 The article discusses a bias correction method developed for climate impact modeling within the Intersectoral Impact Model Intercomparison Project, ISIMIP. The goal is to correct simulated historical data for systematic deviations from observations using transfer functions generated to map the distribution of the simulated data to that of the observations. The bias correction method preserves the warming signal and applies it to future projections in the agriculture, water, biome, health, and infrastructure sectors. The proposed methodology is a modification of the transfer function approach used in the Water Model Intercomparison Project, water MIP. The article discusses the potential and limitations of the applied bias correction, including its ability to represent trends in long-term means, but struggles with adjusting variability, which may affect small-scale features or extremes. This article was authored by S. Hempel, K. Freeler, L. Warsawski, and others. We are article.tv, links in the description below.