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. Tang et al. (2023) analyze how uncertainties in meteorological forcing data affect hydrological modeling in 289 representative cryosphere basins 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 results reveal the magnitude, spatial distribution, and scale effect of uncertainties in meteorological, snow, runoff, soil water, and energy variables.

{"references": ["Guoqiang Tang, Martyn P. Clark, Wouter J. M. Knoben, Hongli Liu, Shervan Gharari, Louise Arnal, Hylke E. Beck, Andrew W. Wood, Andrew J. Newman, Simon Michael Papalexiou. The impact of meteorological forcing uncertainty on hydrological modeling in cryosphere basins: A global analysis. Water Resources Research. 2023"]}