Modification of the climate change signal by bias correction

What is it about?

The paper introduces a novel analytical theory of the effect of intensity-dependent model biases on the climate change signal (CCS) of climate statistics. The theory is applied to daily precipitation over the alpine topography and is shown to perform well.

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Why is it important?

The analytical theory describes the effect of one of the most popular bias correction methods including quantile mapping on the climate change signal of climate statistics. It can help understand the modification of the climate change signal due to bias correction, detect model biases with high potential to distort the CCS and can be used to efficiently generate novel, improved CCS datasets. The latter are highly relevant for the development of appropriate climate change adaptation, mitigation, and resilience strategies. The results demonstrate that the CCS modification by bias correction is a direct consequence of removing model biases. Therefore, provided that application of intensity-dependent bias correction is scientifically appropriate, the CCS modification should be a desirable effect.

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