DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D3, Vertical level 10m, 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（EU Project DISTENDER）针对5个案例研究，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：https://distender.eu/the-project。 该统计降尺度数据集的原始数据来自3款全球气候模式（global climate models）的输出结果，并已通过参数分位数映射法（Parametric quantile mapping）完成偏差校正。 关于研究区域、所提供的变量、层级及时段的更多详细信息，请参见README文件。