气候变化领域集成服务门户(CCPortal): Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape

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DOI	10.5194/tc-10-2241-2016
	Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape
	Kumar J.; Collier N.; Bisht G.; Mills R.T.; Thornton P.E.; Iversen C.M.; Romanovsky V.
发表日期	2016
ISSN	19940416
卷号	10 期号:5
英文摘要	Vast carbon stocks stored in permafrost soils of Arctic tundra are under risk of release to the atmosphere under warming climate scenarios. Ice-wedge polygons in the low-gradient polygonal tundra create a complex mosaic of microtopographic features. This microtopography plays a critical role in regulating the fine-scale variability in thermal and hydrological regimes in the polygonal tundra landscape underlain by continuous permafrost. Modeling of thermal regimes of this sensitive ecosystem is essential for understanding the landscape behavior under the current as well as changing climate. We present here an end-to-end effort for high-resolution numerical modeling of thermal hydrology at real-world field sites, utilizing the best available data to characterize and parameterize the models. We develop approaches to model the thermal hydrology of polygonal tundra and apply them at four study sites near Barrow, Alaska, spanning across low to transitional to high-centered polygons, representing a broad polygonal tundra landscape. A multiphase subsurface thermal hydrology model (PFLOTRAN) was developed and applied to study the thermal regimes at four sites. Using a high-resolution lidar digital elevation model (DEM), microtopographic features of the landscape were characterized and represented in the high-resolution model mesh. The best available soil data from field observations and literature were utilized to represent the complex heterogeneous subsurface in the numerical model. Simulation results demonstrate the ability of the developed modeling approach to capture-without recourse to model calibration – several aspects of the complex thermal regimes across the sites, and provide insights into the critical role of polygonal tundra microtopography in regulating the thermal dynamics of the carbon-rich permafrost soils. Areas of significant disagreement between model results and observations highlight the importance of field-based observations of soil thermal and hydraulic properties for modeling-based studies of permafrost thermal dynamics, and provide motivation and guidance for future observations that will help address model and data gaps affecting our current understanding of the system. © 2016 The Author(s).
学科领域	carbon sequestration; digital elevation model; landscape structure; microtopography; numerical model; permafrost; spatial variation; temporal variation; thermal regime; tundra; Alaska; Barrow; United States
语种	英语
scopus关键词	carbon sequestration; digital elevation model; landscape structure; microtopography; numerical model; permafrost; spatial variation; temporal variation; thermal regime; tundra; Alaska; Barrow; United States
来源期刊	Cryosphere
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/119574
作者单位	Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States; Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States; Lawrence Berkeley National Laboratory, Berkeley, CA, United States; Intel Corporation, Hillsboro, OR, United States; Geophysical Institute, University of Alaska FairbanksAK, United States
推荐引用方式 GB/T 7714	Kumar J.,Collier N.,Bisht G.,et al. Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape[J],2016,10(5).
APA	Kumar J..,Collier N..,Bisht G..,Mills R.T..,Thornton P.E..,...&Romanovsky V..(2016).Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape.Cryosphere,10(5).
MLA	Kumar J.,et al."Modeling the spatiotemporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape".Cryosphere 10.5(2016).