Kilometer-scale distributed temperature sensing reveals heterogeneous permafrost warming near Arctic infrastructure
Abstract. Accelerated Arctic warming is destabilizing permafrost, threatening ecosystems, infrastructure, and northern communities, yet permafrost thermal dynamics remain poorly characterized and highly uncertain due to sparse observations and limited representation of fine-scale heterogeneity. Here we combine kilometer-scale distributed temperature sensing (DTS) with data-driven hysteresis modeling to resolve spatiotemporal variability in permafrost temperatures across disturbed and undisturbed Arctic landscapes near Utqiaġvik, Alaska. A 2-km fiber-optic array recorded continuous ground temperatures from 2021 to 2024, revealing persistent warming associated with civil infrastructure and pronounced thermal heterogeneity in patterned tundra. Ice-wedge polygon troughs consistently exhibit lower temperatures than polygon centers, highlighting the role of subsurface ice distribution in controlling ground thermal regimes. Using these observations, we develop a multivariate hysteresis model that captures lagged ground–air temperature responses and incorporates snow, precipitation, wind, atmospheric pressure, and ground surface conditions. The model accurately reproduces observed permafrost temperatures, fills observational gaps, and enables projections under future climate scenarios. Projections indicate continued warming through 2075, with enhanced temperature increases in infrastructure areas and ice-rich terrains. Our results demonstrate the power of DTS to resolve permafrost thermal heterogeneity at unprecedented scales and provide a transferable framework for predicting permafrost temperature dynamics in a rapidly warming Arctic.
Great paper! Minor feedback.
Abstract: Concise, well written. Excellent to see such a long term study. Ready to read the paper.
86-88 – Well set up to describe the novel data set and analysis presented in this paper.
99-100 – “A defining feature…” citation?
102-105 – “Although hysteresis has been recognized in observational and modeling studies, it is often treated implicitly rather than incorporated explicitly…” – Any more recent citations on this than 2003? Modeling has changed a lot.
109-111 – “A 2-km fiber-optic DTS array recorded continuous ground temperatures from 2021 to 2024 across civil infrastructure, non patterned tundra, and ice-wedge polygon terrain.” – AWESOME
117-119 – “The model reproduces observed permafrost temperatures, fills observational gaps, and enables projections of future ground temperatures under climate-change scenarios both along the DTS transect.” This sentence is a little confusing. Suggest rewording.
140-144 – Confirming that 2 km of cable was installed one shovel width at a time?
144-145 – So 1km of cable was installed, but the fiber was spliced upon itself to make 2km?
160-164 – Sentence is a bit long and mixes present and past tense. Might read more easily as two sentences.
169-170 – Did you see drift? At 1-2km?
173 – How were the in situ reference baths performed?
176-177 – How often did the power interruptions and unstable sensors occur? What percentage of the data was removed? How much of the data was anomalous?
199-210 – so pressure only has a weak to moderate correlation and relative humidity negligibly correlates to wind speed.
216-228 – did you come up with these equations?
258-259 – “The effects of precipitation…” is there a citation, or was this your own analysis?
308-310 – How many points are represented here? How many are in a, b, and c for Oct-Dec 22/23, Jan-May 24, and May-Sept23. Why are the dates broken up like that? 3 months, 5 months, 5 months?
332-340 – definitely helpful to have clarity in 144-145 to interpret this section.
342-360 – In Figure 5, would be helpful to add thermometer readings / other validation to this somehow. In Figure 6, though a PDF can be zoomed in, it’s still challenging to see the time series, particularly the yellow civil thermometer and the gray/purple tundra thermometer. Relatively, it does not look like the tundra thermometer agrees with the DTS? The legend is a tad confusing, are there many tundra thermometers? I see a lot of gray lines and a dark line that doesn’t look like it’s gray for purple/blue. Suggest updating this figure. Would be great to understand it better!!!
364-369 – would be neat if you had a figure showing this geospatially.
371-382 – Different time periods selected than 308-310. These periods are explained in this section (excellent!). Leads back to the 308-310 question of why that time breakout? Figure 7 – not sure I understand the arrows. Freezing is happening below -5 and thawing above -2.5? Could something be thawing from -5 to 15? Could something be freezing from 0 down to -25?
397-400 – would be neat to know what the warmer spots (particularly in b) are attributed to.. could add a text box in the fig depending on the reason.
415-419 – nice!
421-423 – Excellent Fig. clearly shows impact of infrastructure.
447-450 – Figure 10 is important. Suggest overlaying horizontal lines / zones where the model has filled in the missing information. It would be easier for the reader to see how challenging it might have been for the model to match up with measured data.
467-476 – Figure 10, great fig
501-513 – Interesting. Is there any engineering work to point to that would make linear infrastructure less influential?
530-544 – would be nice to highlight a more temperature volatile period the model successful produced.
605-610 – Does this work continue? Can you project to 2030 and then cross check your predictions in a few years?
743-745 – Figure B2 is GREAT. Would be help to do something like this for 397-400
752-756 – Again – curious about why those time periods. Confusing figs