Impacts potentiels d’un changement climatique sur le pergélisol dans le nord canadien

This thesis explores the potential impacts of a climate change due to the greenhouse gases on the state and the evolution of the permafrost in the Canadian North. The permafrost represents the half of the Canadian national territory and a change of its current state will echo in all spheres of activity, on the biosphere and on the environment generally. In spite of the evident importance of the subject, there is no precise idea as to how the permafrost will react to the climate change and to what extent the frozen layer will be disrupted. This thesis investigates this problem by using a methodological approach inspired by the Canadian model on the evolution of permafrost (TTOP) coupled with a theoretical approach based on the theory of the complex neuronal systems.   The general objective of this thesis is to improve the Canadian model of evolution of permafrost (TTOP-Temperature one the Top Of Permafrost) created by Smith and Riseborough in 1996, its structure of computation, spatial resolution and to determine the state of the permafrost in the study area between 2010 and 2100. The study zone is situated in the Mackenzie Basin (N-W.T) on a north-south transect of 1440 by 720 km. The first objective of the research is to derive maps of the annual values of temperature on the top of the permafrost from 2010 to 2100 by using an improved dynamic model of the evolution of permafrost (TTOP-A). Thereafter, these values are compared with those obtained by Smith and Riseborough (1996). The values of the evolution of air temperature for this period are supplied by the climatic scénarios CGCM3  SRES A1B, CGCM3 SRES A2 and CGCM3 SRES B1. Secondly, this thesis has as an objective the production of the maps of the thickness of permafrost for 2100 with a spatial resolution of 25 km. More exactly, we determine the evolution of the values of thickness of permafrost for the three climatic scénarios mentioned above. Furthermore, the study proposes: i) a new method for downscaling of climate data by using a Determined Stochastic Model, ii) the integration of soil type, iii) the integration of the soil humidity, iv) the integration of the values of thickness of the snow layer and v) the integration of remote sensing data (SSM/I).  As a rule, the results obtained by the TTOP-A model reveal that the mean values of temperature at the surface of the permafrost follow closely the values of air temperature and that they are similar to those found by Smith and Riseborough (1996) and Heginbottom and coll. (1995). Also, the differences of the values of temperature on the surface of permafrost between 2010 and 2100 are similar to the values published by the Intergovernmental Panel on Climate Change (IPCC). Concerning the second objective of this thesis, the spatio-temporal dynamics of the permafrost until 2100 demonstrates that, in the study zone, the surface perturbed by global warming will be 37 %, 60 % and 29 % according to the scénarios CGCM3 SRES A1B, CGCM3 SRES A2 and CGCM3 SRES B1 respectively. The permafrost layer inside this zone will disappear by 20 %, 32 % and 18 % according to the scénarios mentioned before. These results lead us to believe that the estimations made by Smith and Riseborough were overvalued in the context of two of three current climates scénarios compared to that of the 1996. Finally, this study demonstrates that the method of downscaling of climate data using the neuronal network within a Determined Stochastic Model gives good results and it represents a reliable option which lends itself to large-scale generalizations.

Keyphrases: TTOP, permafrost, downscaling, snow, soil humidity, climate scenario, neuronal network, Determined Stochastic Model, climate change, CGCM3