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| Titel |
Using field observations to inform thermal hydrology models of permafrost dynamics with ATS (v0.83) |
| VerfasserIn |
A. L. Atchley, S. L. Painter, D. R. Harp, E. T. Coon, C. J. Wilson, A. K. Liljedahl, V. E. Romanovsky |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1991-959X
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| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 8, no. 9 ; Nr. 8, no. 9 (2015-09-01), S.2701-2722 |
| Datensatznummer |
250116549
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| Publikation (Nr.) |
 copernicus.org/gmd-8-2701-2015.pdf |
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| Zusammenfassung |
| Climate change is profoundly transforming the carbon-rich Arctic tundra
landscape, potentially moving it from a carbon sink to a carbon source by
increasing the thickness of soil that thaws on a seasonal basis. However,
the modeling capability and precise parameterizations of the physical
characteristics needed to estimate projected active layer thickness (ALT)
are limited in Earth system models (ESMs). In particular, discrepancies in
spatial scale between field measurements and Earth system models challenge
validation and parameterization of hydrothermal models. A recently developed
surface–subsurface model for permafrost thermal hydrology, the Advanced Terrestrial Simulator (ATS), is used in combination with field measurements
to achieve the goals of constructing a process-rich model based on plausible
parameters and to identify fine-scale controls of ALT in ice-wedge polygon
tundra in Barrow, Alaska. An iterative model refinement procedure that
cycles between borehole temperature and snow cover measurements and
simulations functions to evaluate and parameterize different model processes
necessary to simulate freeze–thaw processes and ALT formation. After model
refinement and calibration, reasonable matches between simulated and
measured soil temperatures are obtained, with the largest errors occurring
during early summer above ice wedges (e.g., troughs). The results suggest
that properly constructed and calibrated one-dimensional thermal hydrology
models have the potential to provide reasonable representation of the
subsurface thermal response and can be used to infer model input parameters
and process representations. The models for soil thermal conductivity and
snow distribution were found to be the most sensitive process
representations. However, information on lateral flow and snowpack evolution
might be needed to constrain model representations of surface hydrology and
snow depth. |
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