A bias correction method designed for weather and climate extremes / Andrew Dowdy

"While weather and climate models have generally shown improvement over time in their simulation of physical processes, their output data can still contain some systematic biases. These biases can relate to a wide range of factors, such as model resolution typically being coarser than the scale of some physical processes (including for convection, turbulence, orographic features, etc.). To help with the use of data in practical applications, methods for bias correction (or sometimes also called bias adjustment) can be applied for post processing the model outputs. There are numerous different types of methods available for bias correction, including that can be applied across various spatio-temporal scales, as described in studies such as Teutschbein and Seibert (2012), Maraun et al. (2017) and references therein. This report describes the QME method for bias correction that has been developed specifically for application to weather and climate model data, including with attention to detail for considering how extremes are handled."--Introduction.