DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D0, Vertical level 2000m, Global model MPI-ESM1-2-HR, scenario ssp126 - The Metropolitan City of Turin (CMTo, Italy)

Local (high resolution) climate data produced applying statistical downscaling techniques in the EU Project DISTENDER for five case studies. https://distender.eu/the-project . The datasets from the statistical downscaling come from the outputs of three global climate models that have been bias corrected (Parametric quantile mapping). More details about the domains, the provided variable, levels and periods are provided in the README file.本数据集为欧盟DISTENDER项目中针对五个案例研究，采用统计降尺度（statistical downscaling）技术生成的局地高分辨率气候数据。项目官方网址：https://distender.eu/the-project。该统计降尺度数据集的数据源为三款经过偏差校正的全球气候模型（global climate model）输出结果，校正方法采用参数分位数映射法（Parametric quantile mapping）。有关研究区域、提供的变量、层级及时段的详细信息，请参阅README文件。