DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D1, Vertical level sfc, Global model EC-EARTH3, 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（EU Project DISTENDER）针对五项案例研究，采用统计降尺度技术生成的局地高分辨率气候数据，项目详情可访问：https://distender.eu/the-project。 该统计降尺度后的数据集源自三个经过偏差校正的全球气候模型的输出结果，校正方法采用参数分位数映射法（Parametric quantile mapping）。 有关研究区域、所提供变量、数据层级及时段的详细信息，请参见README文件。