Most spatial modelling of climate change impacts on permafrost has been conducted at half-degree latitude/longitude or coarser spatial resolution. At such coarse resolution, topographic effects on insolation cannot be considered accurately and the results are not suitable for land-use planning and ecological assessment. Here we mapped climate change impacts on permafrost from 1968 to 2100 at 10 m resolution using a process-based model for Ivvavik National Park, an Arctic region with complex terrain in northern Yukon, Canada. Soil and drainage conditions were defined based on ecosystem types, which were mapped using SPOT imagery. Leaf area indices were mapped using Landsat imagery and the ecosystem map. Climate distribution was estimated based on elevation and station observations, and the effects of topography on insolation were calculated based on slope, aspect and viewshed. To reduce computation time, we clustered climate distribution and topographic effects on insolation into discrete types. The modelled active-layer thickness and permafrost distribution were comparable with field observations and other studies. The map portrayed large variations in active-layer thickness, with ecosystem types being the most important controlling variable, followed by climate, including topographic effects on insolation. The results show deepening in active-layer thickness and progressive degradation of permafrost, although permafrost will persist in most of the park during the 21st century. This study also shows that ground conditions and climate scenarios are the major sources of uncertainty for high-resolution permafrost mapping

Abstract. Northern peatlands in permafrost regions contain a large amount of organic carbon (C) in the soil. Climate warming and associated permafrost degradation are expected to have significant impacts on the C balance of these ecosystems, but the magnitude is uncertain. We incorporated a permafrost model, Northern Ecosystem Soil Temperature (NEST), into a biogeochemical model, DeNitrificationDeComposition (DNDC), to model C dynamics in highlatitude peatland ecosystems. The enhanced model was applied to assess effects of permafrost thaw on C fluxes of a subarctic peatland at Stordalen, Sweden. DNDC simulated soil freeze-thaw dynamics, net ecosystem exchange of CO 2 (NEE), and CH 4 fluxes across three typical land cover types, which represent a gradient in the process of ongoing permafrost thaw at Stordalen. Model results were compared with multiyear field measurements, and the validation indicates that DNDC was able to simulate observed differences in seasonal soil thaw, NEE, and CH 4 fluxes across the three land cover types. Consistent with the results from field studies, the modeled C fluxes across the permafrost thaw gradient demonstrate that permafrost thaw and the associated changes in soil hydrology and vegetation not only increase net uptake of C from the atmosphere but also increase the annual to decadal radiative forcing impacts on climate due to increased CH 4 emissions. This study indicates the potential of utilizing biogeochemical models, such as DNDC, to predict the soil thermal regime in permafrost areas and to investigate impacts of permafrost thaw on ecosystem C fluxes after incorporating a permafrost component into the model framework.

Abstract. Spatially detailed information on permafrost distribution and change with climate is important for land use planning, infrastructure development, and environmental assessments. However, the required soil and surficial geology maps in the North are coarse, and projected climate scenarios vary widely. Considering these uncertainties, we propose a new approach to mapping permafrost distribution and change by integrating remote sensing data, field measurements, and a process-based model. Land cover types from satellite imagery are used to capture the general land conditions and to improve the resolution of existing permafrost maps. For each land cover type, field observations are used to estimate the probabilities of different ground conditions. A process-based model is used to quantify the evolution of permafrost for each ground condition under three representative climate scenarios (low, medium, and high warming). From the model results, the probability of permafrost occurrence and the most likely permafrost conditions are determined. We apply this approach at 20 m resolution to a large area in Northwest Territories, Canada. Mapped permafrost conditions are in agreement with field observations and other studies. The data requirements, model robustness, and computation time are reasonable, and this approach may serve as a practical means to mapping permafrost and changes at high resolution in other regions.

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