Authors: Erin Towler, Mimi Hughes, Rob Cifelli, William Ryan Currier, Anna Pfohl, and Engela Sthapit – NOAA Physical Sciences Laboratory
Title: Enhancing ensemble streamflow predictions using post-processed precipitation forecasts
Abstract: Improving probabilistic water forecasts for a variety of societal applications is a priority, as well as a grand challenge, for the hydrologic modeling community. Errors in water forecasts arise from a variety of sources, one of which is meteorological input uncertainty. To address this, meteorological forecast ensembles – such as those derived from Numerical Weather Prediction (NWP) models – are often statistically post-processed before being used as inputs to hydrologic models. As part of a project underway at the NOAA Physical Sciences Laboratory, this poster will describe work towards the development and evaluation of post-processing techniques, with a focus on precipitation, and the impact on streamflow forecasts. Applications are shown for case studies relevant to Forecast Informed Reservoir Operations (FIRO), and streamflow is simulated using NOAA water tools, including from the NextGen Framework.