Abstract
Multi-model ensembles are commonly used to decrease the extent of errors in climate-change projections. This study investigates the magnitude of residual errors in the fifth-generation of the Canadian Regional Climate Model (CRCM5) climate-change representations and proposes a bias-correction method to improve model accuracy. To this end, CRCM5 is used to dynamically downscale two global climate model simulations of the transient climate change for the period 1950–2100 over North America. The CRCM5 is driven in parallel by data from the Canadian Earth System Model (CanESM2) and the Max Planck Institute Earth System Model (MPI-ESM-LR) simulations, based on the historical (1850–2005) and future (2006–2100) RCP 4.5 radiative forcing scenario. The proposed bias correction method is demonstrated to correct the CRCM5 climate-change signal taking into consideration the differences between the model and observations in a historical reference period.
Published Version
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