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Abstract This research attempts to use operational radar and satellite products to identify potential locations of quasi-linear convective system (QLCS) tornadogenesis, which can be difficult to predict. It is hypothesized that deep, discrete updrafts indicate portions of the QLCS capable of producing tornadoes, whereas shallower convection indicates more benign portions of the QLCS. To address this hypothesis, storm reports and storm surveys on 30–31 March 2022, during the second intensive observing period of the 2022 Propagation, Evolution, and Rotation in Linear Storms (PERiLS) field campaign, are used to identify locations of tornadoes within the QLCS. These tornado locations are then compared to representations of upper-tropospheric updrafts, namely, overshooting tops (OTs), which are identified with an algorithm using 1-min-resolution mesoscale sector data fromGOES-16Advanced Baseline Imager infrared brightness temperatures, and radar reflectivity cores aloft, identified with Multi-Radar Multi-Sensor (MRMS) 3D mosaic reflectivity products. Only a fraction (less than 30%) of tornadoes within the QLCS are associated with OTs, though over 85% of tornadoes are located near convective cores as indicated by cores of enhanced reflectivity at 9 km MSL. A numerical simulation of the event is also conducted using the Weather Research and Forecasting (WRF) Model which shows a strong relationship between simulated updraft intensity and reflectivity aloft. Given this apparent support of the hypothesis, the identification of updraft signatures within MRMS and high-resolution geostationary satellite data may ultimately help improve the identification of regions within QLCSs most likely to result in tornadoes.
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This content will become publicly available on July 29, 2027
Characteristics of Discrete Updrafts in Quasi-Linear Convective Systems, Environmental Influences, and Implications for Tornadogenesis Prediction
Abstract Quasi-linear convective system (QLCS) tornadoes are particularly difficult for forecasters to predict, commonly resulting in short or negative warning lead times. However, it is hypothesized that relatively deep, discrete updrafts may provide a nowcasting tool, indicating portions of a linear system where tornadogenesis is most probable due to enhanced low-level lifting capable of tilting and stretching vorticity. It is further hypothesized that discrete updraft properties correlate to tornado intensity and duration. Deep, discrete updrafts are easily identifiable in upper-tropospheric radar data, which are still available far from the nearest radar site, where low-level rotation data are unavailable. Using a dataset covering four years (2021–2024), it is shown 59.5% of QLCS tornadoes are preceded by discrete radar reflectivity cores several kilometers aloft, identified using gridded Multi-Radar Multi-Sensor (MRMS) data and indicating the presence of a deep updraft. The percentage of reflectivity core co-locations is higher for both more intense QLCS tornadoes (85.7% for EF-3 tornadoes) and for tornadoes occurring in the cool season (66.1%). Analysis of the near-storm environments in each case reveals 5–10 km shear is the best predictor both of tornado intensity and which tornadoes will be co-located with reflectivity cores, with greater shear resulting in more tornadoes having discrete updrafts. The operational applicability of reflectivity cores for QLCS tornadogenesis anticipation may be limited by the frequency of nontornadic cores, tornadoes without reflectivity cores, and cores offering only short lead times.
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- Award ID(s):
- 2020462
- PAR ID:
- 10704170
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Weather and Forecasting
- ISSN:
- 0882-8156
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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