The ISI-MIP (Inter-Sectoral Impact Model Intercomparison Project) has developed a bias correction method to address systematic deviations between climate model data and observed climate data, ensuring consistency with global temperature information. The method preserves the absolute changes in monthly temperature and relative changes in monthly precipitation and other variables. It involves two main steps: correcting the monthly means and daily variability around these means. The correction of monthly means uses a constant offset or multiplicative factor to align the simulated and observed data, while the daily variability is adjusted using transfer functions. The method aims to preserve the long-term trend in the climate data, which is crucial for impact projections. The paper discusses the methodology, its application to climate model data, and its evaluation, highlighting both its strengths and limitations, particularly in handling variability and extremes. The ISI-MIP approach is designed to provide consistent impact projections across multiple sectors at different levels of global warming, ensuring that the climate signal is accurately represented.The ISI-MIP (Inter-Sectoral Impact Model Intercomparison Project) has developed a bias correction method to address systematic deviations between climate model data and observed climate data, ensuring consistency with global temperature information. The method preserves the absolute changes in monthly temperature and relative changes in monthly precipitation and other variables. It involves two main steps: correcting the monthly means and daily variability around these means. The correction of monthly means uses a constant offset or multiplicative factor to align the simulated and observed data, while the daily variability is adjusted using transfer functions. The method aims to preserve the long-term trend in the climate data, which is crucial for impact projections. The paper discusses the methodology, its application to climate model data, and its evaluation, highlighting both its strengths and limitations, particularly in handling variability and extremes. The ISI-MIP approach is designed to provide consistent impact projections across multiple sectors at different levels of global warming, ensuring that the climate signal is accurately represented.