Empirical bias correction of global and regional climate models for the meteorological forcing of hydrological models

The aim of this project is to assess the applicability of an innovative approach recently developed by Environment and Climate Change Canada’s Canadian Centre for Climate Modelling and Analysis.

Project details
Scientific program
2020-2025 programming
Theme(s) and priority(s)
Climate Science and Climate Services
Start and duration
June 2022 • 9 months
Project Status
In progress
Principal(s) investigator(s)
Dominic Matte
John Scinocca
Centre Canadien de la modélisation et de l'analyse climatique


The Canadian Centre for Climate Modelling and Analysis (CCCma) wishes to evaluate the improvement brought by the empirical bias correction (EBC) method when scaled by two regional climate models (RCMs), including the Canadian Regional Climate Model (CRCM5). This work will involve complex meteorological, climate and statistical analyses, requiring in-depth knowledge of the physics of the RCMs and the production of regional simulations.

The approach taken in this project is promising because it could provide more realistic meteorological information for hydrological models. Studies on the impact of climate change in hydrology would gain in credibility since the data produced by the RCMs would require fewer adjustments. This innovation could then be used in fields of study other than hydrology, such as agriculture, health, infrastructure or forest fires. 



The primary aim of this project is to assess the applicability of an innovative approach recently developed by Environment and Climate Change Canada’s CCCma. The EBC method applied to their CanESM global climate model improved future climate projections. The application of this method improves the overall data. The data is then used to drive regional climate simulations on a finer scale, with regional climate models (RCMs). The strength of this new approach lies in the use of corrected data as an input and the potential added value to the climate simulated by the RCM. 

This project will also compare the impact of the global CanESM data improved by the EBC method on two RCMs. This will make it possible to assess the added value of simulated meteorological variables used as inputs into hydrological models for producing climate change impact studies. Two RCMs will be considered in this project: the CanRCM5, developed by the CCCma, and the CRCM5, developed in collaboration with UQAM and Environment and Climate Change Canada, and operationalized by Ouranos. 


The research will involve:

  1. The analysis and documentation of the added value in RCM simulations scaled with the new EBC method during the historical period (recent past) 

  2. The analysis and documentation of simulations scaled with the new EBC method in the projections by the CanRCM5 and CRCM5 RCMs

  3. The analysis of the added value of RCMs compared to the global CanESM model

  4. The analysis and evaluation of the additional benefit of applying the EBC method to the RCMs 

This study will focus on the EBC’s improvements to RCM meteorological fields used as inputs into hydrological models, such as surface temperature, precipitation, humidity and wind speed. The study will involve close collaboration between CCCma researchers, the authors of the base method, and researchers from Ouranos. 

Expected results

The expected result of this project is the evaluation of the EBC method, including:

  • Its expected added value compared to uncorrected RCM data 

  • Its ability to replicate the range of future projections

  • Its usefulness for the community as a method to reduce the uncertainty of scaled projections of the future climate 

Benefits for adaptation

Benefits for adaptation

This project will promote the advancement of knowledge on an innovative subject and will address a key issue related to the correction of biases in climate models, since it is these climate models that provide meteorological variables for the hydrological models used to conduct impact studies in hydrology.

The key results will be disseminated to the wider scientific community through Environment and Climate Change Canada data portals and through the Ouranos network of researchers.


Other participants

  • Dominique Paquin, Ouranos

  • Marie-Pier Labonté, Ouranos

  • Slava Kharin, Canadian Centre for Climate Modelling and Analysis

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