Monitoring of the ground surface temperature and the active layer in NorthEastern Canadian permafrost areas using remote sensing data assimilated in a climate land surface scheme.

Tuesday, 16 December 2014
Nicolas Marchand1, Alain Royer1, Gerhard Krinner2 and Alexandre Roy1, (1)University of Sherbrooke, Sherbrooke, QC, Canada, (2)LGGE Laboratoire de Glaciologie et Géophysique de l’Environnement, Saint Martin d'Hères, France
Projected future warming is particularly strong in the Northern high latitudes where increases of temperatures are up to 2 to 6 °C. Permafrost is present on 25 % of the northern hemisphere lands and contain high quantities of « frozen » carbon, estimated at 1400 Gt (40 % of the global terrestrial carbon).

The aim of this study is to improve our understanding of the climate evolution in arctic areas, and more specifically of land areas covered by snow. The objective is to describe the ground temperature year round including under snow cover, and to analyse the active layer thickness evolution in relation to the climate variability. We use satellite data (fusion of MODIS land surface temperature « LST » and microwave AMSR-E brightness temperature « Tb ») assimilated in the Canadian Land Surface Scheme (CLASS) of the Canadian climate model coupled with a simple radiative transfer model (HUT). This approach benefits from the advantages of each of the data type in order to complete two objectives : 1- build a solid methodology for retrieving the ground temperature, with and without snow cover, in taïga and tundra areas ; 2 – from those retrieved ground temperatures, derive the summer melt duration and the active layer depth.

We describe the coupling of the models and the methodology that adjusts the meteorological input parameters of the CLASS model (mainly air temperature and precipitations derived from the NARR database) in order to minimise the simulated LST and Tb ouputs in comparison with satellite measurements. Using ground-based meteorological data as validation references in NorthEastern Canadian tundra, the results show that the proposed approach improves the soil temperatures estimates when using the MODIS LST and Tb at 10 and 19 GHz to constrain the model in comparison with the model outputs without satellite data. Error analysis is discussed for the summer period (2.5 - 4 K) and for the snow covered winter period (2 – 3.5 K). Further steps are described to apply this methodology over a taiga environment, as we have to take into account the vegetation effects in the radiative transfer.

A better understanding of the permafrost evolution processes, and particularly the impact of the snow cover should enable us to better apprehend the impact of the global warming on the melt of permafrost and the futur of their carbon stock.