Gibbs, J. G., 2016: A skill assessment of techniques for real-time diagnosis and short-term prediction of tornado intensity using the WSR-88D. J. Operational Meteor., 4 (13), 170181 The guidance is found to be sufficiently skillful at diagnosing tornado intensity. Perhaps most usefully, when attempting to differentiate between weak and strong/violent tornadoes in real-time, skill scores peak at the threshold of 20.57 m s -1 (40 kt) of rotational velocity when the velocity couplet is combined with a TDS. Skill sufficient for operational decision making also is evaluated and found in other permutations of rotational velocity, with and without a TDS, and the guidance regarding the height of the TDS. Beyond realtime diagnosis, several subjectively analyzed radar parameters show skill within the dataset at differentiating between strong/violent and weak tornadoes with lead times of 2-3 volume scans.

We identified drug overdose as a strong predictor of ICU admission, while age, drug overdose and history of previous suicide attempts predict hospital admission. We recommend reviewing physician practices, especially safe medication, in suicide risk patients. Our study also highlights the need for continued close collaboration by acute care and community mental health providers for quality improvement.

Weakly forced large-scale weather patterns often dominate the warm season (June-September) in the Lower Rio Grande Valley of Texas. In this regime, forecasting thunderstorm development is often tied to very subtle features, making this task particularly challenging. There appears to be a link between middleand lower-level moisture content (specifically at 850-700 hPa) and the frequency of thunderstorm development, with little variability in many other meteorological variables. Higher 850-700-hPa relative humidity values link to much higher rates of thunderstorm development.

Previous work has considered tornado occurrence with respect to radar data, both WSR-88D and mobile research radars, and a few studies have examined techniques to potentially improve tornado warning performance. To date, though, there has been little work focusing on systematic, large-sample evaluation of National Weather Service (NWS) tornado warnings with respect to radar-observable quantities and the near-storm environment. In this work, three full years (2016–2018) of NWS tornado warnings across the contiguous United States were examined, in conjunction with supporting data in the few minutes preceding warning issuance, or tornado formation in the case of missed events. The investigation herein examines WSR-88D and Storm Prediction Center (SPC) mesoanalysis data associated with these tornado warnings with comparisons made to the current Warning Decision Training Division (WDTD) guidance.Combining low-level rotational velocity and the significant tornado parameter (STP), as used in prior work, shows promise as a means to estimate tornado warning performance, as well as relative changes in performance as criteria thresholds vary. For example, low-level rotational velocity peaking in excess of 30 kt (15 m s−1), in a near-storm environment which is not prohibitive for tornadoes (STP > 0), results in an increased probability of detection and reduced false alarms compared to observed NWS tornado warning metrics. Tornado warning false alarms can also be reduced through limiting warnings with weak (<30 kt), broad (>1nm) circulations in a poor (STP=0) environment, careful elimination of velocity data artifacts like sidelobe contamination, and through greater scrutiny of human-based tornado reports in otherwise questionable scenarios.

Tornadoes produced by quasi-linear convective systems (QLCS) present a significant challenge to National Weather Service warning operations. Given the speed and scale at which they develop, different methods for tornado warning decision making are required than what traditionally are used for supercell storms. This study evaluates the skill of one of those techniques—the so-called three-ingredients method—and produces new approaches. The three-ingredients method is found to be reasonably skillful at short lead times, particularly for systems that are clearly linear. From the concepts and science of the three-ingredients method, several new combinations of environmental and radar parameters emerge that appear slightly more skillful, and may prove easier to execute in real time. Similar skill between the emerging methods provides the forecaster with options for what might work best in any given scenario. A moderate positive correlation with overall wind speed with some radar and environmental variables also is identified. Additionally, mesoscale convective vortices and supercell-like features in QLCS are found to produce tornadoes at a much higher rate than purely linear systems.