A Performance Evaluation of the World Wide Lightning Location Network (WWLLN) over the Tibetan Plateau

Fan, Penglei; Zheng, Dong; Zhang, Yijun; Gu, Shanqiang; Zhang, Wenjuan; Yao, Wen; Yan, Binbin; Xu, Yujuan

doi:10.1175/jtech-d-17-0144.1

Cited by 23 publications

(33 citation statements)

References 32 publications

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“…In both the PV and TC thunderstorms, the system developed from east to west, and both were dominated by negative CG lightning; this agrees with Fan et al (2018), who found that the proportion of positive CG lightning in the eastern part of the QTP is low. The liquid water content and convective activities within the clouds have a key influence on the initiating discharge process, and the cold cloud regions (TBB < −40 °C) and the regions with a large TBB gradient are more favorable to the development of CG lightning, which is consistent with the analysis of strong thunderstorm weather in Hohhot (Li et al, 2021).…”

Section: Discussionsupporting

confidence: 87%

Characteristics of two different types of thunderstorms in summer over the Nagqu area in China

Yan

Zhou²,

Hui³

2022

Front. Earth Sci.

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To investigate further the characteristics of thunderstorms on the Qinghai–Tibet plateau, a plateau vortex (PV) thunderstorm and a local thermoconvective (TC) thunderstorm over the Nagqu area are analyzed using cloud-radar, microwave-radiometer, and raindrop-spectrometer data, and their macrophysical and microphysical evolution characteristics are discussed in terms of thermodynamic processes, microphysical processes, and lightning activities. The results show the following. 1) The cloud layer was deeper in the PV thunderstorm, but the TC thunderstorm had a stronger short-time updraft with a radial velocity exceeding 10 m/s, and the warming from the strong updraft action and latent heat release from the hydromorphic phase change was about twice that of the PV thunderstorm. 2) The water vapor density increased significantly when the thunderstorm cloud passed, and the liquid water content in the middle and lower layers exceeded 4 g/m3. The maximum ice water content in the TC thunderstorm was twice bigger than that in the PV thunderstorm. The trends of raindrop number concentration and rain intensity of the PV thunderstorm were similar, and the average particle size of raindrops was smaller than that of the TC thunderstorm. 3) Both types of thunderstorms accounted for more than 90% of negative cloud-to-ground (CG) lightning, and the regions with black-body temperature (TBB) less than −40 °C and a larger TBB gradient were more favorable for the occurrence of CG lightning. 4) Thermodynamic fields bring water vapor and lift for microphysical processes, and microphysical changes release latent heat to enhance the dynamic effects, which together promote the development of lightning activities. The peak radial velocity and ice-phase particle concentration were more than 10 min ahead of the active peak of the CG lightning. This study reveals the macrophysical and microphysical evolution characteristics of different types of thunderstorms and provides a certain scientific basis for disaster prevention and mitigation regarding thunderstorms over the Nagqu area.

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Section: Discussionsupporting

confidence: 87%

Characteristics of two different types of thunderstorms in summer over the Nagqu area in China

Yan

Zhou²,

Hui³

2022

Front. Earth Sci.

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“…A CG lightning strike consists of one to multiple strokes within a specified time and distance. As a result, a strike is defined as a set of strokes sequentially separated in time by no more than 0.5 s and in space by no more than 10 km (Zheng et al ., 2016a; Zheng et al ., 2016b; Fan et al ., 2018). For the LS‐scheme, a definition method similar to that of Ukkonen and Mäkelä (2019) was adopted.…”

Section: Data Processing and Methodsmentioning

confidence: 99%

“…Then, the user workstation processes or issues lightning information. The lightning information for a certain period is the CG lightning detection data, which include the precise occurrence time, latitude, longitude, polarity and peak current of any single lightning strike (Fan et al ., 2018).…”

Section: Study Area and Datamentioning

confidence: 99%

Modelling deep convective activity using lightning clusters and machine learning

Shi

Zhang

Fan

et al. 2021

Intl Journal of Climatology

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Retrieving thunderstorm activity through specific thermodynamic and kinematic parameters is paramount for predicting deep convective weather and investigating long‐term climatology of storm. However, the reliability of the relationship between parameters and convective events is restricted by the modelling methods and sampling of thunderstorm activity. There is no objective definition of a thunderstorm, so the clustering method is applied to the cloud‐to‐ground (CG) lightning stroke data in Central China to identify lightning clusters. These clusters are then gridded and associated with environmental variables derived from ERA5 reanalysis. Finally, machine learning (ML) technologies are applied to model the occurrence of thunderstorms. In addition, ERA5 is also evaluated. The parameters related to moisture and lapse rate calculated by ERA5 are close to sounding measurements, such as Td850, PW, LR700_400 and KI, whose correlation coefficients exceed 0.90. ERA5 has a good estimation of some parameters that are susceptible to the influence of the boundary layer. Compared with the lightning strike‐based scheme, our scheme obtains the best performance index values. An agreement between observations and predictions based on lightning clusters is also evident from the diurnal cycle of thunderstorm probabilities. Although thunderstorm activity on complex terrain is underestimated, the created ML model can explain 61.4% of the variance in the observed frequency. The results of the significance test reveal that there are statistically significant differences between the soundings corresponding to some isolated CG strikes and the thunderstorm class, but the distribution is the same as that of the non‐thunderstorm class. Solar radiation, topographic features and lake distribution play a major role in promoting the occurrence and development of thunderstorms.

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“…Therefore, the WWLLN strokes were grouped into flashes in this study to analyze the corresponding flash activities. The grouping algorithm is based on time and space criteria of 0.5 s and 30 km, respectively [66]. Here, a "WWLLN flash" is a collection of strokes that occur near each other in time and space and are not necessarily part of the same lightning flash.…”

Section: Wwllnmentioning

confidence: 99%

Preliminary Observations from the China Fengyun-4A Lightning Mapping Imager and Its Optical Radiation Characteristics

et al. 2020

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The Fengyun-4A (FY-4A) Lightning Mapping Imager (LMI) is the first satellite-borne lightning imager developed in China, which can detect lightning over China and its neighboring regions based on a geostationary satellite platform. In this study, the spatial distribution and temporal variation characteristics of lightning activity over China and its neighboring regions were analyzed in detail based on 2018 LMI observations. The observation characteristics of the LMI were revealed through a comparison with the Tropical Rainfall Measuring Mission (TRMM)-Lightning Imaging Sensor (LIS) and World Wide Lightning Location Network (WWLLN) observations. Moreover, the optical radiation characteristics of lightning signals detected by the LMI were examined. Factors that may affect LMI detection were discussed by analyzing the differences in optical radiation characteristics between LMI and LIS flashes. The results are as follows. Spatially, the flash density distribution pattern detected by the LMI was similar to those detected by the LIS and WWLLN. High-flash density regions were mainly concentrated over Southeastern China and Northeastern India. Temporally, LMI flashes exhibited notable seasonal and diurnal variation characteristics. The LMI detected a concentrated lightning outbreak over Northeastern India in the premonsoon season and over Southeastern China in the monsoon season, which was consistent with LIS and WWLLN observations. LMI-observed diurnal peak flash rates occurred in the afternoon over most of the regions. There was a “stepwise” decrease in the LMI-observed optical radiance, footprint size, duration, and number of groups per flash, from the ocean to the coastal regions to the inland regions. LMI flashes exhibited higher optical radiance but lasted for shorter durations than LIS flashes. LMI observations are not only related to instrument performance but are also closely linked to onboard and ground data processing. In future, targeted improvements can be made to the data processing algorithm for the LMI to further enhance its detection capability.

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A Performance Evaluation of the World Wide Lightning Location Network (WWLLN) over the Tibetan Plateau

Cited by 23 publications

References 32 publications

Characteristics of two different types of thunderstorms in summer over the Nagqu area in China

Characteristics of two different types of thunderstorms in summer over the Nagqu area in China

Modelling deep convective activity using lightning clusters and machine learning

Preliminary Observations from the China Fengyun-4A Lightning Mapping Imager and Its Optical Radiation Characteristics

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