Moving to Ensembles and Probabilistic Data: Ensuring Forecasters Are Ready

The National Weather Service (NWS) is on a path towards migrating to probabilistic services, as highlighted by "Ken's 10 Probabilistic IDSS'' initiative. A critical piece to this migration is for forecasters to understand ensembles. Since the NWS inception, NWS forecasters have been faced with creating a deterministic forecast, often with only a few deterministic models. However, significant advances have occurred to NWP in the past two decades such that ensembles even on the global scale are catching up to their deterministic models. This is forcing NWS forecasters to integrate ensemble data into their forecast process, and also think about how to communicate probabilistically so that partners can make better decisions. (Ripberger et al., 2022). Since ensembles vastly increase the amount of data to look at, forecasters need to have a greater understanding of statistics, resolvability, post processed guidance from ensembles and how to communicate this information. NWS's Forecast Development and Training Division (FDTD) was tasked to develop a curriculum on ensemble fluency, tackling many of the aforementioned needs. A national team was developed to assist FDTD in this effort.

The presentation will dig into the ensemble fluency training FDTD and the national team developed. Additionally the presentation will tackle how this training will help forecasters as Artificial Intelligence and Machine Learning become more prominent in weather forecasting.