Investigating the sensitivity of soil heterotrophic respiration to recent snow cover changes in Alaska using a satellite-based permafrost carbon model

Yi, Yonghong; Kimball, John S.; Watts, Jennifer D.; Natali, Susan M.; Zona, Donatella; Liu, Junjie; Ueyama, Masahito; Kobayashi, Hideki; Oechel, Walter; Miller, Charles E.

doi:https://doi.org/10.5194/bg-17-5861-2020

Articles | Volume 17, issue 22

https://doi.org/10.5194/bg-17-5861-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-17-5861-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 22

Research article

| Highlight paper

|

27 Nov 2020

Research article | Highlight paper |

| 27 Nov 2020

Investigating the sensitivity of soil heterotrophic respiration to recent snow cover changes in Alaska using a satellite-based permafrost carbon model

Yonghong Yi, John S. Kimball, Jennifer D. Watts, Susan M. Natali, Donatella Zona, Junjie Liu, Masahito Ueyama, Hideki Kobayashi, Walter Oechel, and Charles E. Miller

Supplement

https://doi.org/10.5194/bg-17-5861-2020-supplement

Model code and software

STM-C: A remote sensing driven permafrost carbon model software Yonghong Yi https://github.com/yiyh05/STM-C

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Short summary

We developed a 1 km satellite-data-driven permafrost carbon model to evaluate soil respiration sensitivity to recent snow cover changes in Alaska. Results show earlier snowmelt enhances growing-season soil respiration and reduces annual carbon uptake, while early cold-season soil respiration is linked to the number of snow-free days after the land surface freezes. Our results also show nonnegligible influences of subgrid variability in surface conditions on model-simulated CO₂ seasonal cycles.