Abstract
Simulated stable oxygen isotopic composition (δ18O) of precipitation from isotope-enabled GCMs (iGCMs) have gained significant visibility nowadays. This study evaluates bias correction techniques to reduce the systematic and dispersion biases of the modelled δ18O by the ECHAM5-wiso model compared to the Global Network of Isotopes in Precipitation (GNIP) observations over Central Europe. mean bias error (MBE) and Root Mean Square Error (RMSE) are substantially reduced by more than 70% and 10%, respectively, depending on the bias correction scheme, with better results for Generalized Additive Model (GAM) and linear scaling approach (SCL) methods. The bias-corrected δ18OECHAM5-wiso values successfully describe the long-term isotopic composition of precipitation and the isotopic amplitude with the best performances for the EQM method. The necessity of applying bias correction algorithms is verified by the excellent agreement between the corrected δ18OECHAM5-wiso with GNIP in high-altitude areas where ECHAM5-wiso fails to reproduce the observed isotopic variability. The results are expected to bring valuable insights into the utilization of iGCMs’ relationships in climate studies for understanding the present and past water cycle under the isotopic perspective.
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