Bias adjustment is commonly applied to adjust results from climate models to make them compatible with impact models and for calculations of climate indicators. The issues arise from systematic deviations at regional and seasonal scales in climate model compared to observations. The core of a bias adjustment is an algorithm that transfers the model values toward a reference, often using a distribution of vales.The MIdAS (MultI-scale bias AdjuStment) method has been developed for bias adjustment at SMHI. A literature study was performed by a core group of researchers in different fields within SMHI to define the state-of-the-art in bias adjustment. With a focus on the main disciplines of SMHI (meteorology, hydrology and oceanography) and the parameters involved, a method for evaluation of historical and future performance was designed and applied to regions within Sweden and in several regions around the globe. The evaluation of multiple common bias adjustment methods showed that relatively simple methods perform equally well or even better than more intricate methods, besides a larger impact on the magnitude of climate change signals in some cases. The implementation of MIdASv0.1 performs generally equally and sometimes better than other analysed methods.