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Title: Microtopographic characterization of ice-wedge polygon landscape in Barrow, Alaska: a digital map of troughs, rims, centers derived from high resolution (0.25 m) LiDAR data

The dataset represents microtopographic characterization of the ice-wedge polygon landscape in Barrow, Alaska. Three microtopographic features are delineated using 0.25 m high resolution digital elevation dataset derived from LiDAR. The troughs, rims, and centers are the three categories in this classification scheme. The polygon troughs are the surface expression of the ice-wedges that are in lower elevations than the interior polygon. The elevated shoulders of the polygon interior immediately adjacent to the polygon troughs are the polygon rims for the low center polygons. In case of high center polygons, these features are the topographic highs. In this classification scheme, both topographic highs and rims are considered as polygon rims. The next version of the dataset will include more refined classification scheme including separate classes for rims ad topographic highs. The interior part of the polygon just adjacent to the polygon rims are the polygon centers.
Publication Date:
DOE Contract Number:
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Research Org(s):
Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
54 Environmental Sciences; High center polygons; low center polygons; LiDAR; digital elevation model; Barrow, AK topography; NGEE LiDAR; troughs, rims, centers
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  1. This Modeling Archive is in support of an NGEE Arctic discussion paper under review and available at Vast carbon stocks stored in permafrost soils of Arctic tundra are under risk of release to atmosphere under warming climate. Ice--wedge polygons in the low-gradient polygonal tundramore » create a complex mosaic of microtopographic features. The 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 behaviour under 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 at Barrow, Alaska spanning across low to transitional to high-centered polygon and representative of broad polygonal tundra landscape. A multi--phase subsurface thermal hydrology model (PFLOTRAN) was developed and applied to study the thermal regimes at four sites. Using high resolution LiDAR DEM, microtopographic features of the landscape were characterized and represented in the high resolution model mesh. Best available soil data from field observations and literature was utilized to represent the complex hetogeneous subsurface in the numerical model. This data collection provides the complete set of input files, forcing data sets and computational meshes for simulations using PFLOTRAN for four sites at Barrow Environmental Observatory. It also document the complete computational workflow for this modeling study to allow verification, reproducibility and follow up studies. « less
  2. This dataset represent a map of the high center (HC) and low center (LC) polygon boundaries delineated from high resolution LiDAR data for the arctic coastal plain at Barrow, Alaska. The polygon troughs are considered as the surface expression of the ice-wedges. The troughs aremore » in lower elevations than the interior polygon. The trough widths were initially identified from LiDAR data, and the boundary between two polygons assumed to be located along the lowest elevations on trough widths between them. « less
  3. Arctic ecosystems have been observed to be warming faster than the global average and are predicted to experience accelerated changes in climate due to global warming. Arctic vegetation is particularly sensitive to warming conditions and likely to exhibit shifts in species composition, phenology and productivitymore » under changing climate. Mapping and monitoring of changes in vegetation is essential to understand the effect of climate change on the ecosystem functions. Vegetation exhibits unique spectral characteristics which can be harnessed to discriminate plant types and develop quantitative vegetation indices. We have combined high resolution multi-spectral remote sensing from the WorldView 2 satellite with LIDAR-derived digital elevation models to characterize the tundra landscape on the North Slope of Alaska. Classification of landscape using spectral and topographic characteristics yields spatial regions with expectedly similar vegetation characteristics. A field campaign was conducted during peak growing season to collect vegetation harvests from a number of 1m x 1m plots in the study region, which were then analyzed for distribution of vegetation types in the plots. Statistical relationships were developed between spectral and topographic characteristics and vegetation type distributions at the vegetation plots. These derived relationships were employed to statistically upscale the vegetation distributions for the landscape based on spectral characteristics. Vegetation distributions developed are being used to provide Plant Functional Type (PFT) maps for use in the Community Land Model (CLM). « less
  4. This data set reports the results of spatial surveys of aqueous geochemistry conducted at Intensive Site 1 of the Barrow Environmental Observatory in 2013 and 2014 (Herndon et al., 2015). Surface water and soil pore water samples were collected from multiple depths within the tundramore » active layer of different microtopographic features (troughs, ridges, center) of a low-centered polygon (area A), high-centered polygon (area B), flat-centered polygon (area C), and transitional polygon (area D). Reported analytes include dissolved organic and inorganic carbon, dissolved carbon dioxide and methane, major inorganic anions, and major and minor cations. « less
  5. This Modeling Archive is in support of an NGEE Arctic publication available at doi:10.5194/tc-10-341-2016. This dataset contains an ensemble of thermal-hydro soil parameters including porosity, thermal conductivity, thermal conductivity shape parameters, and residual saturation of peat and mineral soil. The ensemble was generated using amore » Null-Space Monte Carlo analysis of parameter uncertainty based on a calibration to soil temperatures collected at the Barrow Environmental Observatory site by the NGEE team. The micro-topography of ice wedge polygons present at the site is included in the analysis using three 1D column models to represent polygon center, rim and trough features. The Arctic Terrestrial Simulator (ATS) was used in the calibration to model multiphase thermal and hydrological processes in the subsurface. « less