Towards process-informed bias correction of climate change simulations
Maraun D, Shepherd T, Widmann M, Zappa G, Walton D, Gutierrez JM, Hagemann S, Richter I, Soares PMM, Hall A, Mearns L
Nature Climate Change, 7:764–773, doi:10.1038/nclimate3418
Climate scientists are confronted with a growing pressure to support adaptation decisions and face the dilemma of operationalizing what is still foundational research. The models often used to inform adaptation decisions global coupled atmosphere ocean general circulation models (GCMs), potentially downscaled with regional climate models (RCMs)have horizontal resolutions often far coarser than those demanded, and suffer from substantial biases. To reduce biases and to overcome the scale gap between the numerical model grid and the desired scale, climate model output is almost routinely post-processed by bias correction (often called bias adjustment) methods.