Water supply patterns over Germany under climate change conditions

[摘要] A large ensemble of 24 bias-corrected and uncorrected regional climate model(RCM) simulations is used to investigate climate change impacts on watersupply patterns over Germany using the seasonal winter and summerStandardized Precipitation Index (SPI) based on 6-month precipitation sums.The climate change signal is studied comparing SPI characteristics for thereference period 1971–2000 with those of the "near" (2036–2065) and the"far" (2071–2100) future. The spread of the climate change signal withinthe simulation ensemble of bias-corrected versus non-corrected data isdiscussed. Ensemble scenarios are evaluated against availableobservation-based data over the reference period 1971–2000. After correctingthe model biases, the model ensemble underestimates the variability of theprecipitation climatology in the reference period, but replicates the meancharacteristics. Projections of water supply patterns based on the SPI forthe time periods 2036–2065 and 2071–2100 show wetter winter months duringboth future time periods. As a result soil drying may be delayed to latespring extending into the summer period, which could have an important effecton sensible heat fluxes. While projections indicate wetting in summer during2036–2065, drier summers are estimated towards the south-west of Germany forthe end of the 21st century. The use of the bias correction intensifies thesignal to wetter conditions for both seasons and time periods. The spread inthe projection of future water supply patterns between the ensemble membersis explored, resulting in high spatial differences that suggest a higheruncertainty of the climate change signal in the southern part of Germany. Itis shown that the spread of the climate change signals between SPIs based onsingle ensemble members is twice as large as the difference between the meanclimate change signal of SPIs based on bias-corrected and uncorrectedprecipitation. This implies that the sensitivity of the SPI to the modelledprecipitation bias is small compared to the range of the climate changesignals within our ensemble. Therefore, the SPI is a very useful tool forclimate change studies allowing us to avoid the additional uncertainties causedby bias corrections.

[学科分类] 地球化学与岩石