Tundra Nunavik: Set of 27 interpolated bioclimate variables derived from the NCEP climate system reanalysis for Labrador and northern Quebec for the period 1981-2010

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).尽管绝大多数生态学研究均围绕气候变化对特定种群或物种的影响展开，但学界仍亟需更具全局性的基于生态系统的信息，以更精准地预测北极地区的未来状态。为此，我们开展了一项大规模研究，旨在通过建模手段刻画苔原生态系统对气候变化的脆弱性。作为本研究的一部分，我们获取了基准期（1981年-2010年）内，北纬50度以北魁北克省的气候相关变量，空间分辨率为高精度的10km×10km网格单元。由于北部地区气象站点匮乏，这一数据获取环节面临极大挑战。 原始气候数据（1981年1月至2010年12月的逐月最低气温、最高气温与总降水量）源自美国国家环境预报中心（National Centers for Environmental Prediction, NCEP）的气候预报系统再分析数据集（Climate Forecast System Reanalysis, CFSR）（Saha等，2010；数据可从https://rda.ucar.edu/datasets/ds093.1获取）。我们基于这些原始栅格图层，推导并通过自然邻域插值法（Natural neighbor interpolation，详见补充文档章节）生成了27项年度气候变量，涵盖年平均气温、年总降水量、最冷/暖/干/湿月的气温与降水量、生长度日/冻结度日、生长季/冻结期相关日期以及水量平衡等（完整变量列表参见补充文档章节）。最终，我们对年度数值取平均，构建出基准期（1981年-2010年）的气候基准值数据集。本研究生成的27项气候栅格图层均采用10km×10km的空间分辨率，格式为网络通用数据格式（NetCDF）（关于如何在R语言中使用NetCDF文件，请参见补充文档章节）。