DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D3, Vertical level sfc, Global model MPI-ESM1-2-HR, scenario ssp245 - 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项目中针对五个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。项目详情可访问官网：https://distender.eu/the-project。本次统计降尺度所用的输入数据集，源自三款经参数分位数映射法（Parametric quantile mapping）完成偏差校正的全球气候模型的输出结果。 关于研究区域、所提供的变量、层级及时段的更多细节，请参见README文件。