سابِق|تال

Spatiotemporal change in permafrost active layer thickness in the Pan-Arctic region

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

  • Email：caihy@igsnrr.ac.cn
  • Introduction： 蔡红艳,1983年生, 女, 副研究员,研究方向为资源环境遥感。E-mail: caihy@igsnrr.ac.cn
CAI Hongyan1,  
  • Affiliation：

    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

HAN Dongrui13,  
  • Affiliation：

    Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

YANG Linsheng23,  
  • Affiliation：

    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

CHEN Mulin13,  
  • Affiliation：

    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

YANG Xiaohuan13

ملخص

Understanding of the spatiotemporal changes in permafrost Active Layer Thickness (ALT) in the Pan-Arctic region is important for global carbon flux simulation, climate change prediction, and freeze–thaw risk assessment. Many studies have been conducted on this subject. However, most previous works have relied on limited sites or regional simulation with a spatial resolution of 25 km or coarser. The spatiotemporal characteristics of ALT change at a landscape level needs to be explored, especially in the crucial infrastructure concentrated region. This study simulated the permafrost ALT in the Pan-Arctic region from 2001 to 2017 at kilometer level using Stefan method and permafrost site records, MOD11B3, and MCD12C1 data. Results showed that approximately 78.4% of the study area had an increase trend in ALT with a rate of 0.22 cm/a (p<0.05). Furthermore, the change in ALT spatially varied. The significantly increased areas were mainly distributed in Rocky Mountains, Laurentian Plateau of Canada, Central Siberian Plateau, and Central Siberian Plateau of Russia, with an increase rate between 0.5 and 1 cm/a. Meanwhile, the decreased areas were mainly concentrated in Hudson Bay Coastal Plain, Labrador Plateau of Canada, north East Siberian Mountains, north Central Siberian Plateau, east of Lake Baikal, and Taylor Peninsula of Russia. During this period, the ALT in 80% of the oil and gas areas had increased, with an increase rate between 0.1 and 0.7 cm/a. The variation in ALT was consistent with the temperature change. The ALT also varied with vegetation types in the order of ALT in forests > ALT in grasslands > ALT in savannahs > ALT in shrublands. However, the relationship between ALT and the thickness of snow cover was highly complicated. The results will deepen our understanding of the permafrost freeze–thaw pattern in the northern high latitudes and provide insights into the identification and prevention of freeze–thaw risk in the Pan-Arctic permafrost region.

مفهوم

Pan-Arctic region;climate change;permafrost;active layer thickness;remote sensing

References

  1. 1.
    Aalto J, Karjalainen O, Hjort J and Luoto M . 2018. Statistical forecasting of current and future circum-Arctic ground temperatures and active layer thickness. Geophysical Research Letters, 45(10): 4889-4898
  2. 2.
    Akerman H J and Johansson M . 2008. Thawing permafrost and thicker active layers in sub-arctic Sweden. Permafrost and Periglacial Processes, 19(3): 279-292
  3. 3.
    Brown J, Hinkel K M and Nelson F E . 2000. The circumpolar active layer monitoring (CALM) program: research designs and initial results. Polar Geography, 24(3): 166-258
  4. 4.
    Cao Y F and Liang S L . 2018. Recent advances in driving mechanisms of the Arctic amplification: a review. Chinese Science Bulletin, 63(26): 2757-2771
  5. 5.
    Ding H J, Zhou L L, Zha B and Zhai G Q . 2007. An analysis on the abnormal high temperature weather in the south Yangtze Valley during summer 2003. Journal of Zhejiang University (Science Edition), 34(1): 100-105, 120
  6. 6.
    Du Q . 2011. Study on the characteristics of dense sandstone oil and gas reservoirs. West-China Exploration Engineering, 23(7): 37-38, 42
  7. 7.
    Feng Y Q, Liang S H, Wu Q B, Chen J W, Tian X and Wu P . 2016. Vegetation responses to permafrost degradation in the Qinghai-Tibetan Plateau. Journal of Beijing Normal University (Natural Science), 52(3): 311-316
  8. 8.
    Frauenfeld O W, Zhang T J, Barry R G and Gilichinsky D . 2004. Interdecadal changes in seasonal freeze and thaw depths in Russia. Journal of Geophysical Research, 109 (D 5): D05101
  9. 9.
    Guo D L, Li D and Hua W . 2018. Quantifying air temperature evolution in the permafrost region from 1901 to 2014. International Journal of Climatology, 38(1): 66-76
  10. 10.
    Hayes D J, Kicklighter D W, McGuire A D, Chen M, Zhuang Q L, Yuan F M, Melillo J M and Wullschleger S D . 2014. The impacts of recent permafrost thaw on land-atmosphere greenhouse gas exchange. Environmental Research Letters, 9(4): 045005
  11. 11.
    Hinkel K M and Nelson F E . 2003. Spatial and temporal patterns of active layer thickness at circumpolar active layer monitoring (CALM) sites in northern Alaska, 1995-2000. Journal of Geophysical Research, 108 (D 2): 8168
  12. 12.
    Hu L Q, Wu P F, Liang F C and Zhang W H . 2014. Analyzing the effect of snow cover in spring and winter and air temperature on frozen ground depth in Xinjiang. Journal of Glaciology and Geocryology, 36(1): 48-54
  13. 13.
    Karlsson J M, Lyon S W and Destouni G . 2012. Thermokarst lake, hydrological flow and water balance indicators of permafrost change in Western Siberia. Journal of Hydrology, 464-465: 459-466
  14. 14.
    Kim Y, Kimball J S, Glassy J and Du J Y . 2017. An extended global earth system data record on daily landscape freeze-thaw status determined from satellite passive microwave remote sensing. Earth System Science Data, 9(1): 133-147
  15. 15.
    Kong Y and Wang C H . 2017. Responses and changes in the permafrost and snow water equivalent in the Northern Hemisphere under a scenario of 1.5 ℃ warming. Climate Change Research, 13(4): 316-326
  16. 16.
    Li K . 2017. Risk analysis and control measures of frost heaving and thaw collapsing in perma-frost regions. Oil-Gasfield Surface Engineering, 36(11): 55-57
  17. 17.
    Lujala P, Rød J K and Thieme N . 2007. Fighting over oil: introducing a new dataset. Conflict Management and Peace Science, 24(3): 239-256
  18. 18.
    Mölders N and Romanovsky V E . 2006. Long-term evaluation of the hydro-thermodynamic soil-vegetation scheme's frozen ground/permafrost component using observations at barrow, Alaska. Journal of Geophysical Research, 111 (D 4): D04105
  19. 19.
    Nelson F E, Anisimov O A and Shiklomanov N I . 2001. Subsidence risk from thawing permafrost. Nature, 410(6831): 889-890
  20. 20.
    Nicolsky D J, Romanovsky V E, Alexeev V A and Lawrence D M . 2007. Improved modeling of permafrost dynamics in a GCM land-surface scheme. Geophysical Research Letters, 34(8): L08501
  21. 21.
    Overpeck J, Hughen K, Hardy D, Bradley R, Case R, Douglas M, Finney B, Gajewski K, Jacoby G, Jennings A, Lamoureux S, Lasca A, MacDonald G, Moore J, Retelle M, Smith S, Wolfe A and Zielinski G . 1997. Arctic environmental change of the last four centuries. Science, 278(5341): 1251-1256
  22. 22.
    Park H, Fedorov A N, Zheleznyak M N, Konstantinov P Y and Walsh J E . 2015. Effect of snow cover on pan-Arctic permafrost thermal regimes. Climate Dynamics, 44( 9/10): 2873-2895
  23. 23.
    Park H, Iijima Y, Yabuki H, Ohta T, Walsh J, Kodama Y and Ohata T . 2011. The application of a coupled hydrological and biogeochemical model (change) for modeling of energy, water, and CO2 exchanges over a larch forest in Eastern Siberia. Journal of Geophysical Research, 116 (D 15): D15102
  24. 24.
    Park H, Kim Y and Kimball J S . 2016. Widespread permafrost vulnerability and soil active layer increases over the high northern latitudes inferred from satellite remote sensing and process model assessments. Remote Sensing of Environment, 175: 349-358
  25. 25.
    Peng X Q, Zhang T J, Frauenfeld O W, Wang K, Luo D L, Cao B, Su H, Jin H J and Wu Q B . 2018. Spatiotemporal changes in active layer thickness under contemporary and projected climate in the Northern Hemisphere. Journal of Climate, 31(1): 251-266
  26. 26.
    Qiao Z and Tian G J . 2014. Spatiotemporal diversity and regionalization of the urban thermal environment in Beijing. Journal of Remote Sensing, 18(3): 715-734
  27. 27.
    Qiao Z and Tian G J . 2015. Dynamic monitoring of the footprint and capacity for urban heat island in Beijing between 2001 and 2012 based on MODIS. Journal of Remote Sensing, 19(3): 476-484
  28. 28.
    Smith N V, Saatchi S S and Randerson J T . 2004. Trends in high northern latitude soil freeze and thaw cycles from 1988 to 2002. Journal of Geophysical Research, 109 (D 12): D12101
  29. 29.
    Streletskiy D A, Shiklomanov N I, Nelson F E and Klene A E . 2008. Thirteen years of observations at Alaskan CALM sites: Long-term active layer and ground surface temperature trends. Proceedings of the Ninth International Conference on Permafrost. Fairbanks: University of Alaska Press: 1727-1732.
  30. 30.
    Torre Jorgenson M, Harden J, Kanevskiy M, O'Donnell J, Wickland K, Ewing S, Manies K, Zhuang Q L, Shur Y, Striegl R and Koch J . 2013. Reorganization of vegetation, hydrology and soil carbon after permafrost degradation across heterogeneous boreal landscapes. Environmental Research Letters, 8(3): 035017
  31. 31.
    Vonk J E, Mann P J, Davydov S, Davydova A, Spencer R G M, Schade J, Sobczak W V, Zimov N, Zimov S, Bulygina E, Eglinton T I and Holmes R M . 2013. High biolability of ancient permafrost carbon upon thaw. Geophysical Research Letters, 40(11): 2689-2693
  32. 32.
    Wan Z M . 2014. New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product. Remote Sensing of Environment, 140: 36-45
  33. 33.
    Wu X B, Nan Z T, Wang W Z and Zhao L . 2018. Simulation of the impact of vegetation and soil characteristics on permafrost over the Tibetan Plateau based on the Noah land surface model. Journal of Glaciology and Geocryology, 40(2): 279-287
  34. 34.
    Xu X M, Wu Q B and Zhang Z Q . 2017. Responses of active layer thickness on the Qinghai-Tibet Plateau to climate change. Journal of Glaciology and Geocryology, 39(1): 1-8
  35. 35.
    You M D, Li H B, Ge M and Zang S Y . 2018. The influence factors of permafrost active layer depth and their annual change in Heilongjiang Province. Journal of Glaciology and Geocryology, 40(3): 480-491
  36. 36.
    Zhang T J, Frauenfeld O W, Serreze M C, Etringer A, Oelke C, McCreight J, Barry R G, Gilichinsky D, Yang D Q, Ye H C, Ling F and Chudinova S . 2005. Spatial and temporal variability in active layer thickness over the Russian Arctic drainage basin. Journal of Geophysical Research, 110 (D 16): D16101
  37. 37.
    Zhang Y, Chen W J and Cihlar J . 2003. A process-based model for quantifying the impact of climate change on permafrost thermal regimes. Journal of Geophysical Research, 108 (D 22): 4695
  38. 38.
    Zhang Y, Chen W J and Riseborough D W . 2006. Temporal and spatial changes of permafrost in Canada since the end of the little ice age. Journal of Geophysical Research, 111 (D 22): D22103
  39. 39.
    Zhang W, Zhou J, Wang G X, Kinzelbach W, Cheng G D, Ye B S, He X B and Li H Y . 2013. Monitoring and modeling the influence of snow cover and organic soil on the active layer of permafrost on the Tibetan Plateau. Journal of Glaciology and Geocryology, 35(3): 528-540
  40. 40.
    Zhang Z Q and Wu Q B . 2012. Predicting changes of active layer thickness on the Qinghai-Tibet Plateau as climate warming. Journal of Glaciology and Geocryology, 34(3): 505-511

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