While most ecological studies focus on the impact of climate change on some populations or species, broader, ecosystem-based information is needed to better predict the future state of the Arctic. We therefore conducted a large-scale study aimed at characterizing the vulnerability of tundra ecosystems to climate change through modelling. As part of this study, we obtained variables describing the climate of the province of Québec north of the 50th parallel during our baseline period (1981-2010) at a fine resolution (10km x 10km grid cells). This step was particularly difficult due to the lack of meteorological stations in the North.
Raw climate data (monthly minimum and maximum temperatures and total precipitation from January 1981 to December 2010) come from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) (Saha et al. 2010; data available at https://rda.ucar.edu/datasets/ds093.1). From these raw layers we derived and interpolated (Natural neighbor interpolation, see the Supplementary documentation section for further details) 27 annual climate variables, including mean annual temperature, total annual precipitation, temperature/precipitation of the coldest/warmest/driest/wettest month, growing/freezing degree-days, growing/freezing dates, and water balance(see exhaustive list in the Supplementary documentation section) . Finally, we averaged annual values to build climate normals for our baseline period (1981-2010). The 27 climate layers are available at a 10km x 10km spatial resolution in at the NetCDF format (see the Supplementary documentation section to use the NetCDF file with R).
