Snowmelt detection using QuikSCAT over Eastern Canada during the 2000-2009 period

Snow cover plays a key role in the climate system by influencing the transfer of energy, gas and mass between the soil and the atmosphere. In particular, the amount of snow water equivalent (SWE) accumulated in a snowpack and the characteristics of the snowmelt (e.g. frequency, timing, and intensity) are of particular importance for hydrologic and climate processes. This is particularly true under the present warming climate with increasing occurrence of winter rain episodes and early snowmelt. This study presents an analysis of snowmelt detection using QuikSCAT data over Québec, Canada, with the optimization of a backscattering coefficient threshold on every grid point. This method makes use of a dynamic empirical threshold linked to the mean backscattering coefficient by a linear function during winter prior to snowmelt. This can be shown by the effect of winter mean temperatures driving the surface conditions specific to every winter, which have a significant impact on the mean backscattering coefficient. Results are compared to snow simulations from the SNOWPACK model driven by the North American Regional Reanalysis (NARR) data and validated at various locations where field observations are available.