Description:

During the past decade there has been an explosion in the amount of Impact-based Decision Support Services (IDSS) across the Weather Enterprise. This has resulted in significant changes to forecast operations and the responsibilities of forecasters. For example, much more emphasis has been placed on communication and social science. Meanwhile, the amount of model data forecasters have available to them has increased dramatically, such as hourly updating convective allowing models and the development of the National Blend of Models. In addition, ensembles are now run at the resolution of what deterministic models were just four to five years ago. This increase in data and model resolution has allowed for the implementation of improved post processing techniques and making the delivery of probabilistic information, an area strongly recommended by social science, an emerging reality. We are now at a crossroads where users and partners are comfortable with deterministic forecasts, yet we have the capability of providing a much broader range of probabilistic forecast information and services that present a richer view of potential forecast outcomes, including those tailored to specific decision points. As we move into a more probabilistic-based world, a challenge for the Weather Enterprise will be the need to educate users on the availability and interpretation of such output. These changes and opportunities challenge the traditional role of the forecaster, and present us with the need to rethink where and how forecasters can best utilize their knowledge and skills moving forward.

In this session we are looking for abstracts focused on the changing role of the forecaster, how forecasters can potentially interface with rapidly refreshing model output, probabilistic information and sophisticated model blends, as well as strategies for providing probabilistic information to users.