Comparing snow models under current and future climates over three Nordic catchments: uncertainties and implications for hydrological impact studies

Abstract:

Projected climate change effects on snow hydrology are investigated for the 2041-2060 horizon following the SRES A2 emissions scenario over three catchments in Quebec, Canada. A 16-member ensemble of eight snow models (SM) simulations, based on the high-resolution Canadian Regional Climate Model (CRCM-15km) simulations driven by two realizations of the Canadian Global Climate Model (CGCM3), is established per catchment.

This study aims to compare a range of SMs in their ability at simulating snow processes under current climate, and to evaluate how they affect the assessment of the climate change-induced snow impacts at the catchment scale. The variability of snow processes caused by the use of two SM approaches (degree-day versus mixed degree-day/energy balance) is evaluated, as well as the uncertainty of natural climate variability (CRCM inter-member variability). The simulations in the virtual world cover 1961-1990 in the present period and 2041-2060 in the future period. This virtual world offers a high-resolution coherent dataset with no missing data or inconsistencies in time and in space. The virtual world experiments were compared to the same experiments over a short validation in the real world.

The results show that, when comparing to snow water equivalent (SWE) from the virtual world, all SMs perform similarly at modeling SWE for the reference and future periods. These findings can be extended to the real world, where the SMs lead to a high level of agreement with the observations in reproducing catchment scale snow hydrology.

The results of various snow indicators show that most of the uncertainty arises from natural climate variability followed by the SM. The uncertainty linked to the choice of a SM is larger than that associated with the choice of the SM approach in quantifying the snow hydrology impacts. Overall, the SMs provide a low degree of uncertainty to the total uncertainty in hydrologic modeling for climate change impact studies.

Keywords: CRCM; virtual world; snow water modeling; uncertainty; Canada.