Conceptual Model to Simulate Long-term Soil Organic Carbon and Ground Ice Budget with Permafrost and Ice Sheets (SOC-ICE-v1.0)

• Main Authors: Saito, Kazuyuki, Machiya, Hirokazu, Iwahana, Go, Yokohata, Tokuta, Ohno, Hiroshi
• Format: Text
• Language: English
• Published: 2020
• Subjects: Arctic; Greenland; Climate change; Greenland ice core; Ice; ice core; permafrost
• Online Access: https://doi.org/10.5194/gmd-2020-80; https://gmd.copernicus.org/preprints/gmd-2020-80/

Degradation of permafrost is a large source of uncertainty in understanding the behaviour of Earth’s climate system and in projecting future impacts of climate change. In assessing and projecting the relative risks and impacts of permafrost degradation, the spatial distribution of soil organic carbon (SOC) and ground ice (ICE) provides essential information. However, uncertainties in geographical distribution and in the estimated range of total amount of stored carbon and ice are still large. A conceptual and a numerical soil organic carbon–ground ice budget model, SOC-ICE-v1.0, was developed, which considers essential aspects of carbon and hydrological processes for above ground and subsurface environments and frozen ground (permafrost) and land cover changes (ice sheets and coastlines), to calculate long-term evolution of soil organic carbon (SOC) and ground ice (ICE). The model was integrated for the last 125 thousand years, from the Last Interglacial until today for areas north of 50° N, to simulate the balance between accumulation and dissipation of carbon and ice. Model performance was compared with observation-based data and evaluated to assess allogenic (external) impacts on soil carbon dynamics in the circum-Arctic region on a glacial-interglacial time scale. Despite the limitation of forcing climate data being constructed on the basis of a single Greenland ice core dataset, the simulated results successfully reproduced temporal changes in northern SOC and ICE, consistent with current knowledge. The simulation also captured regional differences in different geographical and climatic characteristics within the circum-Arctic region. The model quantitatively demonstrated allogenic controls on soil carbon evolution by climatological and topo-geographical factors. The resulting circum-Arctic set of simulated time series can be compiled to produce snapshot maps of SOC and ICE distributions for past and present assessments or future projection simulations. Despite a simple modelling framework, SOC-ICE-v1.0 provided substantial information on the temporal evolution and spatial distribution of circum-Arctic soil carbon and ground ice. Model improvements in terms of forcing climate data, improvement of soil carbon dynamics, and choice of initial values are, however, required for future research.