Permafrost thaw and resulting soil moisture changes regulate projected high-latitude CO2 and CH4 emissions

By D. Lawrence, C. Koven, S. Swenson, William J. Riley, A. Slater. 2015

282 citations recorded by the source corpus.

The fate of currently frozen permafrost carbon as high-latitude climate warms remains highly uncertain and existing models give widely varying estimates of the permafrost carbon-climate feedback. This uncertainty is due to many factors, including the role that permafrost thaw-induced transitions in soil hydrologic conditions will have on organic matter decomposition rates and the proportion of aerobic to anaerobic respiration. Large-scale permafrost thaw, as predicted by the Community Land Model (CLM) under an unmitigated greenhouse gas emissions scenario, results in significant soil drying due to increased drainage following permafrost thaw, even though permafrost domain water inputs are projected to rise (net precipitation minus evaporation >0). CLM predicts that drier soil conditions will accelerate organic matter decomposition, with concomitant increases in carbon dioxide (CO2) emissions. Soil drying, however, strongly suppresses growth in methane (CH4) emissions. Considering the global warming potential (GWP) of CO2 and CH4 emissions together, soil drying weakens the CLM projected GWP associated with carbon fluxes from the permafrost zone by more than 50% compared to a non-drying case. This high sensitivity to hydrologic change highlights the need for better understanding and modeling of landscape-scale changes in soil moisture conditions in response to permafrost thaw in order to more accurately assess the potential magnitude of the permafrost carbon-climate feedback.

Subfields: Atmospheric Science

View Paper: https://www.semanticscholar.org/paper/ea8a4dda1bccf551fee2f75af158bbe68c64719f

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In Atmospheric Science

1. Gordon Bonan
2. William J. Riley
3. C. Koven
4. A. Slater
5. D. Lawrence
6. S. Swenson
7. L. Ruby Leung
8. M. Clark

Citations in the corpus

• The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty (2019, methodology): “The projection period (2015–2300) simulations, which used the “anomaly forcing” method (Lawrence et al., 2015), and the no land use change simulations are not assessed here but are available to the community via the data portal for use.”