J1A.1 NWS Probabilistic Impact-based Decision Support Services - Delivering Science-based Probabilistic Forecast Information

Monday, 13 January 2025: 8:30 AM
206 (New Orleans Ernest N. Morial Convention Center)
Kathryn K. Gilbert, NWS, College Park, MD; and R. Bandy, J. S. Waldstreicher, G. Cooper, S. B. Smith, M. E. Jeglum, S. Perfater, A. Foster, K. Scharfenberg, J. S. Lee, M. J. Glaudemans, J. Brooks, G. Mann, A. Boxell, B. Smith, D. E. Levin, M. J. Moreland, D. C. Strom, K. E. Landry-Guyton, J. J. Brost, S. R. Baxter, B. De Rosa, and D. Nagele, PhD

Probabilistic Impact-based Decision Support Services (IDSS) are about helping core partners make informed, risk-based decisions by assessing the full range of possible outcomes and providing the analysis and forecast information that best guides their unique decision-making needs. The NWS is building our expertise and tools to increase our capacity to understand, interpret and communicate risk-based, probabilistic information to drive Probabilistic IDSS. The evolution of our products and services will allow our partners and the public to make informed decisions based on their unique circumstances, risk tolerances, and decision thresholds for all time scales from minutes to months.

The expansion of Probabilistic IDSS relative to traditional deterministic forecasting is enabled by the introduction of advanced tools and a shift towards a decision-making focus. Probabilistic data and visualization tools have matured to now offer graphical and data services that are clear, accessible, and aligned with the decision-making needs of our users. Whereas we previously asked our partners, “What services do you need?” we will now ask, “What decisions are you making?” This shift enables us, as scientific experts, to guide partners to the most relevant information for their specific needs.

Adopting a fully Probabilistic IDSS model requires a comprehensive, NWS-wide strategy. This includes everything from producing foundational data to using analysis and visualization tools, training for the workforce, and engaging directly with core partners. Probabilistic IDSS will require an understanding of how we can aid our core partners’ decision-making before, during, and after impactful weather, water, and/or climate events. By nurturing the feedback loop with our core partners, we will continually refine and improve our data and services.

The transition to a Probabilistic IDSS paradigm will unfold over the next decade, following a “build a little, test a little, field a little” approach. Developing and refining our infrastructure to fully support Probabilistic IDSS will take time. This presentation will showcase the current projects and development efforts which are leading the way toward achieving this vision.

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