On the need of bias adjustment for more plausible climate change projections of extreme heat

The assessment of climate change impacts in regions with complex orography and land-sea interfaces poses a challenge related to shortcomings of global climate models. Furthermore, climate indices based on absolute thresholds are especially sensitive to systematic model biases. Here we assess the effect of bias adjustment (BA) on the projected changes in temperature extremes focusing on the number of annual days with maximum temperature above 35 degrees C. To this aim, we use three BA methods of increasing complexity (from simple scaling to empirical quantile mapping) and present a global analysis of raw and BA CMIP5 projections under different global warming levels. The main conclusions are (1) BA amplifies the magnitude of the climate change signal (in some regions by a factor 2 or more) achieving a more plausible representation of future heat threshold-based indices; (2) simple BA methods provide similar results to more complex ones, thus supporting the use of simple and parsimonious BA methods in these studies.

Automated summary

The study demonstrates that bias adjustment can amplify the magnitude of climate change signals, resulting in a more credible representation of future heat threshold indices. Simple bias adjustment methods can provide similar results to more complex ones, supporting the use of simple and parsimonious bias adjustment methods in these studies.