Northern Hemisphere Monthly Downscaled Snow Depth (NHMSD) Datasets at 0.05° Resolution from 21 CMIP6 Models for Ski Seasons

Accurate snow depth datasets are crucial for advancing the winter tourism industry, especially for ski industry planning, amidst rapid climate change. This study combines the delta and snow cover probability-based downscaling methods to generate monthly downscaled 0.05° ski season snow depth datasets for the northern hemisphere (NHMSD), using 21 major general circulation models and four shared socioeconomic pathways from the Sixth Coupled Model Intercomparison Project, covering 1980–2014 (historical) and 2015–2100 (projected). Validation with 1965 ground snow depth observations demonstrated that NHMSD outperformed reanalysis datasets, including the European Centre for Medium-Range Weather Forecasts Reanalysis 5-Land and the Global Land Data Assimilation System, in terms of root mean square error, bias, and mean absolute error for 1980–2014 and 2015–2023. Moreover, spatiotemporal analysis using NHMSD projects ski season snow depth to increase during the ski season in Eastern Eurasia and decrease in North America. These findings provide valuable insights for Northern Hemisphere snow depth changes, which are beneficial for the planning of snow-related industries, such as ski resort site selection. Due to data upload size limitation, we provide DOIs for different modal data of NHMSD in (NHMSD 1980-2100.txt), which can be downloaded by users as needed.