Global warming is assumed to accelerate the global water cycle. However, quantification of the acceleration and regional analyses remain open. Accordingly, in this study we address the fundamental hydrological question: Is the water cycle regionally accelerating/decelerating under global warming? For our investigation we have implemented the age-weighted regional water tagging approach into the Weather Research and Forecasting WRF model, namely WRF-age, to follow the atmospheric water pathways and to derive atmospheric water residence times accordingly. Moreover, we have implemented the three-dimensional online budget analysis of the total, tagged, and aged atmospheric water into WRF-age to provide a prognostic equation of the atmospheric water residence times. The newly developed, physics-based WRF-age model is used to regionally downscale the reanalysis of ERA-Interim and the MPI-ESM Representative Concentration Pathway 8.5 scenario (RCP8.5) simulation exemplarily for an East Asian monsoon region, i.e., the Poyang Lake basin (the tagged moisture source area), for two 10-year slices of historical (1980-1989) and future (2040-2049) times. In comparison to the historical simulation, the future 2-meter temperature rises by +1.4 °C, evaporation increases by +6%, and precipitation decreases by -38% under RCP8.5 on average. In this context, global warming leads to regionally decreased residence times for the tagged water vapor by 8 hours and the tagged condensed moisture by 12 hours in the atmosphere, but increased transit times for the tagged precipitation by 4 hours over the land surface that is partly attributed to a slower fallout of precipitating moisture components in the atmosphere under global warming.

Since 2000s, most of West-African countries and particularly Benin have experienced an increased frequency of extreme flood events. In this study we focus on the case of the Ouémé-river basin in Benin for the period 2008-2010. To investigate on how to early warn flood events in this basin, the coupled atmosphere-hydrology model system WRF-Hydro is selected. Such a coupled model allows to explore the contribution of atmospheric components into the flood event, and its ability to simulate and predict accurate streamflow. The potential of WRF-Hydro in correctly simulating streamflow in the Ouémé-river basin is assessed by forcing the model with operational analysis datasets from the ECMWF. Atmospheric and land surface processes are resolved at a spatial resolution of 5km. The additional surface and subsurface water flow routing is computed at a resolution 1:10. Key parameters of the hydrological module of WRF-Hydro are calibrated offline, and tested online with the coupled WRF-Hydro. The uncertainty of atmospheric modeling on coupled results is assessed with the stochastic kinetic-energy backscatter scheme (SKEBS). WRF-Hydro is able to simulate the discharge in Ouémé river on offline and fully-coupled modes with a Kling-Gupta Efficiency (KGE) around 0.70 and 076 respectively. In fully-coupled mode the model captures the flood event that occurred in 2010. A stochastic perturbation ensemble of 10 members for three rain seasons shows that the coupled model performance in terms of KGE is from 0.14 to 0.79. This ability in realistically reproducing observed discharge in the Ouémé-river basin demonstrates the potential of the coupled WRF-Hydro modeling system for future flood forecasting applications.