Foundational Needs of Forecasters for Probabilistic Winter Forecasting

Abstract

Abstract This study explores forecaster perceptions of emerging needs for probabilistic forecasting of winter weather hazards through a nationwide survey disseminated to National Weather Service (NWS) forecasters. Questions addressed four relevant thematic areas: 1) messaging timelines for specific hazards, 2) modeling needs, 3) current preparedness to interpret and communicate probabilistic winter information, and 4) winter forecasting tools. The results suggest that winter hazards are messaged on varying time scales that sometimes do not match the needs of stakeholders. Most participants responded favorably to the idea of incorporating new hazard-specific regional ensemble guidance to fill gaps in the winter forecasting process. Forecasters provided recommendations for ensemble run length and output frequencies that would be needed to capture individual winter hazards. Qualitatively, forecasters expressed more difficulties communicating, rather than interpreting, probabilistic winter hazard information. Differences in training and the need for social-science-driven practices were identified as a few of the drivers limiting forecasters’ ability to provide strategic winter messaging. In the future, forecasters are looking for new winter tools to address forecasting difficulties, enhance stakeholder partnerships, and also be useful to the local community. On the regional scale, an ensemble system could potentially accommodate these needs and provide specialized guidance on timing and sensitive/high-impact winter events. Significance Statement Probabilistic information gives forecasters the ability to see a range of potential outcomes so that they can know how much confidence to place in the forecast. In this study, we surveyed forecasters so that we can understand how the research community can support probabilistic forecasting in winter. We found that forecasters want new technologies that help them understand hard forecast situations, improve their communication skills, and that are useful to their local communities. Most forecasters feel comfortable interpreting probabilistic information, but sometimes are not sure how to communicate it to the public. We asked forecasters to share their recommendations for new weather models and tools and we provide an overview of how the research community can support probabilistic winter forecasting efforts.