Improving pan-European hydrological simulation of extreme events through statistical bias correction of RCM-driven climate simulations

摘要

In this work we asses the benefits of removing bias in climate forcing dataused for hydrological climate change impact assessment at pan-European scale,with emphasis on floods. Climate simulations from the HIRHAM5-ECHAM5 modeldriven by the SRES-A1B emission scenario are corrected for bias using ahistogram equalization method. As target for the bias correction weemploy gridded interpolated observations of precipitation, average, minimum,and maximum temperature from the E-OBS data set. Bias removal transferfunctions are derived for the control period 1961–1990. These aresubsequently used to correct the climate simulations for the control period,and, under the assumption of a stationary error model, for the future timewindow 2071–2100. Validation against E-OBS climatology in the control periodshows that the correction method performs successfully in removing bias inaverage and extreme statistics relevant for flood simulation over themajority of the European domain in all seasons. This translates intoconsiderably improved simulations with the hydrological model of observedaverage and extreme river discharges at a majority of 554 validation riverstations across Europe. Probabilities of extreme events derived employingextreme value techniques are also more closely reproduced. Results indicatethat projections of future flood hazard in Europe based on uncorrectedclimate simulations, both in terms of their magnitude and recurrenceinterval, are likely subject to large errors. Notwithstanding the inherentlimitations of the large-scale approach used herein, this study stronglyadvocates the removal of bias in climate simulations prior to their use inhydrological impact assessment.