the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Observed Evolution of Arctic Amplification over the Past 45 Years
Abstract. To address research gaps in understanding Arctic Amplification, we use data from ERA5 and sea ice concentration to examine the seasonal, spatial and decadal evolutuion of Arctic 2-meter and lower tropospheric temperatures and lower tropospheric (surface to 850 hPa) static stability over the past 45 years. A Local Amplification Anomaly (LAA) metric is used to examine how spatial patterns of Arctic 2-meter temperature anomalies compare to anomalies for the globe as a whole. Pointing to impacts of seasonally-delayed albedo feedback, growing areas of end-of-summer (September) open water largely co-locate with the strongest positive anomlies of 2-meter temperatures through autumn and winter and their growth through time; small summer trends reflect the effects of a melting sea ice cover. Because of seasonal ice growth, the association between rising 2-meter temperatures and sea ice weakens from autumn into winter, except in the the Barents Sea where there have been prominent downward trends in winter ice extent. Imprints of variable atmospheric circulation are prominent in the Arctic temperature evolution. Low-level (surface to 850 hPa) stability over the Arctic increases from autumn through winter, consistent with the greater depth of surface-based atmospheric heating seen in autumn. However, trends towards weaker static stability dominate the Arctic Ocean in autumn and winter, especially over areas of September and wintertime ice loss. Sea ice thinning, leading to increased conductive heat fluxes though the ice, likely also contributes to reduced stability.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-3690', Anonymous Referee #1, 07 Sep 2025
- RC2: 'Comment on egusphere-2025-3690', Anonymous Referee #2, 08 Sep 2025
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RC3: 'Comment on egusphere-2025-3690', Anonymous Referee #3, 16 Sep 2025
This is an interesting paper which explores the regional (or local) aspects of AA. Many studies will refer to the nature or impacts of Arctic change as a whole, but this manuscript delves a little deeper into the issue. The submission has the potential to make a significant contribution to the literature, but it is not quite there yet. Before I would be able to recommend acceptance, there are a number of issues which need to be addressed.
Lines 24 - : In this introductory survey and remarks it would be appropriate to mention the ‘PAMIP’ project …
Doug M. Smith, James A. Screen, Clara Deser, Judah Cohen, John C. Fyfe, Javier Garcia-Serrano, Thomas Jung, Vladimir Kattsov, … and Xiangdong Zhang, 2019: The Polar Amplification Model Intercomparison Project (PAMIP) contribution to CMIP6: Investigating the causes and consequences of polar amplification. Geoscientific Model Development, 12, 1139-1164, doi: 10.5194/gmd-12-1139-2019.
Line 39: ‘Graversen et al.’ should be ‘Graversen and Burtu’.
Line 45: Important additional rationale for this work is that the local characteristics of AA have broader implications. Beneficial here to support this by referencing study of Wenqin Zhuo, Yao Yao & co-authors, 2023: The key atmospheric drivers linking regional Arctic amplification with East Asian cold extremes. Atmosp. Res, 283, 106557, doi: 10.1016/j.atmosres.2022.106557 who demonstrate the AA regionality is important in producing very different remote influences, via teleconnection patterns, into the midlatitudes.
Line 73: Better to write as ‘2’ and ‘5’.
Line 80 (Figures): Showing the values of longitude at every 5 degrees makes these plots look unnecessarily busy. Much less frequent would be ample.
Also the headers on the plots should read ‘trend’ and not ‘change’
The caption reads … ‘Shading is used for trends significant at p<0.05’. This is confusing, especially as in the caption of Figure 2 the authors have (a better expression of) ‘Only trends significant at p<0.05 are shaded’. Be consistent and as clear as possible.
Line 85: The authors must explain how they performed the statistical significance test. An additional aspect on this is that the parameters discussed here have considerable memory (autocorrelation). This has the effect of reducing the ‘effective’ number of data points and hence reduces to degrees of freedom. Please to allow for this also – see approach of Christopher S. Bretherton, Martin Widmann, Valentin P. Dymnikov, John M. Wallace and Ileana Bladé, 1999: The effective number of spatial degrees of freedom of a time-varying field. Journal of Climate, 12, 1990-2009, doi: 10.1175/1520-0442(1999)012<1990:TENOSD>2.0.CO;2.
Line 143: The third and fourth entries into the first column of Table 1 should be ‘2000-2009’ and ‘2010-2019’.
Lines 175-180: An interesting argument is made here. Note that in the three later decades shown in Figure 4 the AA over Eurasia is prominently negative. This ties in neatly with the Warm arctic-cold Eurasia (WACE) phenomenon (refence here Li, M., et al., 2021: Anchoring of atmospheric teleconnection patterns by Arctic Sea ice loss and its link to winter cold anomalies in East Asia. Int. J. Climatol., 41, 547–558). In line with the authors’ comments here regarding the impact of the phase of the North Atlantic Oscillation in the earlier period, studies have shown that in more recent times other large-scale modes (such as
Interdecadal Pacific Oscillation and the Atlantic Multidecadal Oscillation) have influenced the nature of the WACE pattern (see …
Luo, et al., 2022: The modulation of Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation on winter Eurasian cold anomaly via the Ural blocking change. Climate Dyn., doi: 10.1007/s00382-021-06119-7 and
Luo, B., D. Luo, and coauthors, 2022: Decadal variability of winter warm Arctic-cold Eurasia dipole patterns modulated by Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation. Earth's Future, 10, e2021EF002351, doi: 10.1029/2021EF002351). The paper will benefit from a more incisive argument along these lines on the structure of the Fig. 4 plots.
Line 183 (Figure 3): Figs. 3 and 4 present much more information than does Table 1. Perhaps consider deleting the Table as it contains lots of number. If you follow that, maybe also here show LAA Figs. covering spring and summer.
Also suggest ‘LAA’ rather than ‘AA’ in the headings of the sub-plots.
Line 207: Support this point by also referencing Lee S, Gong T et al. (2017) Revisiting the cause of the 1989-2009 Arctic surface warming using the surface energy budget: Downward infrared radiation dominates the surface fluxes. Geophys. Res. Lett. 44: 10,654–10,661 doi: 10.1002/2017GL075375.
Lines 234-5: Why just October and December, when up till now you have been considering SON and DJF?
Line 251: Paper has been using ‘deg C’ up to here, and now ‘K’. Please revert to deg C here in the subsequent occurrences.
Line 271 (Heading on Figures): Please to change ‘mb’ to ‘hPa’. (Similar for Figure 9).
Lines 276-286: reinforce these arguments by referencing paper of Simmonds et al. (2021 - Trends and variability in polar sea ice, global atmospheric circulations, and baroclinicity Ann. NY Acad. Sci. 1504 167-86) showing strong decreases in the Brunt–Vaisalla frequency over the Artic and its broader region.
On this issue the B-V frequency is more strongly connected to the (thermo)dynamics than is ‘delta theta’. It also contains a ‘1/theta’ term which highlights the impact in the colder regions. Some words on this are warranted here.
Lines 302-303: Valuable to mention in text here that Xin Wang and Jinping Zhao used three data sets, namely NCEP-R2, ERA5, and JRA-55, to make it explicit that ERA5 (as used here) was one of the sets.
Lines 412-413: Please to include full bibliographic details (volume, article number, …) here …
Liu Y, Zhang J (2025) Conductive heat flux over Arctic sea ice from 1979 to 2022. J. Geophys. Res. 130: e2024JC022062 doi: 10.1029/2024JC022062.
Lines 446-7: Reference is repeated. From context, I suspect authors meant to make Screen JA, Simmonds I (2010) Increasing fall-winter energy loss from the Arctic Ocean and its role in Arctic temperature amplification. Geophys. Res. Lett. 37: L16707 doi: 10.1029/2010GL044136 as ‘part b’.
More missing details in References …
Stroeve, J. C., Markus, T., Boisvert, L., Miller, J. and Barrett, A. 2014. 'Changes in Arctic melt season and implications for sea ice loss', Geophys. Res. Lett. 41, 1216-1225, doi: 10.1002/2013gl058951,
Stroeve, J. and Notz, D. 2018. Changing state of Arctic sea ice across all seasons. Env. Res. Lett. 13, 103001. DOI: 10.1088/1748-9326/aade56. …
Please to check all reference informations carefully.
Citation: https://doi.org/10.5194/egusphere-2025-3690-RC3
Data sets
ERA5 Reanalysis (0.25 Degree Latitude-Longitude Grid) European Centre for Medium-Range Weather Forecasts https://doi.org/10.5065/BH6N-5N20
Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 2 N. E. DiGirolamo et al. https://nsidc.org/data/nsidc-0051/versions/2
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General Comments:
This study provides an overview on the seasonal and long-term change in Arctic amplification (AA) over the last several decades using ERA5 reanalysis and satellite-derived sea ice data. The authors introduce a metric called the “Local Amplification Anomaly” (LAA), which is used to diagnose how Arctic near-surface temperatures are changing relative to the global average on a point-by-point basis. In addition to this, they look at changes in low-level stability over the Arctic, again through season and time. Overall, this study highlights the tightly coupled and complex set of relationships between sea ice melt/growth, upper ocean heat accumulation, and near-surface AA ratios, with a focus on the importance of considering these interactions depending on the season.
Overall, the methods and results are logical, and the paper is particularly well-written. The authors did a great job in describing AA in very clear and concise language. I just have some additional thoughts, questions, and comments below, which I hope are useful in the revision process.
Specific Comments:
Technical Comments:
Figures/Tables:
Reviewer’s References:
Esau, I., Pettersson, L. H., Cancet, M., Chapron, B., Chernokulsky, A., Donlon, C., ... & Johannesen, J. A. (2023). The arctic amplification and its impact: A synthesis through satellite observations. Remote Sensing, 15(5), 1354.
Henderson, G. R., Barrett, B. S., Wachowicz, L. J., Mattingly, K. S., Preece, J. R., & Mote, T. L. (2021). Local and remote atmospheric circulation drivers of Arctic change: A review. Frontiers in Earth Science, 9, 709896.
Previdi, M., Smith, K. L., & Polvani, L. M. (2021). Arctic amplification of climate change: a review of underlying mechanisms. Environmental Research Letters, 16(9), 093003.
Taylor, P. C., Boeke, R. C., Boisvert, L. N., Feldl, N., Henry, M., Huang, Y., ... & Tan, I. (2022). Process drivers, inter-model spread, and the path forward: A review of amplified Arctic warming. Frontiers in Earth Science, 9, 758361.
Tian, T., Yang, S., Høyer, J. L., Nielsen-Englyst, P., & Singha, S. (2024). Cooler Arctic surface temperatures simulated by climate models are closer to satellite-based data than the ERA5 reanalysis. Communications Earth & Environment, 5(1), 111.
Wang, C., Graham, R. M., Wang, K., Gerland, S., & Granskog, M. A. (2019). Comparison of ERA5 and ERA-Interim near-surface air temperature, snowfall and precipitation over Arctic sea ice: effects on sea ice thermodynamics and evolution. The Cryosphere, 13(6), 1661-1679.
Yu, Y., Xiao, W., Zhang, Z., Cheng, X., Hui, F., & Zhao, J. (2021). Evaluation of 2-m air temperature and surface temperature from ERA5 and ERA-I using buoy observations in the Arctic during 2010–2020. Remote Sensing, 13(14), 2813