A Near-Worst-Case Scenario in East-Central Kansas
During the afternoon and early evening of 28 May 2019, a violent, long-lived tornado
traversed portions of Douglas and Leavenworth Counties in east-central and northeast Kansas --
coming within just a few miles of the major university town of Lawrence, Kansas. Not only was
this tornado one-mile wide at its widest point, but it was heading directly toward one of the
most populated cities in NWS Topeka’s County Warning Area. This operational workflow was
emblematic of a strongly integrated, whole-office concept -- leveraging both
research-to-operations and operations-to-research applications in providing services that
ultimately contributed to absolutely zero fatalities despite this tornado being violent. This
presentation will address ways in which local-office training, excellent teamwork, and research
applications were vital to enhancing IDSS, including warning services and related messaging.
While the overall synoptic-scale pattern of 28 May was favorable for tornadic supercells, there were several open-warm-sector factors at the mesoscale level that cast considerable doubt regarding prospects for sustained, rotating convection to evolve. For instance, cloudiness across the open warm sector offered both zones of enhanced static stability suppressing convective potential, with flanking differential-heating zones potentially enhancing convective intensity. Ultimately, the explicit delegation of mesoscale analysis to a subset of the staff was vital to developing and messaging anticipatory assertions regarding subsequent, potentially damaging convective potential -- directly providing the science foundation for enhanced IDSS. Comparisons to mesoanalysis pattern archetypes for past violent-tornado events as research applications (Bunker et al. 2019) were foundational for improving the tactical precision of high-end tornado threat area -- including highlighting the highest tornado threat areas within a short-term graphicast. Moreover, the integration of output from the Statistical Severe Convective Risk Assessment Model (SSCRAM; Hart and Cohen 2016) was critical in contextualizing the mesoscale parameter space in terms of quantified severe-thunderstorm hazard potential in the short-term based on past environments, cloud-to-ground lightning, and downstream severe-thunderstorm reports.
As described above, this presentation will provide unique applications to some of the latest cutting-edge research in severe-storms meteorology. In line with this, NWS Topeka meteorologists have implemented the usage of a tornado-probability model from Cohen et. al (2018) within warning operations. This blended approach of simultaneously combining storm-scale characteristics and mesoscale-environmental conditions provided meteorologists with real-time, quantified, objective, reproducible guidance contextualizing radar today. As a result, this contributed additional confidence to the primary radar operator to message the extreme impacts for a long-lived violent tornado as a Tornado Emergency for southeast Lawrence to Eudora, with initial Tornado Warning lead times on the order of around 40 minutes. As a result, a critical component of this presentation is to showcase research and mesoanalysis applications to enhancing our abilities to enhance the spatiotemporal precision and accuracy of severe-thunderstorm hazards -- contributing to fulfilling our mission of life- and property protection. This presentation will conclude with some discussion of the challenges and intricacies of assessing tornado damage, which has been an important component of compiling post-storm information for the public and NWS partners.