While the spring and summer months are typically the severe weather climatological peak for the East-Central United States, severe thunderstorms and deadly regional tornado outbreaks can occur during the cool season months (e.g., October-March). In an effort to better document and improve operational forecasting of these events, this study focuses on cool season severe thunderstorms in the Ohio and Tennessee Valleys during the 1995-2002 cool seasons.Most severe thunderstorm and tornado events in the East-Central United States during the cool season are characterized by a high frequency of wind reports compared to hail and tornado reports. All severe report classes (i.e. tornadoes, hail, and wind) displayed a frequency tendency to remain high in the late evening and overnight hours. Additionally, it was found that tornado occurrence typically came in the form of a tornado outbreak. Additionally, when tornadoes did occur, they were found to be statistically more intense than tornadoes outside of the EC region during the same period. It is also concluded tornadoes favor the southern half of the region, whereas hail and wind reports tend to favor the southern two thirds of the region. In examination of cool season supercell characteristics, supercells favors a west-southwest to east-northeast mean motion around 45 mph. The relationship of only 11 percent between the distances of supercell tornado paths to tornadic supercell paths is an operationally important discovery. Knowing on average, how long a cool season supercell tornado is on the ground with respect to the parent supercell can aid operational warning decisions. / Department of Geography

Thesis (M.S.)--Ohio University, August, 2004. / Includes bibliographical references (p. 95-98)

Thesis (M.S.)--University of Wisconsin--Madison, 1965. / eContent provider-neutral record in process. Description based on print version record. Bibliography: l. 30-32.

Thesis (M.S.)--University of Wisconsin--Madison, 1966. / eContent provider-neutral record in process. Description based on print version record. Bibliography: l. 95-102.

Thesis (M.S.)--University of Wisconsin--Madison, 1968. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--Ohio University, August, 2004. / Title from PDF t.p. Includes bibliographical references (p. 95-98)

Tornado outbreaks have significant human impact, so it is imperative forecasts of these phenomena are accurate. As a synoptic setup lays the foundation for a forecast, synoptic-scale aspects of Storm Prediction Center (SPC) outbreak forecasts of varying accuracy were assessed. The percentages of the number of tornado outbreaks within SPC 10% tornado probability polygons were calculated. False alarm events were separately considered. The outbreaks were separated into quartiles using a point-in-polygon algorithm. Statistical composite fields were created to represent the synoptic conditions of these groups and facilitate comparison. Overall, temperature advection had the greatest differences between the groups. Additionally, there were significant differences in the jet streak strengths and amounts of vertical wind shear. The events forecasted with low accuracy consisted of the weakest synoptic-scale setups. These results suggest it is possible that events with weak synoptic setups should be regarded as areas of concern by tornado outbreak forecasters.

The busiest regions of airspace in the U.S. are congested during much of the day from traffic volume, weather, and other airspace restrictions. The projected growth in demand for airspace is expected to worsen this congestion while reducing system efficiency and safety. This dissertation focuses on providing methods to analyze en route airspace congestion during severe convective weather (i.e. thunderstorms) in an effort to provide more efficient aircraft routes in terms of: en route travel time, air traffic controller workload, aircraft collision potential, and equity between airlines and other airspace users. The en route airspace is generally that airspace that aircraft use between the top of climb and top of descent. Existing en route airspace flight planning models have several important limitations. These models do not appropriately consider the uncertainty in airspace demand associated with departure time prediction and en route travel time. Also, airspace capacity is typically assumed to be a static value with no adjustments for weather or other dynamic conditions that impact the air traffic controller. To overcome these limitations a stochastic demand, stochastic capacity, and an incremental assignment method are developed. The stochastic demand model combines the flight departure uncertainty and the en route travel time uncertainty to achieve better estimates for sector demand. This model is shown to reduce the predictive error for en route sector demand by 20\% at a 30 minute look-ahead time period. The stochastic capacity model analyzes airspace congestion at a more macroscopic level than available in existing models. This higher level of analysis has the potential to reduce computational time and increase the number of alternative routing schemes considered. The capacity model uses stochastic geometry techniques to develop predictions of the distribution of flight separation and conflict potential. A prediction of dynamic airspace capacity is calculated based on separation and conflict potential. The stochastic demand and capacity models are integrated into a graph theoretic framework to generate alternative routing schemes. Validation of the overall integrated model is performed using the fast time airspace simulator RAMS. The original flight plans, the routing obtained from an integer programming method, and the routing obtained from the incremental method developed in this dissertation are compared. Results of this validation simulation indicate that integer programming and incremental routing methods are both able to reduce the average en route travel time per flight by 6 minutes. Other benefits include a reduction in the number of conflict resolutions and weather avoidance maneuvers issued by en route air traffic controllers. The simulation results do not indicate a significant difference in quality between the incremental and integer programming methods of routing flights around severe weather. / Ph. D.

That tornadoes cannot occur in mountains due to disruptive influences of the complex terrain is a common misperception. Multiple tornadoes occur each year in mountainous environments, including the Appalachian Mountains. Copious research examines the influences of complex terrain on large severe weather systems such as multicell convective systems and squall lines, but research is lacking investigating this same relationship for smaller-scale severe weather phenomena like supercells and tornadoes. This study examines how complex terrain may have influenced the rotational low-level wind fields of fourteen supercell thunderstorms in the Appalachians. The terrain variables include elevation, land cover, slope, and aspect. Using GIS mapping techniques, the individual storm tracks were overlaid onto elevation, land cover, slope, and aspect layers; points along the storm tracks were measured to correlate storm intensities with the underlying terrain. Hypotheses predict that lower elevations, areas of shallower slopes, agricultural land covers, and terrain features with a southeasterly orientation represent terrain variables that would enhance low-level rotation in the lower levels. Results indicate that elevation has a significant impact on storm rotational intensity, especially in mountainous regions. Lower and flatter elevations augment storm rotational intensity, and higher elevations decrease storm rotational intensity. Additionally, northern and western facing slopes exhibited a negative relationship to storm intensity. A qualitative examination revealed vorticity stretching to be evident in eight of the fourteen storms; with vorticity stretching evident on both southeasterly and northwesterly slopes. Future research on appropriate scale for storm-terrain interactions could reveal even stronger relationships between topography and supercell thunderstorms. / Master of Science

Many studies have been done on synopticallyorced systems and heavy rainfall, but little research has gone into forecasting training convective storms. The research in this paper examines 38 separate synopticallyorced convective extreme precipitation training (SCEPT) events to find trends and consistencies in the synoptic environment. Three separate cases were found in which a SCEPT event occurred: Closed Upper-Level Trough (CULL), Upper-Level Trough (ULT), and 850 Trough/Low (850TL). Each event occurred in areas of precipitable water greater than 36.42 mm (1.43 inches), near maximums of 850 hPa moisture convergence and 700 hPa upper-vertical velocities, under the 850 hPa jet, and in the warm sector of a mid-latitude cyclone. CULL and ULT events occurred in strongly forced synoptic environments where 500 and 300 hPa troughs were evident and generally positively tilted. Little upper-level forcing, above 700 hPa, was found in 850TL events.