Insights into spatiotemporal evolution of permafrost under climate change - hydrologic-land surface modelling in the Canadian subarctic
Abstract
Permafrost plays a critical role in cold regions with significant impacts on hydrological processes, energy flux partitioning, carbon dynamics, and plant communities. In recent decades, permafrost degradation has been observed in the Northern Hemisphere and is expected to accelerate under continued global warming. The assessment of this trend requires an improved understanding of the evolution and dynamics of surface/subsurface thermal and hydrologic regimes. Land surface models (LSMs) are well suited for such predictions due to their physical basis and large-scale applicability. However, modelling permafrost dynamics is challenged by several issues, including the large number of model parameters (and their interactions), complex memory of state variables, and scarcity of permafrost observations (thermal/hydraulic regimes). In this study, we report model experiments conducted with the Modélisation Environmentale Communautaire - Surface and Hydrology (MESH) modelling framework and its embedded Canadian Land Surface Scheme (CLASS). We configure a hydrologic land surface model for the Liard River Basin (a major tributary of the Mackenzie River basin with a drainage area of 277K km2) that can simultaneously simulate permafrost signatures, water balance, and streamflow dynamics. We then force the model with an ensemble of different downscaled and bias-corrected CMIP6 projections under different shared socio-economic pathways (SSPs). Results highlight that modellers may encounter significant trade-offs when selecting a unique parameter set that can replicate the observed streamflow, local-scale permafrost observations, and grid-based permafrost datasets. Further, we assess the propagated parameter/forcing uncertainties into the future, which reveals permafrost thawing, both vertically and laterally, that affects streamflow seasonality and the partitioning of water fluxes. Besides, the study sheds more light on the temporal/spatial evolution of different vegetation classes underlain by permafrost, which provides a better understating of each permafrost zone's dynamics. These insights will hopefully inform future adaptation strategies to mitigate the negative impacts of climate change.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.H15D..07A