EGU24-14970, updated on 09 Mar 2024
https://doi.org/10.5194/egusphere-egu24-14970
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Bias-corrected high-resolution temperature and precipitation projections for Canada 

Chandra Rupa Rajulapati1, Hebatallah Mohamed Abdelmoaty2, Sofia Nerantzaki3, and Simon Michael Papalexiou2,4
Chandra Rupa Rajulapati et al.
  • 1University of Manitoba, Winnipeg, Canada (chandra.rajulapati@umanitoba.ca)
  • 2University of Calgary, Calgary, Canada (heba.abdelmoaty@ucalgary.ca, simon.papalexiou@ucalgary.ca)
  • 3University of Saskatchewan, Saskatoon, Canada (sofia_ner@hotmail.com)
  • 4Czech University of Life Sciences, Prague (simon.papalexiou@ucalgary.ca)

High-resolution precipitation and temperature projections are indispensable for informed decision-making, risk assessment, and planning. Here, we have developed an extensive database of high-resolution (0.1°) precipitation, maximum, and minimum 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 distinct Shared Socio-economic Pathways. SPQM is simple, yet robust, in reproducing the observed marginal properties, trends, and variability according to future scenarios, and maintaining a smooth transition from observations to projected simulations. The database encompasses a substantial collection of 759 simulations derived from 37 diverse climate models for precipitation. Similarly, for maximum and minimum temperature projections, our database comprises 652 simulations from 30 climate models. These meticulously curated projections carry immense value for hydrological, environmental, and ecological studies, offering a comprehensive resource for analyses within these domains. Furthermore, these projections serve as a valuable asset for the quantification of uncertainties arising from variant labels, climate models, and future scenarios.

How to cite: Rajulapati, C. R., Abdelmoaty, H. M., Nerantzaki, S., and Papalexiou, S. M.: Bias-corrected high-resolution temperature and precipitation projections for Canada , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14970, https://doi.org/10.5194/egusphere-egu24-14970, 2024.