DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D3, Vertical level sfc, Global model MPI-ESM1-2-HR, scenario Historical - 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项目中应用统计降尺度（statistical downscaling）技术，针对五个案例研究生成的局地（高分辨率）气候数据。项目相关详情可访问：https://distender.eu/the-project。 该统计降尺度数据集源自三个已完成偏差校正的全球气候模式的输出结果，校正采用参数分位数映射（Parametric quantile mapping）方法。 有关研究区域、所提供的变量、层级及时段的更多详细信息，请参见自述文件（README）。