refers to.
P20L427: Change “… being the warming more pronounced at the …” to “… with more pronounced warming at the…”
P20L429: Remove “For most of the observatories, “ Then, the sentence will make more sense.
P20L434–437: Maybe move this paragraph before the previous one. Definitely, it is better to start with the statement that all stations host permafrost at present, and then describe that it will warm and likely degrade or disappear at some of them.
P20L439: Again, it is unclear what the first trend of 2.59±0.20 °C refers to.
P21L469–470: Change “At Cierva despite a warming rate of 0.51 ± 0.01 °C.dec-1 positive MAGT is projected…” to “At Cierva, despite a warming rate of 0.51 ± 0.01 °C.dec-1, positive MAGT is projected…”
P21L476: Table 5 has a misleading caption because it presents other temperature variables in addition to the mean annual ground temperature at 20 m.
P22L480: Fig. 5 has a misleading caption because air temperature cannot be referred to as ground temperature.
P24L505–509: The interpretation that ground temperature warming in the periods 1950–1975 and 2015–2020 was favoured by decreased snowfall and shorter duration of the snow cover contradicts former explanations that thicker and longer snow cover tends to warm the ground. Likewise, cooling simulated for 2000–2015 is difficult to explain by reduced snowfall.
P24L513–514: Remove the first sentence in the section 5.2; it is redundant.
P24L516: Why are the periods 2000–2015 and 2016–2022 discussed in the section entitled “Future evolution of permafrost temperature (2022 - 2100)”?
P25L532: Change “Under the more optimistic SSP1-2.6 scenario, …” to “Under the SSP1-2.6 scenario, …”
P25L539: Add “with values ranging from 1 to 2 °C in 2100.”
P26L557: Specify to what depth the bias refers to.
P26L574: Change “In the worst-case scenario (SSP5-8.5), …” to “Under the SSP5-8.5 scenario, …”
P27L582: Change “thermokarst and landslide activity should increase” to “thermokarst and landslide activity will likely increase”
P31L666: Change “An historical period …” to “A historical period …”
P31L674: Change “improved coupled between” to “improved coupling between”
P31L679: Change “a RMSE of 1.33 °C. and a standard deviation” to “a RMSE of 1.33 °C and a standard deviation”
References
Baptista, J., Brito Guapo Teles Vieira, G., Manuel De Carvalho Soares Correia, A., Lee, H., Westermann, S., 2025. Modelling the evolution of permafrost temperatures and active layer thickness in King George Island, Antarctica, since 1950, The Cryosphere, 19, 3459–3476, https://doi.org/10.5194/tc-19-3459-2025
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All the best,
Tomáš Uxa