Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape: Modeling Archive
This Modeling Archive is in support of an NGEE Arctic publication available at https://doi.org/10.5194/tc-10-2241-2016 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 tundr...
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Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); NGEE Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
2016
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Online Access: | https://dx.doi.org/10.5440/1184018 https://www.osti.gov/servlets/purl/1184018/ |
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ftdatacite:10.5440/1184018 2023-05-15T15:02:01+02:00 Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape: Modeling Archive Kumar, Jitendra Collier, Nathan Bisht, Gautam Mills, Richard Thornton, Peter Iversen, Colleen Romanovsky, Vladimir 2016 https://dx.doi.org/10.5440/1184018 https://www.osti.gov/servlets/purl/1184018/ en eng Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); NGEE Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) https://dx.doi.org/10.5194/tc-10-2241-2016 54 Environmental Sciences ;Barrow, Alaska;Barrow Environmental Observatory;Utqiagvik, Alaska dataset Numeric Data Dataset 2016 ftdatacite https://doi.org/10.5440/1184018 https://doi.org/10.5194/tc-10-2241-2016 2021-11-05T12:55:41Z This Modeling Archive is in support of an NGEE Arctic publication available at https://doi.org/10.5194/tc-10-2241-2016 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 tundra 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 heterogeneous 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. Dataset DOI: 10.5440/1184018; https://doi.org/10.5440/1184018 Dataset Arctic Barrow Ice permafrost Tundra wedge* Alaska DataCite Metadata Store (German National Library of Science and Technology) Arctic |
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Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
54 Environmental Sciences ;Barrow, Alaska;Barrow Environmental Observatory;Utqiagvik, Alaska |
spellingShingle |
54 Environmental Sciences ;Barrow, Alaska;Barrow Environmental Observatory;Utqiagvik, Alaska Kumar, Jitendra Collier, Nathan Bisht, Gautam Mills, Richard Thornton, Peter Iversen, Colleen Romanovsky, Vladimir Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape: Modeling Archive |
topic_facet |
54 Environmental Sciences ;Barrow, Alaska;Barrow Environmental Observatory;Utqiagvik, Alaska |
description |
This Modeling Archive is in support of an NGEE Arctic publication available at https://doi.org/10.5194/tc-10-2241-2016 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 tundra 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 heterogeneous 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. Dataset DOI: 10.5440/1184018; https://doi.org/10.5440/1184018 |
format |
Dataset |
author |
Kumar, Jitendra Collier, Nathan Bisht, Gautam Mills, Richard Thornton, Peter Iversen, Colleen Romanovsky, Vladimir |
author_facet |
Kumar, Jitendra Collier, Nathan Bisht, Gautam Mills, Richard Thornton, Peter Iversen, Colleen Romanovsky, Vladimir |
author_sort |
Kumar, Jitendra |
title |
Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape: Modeling Archive |
title_short |
Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape: Modeling Archive |
title_full |
Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape: Modeling Archive |
title_fullStr |
Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape: Modeling Archive |
title_full_unstemmed |
Modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape: Modeling Archive |
title_sort |
modeling the spatio-temporal variability in subsurface thermal regimes across a low-relief polygonal tundra landscape: modeling archive |
publisher |
Next Generation Ecosystems Experiment - Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (US); NGEE Arctic, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) |
publishDate |
2016 |
url |
https://dx.doi.org/10.5440/1184018 https://www.osti.gov/servlets/purl/1184018/ |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Barrow Ice permafrost Tundra wedge* Alaska |
genre_facet |
Arctic Barrow Ice permafrost Tundra wedge* Alaska |
op_relation |
https://dx.doi.org/10.5194/tc-10-2241-2016 |
op_doi |
https://doi.org/10.5440/1184018 https://doi.org/10.5194/tc-10-2241-2016 |
_version_ |
1766334010349322240 |