Decision makers base their choices of adaptation strategies on climate change projections and their associated hydrological consequences. New insights of climate change gained under the new generation of climate models belonging to the IPCC 5th assessment report may influence (the planning of) adaption measures and/or future expectations. In this study, hydrological impacts of climate change as projected under the new generation of climate models for the Rhine were assessed. Hereto we downscaled 31 General Circulation Models (GCMs), which were developed as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5), using an advanced Delta Change Method for the Rhine basin. Changes in mean monthly, maximum and minimum flows at Lobith were derived with the semi-distributed hydrological model HBV of the Rhine. The projected changes were compared to changes that were previously obtained in the trans-boundary project Rheinblick using eight CMIP3 GCMs and Regional Climate Models (RCMs) for emission scenario A1B. All eight selected CMIP3 models (scenario A1B) predicted for 2071-2100 a decrease in mean monthly flows between June and October. Similar decreases were found for some of the 31 CMIP5 models for Representative Concentration Pathways (RCPs) 4.5, 6.0 and 8.5. However, under each RCP, there were also models that projected an increase in mean flows between June and October and on average the decrease was smaller than for the eight CMIP3 models. For 2071-2100, also the mean annual minimum 7-days discharge decreased less in the CMIP5 model simulations than was projected in CMIP3. When assessing the response of mean monthly flows of the CMIP5 simulation with the CSIRO-Mk3-6-0 and HadGEM2-ES models with respect to initial conditions and RCPs, it was found that natural variability plays a dominant role in the near future (2021-2050), while changes in mean monthly flows are dominated by the radiative forcing in the far future (2071-2100). According to RCP 8.5 model simulations, the change in mean monthly flow from May to November may be half the change in mean monthly flow projected by RCP 4.5. From January to March, RCP 8.5 simulations projected higher changes in mean monthly flows than RCP 4.5 simulations. These new insights based on the CMIP5 simulations imply that for the Rhine, the mean and low flow extremes might not decrease as much in summer as was expected under CMIP3. Stresses on water availability during summer are therefore also less than expected from CMIP3.
Abstract This paper presents the methodology for the construction of the KNMI'23 national climate scenarios for the Netherlands. We have developed six scenarios, that cover a substantial part of the uncertainty in CMIP6 projections of future climate change in the region. Different sources of uncertainty are disentangled as much as possible, partly by means of a storyline approach. Uncertainty in future emissions is covered by making scenarios conditional on different SSP scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5). For each SSP scenario and time horizon (2050, 2100, 2150), we determine a global warming level based on the median of the constrained estimates of climate sensitivity from IPCC AR6. The remaining climate model uncertainty of the regional climate response at these warming levels is covered by two storylines, which are designed with a focus on the annual and seasonal mean precipitation response (a dry‐trending and wet‐trending variant for each SSP). This choice was motivated by the importance of future water management to society. For users with specific interests we provide means how to account for the impact of the uncertainty in climate sensitivity. Since CMIP6 GCM data do not provide the required spatial detail for impact modeling, we reconstruct the CMIP6 responses by resampling internal variability in a GCM‐RCM initial‐condition ensemble. The resulting climate scenarios form a detailed storyline of plausible future climates in the Netherlands. The data can be used for impact calculations and assessments by stakeholders, and will be used to inform policy making in different sectors of Dutch society.
Dataset associated with Van der Wiel et al. (202?): KNMI'23 climate scenarios for the Netherlands: storyline scenarios of regional climate change, Earth's Future, in review. This dataset contains the CMIP6 data and EC-Earth3/RACMO data that formed the basis for the KNMI'23 national climate scenarios for the Netherlands (www.knmi.nl/klimaatscenarios). Full details on the methodology, including the origin of this dataset, can be found in the above referenced paper. original_ensembles.tar.gz - Contains the original CMIP6, EC-Earth3 and RACMO-based time series for the NL and NL+RM regions, for all variables of interest (TAS, PR, PET, WBDEFICIT, RSDS, PR10DMAX). Additionally, for TAS also global-mean time series are provided. Data from the historical experiment and three SSP-scenario experiments (SSP1-2.6, SSP2-4.5, SSP5-8.5) are provided. resampled_ensembles.tar.gz - Contains resampled datasets of EC-Earth3 and RACMO data, for each scenario-time horizon combination (Ld,Ln,Md,Mn,Hd,Hn, and 2050,2100,2150). Again these are the NL and NL+RM regional mean time series, for the variables of interest. Final data products for the KNMI'23 national climate scenarios can be downloaded from https://klimaatscenarios-data.knmi.nl/.
The Netherlands are situated at the downstream end of the Rhine River. A large part of the country can be supplied with water from the river in the case of precipitation deficits. For the assessment of the economical damage due to drought it is necessary to consider the rainfall and river inflow simultaneously. Transformed normal distributions as well as Gumbel distributions have been fitted to the observed precipitation and discharge deficits. The sensitivity of joint probabilities to the choice of the marginal distributions, the dependence structure and the `failure region' is investigated. It is found that the bivariate normal distribution underestimates the probability that both the rainfall and runoff deficit are extreme due to its asymptotic independence.
