Meteorological forcing is a major source of uncertainty in hydrological modeling. The recent development of probabilistic large-domain meteorological datasets enables convenient uncertainty characterization, which however is rarely explored in large-domain research. We analyze how uncertainties in meteorological forcing data affect hydrological modeling on the global scale by forcing the Structure for Unifying Multiple Modeling Alternatives (SUMMA) and mizuRoute models with precipitation and air temperature ensembles from the Ensemble Meteorological Dataset for Planet Earth (EM-Earth). EM-Earth probabilistic estimates are used in ensemble simulation for uncertainty analysis. The global land area is divided into ~3 million sub-basins using the MERIT-Basins dataset. This dataset contains the SUMMA and mizuRoute configuration files (e.g., diverse land attributes, model parameters, and model physics decisions) to reproduce the global simulation results. The global land is divided into different continents, including Africa, Arctic, Europe, North America, North Asia, Oceania, SouthAmerica, and SouthAsia. Greenland is not included because of its complexity and low quality of available data. Antarctic is not included in MERIT-Basins.