DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level 10m, 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项目中针对五项案例研究采用统计降尺度技术（statistical downscaling techniques）生成的局地高分辨率气候数据，项目官方网址为https://distender.eu/the-project。该统计降尺度数据集源自三个经过偏差校正的全球气候模型输出结果，校正所用方法为参数分位数映射法（Parametric quantile mapping）。关于研究区域、所提供的变量、层级及时段的详细信息，请参阅README文件。