StableClim

StableClim V1.0.1Dataframes for the results of the global and regional regressions under pre-industrial, past, and historical/RCP conditions are stored as data.tables in named lists in a compressed RDS format.The gridded datasets have been created as NetCDF files. A geopackage containing the aggregated IPCC regions and the Wallace zoogeographic regions and realms can also be found in the ‘gpkg’ folder within StableClim.The naming convention for the results of the global and regional regressions is:StableClim__.RDSwhere scenario is the name of the scenario (piControl, past, spliced historical), and var represent either global and regional regression thresholds for the pre-industrial control simulation, or the slopes for global/regional temperature regressions for the past and historical/RCP data.The naming convention for the ensemble mean monthly data is:StableClim_MonthlyEnsemble__.ncand for the regression files:StableClim_Regression__.ncwhere scenario is the name of the scenario (past, spliced historical RCP 2.6 – RCP 8.5), and var is pr (precipitation) or ts (air temperature).The monthly ensemble temperature and precipitation have the following dimensions – 72 x latitude, 144 x longitude, 3012 x months. The units for the monthly ensembles are pr = mm/day, ts = °C. Each of the regression files contains three record variables: (1) = Trend, (2) = Variability, (3) = Signal:Noise ratio. These record variables have the following dimensions – 72 x latitude, 144 x longitude, and year [20,902 for the past, 251 for the historical/RCP]. Units for the regressions are pr = mm/year, ts = °C/year.Change log:2020-08-04 - Updated to StableClim v 1.0.1 - Climate change thresholds had been incorrectly calculated during bootstrapping. The thresholds have now been bootstrapped correctly and updated as appropriate.- CSV files for global and regional regressions are now also provided in a gzip archive [GlobalRegionalThresholdsRegressions.tar.gz].- An R tutorial is now provided [StableClim-Tutorial.pdf] which shows how to extract, subset, plot, and calculate pattern scaled trends from the data contained in StableClim.

StableClim V1.0.1 数据框中存储了工业革命前、历史时期以及历史/RCP条件下的全球及区域回归结果，这些数据以压缩的 RDS 格式组织于命名列表中。网格化数据集已被创建为 NetCDF 文件。包含综合 IPCC 区域、Wallace 动物地理区及领域的地理包件亦可在 StableClim 的 'gpkg' 文件夹中找到。全球及区域回归结果之命名规范为：StableClim__.RDS，其中场景（piControl、past、spliced historical）为场景名称，var 代表工业革命控制模拟的全球及区域回归阈值，或过去及历史/RCP 数据的全球/区域温度回归的斜率。集合平均月度数据之命名规范为：StableClim_MonthlyEnsemble__.nc，回归文件之命名规范为：StableClim_Regression__.nc，其中场景（past、spliced historical RCP 2.6 – RCP 8.5）为场景名称，var 为 pr（降水量）或 ts（空气温度）。月度集合温度及降水量具有以下维度：72 x 纬度，144 x 经度，3012 x 月份。月度集合的单位为 pr = 毫米/天，ts = 摄氏度。每个回归文件包含三个记录变量：（1）趋势，（2）变异性，（3）信号与噪声比。这些记录变量具有以下维度：72 x 纬度，144 x 经度，以及年份 [20,902 为过去，251 为历史/RCP]。回归的单位为 pr = 毫米/年，ts = 摄氏度/年。变更日志：2020-08-04 - 更新至 StableClim v 1.0.1 - 在引导过程中，气候变化阈值计算出现错误。现已正确引导阈值并相应更新。- 全球及区域回归的 CSV 文件现在也以 gzip 存档提供 [GlobalRegionalThresholdsRegressions.tar.gz]。- 提供了 R 教程 [StableClim-Tutorial.pdf]，展示了如何从 StableClim 数据中提取、子集、绘图和计算模式缩放趋势。