Comment on “Bias Correction, Quantile Mapping, and Downscaling: Revisiting the Inflation Issue” Journal of Climate

Several papers in the Journal of Climate have discussed the use of inflation of regression estimates (e.g., Karl et al. 1990; von Storch 1999), a recent one being Maraun (2013). Generally, Maraun (2013, 2014) disparages the inflation concept and is very specific in Maraun (2014) where he states that “. . . inflation is appropriate for neither prediction nor simulation” (p. 1823). He also states, “In the early years of numerical weather forecasting, a tendency of the regression method to ‘not forecasting the extremes as often as they are observed’ (Klein et al. 1959) had been noted, basically because erroneously only the predicted mean ax had been considered for the forecast but not the distribution around it. As a ‘correction’ inflation has been suggested . . .” (p. 1823). I believe Maraun’s statement (Maraun 2014) that the inflation procedure is “flawed” is unjustified and his statement that it is not appropriate for prediction is incorrect. Maraun’s treatment of inflation may inhibit its use where it would be appropriate. His statement concerning the distribution around the mean implies probability forecasts, and that would be an excellent avenue to take, provided the users of the forecasts would accept them in lieu of a specific value forecast; however, since that is many times not the case, a specific value is imperative. My purpose here is not to justify inflation as the best way to achieve regression estimates of the more rare events, as Klein et al. (1959) long ago stated, but rather to indicate that it can be used successfully as one way.