Characterizing permafrost soil active layer dynamics and sensitivity to landscape spatial heterogeneity in Alaska [electronic resource].

Published: Washington, D.C. : National Aeronautics and Space Administration Announcement, 2017.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy
Physical Description: pages 1-32 : digital, PDF file
Additional Creators: Argonne National Laboratory, National Aeronautics and Space Administration Announcement, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information

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Summary

An important feature of the Arctic is large spatial heterogeneity in active layer conditions, which is generally poorly represented by global models. In this study, we developed a spatially integrated modelling and analysis framework combining field observations, local scale (~ 50 m) active layer thickness (ALT) and soil moisture maps derived from airborne low frequency (L + P-band) radar measurements, and global satellite environmental observations to investigate the ALT sensitivity to recent climate trends and landscape heterogeneity in Alaska. Model simulated ALT results show good correspondence with in-situ measurements in higher permafrost probability (PP ≥ 70 %) areas (n = 33, R = 0.60, mean bias = 1.58 cm, RMSE = 20.32 cm). The model results also reveal widespread ALT deepening since 2001, with smaller ALT increases in northern Alaska (mean trend = 0.32 ± 1.18 cm yr^-1) and much larger increases (> 3 cm yr^-1) across interior and southern Alaska. The positive ALT trend coincides with regional warming and a longer snow-free season (R = 0.60 ± 0.32). Uncertainty in the spatial and vertical distribution of soil organic carbon (SOC) was found to be the most important factor affecting model ALT accuracy. Here, potential improvements in characterizing SOC heterogeneity, including better spatial sampling of soil conditions and advances in remote sensing of SOC and soil moisture, will enable more accurate predictions of permafrost active layer conditions.

Report Numbers

E 1.99:1402081

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Published through SciTech Connect.
05/30/2017.
"136147"
The Cryosphere Discussions 2017 ISSN 1994-0440 AM
Yonghong Yi; John S. Kimball; Richard Chen; Mahta Moghaddam; Rolf H. Reichle; Umakant Mishra; Donatella Zona; Walter C. Oechel.

Funding Information

AC02-06CH11357

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