Assessing Training and Competency Requirements in the Probabilistic Forecasting Era

The National Weather Service is evolving toward an operations concept focusing on probabilistic forecasting and impact-based decision support services. To facilitate this transformation, a team has been created within the NWS to assess training gaps within the existing workforce and evaluate the competencies that will be needed in the future workforce.

Foundational training and competencies should be applicable across the spectrum of weather, water, and climate hazards spanning from minutes to multi-year scales. Meteorologists will need to have high numeracy skills along with a deep understanding of ensemble model output, probabilities, statistics, and machine learning. A large volume of post-processed output will necessitate proficiency with increasingly-complex visualization tools. Forecasters will need to be able to quickly synthesize large amounts of data to support tailored messaging and impact-based decision support services. Effective communication skills will be required to ensure the forecasts have optimal benefit to decision makers and publics via graphics, chat messages, and social media.

This presentation will provide an overview on the findings and recommendations developed to date as part of the assessment process. Ongoing and planned activities to bridge the identified training gaps, such as “ensemble fluency” training within the NWS, will be outlined. Thoughts will be offered regarding competencies that will need to be developed at the University level to serve future probabilistic forecasting and IDSS operations in the public sector.