The Canadian Land Surface Scheme (CLASS) has been applied over the years in coupled and uncoupled (offline) modes at local, regional, and global scales using various forcing datasets. In this study, CLASS is applied at a local scale in the offline configuration to evaluate its performance when driven by the ERA5 reanalysis. Simulated surface energy fluxes, as well as several other water balance components, are investigated at four sites across the Canadian boreal biome. The results from CLASS driven by ERA5 (CLASS-RNL) are compared with available in situ measurements, as well as with results from CLASS driven by observations (CLASS-CTL). Additional simulations are conducted to evaluate the effects of biases in the ERA5 precipitation, where CLASS is forced by ERA5 data, but with ERA5 precipitation being replaced by observed precipitation (CLASS-RNL-ObsP). The results show that simulated surface variables in CLASS-RNL are in good agreement with observations as well as with those simulated in CLASS-CTL. The CLASS-RNL captures well the observed annual cycles of the surface energy and water fluxes, as well as the year-to-year variation of snow depth, soil temperature, and soil moisture. A strong correlation is found between the observed and CLASS-RNL simulated snow depth and soil temperature. Biases in the ERA5 precipitation did not affect the simulation of soil state variables, whereas the simulated surface heat and water fluxes, as well as the snow depth, were significantly affected. For instance, the simulated runoff in CLASS-RNL is much higher than in CLASS-RNL-ObsP and CLASS-CTL at the most humid sites due to significant positive bias in ERA5 precipitation.