PINS

The dataset is based on a selection of regional simulations from the NA-CORDEX and Ouranos ensembles and considers the models’ ability to reproduce the seasonality of snow cover in southern Quebec. The diversity of regional models and global drivers was maintained in the final selection in order to cover a good portion of the uncertainties related to imperfections in climate models. This combination of performance and diversity strengthens the robustness of the results.

Snow cover influences many socio-economic sectors in the northern climate, including hydrology, transport, agriculture, hydroelectricity, infrastructure and winter tourism. The warming climate has already begun to impact this component of the cryosphere. Having a dataset developed specifically for this variable makes it possible to anticipate potential impacts and to target adaptation strategies. 

The dataset also offers several common snow cover indicators, which are listed above. Intuitive and user-friendly, these indicators are all derived from snow water equivalent, the most commonly used unit of measurement in the scientific literature.

The common practice in climate services is to correct the bias of climate simulations to make them compatible with impact models and field applications. However, very little research exists on methods for correcting bias in snow water equivalent, which hinders the development and publication of corrected datasets. The PINS dataset has overcome this obstacle, which is an innovation in the field.