Bias Correction of GCM Precipitation by Quantile Mapping: How Well Do Methods Preserve Changes in Quantiles and Extremes?

By Alex J. Cannon, Stephen Sobie, Trevor Murdock. 2015

1,332 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/d4be1024e3d1151fa6b6bf8dc9863184c30e0589

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. A. Koutroulis
2. S. Lange
3. Peter Troch
4. Ioannis K. Tsanis
5. C. Castro
6. M. Grillakis

In Global and Planetary Change

1. A. Koutroulis
2. S. Lange
3. Peter Troch
4. Ioannis K. Tsanis
5. C. Castro
6. M. Grillakis

Citations in the corpus

• Scaled distribution mapping: a bias correction method that preserves raw climate model projected changes (2016, methodology): “More recently, the standard non-parametric QM method has been adapted to more explicitly preserve the raw modeled climate change signals (Michelangeli et al., 2009; Olsson et al., 2009; Willems and Vrac, 2011; Sunyer et al., 2015; Wang and Chen, 2014; Cannon et al., 2015).”
• Robust bias-correction of precipitation extremes using a novel hybrid empirical quantile-mapping method (2021, methodology): “Bias-correction methods for precipitation range from simple approaches such as the “delta change” or “delta factor” method (Teutschbein and Seibert 2012) to more flexible and effective quantile-mapping based methods (Teutschbein and Seibert 2012; Cannon et al. 2015; Wood et al. 2002).”
• Evaluation of Historical CMIP6 Model Simulations of Seasonal Mean Temperature over Pakistan during 1970–2014 (2020, background): “Many errors were solvable through bias correction techniques; however, biases due to nonlinearity and complex dynamical processes were uncorrectable at the current model developments [55].”
• Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0) (2019, positive): “These days are randomly selected following Cannon et al. (2015): All values below the lower threshold, α, and above the upper threshold, 10 β, are replaced by random numbers drawn from the open interval (a,α) and (β,b), where a and b are the lower bound and the upper bound, respectively.”
• A method to preserve trends in quantile mapping bias correction of climate modeled temperature (2017, methodology): “…BC-TREND version that was used for the central England example, it was found that it tends to preserve the long-term statistics as also noted by Cannon et al. (2015), but the 5-year average that was used for the trend preservation still cannot encompass the changes in each year’s CDF, as the…”