Bias correction and resampling of RACMO output for the hydrological modelling of the Rhine

A. Bakker, B. van den Hurk, Ministerie van Infrastructuur en Milieu, Koninklijk Nederlands Meteorologisch Instituut
De Bilt : KNMI

Extreme discharges of the Rhine are likely to change as a result of the changing climate. A common way to assess impacts of climate change is to use Regional Climate Model (RCM) output to drive impact models. For the assessment of very rare discharge events in a large river basin (e.g. with return periods of 1250 years) there are two major problems. First, available RCM simulations are usually way too short for the robust estimation of such rare events. Second, RCM output is generally too biased for direct use in impact models. Nearest Neighbour Resampling (NRR) stochastically extends meteorological time series to any length. The generated synthetic time series are subject to the same characteristics as the reference time series and are generally thought to contain rare multi-day extremes in accordance with the time series length. The discharge of the Rhine at Lobith is closely related to the upstream precipitation of multiple preceding days. So, hydrological modelling on the basis of very long synthetic time series may result in more robust estimation of very rare discharge events at Lobith.

32 p.
(Technical report = Technisch rapport ; TR-307)
With ref.