The 32nd Conference on Hydrology is hosting a joint session with the 25th Conference Probability and Statistics on probabilistic hydrometeorological forecasting and uncertainty analysis. Over the last several decades, substantial progresses have been achieved in probabilistic hydrometeorological forecasting theories and applications. However, significant challenges still exist in assessing the quality and uncertainty of complex hydrometeorological processes and improving hydrometeorological predictions, especially high-impact hydrometeorological events. This session solicits papers that focus on, but are not limited to, (1) addressing uncertainty in hydrometeorological forecasting from different sources in both offline and couple systems, and (2) hydrometeorological ensemble forecasting methods. The former might include uncertainties in forcing data (quantitative precipitation estimation, meteorological forcing data, and so on), initial conditions (such as soil moisture and heterogeneous geographical conditions), parameters, model structure (physics), calibration, and statistical postprocessing of hydrometeorological model output, and innovative methods for assessing uncertainty information from observations to modeling and postprocessing processes. The latter emphasizes integrated ensemble methods to improve individual hydrologic and atmospheric models, or coupled atmosphere–land–hydrology systems, verification methods to evaluate probabilistic hydrometeorological forecasting, and technologies to process systematic errors of hydrometeorological forecasting at different spatial and temporal scales.