ABoVE: Landsat tundra greenness and summer air temperatures, Arctic tundra biome, 1985-2016

Rapid climate warming is impacting tundra ecosystems, but much remains unclear about the nature and extent of recent ecological change. This dataset provides information on annual tundra greenness and summer air temperatures from 1985 to 2016 across the Arctic tundra biome. Annual tundra greenness was assessed at about 50,000 random vegetated sampling sites using the annual maximum Normalized Difference Vegetation Index (NDVImax) derived from surface reflectance measured by sensors on the Landsat satellites. Summer air temperatures were quantified using the Summer Warmth Index (SWI) derived from an ensemble of five global temperature datasets. This dataset includes tabular data on annual NDVImax and SWI from 1985 to 2016 for each sampling site in the Arctic tundra biome. The dataset also includes raster data quantifying (1) annual SWI from 1985 to 2016; (2) temporal trends in annual NDVImax and SWI from 1985 to 2016 and 2000 to 2016; and (3) temporal correlations between annual NDVImax – SWI during these two periods. These raster data span the Arctic tundra biome at a 50 km resolution. Each component of this dataset includes estimates of uncertainty that were generated using Monte Carlo simulations. The repository also includes all of the scripts developed for the analysis by Berner et al. (2020).快速气候变暖正持续影响苔原生态系统，但学界对近期生态变化的本质与影响范围仍存在诸多认知空白。本数据集提供了1985年至2016年北极苔原生物群区的年度苔原绿度与夏季气温数据。年度苔原绿度通过基于Landsat卫星传感器获取的地表反射率计算得到的年度最大归一化差分植被指数（Normalized Difference Vegetation Index Max, NDVImax），在约5万个随机植被覆盖采样点上完成评估。夏季气温则采用由5套全球气温数据集集合生成的夏季温暖指数（Summer Warmth Index, SWI）进行量化。本数据集包含两类数据：其一为北极苔原生物群区内各采样点1985年至2016年的年度NDVImax与SWI表格数据；其二为栅格数据，具体包括：(1)1985年至2016年的年度SWI；(2)1985年至2016年及2000年至2016年两个时段内年度NDVImax与SWI的时间趋势；(3)上述两个时段内年度NDVImax与SWI间的时间相关性。上述栅格数据以50km的空间分辨率覆盖整个北极苔原生物群区。本数据集的所有组分均包含通过蒙特卡洛（Monte Carlo）模拟生成的不确定性估计值。本数据集仓库还附带了Berner等人（2020）用于本次分析的全部脚本代码。