Global Streamflow Seasonal Forecast by a novel two-way AOGCM/Land/River coupling

In disaster prevention, water management, agriculture, and hydropower generation, an accurate seasonal streamflow forecast (SSF) is crucial, while global approaches become necessary in regions lacking forecast systems. This study evaluates the Mto-France seasonal prediction system (SYS8) skill for global SSF through hindcasts of river discharges. Contributing to Copernicus Climate Change Services (C3S), the SYS8 employs a fully coupled Atmosphere-Ocean General Circulation Model (AOGCM) with an advanced river routing component (CTRIP) interacting with the ISBA land-surface scheme. This research is part of the European project CERISE, which aims to enhance the C3S seasonal forecast portfolio by improving land initialisation methodologies.SYS8 derives land initial conditions from a historical coupled initialisation run where land-river is weakly constrained, while atmosphere/ocean is nudged to the ERA5/GLORYS re-analysis. This study improves the initialisation run by relaxing soil moisture to fields reconstructed from an offline land simulation. Daily streamflow ensemble hindcasts of 25 members are generated in a 0.5 grid, with a lead time of up to 4 months initialised on the 1st of May/August/November between 1993-2017, allowing hindcasting summer (JJA), fall (SON) and winter (DJF) seasons. Forecast skill is assessed against discharge observations in 1608 monitored basins worldwide (with areas > 3000 km) using deterministic and probabilistic metrics. The classical Ensemble Streamflow Prediction approach (ESP) is a benchmark for evaluating the control SYS8 skill and the additional skill of moisture nudging.Globally, the control SYS8 skill is superior to the ESP, but the bias is higher in dry regions such as northeastern Brazil, western US and some rivers in Spain and Africa. On the other hand, the hindcast with enhanced land surface initial conditions outperformed the control SYS8 and benchmark ESP, especially during summer. Local skill degradation in higher latitudes will be discussed. Still, overall positive results support ongoing efforts to enhance land initialisation through a global land data assimilation system.