DISTENDER Climate Simulations: Statistical Downscaling for CMTo_D0, Vertical level 2000m, Global model EC-EARTH3, scenario ssp370 - 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项目针对5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：https://distender.eu/the-project 。本数据集的源输入数据源自3个已完成偏差校正（bias corrected）的全球气候模型输出结果，校正方法为参数分位数映射法（Parametric quantile mapping）。关于研究区域、提供的变量、层级及时段的更多细节，请参见README文件。