As part of the terrestrial branch of the Japanfunded Arctic Climate Change Research Project (GRENE-TEA), which aims to clarify the role and function of the terrestrial Arctic in the climate system and assess the influence of its changes on a global scale, this model intercomparison project (GTMIP) is designed to (1) enhance communication and understanding between the modelling and field scientists and (2) assess the uncertainty and variations stemming from variability in model implementation/design and in model outputs using climatic and historical conditions in the Arctic terrestrial regions. This paper provides an overview of all GTMIP activity, and the experiment protocol of Stage 1, which is site simulations driven by statistically fitted data created using the GRENE-TEA site observations for the last 3 decades. The target metrics for the model evaluation cover key processes in both physics and biogeochemistry, including energy budgets, snow, permafrost, phenology, and carbon budgets. Exemplary results for distributions of four metrics (annual mean latent heat flux, annual maximum snow depth, gross primary production, and net ecosystem production) and for seasonal transitions are provided to give an outlook of the planned analysis that will delineate the inter-dependence among the key processes and provide clues for improving model performance. Published by CopernicusPublications on behalf of the European Geosciences Union. 2842 S. Miyazaki et al.: GTMIP: overview and experiment protocol for Stage 1 Geosci. Model Dev., 8, 2841-2856, 2015 www.geosci-model-dev.net/8/2841/2015/
Permafrost is a large reservoir of soil organic carbon, accounting for about half of all the terrestrial storage, almost equivalent to twice the atmospheric carbon storage. Hence, permafrost degradation under global warming may induce a release of a substantial amount of additional greenhouse gases, leading to further warming. In addition to gradual degradation through heat conduction, the importance of abrupt thawing or erosion of ice-rich permafrost has recently been recognized. Such ice-rich permafrost has evolved over a long timescale (i.e., tens to hundreds of thousands of years). Although important, knowledge on the distribution of vulnerability to degradation, i.e., location and stored amount of ground ice and soil carbon in ice-rich permafrost, is still limited largely due to the scarcity of accessible in situ data. Improving the future projections for the Arctic using the Earth System Models will lead to a better understanding of the current vulnerability distribution, which is a prerequisite for conducting climatic and biogeochemical assessment that currently constitutes a large source of uncertainty. In this study, present-day circum-Arctic distributions (north of 50°N) in ground ice and organic soil carbon content are produced by a new approach to combine a newly developed conceptual carbon-ice balance model, and a downscaling technique with the topographical and hydrological information derived from a high-resolution digital elevation model (ETOPO1). The model simulated the evolution of ground ice and carbon for the recent 125 thousand years (from the Last Interglacial to the present) at 1°resolution. The 0.2°high-resolution circum-Arctic maps of the present-day ground ice and soil organic carbon, downscaled from the 1°simulations, were reasonable compared to the observationbased previous maps. These data, together with a map of vulnerability of ice-rich permafrost to degradation served as initial and boundary condition data for model improvement and the future projection of additional greenhouse gas release potentially caused by permafrost degradation.
Abstract. The degradation of permafrost is a large source of uncertainty in understanding the behaviour and projecting the future impacts of Earth's climate system. The spatial distributions of soil organic carbon (SOC) and ground ice (ICE) provide essential information for the assessment and projection of risks and impacts of permafrost degradation. However, uncertainties regarding the geographical distribution and estimated range of the total amount of stored carbon and ice are still substantial. A numerical soil organic carbon–ground ice budget model, SOC-ICE-v1.0, that considers essential aspects of carbon and hydrological processes in above-ground and subsurface environments and permanently frozen ground (permafrost) and land cover changes (ice sheets and coastlines) was developed to calculate the long-term evolution of local SOC and ICE. The model was integrated to cover the last 125 kyr – from the last interglacial to date for areas north of 50∘ N at 1∘ resolution – to simulate the balance between accumulation and dissipation of SOC 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 timescale. 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, consist 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 represented by a key parameter that reflects 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. Examples of 1∘ resolution maps for the Last Glacial Maximum and mid-Holocene periods were provided. Despite a simple modelling framework, SOC-ICE-v1.0 provided substantial information on the temporal evolution and spatial distribution of circum-Arctic SOC and ICE. Model improvements in terms of forcing climate data, improvement of SOC and ICE dynamics, and choice of initial values are, however, required for future research.
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