Authors: Dan Tian, Hongxing Liu, Sagy Cohen, Tantu Mandal – The University of Alabama; Lei Wang – Louisiana State University
Title: Innovations toward enhanced ensemble streamflow predictions in NOAA’s HEFS and NextGen frameworks
Presentation Type: Lightning Talk
Abstract: NOAA’s hydrologic forecasts support decision-making across many sectors. Probabilistic streamflow forecasts offer the potential to quantify the inherent uncertainty in predicting streamflow, especially for hydrologic hazards such as droughts and floods, as well as applications such as Forecast Informed Reservoir Operations. This lightning talk will survey a project underway at NOAA’s Physical Science Lab (PSL) to support and contribute to the improvement of NOAA’s ensemble streamflow forecasting tools. Specifically, PSL is establishing an experimental research and development framework for ensemble streamflow prediction that crosswalks NOAA’s operational Hydrologic Ensemble Forecast System (HEFS) and its NextGen National Water Model. The framework provides the ability to test end-to-end potential improvements for ensemble streamflow prediction, spanning improvements in meteorological forcings to streamflow post-processing techniques. Experiments from the framework are being compared to the HEFS benchmark hindcasts, lending operational relevance to our results.