Journal
FRONTIERS IN WATER
Volume 3, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/frwa.2021.713537
Keywords
ensemble projections; performance-based weighting; EURO-CORDEX; climate change; hydrological impact; Europe
Categories
Funding
- EU [776613]
- Deltares Strategic Research Program Natural Hazards
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Ensemble projections of future changes in discharge over Europe show large variation, with different weighting approaches influencing the consistency of the projections. Weighting methods favored projections from the same General Circulation Models, but high weights obtained through past good performance can provide deviating projections for the future. In Central Europe, differences between models become more pronounced, highlighting the need for robust weighting methods to increase the reliability of change signals.
Ensemble projections of future changes in discharge over Europe show large variation. Several methods for performance-based weighting exist that have the potential to increase the robustness of the change signal. Here we use future projections of an ensemble of three hydrological models forced with climate datasets from the Coordinated Downscaling Experiment - European Domain (EURO-CORDEX). The experiment is set-up for nine river basins spread over Europe that hold different climate and catchment characteristics. We evaluate the ensemble consistency and apply two weighting approaches; the Climate model Weighting by Independence and Performance (ClimWIP) that focuses on meteorological variables and the Reliability Ensemble Averaging (REA) in our study applied to discharge statistics per basin. For basins with a strong climate signal, in Southern and Northern Europe, the consistency in the set of projections is large. For rivers in Central Europe the differences between models become more pronounced. Both weighting approaches assign high weights to single General Circulation Models (GCMs). The ClimWIP method results in ensemble mean weighted changes that differ only slightly from the non-weighted mean. The REA method influences the weighted mean more, but the weights highly vary from basin to basin. We see that high weights obtained through past good performance can provide deviating projections for the future. It is not apparent that the GCM signal dominates the overall change signal, i.e., there is no strong intra GCM consistency. However, both weighting methods favored projections from the same GCM.
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