scholarly journals The Foshan Total Lightning Location System in China and Its Initial Operation Results

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 149 ◽  
Author(s):  
Li Cai ◽  
Xin Zou ◽  
Jianguo Wang ◽  
Quanxin Li ◽  
Mi Zhou ◽  
...  
Keyword(s):  
Electromagnetic Waves ◽  
Three Dimensional ◽  
Radar Data ◽  
Time Of Arrival ◽  
Initial Operation ◽  
Lightning Strikes ◽  
Location System ◽  
Lightning Location System ◽  
Total Lightning ◽  
Operation Results

In the summer of 2013, a three-dimensional (3D)-based Foshan Total Lightning Location System (FTLLS), embedded with differential time of arrival (DTOA) techniques, was installed and started its operation in Foshan, Guangdong Province, China. In this paper, the geographical distribution and set-up information of FTLLS, the estimated locating errors and locating results, as well as its initial operation results are presented. FTLLS consists of nine sub-stations that receive electromagnetic waves associated with lightning discharges and locates VLF/LF (200 Hz–500 kHz) radiation sources in 3D. The remote sub-stations acquired triggered waveforms with a duration of 0.5 ms, a resolution of 12-bits, and a GPS-based sferic time tags of 24 h per day. Cloud-to-ground (CG) lightning events, intra-cloud (IC) lightning events and narrow bipolar events (NBEs) were located by FTLLS. Based on the Monte Carlo simulation, the two-dimensional horizontal location error is basically less than 100 m, and the vertical error (altitude) is less than 200 m when the lightning event occurs within the network. On the other hand, over 14 million lightning strikes were recorded successfully by FTLLS during the period of May to October in 2014, among which IC events, CG events and NBEs accounted for 65%, 34% and 1%, respectively. It is shown that FTLLS is capable of a fine three-dimensional (3D) location, in which the altitude parameters obtained are reasonable and well consistent with observed data in the previous studies. The location results of thunderstorms were additionally verified through simultaneously-observed radar data.

scholarly journals Relationships between Deep Convection Updraft Characteristics and Satellite-Based Super Rapid Scan Mesoscale Atmospheric Motion Vector–Derived Flow

2018 ◽  
Vol 146 (10) ◽  
pp. 3461-3480 ◽  
Author(s):  
Jason M. Apke ◽  
John R. Mecikalski ◽  
Kristopher Bedka ◽  
Eugene W. McCaul ◽  
Cameron R. Homeyer ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Deep Convection ◽  
Motion Vector ◽  
Three Dimensional ◽  
Radar Data ◽  
Severe Weather ◽  
Lightning Flash ◽  
Rapid Scan ◽  
Total Lightning ◽  
The Relationship

Abstract Rapid acceleration of cloud-top outflow near vigorous storm updrafts can be readily observed in Geostationary Operational Environmental Satellite-14 (GOES-14) super rapid scan (SRS; 60 s) mode data. Conventional wisdom implies that this outflow is related to the intensity of updrafts and the formation of severe weather. However, from an SRS satellite perspective, the pairing of observed expansion and updraft intensity has not been objectively derived and documented. The goal of this study is to relate GOES-14 SRS-derived cloud-top horizontal divergence (CTD) over deep convection to internal updraft characteristics, and document evolution for severe and nonsevere thunderstorms. A new SRS flow derivation system is presented here to estimate storm-scale (<20 km) CTD. This CTD field is coupled with other proxies for storm updraft location and intensity such as overshooting tops (OTs), total lightning flash rates, and three-dimensional flow fields derived from dual-Doppler radar data. Objectively identified OTs with (without) matching CTD maxima were more (less) likely to be associated with radar-observed deep convection and severe weather reports at the ground, suggesting that some OTs were incorrectly identified. The correlation between CTD magnitude, maximum updraft speed, and total lightning was strongly positive for a nonsupercell pulse storm, and weakly positive for a supercell with multiple updraft pulses present. The relationship for the supercell was nonlinear, though larger flash rates are found during periods of larger CTD. Analysis here suggests that combining CTD with OTs and total lightning could have severe weather nowcasting value.

Observation of lightning by means of time-of-arrival type lightning location system

1997 ◽  
Vol 120 (1) ◽  
pp. 9-15 ◽  
Author(s):  
Ei'ichi Zaima ◽  
Azuma Mochizuki ◽  
Naoki Fukiyama ◽  
Jun'ichi Hojo ◽  
Masaru Ishii
Keyword(s):  
Time Of Arrival ◽  
Location System ◽  
Lightning Location System

Baseline Consideration for Lightning Location System Based on Magnetic Field Direction Finding to Determine Optimal Grid Cell of Lightning Flash Density Map

2015 ◽  
Vol 781 ◽  
pp. 292-295
Author(s):  
Kongtrakul Nattanapong ◽  
Rungseevijitprapa Weerapun
Keyword(s):  
Grid Cell ◽  
Direction Finding ◽  
Lightning Flash ◽  
Magnetic Field Direction ◽  
Grid Cells ◽  
Lightning Strikes ◽  
Location System ◽  
Cloud To Ground Lightning ◽  
Lightning Location System ◽  
Density Map

Lightning flash density map from lightning location system is primary for lightning protection. The baseline of lightning location system affects not only location accuracy, but also accuracy of lightning flash density. In order to obtain lightning flash density map, the different baselines were studied to determine optimum grid cell. This paper utilizes the capabilities of Matlab® software to simulate grid cell by using magnetic direction finding technique and Marquardt method. These baselines were generated between 150 km and 250 km. In addition, grid cells were created at spatial resolutions of 10 km to 50 km, and cloud-to-ground lightning strikes were randomly created at density, ranging from 1 to 10 strikes per square kilometer. The mean error values of lightning location system are obtained between 1.756 km and 2.885 km from baseline 150 km to 250 km. Size of optimal grid cells must be designed 21.8 km and 23 km for baselines 150 km and 250 km respectively.

On the return-stroke current estimation of Foshan Total Lightning Location System (FTLLS)

2021 ◽  
Vol 248 ◽  
pp. 105194
Author(s):  
Quanxin Li ◽  
Jianguo Wang ◽  
Li Cai ◽  
Mi Zhou ◽  
Yadong Fan
Keyword(s):  
Return Stroke ◽  
Location System ◽  
Current Estimation ◽  
Lightning Location System ◽  
Total Lightning

scholarly journals Assimilating FY-4A Lightning and Radar Data for Improving Short-Term Forecasts of a High-Impact Convective Event with a Dual-Resolution Hybrid 3DEnVAR Method

2021 ◽  
Vol 13 (16) ◽  
pp. 3090
Author(s):  
Peng Liu ◽  
Yi Yang ◽  
Anwei Lai ◽  
Yunheng Wang ◽  
Alexandre O. Fierro ◽  
...  
Keyword(s):  
Water Vapor ◽  
Three Dimensional ◽  
Wrf Model ◽  
Radar Data ◽  
Horizontal Resolution ◽  
Wind Fields ◽  
Short Term ◽  
Background Error ◽  
Forecast Performance ◽  
Total Lightning

A dual-resolution, hybrid, three-dimensional ensemble-variational (3DEnVAR) data assimilation method combining static and ensemble background error covariances is used to assimilate radar data, and pseudo-water vapor observations to improve short-term severe weather forecasts with the Weather Research and Forecast (WRF) model. The higher-resolution deterministic forecast and the lower-resolution ensemble members have 3 and 9 km horizontal resolution, respectively. The water vapor pseudo-observations are derived from the combined use of total lightning data and cloud top height from the Fengyun-4A(FY-4A) geostationary satellite. First, a set of single-analysis experiments are conducted to provide a preliminary performance evaluation of the effectiveness of the hybrid method for assimilating multisource observations; second, a set of cycling analysis experiments are used to evaluate the forecast performance in convective-scale high-frequency analysis; finally, different hybrid coefficients are tested in both the single and cycling experiments. The single-analysis results show that the combined assimilation of radar data and water vapor pseudo-observations derived from the lightning data is able to generate reasonable vertical velocity, water vapor and hydrometeor adjustments, which help to trigger convection earlier in the forecast/analysis and reduce the spin-up time. The dual-resolution hybrid 3DEnVAR method is able to adjust the wind fields and hydrometeor variables with the assimilation of lightning data, which helps maintain the triggered convection longer and partially suppress spurious cells in the forecast compared with the three-dimensional variational (3DVAR) method. A cycling analysis that introduced a large number of observations with more frequent small adjustments is able to better resolve the observed convective events than a single-analysis approach. Different hybrid coefficients can affect the forecast results, either in the single deterministic or cycling analysis experiments. Overall, we found that a static coefficient of 0.4 and an ensemble coefficient of 0.6 yields the best forecast skill for this event.

scholarly journals Observation of Lightning by Time-of-Arrival Type Lightning Location System (LPATS)

1996 ◽  
Vol 116 (9) ◽  
pp. 1033-1038
Author(s):  
Ei-Ichi Zaima ◽  
Azuma Mochizuki ◽  
Naoki Fukiyama ◽  
Jun-Ichi Hojo ◽  
Masaru Ishii
Keyword(s):  
Time Of Arrival ◽  
Location System ◽  
Lightning Location System

scholarly journals Automated thunderstorm tracking: utilization of three-dimensional lightning- and radar data

2013 ◽  
Vol 13 (1) ◽  
pp. 2179-2216 ◽  
Author(s):  
V. K. Meyer ◽  
H. Höller ◽  
H. D. Betz
Keyword(s):  
Hybrid Method ◽  
Three Dimensional ◽  
Active Regions ◽  
Radar Data ◽  
Close Monitoring ◽  
Continuous Assessment ◽  
Storm Evolution ◽  
Comprehensive Picture ◽  
Storm Dynamics ◽  
Total Lightning

Abstract. This paper presents a new hybrid method for automated thunderstorm observation by tracking and monitoring of electrically charged cells (ec-TRAM). The developed algorithm combines information about intense ground precipitation derived from low-level radar-reflectivity scans with three-dimensionally resolved lightning data, which are provided by the European VLF/LF lightning detection network LINET. Based on the already existing automated radar tracker rad-TRAM (Kober and Tafferner, 2009), the new method li-TRAM identifies and tracks electrically active regions in thunderclouds using lightning data only. The algorithm ec-TRAM uses the output of the two autonomously operating routines rad-TRAM and li-TRAM in order to assess, track, and monitor a more comprehensive picture of thunderstorms. The main motivation of this work is to assess the benefit of three-dimensionally resolved total lightning information (TL) for thunderstorm tracking and nowcasting. The focus is laid on the temporal development whereby TL is characterized by an effective in-cloud (IC) and cloud-to-ground (CG) event-discrimination. It is found that the algorithms li-TRAM and ec-TRAM are both feasible methods for thunderstorm nowcasting. The tracking performance of li-TRAM turns out to be comparable to that of rad-TRAM, a result that strongly encourages utilization of lightning data as independent data source for thunderstorm tracking. It is found that lightning data allow an accurate and close monitoring of storm regions with intense internal dynamics as soon as convection induces electrical activity. A case study shows that the current short-term storm dynamics are clearly reflected in the amount of strokes, change of stroke rates and IC/CG ratio. The hybrid method ec-TRAM outperforms rad-TRAM and li-TRAM regarding reliability and continuous assessment of storm tracks especially in more complexly developing storms, where the use of discharge information contributes to more detailed information about storm stage and storm evolution.

scholarly journals Assimilation of Flash Extent Data in the Variational Framework at Convection-Allowing Scales: Proof-of-Concept and Evaluation for the Short-Term Forecast of the 24 May 2011 Tornado Outbreak

2016 ◽  
Vol 144 (11) ◽  
pp. 4373-4393 ◽  
Author(s):  
Alexandre O. Fierro ◽  
Jidong Gao ◽  
Conrad L. Ziegler ◽  
Kristin M. Calhoun ◽  
Edward R. Mansell ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Three Dimensional ◽  
Wrf Model ◽  
Radar Data ◽  
Added Value ◽  
Short Term ◽  
Short Term Forecast ◽  
Term Forecast ◽  
Total Lightning ◽  
Tornado Outbreak

Abstract This work evaluates the performance of the assimilation of total lightning data within a three-dimensional variational (3DVAR) framework for the analysis and short-term forecast of the 24 May 2011 tornado outbreak using the Weather Research and Forecasting (WRF) Model at convection-allowing scales. Between the lifted condensation level and a fixed upper height, pseudo-observations for water vapor mass first are created based on either the flash extent densities derived from Oklahoma Lightning Mapping Array data or the lightning source densities derived from the Earth Networks pulse data, and then assimilated by the 3DVAR system. Assimilation of radar data with 3DVAR and a cloud analysis algorithm (RAD) also are performed as a baseline for comparison and in tandem with lightning to evaluate the added value of this lightning data assimilation (LDA) method. Given a scenario wherein the control experiment without radar or lightning data assimilation fails to accurately initiate and forecast the observed storms, the LDA and RAD yield comparable short-term forecast improvements. The RAD alone produces storms of similar strength to the observations during the first 30 min of forecast more rapidly than the LDA alone; however, the LDA is able to better depict individual supercellular features at 1-h forecast. When both the lightning and radar data are assimilated, the 30-min forecast showed noteworthy improvements over RAD in terms of the model’s ability to better resolve individual supercell structures and still maintained a 1-h forecast similar to that from the LDA. The results chiefly illustrate the potential value of assimilating total lightning data along with radar data.

scholarly journals Automated thunderstorm tracking: utilization of three-dimensional lightning and radar data

2013 ◽  
Vol 13 (10) ◽  
pp. 5137-5150 ◽  
Author(s):  
V. K. Meyer ◽  
H. Höller ◽  
H. D. Betz
Keyword(s):  
Hybrid Method ◽  
Three Dimensional ◽  
Active Regions ◽  
Radar Data ◽  
Close Monitoring ◽  
Continuous Assessment ◽  
Storm Evolution ◽  
Comprehensive Picture ◽  
Storm Dynamics ◽  
Total Lightning

Abstract. This paper presents a new hybrid method for automated thunderstorm observation by tracking and monitoring of electrically charged cells (ec-TRAM). The developed algorithm combines information about intense ground precipitation derived from low-level radar-reflectivity scans with three-dimensionally resolved lightning data, which are provided by the European VLF/LF lightning detection network LINET. Based on the already existing automated radar tracker rad-TRAM (Kober and Tafferner, 2009), the new method li-TRAM identifies and tracks electrically active regions in thunderclouds using lightning data only. The algorithm ec-TRAM uses the output of the two autonomously operating routines rad-TRAM and li-TRAM in order to assess, track, and monitor a more comprehensive picture of thunderstorms. The main motivation of this work is to assess the benefit of three-dimensionally resolved total lightning (TL) information for thunderstorm tracking and monitoring. The focus is laid on the temporal development whereby TL is characterized by an effective in-cloud (IC) and cloud-to-ground (CG) event discrimination. It is found that the algorithms li-TRAM and ec-TRAM are both feasible methods for thunderstorm monitoring with potential for nowcasting. The tracking performance of li-TRAM turns out to be comparable to that of rad-TRAM, a result that strongly encourages utilization of lightning data as independent data source for thunderstorm tracking. It is found that lightning data allow an accurate and close monitoring of storm regions with intense internal dynamics as soon as convection induces electrical activity. A case study shows that the current short-term storm dynamics are clearly reflected in the amount of strokes, change of stroke rates and IC/CG ratio. The hybrid method ec-TRAM outperforms rad-TRAM and li-TRAM regarding reliability and continuous assessment of storm tracks especially in more complexly developing storms, where the use of discharge information contributes to more detailed information about storm stage and storm evolution.

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