On the importance of the reference data: Uncertainty partitioning of bias-adjusted climate simulations over eastern Canada
Date
2025
Authors
Lavoie, Juliette
Louis-Philippe, Caron
Logan, Travis
Sobie, Stephen
Turcotte, Richard
Mailhot, Edouard
Pelletier-Dumont, Jasmine
Journal Title
Journal ISSN
Volume Title
Publisher
Climate Services
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.
Description
Keywords
UN SDG 13: Climate Action, #journal article, Pacific Climate Impacts Consortium (PCIC), climate data adaptation, bias-correction, climate simulations, uncertainty, observational reference, reanalysis
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