Impact of bias correction and downscaling through quantile mapping on simulated climate change signal: a case study over Central Italy

  • Lorenzo Sangelantoni
  • Aniello Russo
  • Fabio Gennaretti
Original Paper


Quantile mapping (QM) represents a common post-processing technique used to connect climate simulations to impact studies at different spatial scales. Depending on the simulation-observation spatial scale mismatch, QM can be used for two different applications. The first application uses only the bias correction component, establishing transfer functions between observations and simulations at similar spatial scales. The second application includes a statistical downscaling component when point-scale observations are considered. However, knowledge of alterations to climate change signal (CCS) resulting from these two applications is limited. This study investigates QM impacts on the original temperature and precipitation CCSs when applied according to a bias correction only (BC-only) and a bias correction plus downscaling (BC + DS) application over reference stations in Central Italy. BC-only application is used to adjust regional climate model (RCM) simulations having the same resolution as the observation grid. QM BC + DS application adjusts the same simulations to point-wise observations. QM applications alter CCS mainly for temperature. BC-only application produces a CCS of the median ~ 1 °C lower than the original (~ 4.5 °C). BC + DS application produces CCS closer to the original, except over the summer 95th percentile, where substantial amplification of the original CCS resulted. The impacts of the two applications are connected to the ratio between the observed and the simulated standard deviation (STD) of the calibration period. For the precipitation, original CCS is essentially preserved in both applications. Yet, calibration period STD ratio cannot predict QM impact on the precipitation CCS when simulated STD and mean are similarly misrepresented.

Supplementary material

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Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2018

Authors and Affiliations

  1. 1.CETEMPS, Department of Physical and Chemical SciencesUniversità dell’AquilaL’AquilaItaly
  2. 2.Department of Life and Environmental SciencesUniversità Politecnica delle MarcheAnconaItaly
  3. 3.NATO STO Centre for Maritime Research and ExperimentationLa SpeziaItaly
  4. 4.Université de Lorraine, AgroParisTech, INRA, UMR1434 SilvaNancyFrance

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