Fine-scale variation in projected climate change presents opportunities for biodiversity conservation in Europe

We use a multi-model ensemble of regional climate models to identify areas with significantly high and low climate stability persistent throughout the 21^st century in Europe. Here we present a set of raster files that contain discrete zones of climatic stability and instability, also referred to as hotspots and coldspots. Our analysis of future climatic stability was based on projected changes of nine climate variables selected to proxy key aspects of terrestrial ecosystem dynamics. The underlying climate projection, including different indices, are available at https://zenodo.org/record/3952159#.YNWN_OgzaUl. The cumulative change of all nine climate variables, termed Aggregate Climate Change (ACC), is used to identify regions of significantly higher or lower climatic stability (Getis-Ord Gi* p-value &lt; 0.05) across Europe. We carry out this assessment at the continental and regional scales. While the continental assessment reports the large-scale latitudinal and orographic patterns of climatic stability, the regional assessment explores the residual ACC variation that remained after extracting the large-scale continental trend. The raster files present climatic features that were identified to persist in their location throughout the 21^st century (i.e., in periods 2021-2040, 2041-2060, and 2061-2100) and were supported by a majority of climate projections considered in this study. Specifically, we considered five GCM-RCM pairs driven by two RCP scenarios, RCP4.5 and RCP8.5. The targeted areas of climatic stability were required to be confirmed by four out of five climate models nested within each RCP, at least. The used naming convention is as follows: Scale – Global, Regional Type of the zone – HotSpot (zone of significantly low climatic stability), ColdSpot (zone of significantly high climatic stability) Driving RCP scenario – RCP45, RCP85 Raster files with RCP indicated in their name refer to either RCP4.5 or RCP8.5. These files contain two values referring to the presence (1) or absence (0) of climatic stability areas: Global_HotSpots _RCP45 Global_ColdSpots _RCP45 Regional_HotSpots _RCP45 Regional_ColdSpots _RCP45 Global_HotSpots _RCP85 Global_ColdSpots _RCP85 Regional_HotSpots _RCP85 Regional_ColdSpots _RCP85 Raster files without RCP code in their name contain combinations of both RCPs. The cell values indicate absence (0), presence in RCP4.5 OR RCP8.5 (1), or presence in RCP4.5 AND RCP8.5 (2) of climatic stability areas: Global_HotSpots Global_ColdSpots Regional_HotSpots Regional_ColdSpots The format of raster files is tiff. All data are in the GCS_WGS_1984 geographic coordinate system.本研究采用多模式集合的区域气候模型，识别出21世纪欧洲范围内气候稳定性显著偏高与偏低的持续区域。本研究公开一组栅格文件，其中包含气候稳定与不稳定的离散分区，二者亦分别被称为热点区（hotspots）与冷点区（coldspots）。 本研究针对未来气候稳定性的分析，基于9个经遴选用于表征陆地生态系统动态关键特征的气候变量的预估变化展开。本研究所用的基础气候预估数据（含各类气候指数）可通过以下链接获取：https://zenodo.org/record/3952159#.YNWN_OgzaUl。 本研究将9个气候变量的累积变化定义为总气候变化（Aggregate Climate Change, ACC），以此识别欧洲范围内气候稳定性显著偏高或偏低的区域（盖西斯-奥德Gi*统计量p值<0.05）。本研究分别在大陆尺度与区域尺度开展该项评估：其中，大陆尺度评估可揭示气候稳定性的大尺度纬度与地形格局，而区域尺度评估则探究剔除大尺度大陆趋势后剩余的总气候变化（ACC）变异。 本次公开的栅格文件所呈现的气候特征，需满足在21世纪（即2021-2040年、2041-2060年及2061-2100年三个时段）内持续稳定分布，且得到本研究所用多数气候预估结果的支撑。具体而言，本研究采用由两种典型浓度路径（Representative Concentration Pathway, RCP）——RCP4.5与RCP8.5——驱动的5组全球-区域气候模型（General Circulation Model-Regional Climate Model, GCM-RCM）耦合试验数据。目标气候稳定区域需至少通过每个典型浓度路径下5个气候模型中的4个的验证。 本研究采用如下命名规则： 1. 尺度：全球（Global）、区域（Regional） 2. 分区类型：热点区（HotSpot，气候稳定性显著偏低的区域）、冷点区（ColdSpot，气候稳定性显著偏高的区域） 3. 驱动典型浓度路径：RCP45、RCP85 文件名中包含RCP标识的栅格文件对应单一典型浓度情景（RCP4.5或RCP8.5），此类文件仅包含两个取值：1代表存在气候稳定区域，0代表不存在。对应文件命名如下：Global_HotSpots_RCP45、Global_ColdSpots_RCP45、Regional_HotSpots_RCP45、Regional_ColdSpots_RCP45、Global_HotSpots_RCP85、Global_ColdSpots_RCP85、Regional_HotSpots_RCP85、Regional_ColdSpots_RCP85。 文件名中未包含RCP标识的栅格文件则对应两种典型浓度路径的组合情景，其栅格单元取值含义如下：0代表不存在气候稳定区域，1代表仅在RCP4.5或RCP8.5情景下存在气候稳定区域，2代表在RCP4.5与RCP8.5两种情景下均存在气候稳定区域。对应文件命名如下：Global_HotSpots、Global_ColdSpots、Regional_HotSpots、Regional_ColdSpots。 本次公开的栅格文件格式为TIFF，所有数据均采用GCS_WGS_1984地理坐标系。