Evaluating the Role of the Mesoanalyst in Severe Weather Impacts Based Decision Support Services. Part III—Messaging Focus

During 2019, the National Weather Service (NWS) Operations Proving Ground (OPG) delivered three week-long, proof-of-concept experiments focused on evaluating the potential for expert mesoanalysis to enhance impact-based decision support services (IDSS) at NWS Weather Forecast Offices (WFOs). These experiments evaluated capabilities to convey precise, targeted IDSS associated with high-impact convective weather events by leveraging high-resolution satellite imagery and other meteorological observations, science-based conceptual models and cutting-edge numerical weather prediction datasets. The workshops were comprised of job-relevant simulations involving real weather events, supplemented by instruction from subject matter experts and facilitated group discussions. Real-time feedback from participating core partners was also incorporated, along with reflection and solutions-oriented discussions on evolving NWS culture to embrace and infuse mesoanalysis for enhancing its services. This initiative represents a strong collaboration between the OPG, the Storm Prediction Center, WFOs across the NWS, and the NWS Office of Learning.

This presentation will address the messaging components of the evaluations, and summarize key findings and recommendations. Methods by which NWS meteorologists can apply insight from mesoscale analysis and conceptual models to enhance IDSS messaging will be presented. In addition to traditional convective watches and warnings, specific avenues investigated for communicating targeted convective threat assessments include Enhanced Short-Term Weather Outlooks, Mesoscale Area Forecast Discussions, tactical briefings for NWS core partners, and social media posts. Use of probabilistic information was also explored, both for forecaster decision-making and for conveying confidence information to risk management decision makers. Participants tested methods to enhance weather readiness for conditionally high-impact scenarios, such as resolving and messaging the spectrum of reasonable outcomes for convective hazards within a few hours of their occurrence. Tools to facilitate this included the use of the Statistical Severe Convective Risk Assessment Model, anticipating the evolution of Probability Density Functions associated with those risks, and communicating uncertainty about the likelihood of severe weather to emergency management partners. Prepared exercises, injects, and constructive critique - including feedback from the Johnson County, Kansas Emergency Manager - permitted a full-scale assessment of the efficacy of operations simulated in the evaluation. Ultimately, the goal is to help NWS field offices bridge the temporal gap between watches and warnings with service enhancements that improve hazard information delivery.