Preparing local climate change scenarios for the Netherlands using resampling of climate model output.
by G. Lenderink (KNMI), B.J.J.M. van den Hurk (KNMI), A.M.G. Klein Tank (KNMI), G.J. van Oldenborgh (KNMI), E. van Meijgaard (KNMI)H. de Vries (KNMI)J.J. Beersma (KNMI)
A method to prepare a set of four climate scenarios for the Netherlands is presented. These scenarios for climate change in 2050 and 2085 (compared to present-day) are intended for general use in climate change adaptation in the Netherlands. An ensemble of eight simulations with the global model EC-Earth and the regional climate model RACMO2 (run at 12 km resolution) is used. For each scenario time horizon, two target values of the global mean temperature rise are chosen based on the spread in the CMIP5 simulations. Next, the corresponding time periods in the EC-Earth/RACMO2 simulations are selected in which these target values of the global temperature rise are reached. The model output for these periods is then resampled using blocks of 5-year periods. The rationale of resampling is that natural variations in the EC-Earth/RACMO2 ensemble are used to represent (part of the) uncertainty in the CMIP5 projections. Samples are then chosen with the aim of reconstructing the spread in seasonal temperature and precipitation changes in CMIP5 for the Netherlands. These selected samples form the basis of the scenarios. The resulting four scenarios represent 50 to 80% of the CMIP5 spread for summer and winter changes in seasonal means as well as a limited number of monthly statistics (warm, cold, wet and dry months). The strong point of the method – also in relation to the previous set of the climate scenarios for the Netherlands issued in 2006 – is that it preserves nearly all physical inter-variable consistencies as they exist in the original model output in both space and time.
Lenderink, G., B.J.J.M. van den Hurk, A.M.G. Klein Tank, G.J. van Oldenborgh, E. van Meijgaard, H. de Vries and J.J. Beersma, Preparing local climate change scenarios for the Netherlands using resampling of climate model output.