On the contribution of statistical bias correction to the uncertainty in the projected hydrological cycle

Global hydrological modeling is affected by three sources of uncertainty: (i) the choice of the global climate model (GCM) used to provide meteorological forcing data; (ii) the choice of future greenhouse gas concentration scenario; and (iii) the choice of the decade used to derive the bias correction parameters. We present a comparative analysis of these uncertainties and compare them to the inter-annual variability. The analysis focuses on discharge, integrated runoff and total precipitation over ten large catchments, representative of different climatic areas of the globe. Results are similar for all catchments, all hydrological variables and throughout the year with few exceptions. We find that the choice of different decadal periods over which to derive the bias correction parameters is a source of comparatively minor uncertainty, while other sources play larger and similarly significant roles. This is true for both the means and the extremes of the studied hydrological variables. Citation: Chen, C., J. O. Haerter, S. Hagemann, and C. Piani (2011), On the contribution of statistical bias correction to the uncertainty in the projected hydrological cycle, Geophys. Res. Lett., 38, L20403, doi:10.1029/2011GL049318.