Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape

Kumar, Jitendra; Collier, Nathan; Bisht, Gautam; Mills, Richard T.; Thornton, Peter E.; Iversen, Colleen M.; Romanovsky, Vladimir

doi:https://doi.org/10.5194/tc-10-2241-2016

Articles | Volume 10, issue 5

https://doi.org/10.5194/tc-10-2241-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/tc-10-2241-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 10, issue 5

Research article

|

27 Sep 2016

Research article |

| 27 Sep 2016

Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape

Jitendra Kumar, Nathan Collier, Gautam Bisht, Richard T. Mills, Peter E. Thornton, Colleen M. Iversen, and Vladimir Romanovsky

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Final revised paper (published on 27 Sep 2016)
Preprint (discussion started on 17 Feb 2016)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of Kumar et al.', Anonymous Referee #1, 16 Mar 2016
- AC1: 'Response to comments by Reviewer 1', Jitendra Kumar, 13 May 2016
RC2: 'Review of “Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape” by Kumar et al.', Anonymous Referee #2, 16 Mar 2016
- AC2: 'Response to comments by Reviewer 2', Jitendra Kumar, 13 May 2016
RC3: 'Review of J. Kumar et al.', Anonymous Referee #3, 17 Mar 2016
- AC3: 'Response to comments by Reviewer 3', Jitendra Kumar, 13 May 2016
SC1: 'Comment on Section 5.1 of Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape', Adam Atchley, 12 Apr 2016
- AC4: 'Response to comments by Atchley et al.', Jitendra Kumar, 13 May 2016

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Jitendra Kumar on behalf of the Authors (13 May 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (18 May 2016) by Julia Boike

RR by Anonymous Referee #1 (28 May 2016)

Suggestions for revision or reasons for rejection

The authors have improved the manuscript and answered most points raised. I still do not see convincing evidence that modeling in such detail with PFLOTRAN can really improve the performance compared to simpler approach. This is ultimately a question whether the potential performance gain due to improved model physics (i.e. adding more processes) is annihilated due to the introduction of a multitude of new model parameters for which suitable data sets do not exist and which must therefore be estimated (somehow). But other than the idea stated under point #1 below, I do not see much potential to evaluate the model performance in more detail with the presented field data.

Additional points:
1. Although the authors are understandably reluctant in this point, I still feel that the manuscript could tremendously benefit from including a few “classical” 1D-simulations of heat transfer (e.g. with GIPL2) as reference cases, i.e. with the same surface temperature forcing and the same approximate ground conditions. From the comparison to ground data, I am not at all convinced that the sophisticated model is really “better” in reproducing the ground thermal regime compared to such simpler schemes. I would be delighted to see a convincing case where PFLOTRAN really does a much better job than the simple 1D model, even if it is just for a short episode, e.g. after snowmelt or following precipitation events.
2. Mention clearly in the Abstract and Conclusion the comparatively poor performance of the model regarding active layer thickness. I very much disagree with the statement in the Abstract ”Simulation results demonstrate the ability of the developed modeling approach to model the complex thermal regimes across the sites.” Considering the state-of-the-art in permafrost modeling vs. the presented results, this is simply wrong. Please present a more balanced assessment of model performance to the reader!
3. P. 20, l. 6ff: Active layer thicknesses are highly variable both in space and different years, and it is only meaningful to refer to the modeled situation – please delete the references to the Kuparuk watershed, and also Hubbard et al. (2013) if it does not refer to measurements at the modeled sites and periods. There are regions where permafrost with active layer thickness of 0.5m is found in only 5m distance from a permafrost-free area. But if one models the area with permafrost, the modeled thaw depth should be 50cm, and the presence of the permafrost-free area close by does not make the performance any better if the model does not yield 50cm. It is exactly the purpose of a spatially distributed model to capture such differences. A statement like ”Peterson (2016) indicating the variability due the heterogeneity at the site” is OK in an assessment of a 5km gridded model, but a high-resolution model must be compared to suitable field data sets.
4. I very much like that the authors have now included plots of the thaw depth. I addition, I would like to see a statement like “The modeled thaw depth was (XX+-YY)m (using the ranges from the figures), while the measured thaw depth was ZZ m.” Then the facts are clearly stated.
5. P. 26, l. 43 ff: This is an important clarification of the overall strategy and the context of the paper. Thanks!

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RR by Anonymous Referee #3 (04 Jun 2016)

RR by Anonymous Referee #2 (06 Jun 2016)

ED: Reconsider after major revisions (10 Jun 2016) by Julia Boike

AR by Jitendra Kumar on behalf of the Authors (06 Aug 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (14 Aug 2016) by Julia Boike

RR by Anonymous Referee #1 (23 Aug 2016)

ED: Publish subject to minor revisions (Editor review) (03 Sep 2016) by Julia Boike

AR by Jitendra Kumar on behalf of the Authors (09 Sep 2016) Author's response Manuscript

ED: Publish as is (09 Sep 2016) by Julia Boike

AR by Jitendra Kumar on behalf of the Authors (09 Sep 2016) Manuscript

Short summary

Microtopography of the low-gradient polygonal tundra plays a critical role in these ecosystem; however, patterns and drivers are poorly understood. A modeling-based approach was developed in this study to characterize and represent the permafrost soils in the model and simulate the thermal dynamics using a mechanistic high-resolution model. Results shows the ability of the model to simulate the patterns and variability of thermal regimes and improve our understanding of polygonal tundra.