https://doi.org/10.1038/s41597-025-04396-z

Abdelmoaty, Hebatallah M.; Rajulapati, Chandra Rupa; Nerantzaki, Sofia D.; Papalexiou, Simon Michael (2025) Bias-corrected high-resolution temperature and precipitation projections for Canada, Nature, Scientific Data , Data Descriptors, Vol. 12, Iss. 1, Article number: 191, https://doi.org/10.1038/s41597-025-04396-z

High-resolution precipitation and temperature projections are indispensable for informed decision-making, risk assessment, and planning. Here, we have developed an extensive database (SPQM-CMIP6-CAN) of high-resolution (0.1°) precipitation and temperature projections extending till 2100 at a daily scale for Canada. We employed a novel Semi-Parametric Quantile Mapping (SPQM) methodology to bias-correct the Coupled Model Intercomparison Project, Phase-6 (CMIP6) projections for four Shared Socio-economic Pathways. SPQM is simple, yet robust, in reproducing the observed marginal properties, trends, and variability according to future scenarios, while maintaining a smooth transition from observations to projected simulations. The SPQM-CMIP6-CAN database encompasses 693 simulations derived from 34 diverse climate models for precipitation. Similarly, for temperature projections, our database comprises 581 simulations from 27 climate models. These projections are valuable for hydrological, environmental, and ecological studies, offering a comprehensive resource for analyses within these domains. Furthermore, these projections serve as a vital tool for the quantification of uncertainties arising from climate models, their variant configurations, and future scenarios.

https://doi.org/10.1038/s41597-025-04396-z