On the importance of the reference data: Uncertainty partitioning of bias-adjusted climate simulations over eastern Canada
| dc.contributor.author | Lavoie, Juliette | |
| dc.contributor.author | Louis-Philippe, Caron | |
| dc.contributor.author | Logan, Travis | |
| dc.contributor.author | Sobie, Stephen | |
| dc.contributor.author | Turcotte, Richard | |
| dc.contributor.author | Mailhot, Edouard | |
| dc.contributor.author | Pelletier-Dumont, Jasmine | |
| dc.date.accessioned | 2026-05-20T18:07:58Z | |
| dc.date.available | 2026-05-20T18:07:58Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Bias-adjusted climate simulations are increasingly disseminated through online platforms to support adaptation actions. However, there is no consensus on an operational framework to choose what to include in these ‘‘decision-ready’’ ensembles and for communicating the related uncertainty. In this paper, we use a systematic approach to assess the uncertainty related to bias-adjusted climate simulations across five dimensions: internal variability, greenhouse gases scenario, global climate model, observational reference and bias-adjustment method. We calculate the fraction of uncertainty associated with each dimension for precipitation-based, temperature-based and multivariate indicators over eastern Canada and focus particularly on three locations: Montréal, Gaspé and Kawawachikamach. The results show that the uncertainty associated with the reference dataset can be very large and in some instances can become the first or second largest source of uncertainty. Using simple examples, we show that the resulting differences could lead to different conclusions with respect to some adaptation solutions or possibly create confusion with users. These results raise questions on the robustness of climate projections distributed through these web platforms and the ethical responsibility of data providers to adequately evaluate and communicate the underlying uncertainty. | |
| dc.description.reviewstatus | Reviewed | |
| dc.description.scholarlevel | Faculty | |
| dc.description.sponsorship | This project was funded by the Government of Quebec through the INFO-Crue research program (project 709120). This paper is part of the ‘‘Building Capacity to Use Climate Data in Decision-Making in Canada’’ project at the Computer Research Institute of Montreal (CRIM) with funding by Environment and Climate Change Canada. | |
| dc.identifier.citation | Lavoie, J., Caron, L., Logan, T., Sobie, S., Turcotte, R., Edouard, M., & Pelletier-Dumont, J. (2025). On the importance of the reference data: Uncertainty partitioning of bias-adjusted climate simulations over eastern Canada. Climate Services, 40, 100619. https://doi.org/10.1016/j.cliser.2025.100619 | |
| dc.identifier.uri | https://doi.org/10.1016/j.cliser.2025.100619 | |
| dc.identifier.uri | https://hdl.handle.net/1828/23909 | |
| dc.language.iso | en | |
| dc.publisher | Climate Services | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | UN SDG 13: Climate Action | |
| dc.subject | #journal article | |
| dc.subject | Pacific Climate Impacts Consortium (PCIC) | |
| dc.subject | climate data adaptation | |
| dc.subject | bias-correction | |
| dc.subject | climate simulations | |
| dc.subject | uncertainty | |
| dc.subject | observational reference | |
| dc.subject | reanalysis | |
| dc.title | On the importance of the reference data: Uncertainty partitioning of bias-adjusted climate simulations over eastern Canada | |
| dc.type | Article |