2026-10-13T16:12:09Z https://www.scidb.cn/oai

10.57760/sciencedb.43536 2026-07-24T17:43:08Z

2026-07-24 A high-resolution monthly future precipitation scenario dataset for the Tibetan Plateau, 2015–2100 doi:10.57760/sciencedb.43536 en The Tibetan Plateau is characterized by pronounced topographic relief and strong spatial heterogeneity in precipitation, while the native spatial resolution of global climate models is insufficient for regional studies of hydrology, the cryosphere, ecosystems, and disaster risk. Based on monthly precipitation data from five CMIP6 global climate models and using the monthly TPMFD precipitation dataset as the historical reference, this study developed a monthly future precipitation scenario dataset for the Tibetan Plateau for 2015–2100 at a spatial resolution of 1/30°. The data-processing workflow included calendar and unit harmonization, area-weighted aggregation of TPMFD to the native grids of the individual models, multiplicative quantile bias correction based on historical empirical distributions, construction of supervised samples through artificial degradation, terrain-conditioned residual U-Net downscaling, and coarse-grid precipitation-consistency adjustment. The dataset covers five models—MRI-ESM2-0, BCC-CSM2-MR, CESM2, NorESM2-MM, and MPI-ESM1-2-LR—and four scenarios: SSP126, SSP245, SSP370, and SSP585. It contains 1,720 annual NetCDF files, each recording 12 months of precipitation, with a total data volume of 13.64 GB. The mean coarse-grid precipitation-consistency MAE across 20,640 monthly records was 0.02 mm·month⁻¹. This dataset provides fundamental data support for studies of future precipitation change, water resources, the cryosphere, ecosystems, and disaster risk over the Tibetan Plateau. Tibetan Plateau; CMIP6; statistical downscaling; TPMFD; U-Net. tian wei liang Liu Fenggui Zhou Qiang Chen Qiong Ma Weidong Shen Qinrui Hu Juanjuan PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank