11A.4 Leveraging the Combined Strengths of Local Mesoscale Modeling and Local Forecaster Intelligence to Refine Convective Threat Assessments

Wednesday, 6 October 2004: 5:15 PM
David W. Sharp, NOAA/NWS, Melbourne, FL

In the time since the Central Florida Tornado Outbreak (1998), the Weather Forecast Office (WFO) in Melbourne, FL (MLB) has put forth considerable effort to improve the quality of products and services centered on mitigating the negative impacts of strong/severe convection during the Day-1 period. For MLB, this severe event served as motivation for several local initiatives. The three primary and inter-related initiatives discussed in this paper involve the development and experimental implementation of high resolution diagnostics, high resolution prognostics, and local hazardous threat assessments. The first of these initiatives was directed toward generating high resolution, full volume, analyses of the local atmosphere, to include rapid refresh. Here, analyses are now available every 15-minutes to give the meso-analyst informed insight into the condition of the pre-storm environment before local convection ensues, as well as the condition of the near-storm environment during active convection. The second of these initiatives involves the role of local modeling as a means of smartly considering the character, timing, and distribution of convection during the next 24-hours, especially during the next 6 to 9 hours. Importantly, the diagnostics are used to warm-start a local model which now delivers prognostics to forecasters in 30-minute output intervals as it becomes available. Together, both the diagnostics and prognostics offer the meso-analyst the improved capability to perform a thorough convective threat assessment based on the evolution and differences of local buoyancy/shear profiles across the forecast area, thus fine-tuning Storm Prediction Center regional outlooks. These threat assessments are made manifest in a graphical/gridded version of the Hazardous Weather Outlook, where WFO forecaster intelligence is harnessed to examine and synthesize environmental clues to create a coherent picture of the convective situation for local users. This represents the third initiative. In this paper, details of the three initiatives will be presented to demonstrate how WFO MLB leverages the combined strengths of local modeling and local forecaster intelligence to refine convective threat assessments.
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