DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D0, Vertical level 2000m, Global model MPI-ESM1-2-HR, scenario ssp585 - 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项目中针对五项案例研究，采用统计降尺度（statistical downscaling）技术生成的局地高分辨率气候数据。项目详情可参见官网：https://distender.eu/the-project。该统计降尺度数据集的数据源为三个经过偏差校正（参数分位数映射法（Parametric quantile mapping））的全球气候模型的输出结果。 有关研究区域、所提供变量、层级及时段的详细信息，请参见README文件。