The term elevated convection is used to describe convection where the constituent air parcels originate from a layer above the planetary boundary layer. Because elevated convection can produce severe hail, damaging surface wind, and excessive rainfall in places well removed from strong surface-based instability, situations with elevated storms can be challenging for forecasters. Furthermore, determining the source of air parcels in a given convective cloud using a proximity sounding to ascertain whether the cloud is elevated or surface based would appear to be trivial. In practice, however, this is often not the case. Compounding the challenges in understanding elevated convection is that some meteorologists refer to a cloud formation known as castellanus synonymously as a form of elevated convection. Two different definitions of castellanus exist in the literature-one is morphologically based (cloud formations that develop turreted or cumuliform shapes on their upper surfaces) and the other is physically based (inferring the turrets result from the release of conditional instability). The terms elevated convection and castellanus are not synonymous, because castellanus can arise from surface-based convection and elevated convection exists that does not feature castellanus cloud formations. Therefore, the purpose of this paper is to clarify the definitions of elevated convection and castellanus, fostering a better understanding of the relevant physical processes. Specifically, the present paper advocates the physically based definition of castellanus and recommends eliminating the synonymity between the terms castellanus and elevated convection.
The Super Outbreak of tornadoes over the central and eastern United States on 3-4 April 1974 remains the most outstanding severe convective weather episode on record in the continental United States. The outbreak far surpassed previous and succeeding events in severity, longevity, and extent. In this paper, surface, upper-air, radar, and satellite data are used to provide an updated synoptic and subsynoptic overview of the event. Emphasis is placed on identifying the major factors that contributed to the development of the three main convective bands associated with the outbreak, and on identifying the conditions that may have contributed to the outstanding number of intense and long-lasting tornadoes. Selected output from a 29-km, 50-layer version of the Eta forecast model, a version similar to that available operationally in the mid-1990s, also is presented to help depict the evolution of thermodynamic stability during the event.
Recent literature has identified several supercell/tornado forecast parameters in common use that are operationally beneficial in assessing environments supportive of supercell tornadoes. These parameters are utilized in the computation of tornado forecast guidance such as the significant tornado parameter (STP), a dimensionless parameter developed at the Storm Prediction Center (SPC) that applies a subjectively chosen scale. The goal of this research is to determine if useful logistic regression equations can be developed to estimate the conditional probability of supercell tornadoes that are categorized as level 2 or stronger on the enhanced Fujita scale (EF) when a similar set of environmental background parameters is applied as variables. A large database of Rapid Update Cycle (RUC) analysis soundings in proximity to a representative sample of tornadic and nontornadic supercells over the central and eastern United States, a number of which were associated with EF2 or stronger tornadoes, was used to compute supercell tornado forecast parameters similar to those in the original version of STP. Three logistic regression equations were developed from this database, two of which are described and analyzed in detail. Statistical verification for both equations was accomplished using independent data from 2008 in proximity to supercell storms identified by staff at SPC. A recent version of the STP was utilized as a comparison diagnostic to accomplish part of the statistical verification. The results of this research suggest that output from both logistic regression equations can provide valuable guidance in a probabilistic sense, when adjustments are made for the ongoing convective mode. Case studies presented also suggest that this guidance can provide information complementary to STP in severe weather situations with potential for supercell tornadoes.
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