Lightning activity during convective cell mergers in a squall line and corresponding dynamical and thermodynamical characteristics

2021 ◽  
pp. 105555
Author(s):  
Jingyu Lu ◽  
Xiushu Qie ◽  
Rubin Jiang ◽  
Xian Xiao ◽  
Dongxia Liu ◽  
...  
Keyword(s):  
Convective Cell ◽  
Lightning Activity ◽  
Squall Line

scholarly journals Time Evolution of TGF-Producing Storms Using ERA5, GPS and Geostationary Satellites Observations

2020 ◽  
Author(s):  
Alessandra Tiberia ◽  
A. Mascitelli ◽  
Leo Pio D’Adderio ◽  
Stefano Federico ◽  
Martino Marisaldi ◽  
...  
Keyword(s):  
Convective Cell ◽  
Lightning Activity ◽  
Added Value ◽  
Gps Data ◽  
Atmospheric Conditions ◽  
Convective Systems ◽  
Average Value ◽  
Monthly Average ◽  
Combined Use ◽  
Wide Range

In this article we report the first investigation over time of the atmospheric conditions around TGFs occurrence, using GPS sensors in combination with geostationary satellite observations and ERA5 reanalyses data. The goal is to understand which characteristics are favourable to the development of these events and to investigate if any precursor signals can be expected. A total of 9 TGFs, occurred at a distance lower than 45 km from a GPS sensor, were analysed and two of them are shown here as an example analysis. Moreover, the lightning activity, collected by the World Wide Lightning Location Network (WWLLN) was used in order to identify any links and correlations with TGF occurrence and PWV trends. The combined use of GPS and the stroke rate trends identified, for all cases, a recurred pattern in which an increase of PWV is observed on a timescale of about two hours before the TGF occurrence that can be placed within the lightning peak. The temporal relation between the PWV trend and TGF occurrence is strictly related to the position of GPS sensors in relation to TGF coordinates. The life cycle of these storms observed by geostationary sensors, described TGFs producing clouds as intense with a wide range of extensions and, in all cases, the TGF is located at the edge of the convective cell. Furthermore, the satellite data give an added value in associating the GPS water vapor trend to the convective cell generating the TGF. The investigation with ERA5 reanalyses data showed that TGFs mainly occur in convective environment with not exceptional values with respect to the monthly average value of parameters measured in the same location. Moreover the analysis showed the strong potential of the use of GPS data for the troposphere characterization in areas with complex territorial morphology. This study provided indications on the dynamics of convective systems linked to TGFs and will certainly help refine our understanding on their production highlights a potential approach through the use of GPS data to explore the lightning activity trend and the TGFs occurrence.

scholarly journals Resolution Dependence and Subfilter-Scale Motions in Idealized Squall-Line Simulations

2020 ◽  
Vol 148 (7) ◽  
pp. 3059-3078
Author(s):  
Kwan Tsaan Lai ◽  
Michael L. Waite
Keyword(s):  
Energy Transfer ◽  
General Structure ◽  
Convective Cell ◽  
Horizontal Resolution ◽  
Squall Line ◽  
Grid Spacing ◽  
Convective Systems ◽  
Eddy Simulation ◽  
Turbulence Mixing ◽  
Scale Motion

Abstract In this paper, the sensitivity of idealized squall-line simulations to horizontal resolution, subgrid turbulence mixing scheme, and subfilter-scale motion is discussed. Inconsistent results from numerical simulations of convective systems have suggested that there are issues with the behavior of the subgrid turbulent mixing parameterizations with increasing resolution that still need to be understood. WRF is used to perform large-eddy simulation of an idealized squall line with horizontal grid spacings of 4 km, 2 km, 1 km, 500 m, and 250 m. While 4 km grid spacing is able to produce the general structure of the squall line, higher-resolution simulations produce more detailed structures. Individual convective cell size decreases, the maximum cloud top height increases, and the subgrid turbulence kinetic energy (TKE) ratio decreases as resolution increases. As found in past studies, 4 km grid spacing is not recommended as it contains an unreasonable amount of subgrid TKE, is not sufficient to resolve the large energy-containing eddies, and may even suppress propagation of the squall line. While horizontal resolution of 1 km can produce a squall line, there are several discrepancies between the 1 km case and higher resolutions, including trailing banded structures and inhibited three-dimensionalization. These issues at 1 km resolution are investigated by examining the subfilter energy transfer for the highest-resolution simulation filtered to a horizontal scale of 1 km. The subfilter energy transfer rate at a scale of 1 km is dominated by the streamwise and shear components. While dissipation dominates the transfer, a significant amount of backscatter also exists, which is not represented by most subgrid models.

scholarly journals Time Evolution of Storms Producing Terrestrial Gamma-Ray Flashes Using ERA5 Reanalysis Data, GPS, Lightning and Geostationary Satellite Observations

2021 ◽  
Vol 13 (4) ◽  
pp. 784
Author(s):  
Alessandra Tiberia ◽  
Alessandra Mascitelli ◽  
Leo Pio D’Adderio ◽  
Stefano Federico ◽  
Martino Marisaldi ◽  
...  
Keyword(s):  
Water Vapor ◽  
Gamma Ray ◽  
Convective Cell ◽  
Reanalysis Data ◽  
Geostationary Satellite ◽  
Satellite Observations ◽  
Lightning Activity ◽  
Added Value ◽  
Gps Data ◽  
Wide Range

In this article, we report the first investigation over time of the atmospheric conditions around terrestrial gamma-ray flash (TGF) occurrences, using GPS sensors in combination with geostationary satellite observations and ERA5 reanalysis data. The goal is to understand which characteristics are favorable to the development of these events and to investigate if any precursor signals can be expected. A total of 9 TGFs, occurring at a distance lower than 45 km from a GPS sensor, were analyzed and two of them are shown here as an example analysis. Moreover, the lightning activity, collected by the World Wide Lightning Location Network (WWLLN), was used in order to identify any links and correlations with TGF occurrence and precipitable water vapor (PWV) trends. The combined use of GPS and the stroke rate trends identified, for all cases, a recurring pattern in which an increase in PWV is observed on a timescale of about two hours before the TGF occurrence that can be placed within the lightning peak. The temporal relation between the PWV trend and TGF occurrence is strictly related to the position of GPS sensors in relation to TGF coordinates. The life cycle of these storms observed by geostationary sensors described TGF-producing clouds as intense with a wide range of extensions and, in all cases, the TGF is located at the edge of the convective cell. Furthermore, the satellite data provide an added value in associating the GPS water vapor trend to the convective cell generating the TGF. The investigation with ERA5 reanalysis data showed that TGFs mainly occur in convective environments with unexceptional values with respect to the monthly average value of parameters measured at the same location. Moreover, the analysis showed the strong potential of the use of GPS data for the troposphere characterization in areas with complex territorial morphologies. This study provides indications on the dynamics of con-vective systems linked to TGFs and will certainly help refine our understanding of their production, as well as highlighting a potential approach through the use of GPS data to explore the lightning activity trend and TGF occurrences.

scholarly journals Evolution of Cloud-to-Ground Lightning and Storm Structure in the Spencer, South Dakota, Tornadic Supercell of 30 May 1998

2003 ◽  
Vol 131 (8) ◽  
pp. 1811-1831 ◽  
Author(s):  
Lawrence D. Carey ◽  
Walter A. Petersen ◽  
Steven A. Rutledge
Keyword(s):  
South Dakota ◽  
Lightning Activity ◽  
Squall Line ◽  
Doppler Velocity ◽  
Lightning Flash ◽  
Flash Rate ◽  
Storm Evolution ◽  
Supercell Storms ◽  
The Difference ◽  
Cg Lightning

Abstract On 30 May 1998, a tornado devastated the town of Spencer, South Dakota. The Spencer tornado (rated F4 on the Fujita tornado intensity scale) was the third and most intense of five tornadoes produced by a single supercell storm during an approximate 1-h period. The supercell produced over 76% positive cloud-to-ground (CG) lightning and a peak positive CG flash rate of 18 flashes min−1 (5-min average) during a 2-h period surrounding the tornado damage. Earlier studies have reported anomalous positive CG lightning activity in some supercell storms producing violent tornadoes. However, what makes the CG lightning activity in this tornadic storm unique is the magnitude and timing of the positive ground flashes relative to the F4 tornado. In previous studies, supercells dominated by positive CG lightning produced their most violent tornado after they attained their maximum positive ground flash rate, whenever the rate exceeded 1.5 flashes min−1. Further, tornadogenesis often occurred during a lull in CG lightning activity and sometimes during a reversal from positive to negative polarity. Contrary to these findings, the positive CG lightning flash rate and percentage of positive CG lightning in the Spencer supercell increased dramatically while the storm was producing F4 damage on Spencer. These results have important implications for the use of CG lightning in the nowcasting of tornadoes and for the understanding of cloud electrification in these unique storms. In order to further explore these issues, the authors present detailed analyses of storm evolution and structure using Sioux Falls, South Dakota, (KFSD) Weather Surveillance Radar-1988 Doppler (WSR-88D) radar reflectivity and Doppler velocity and National Lightning Detection Network (NLDN) CG lightning data. The analyses suggest that a merger between the Spencer supercell and a squall line on its rear flank may have provided the impetus for both the F4 tornadic damage and the dramatic increase in positive CG lightning during the tornado, possibly explaining the difference in timing compared to past studies.

scholarly journals Multi-Variable Classification Approach for the Detection of Lightning Activity Using a Low-Cost and Portable X Band Radar

2018 ◽  
Vol 10 (11) ◽  
pp. 1797 ◽  
Author(s):  
Vincenzo Capozzi ◽  
Mario Montopoli ◽  
Vincenzo Mazzarella ◽  
Anna Marra ◽  
Nicoletta Roberto ◽  
...  
Keyword(s):  
Ad Hoc ◽  
Low Cost ◽  
Area Under The Curve ◽  
Skill Score ◽  
Convective Cell ◽  
Probability Of Detection ◽  
Lightning Activity ◽  
Parameter Method ◽  
No Production ◽  
X Band

This work proposes a multi-parameter method for the detection of cloud-to-ground stroke rate (SRCG) associated to convective cells, based on the measurements of a low-cost single-polarization X-band weather radar. To train and test our procedure, we built up a multi-year dataset, collecting 1575 radar reflectivity volumes that were acquired in the pilot study area of Naples metropolitan environment matched with the LIghtning NETwork (LINET) strokes and meteorological in-situ data. Three radar-based variables are extracted simultaneously for each rain cell and properly merged together, using “ad hoc” classification methods, to produce an estimation of the expected lightning activity for each rain cell. These variables, proxies of mixed-phase particles and ice amount into a convective cell, are combined into a single label to cluster the SRCG into two categories: SRCG = 0 (no production of strokes) or SRCG > 0 (stroke production), respectively. Overall, the main results are comparable with those that were obtained from more advanced radar systems, showing a Critical Success Index of 0.53, an Equitable Threat Score of 0.34, a Frequency Bias Index of 1.00, a Heidke Skill Score of 0.42, a Hanssen-Kuiper Skill Score of 0.42, and an area under the curve of probability of detection as a function of false alarm rate (usually referred as ROC curve) equal to 0.78. The developed technique, although with some limitations, outperforms those based on the use of single stroke proxy parameters.

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