Thunderstorm Activity Research Articles

ENSO‐Based Predictability of a Regional Severe Thunderstorm Index

AbstractHere we use coupled climate model forecasts of Niño 3.4 and a regional (Texas, Oklahoma, Arkansas, and Louisiana) tornado environment index (TEI) to examine the modulation of US severe thunderstorm activity by the El Niño‐Southern Oscillation (ENSO). The large number of forecast initializations, leads, and ensemble members reduces sampling variability and increases detail in the analysis. The strongest negative relations between TEI and concurrent Niño 3.4 are found in February and March. Both the average of TEI and its spread are larger during cool ENSO conditions, which raises the question of how predictability differs between warm and cool conditions. Predictability is measured using perfect‐model skill scores. For a deterministic skill score, which is equivalent to signal‐to‐noise ratio, larger spread during cool conditions means less predictability. On the other hand, perfect‐model probabilistic skill scores are slightly higher (higher predictability) during February and March for cool conditions than for warm conditions due to larger probability shifts.

Formation factors of the most electrically active thunderstorm days over Poland (2002–2020)

This research documents atmospheric conditions and development of high electrically active thunderstorm days that occurred over Poland in period 2002–2020. The 8 days with the highest number of detected cloud-to-ground flashes during one storm cell life cycle were analyzed. The study used data from the PERUN lightning detection and location system, ERA5-reanalysis, vertical atmospheric soundings, and synoptic maps as well. As a result of the analysis, it can be concluded that the development of thunderstorms is positively influenced by the low-pressure area above the North Sea and the atmospheric fronts with zone of wind convergence in the lower troposphere. The analyzed storm systems on the analyzed days were created in the atmosphere of a high vertical wind shear (from 10 to 18 m s−1), lifted index (from +0.04 to –8.22), thermodynamic instability (CAPE 1000–3700 J kg−1), rich boundary layer moisture (mixing ratio: 12–14 g kg−1), and high tropospheric moisture (total column water vapour >50 kg m−2). Very moist air masses ahead of the storm systems provided consistent access to large amounts of latent heat released into the clouds and intensified upward mass fluxes and development of intense lightning activity from Cumulonimbus cloud.

A Complete Mission Concept Design and Analysis of the Student-Led CubeSat Project: Light-1

Terrestrial gamma ray flashes (TGF) are intense and prompt bursts of X- and gamma-rays of up to 100 MeV of energy. Typically associated with thunderstorm activity, TGFs are produced by bremsstrahlung effects of electrons accelerated in strong electric fields generated by lightning. TGFs can be effectively targeted by gamma detectors with enhanced time stamping capabilities onboard of satellites operating at near-Earth low obits (LEO). Light-1 is a miniature satellite, a 3U CubeSat designed to detect, monitor and study terrestrial gamma ray flashes in low Earth orbit. The two payload detectors are composed of a photomultiplier tube and silicon photomultipliers. The two detectors are mounted at two ends of the CubeSat and the proposed orientation of the CubeSat will ensure maximum TGF detection probability. To allow an increased frequency of data downlink, Khalifa University has collaborated with NanoAvionics Corp, and hence Light-1 has access to three ground stations situated across the map, Abu Dhabi in United Arab Emirates, Vilnius in Lithuania, and Aalborg in Denmark. The satellite expected to launch in late-2021 is currently in its assembly and integration phase. This paper describes mission, concept, objectives, success criteria, design, analysis, status, and the future plans of Light-1 satellite.

A Tale of Two Rapidly Intensifying Supertyphoons: Hagibis (2019) and Haiyan (2013)

AbstractDevastating Japan in October 2019, Supertyphoon (STY) Hagibis was an important typhoon in the history of the Pacific. A striking feature of Hagibis was its explosive rapid intensification (RI). In 24 h, Hagibis intensified by 100 knots (kt; 1 kt ≈ 0.51 m s−1), making it one of the fastest-intensifying typhoons ever observed. After RI, Hagibis’s intensification stalled. Using the current typhoon intensity record holder, i.e., STY Haiyan (2013), as a benchmark, this work explores the intensity evolution differences of these two high-impact STYs. We found that the extremely high prestorm sea surface temperature reaching 30.5°C, deep/warm prestorm ocean heat content reaching 160 kJ cm−2, fast forward storm motion of ∼8 m s−1, small during-storm ocean cooling effect of ∼0.5°C, significant thunderstorm activity at its center, and rapid eyewall contraction were all important contributors to Hagibis’s impressive intensification. There was 36% more air–sea flux for Hagibis’s RI than for Haiyan’s. After its spectacular RI, Hagibis’s intensification stopped, despite favorable environments. Haiyan, by contrast, continued to intensify, reaching its record-breaking intensity of 170 kt. A key finding here is the multiple pathways that storm size affected the intensity evolution for both typhoons. After RI, Hagibis experienced a major size expansion, becoming the largest typhoon on record in the Pacific. This size enlargement, combined with a reduction in storm translational speed, induced stronger ocean cooling that reduced ocean flux and hindered intensification. The large storm size also contributed to slower eyewall replacement cycles (ERCs), which prolonged the negative impact of the ERC on intensification.

Chemical Response of the Upper Atmosphere Due to Lightning‐Induced Electron Precipitation

AbstractTerrestrial lightning frequently serves as a loss mechanism for energetic electrons in the Van Allen radiation belts, leading to lightning‐induced electron precipitation (LEP). Regardless of the specific causes, energetic electron precipitation from the radiation belts in general has a significant influence on the ozone concentration in the stratosphere and mesosphere. The atmospheric chemical effects induced by LEP have been previously investigated using subionospheric VLF measurements at Faraday station, Antarctica (65.25°S, 64.27°W, L = 2.45). However, there exist large variations in the precipitation flux, ionization production, and occurrence rate of LEP events depending on the peak current of the parent lightning discharge, as well as the season, location, and intensity of the thunderstorm activity. These uncertainties motivate us to revisit the calculation of atmospheric chemical changes produced by LEP. In this study, we combine a well‐validated LEP model and first‐principles atmospheric chemical simulation, and investigate three intense storms in the year of 2013, 2015, and 2017 at the magnetic latitude of 50., 32., and 35., respectively. Modeling results show that the LEP events in these storms can cumulatively drive significant changes in the , , and concentration in the mesosphere. These changes are as high as , , and at 75–85 km altitude, respectively, and comparable to the effects typically induced by other types of radiation belt electron precipitation events. Considering the high occurrence rate of thunderstorms around the globe, the long‐term global chemical effects produced by LEP events need to be properly quantified.

An Assessment of Occurrences of Thunderstorm as an Indicator of Climate Change : A Case Study of Potiskum and its Environs, Yobe State, Nigeria

This study examines the occurrences of thunderstorm and rainfall as indicator of climate change in Potiskum and its environs through exploring the decadal recorded data of rainfall and thunderstorm. The data obtained were used to analyze the changes and activities of thunderstorms with rainfall, and thunderstorms without rainfall for each month of the 30 years under study. A descriptive and Inferential statistics was employed to determine the frequency and trend of thunderstorm activities as well as the intensity of rainfall. The analysis indicated that there was decrease in thunderstorm occurrences from first decade (1987 - 1996), second (1997 - 2006) to third decade (2007 - 2016). The results also showed that there was an increase of rainfall intensity in the third decade and decrease in second decade. The results further indicated that there was a climatic change in thunderstorm and rainfall activities in Potiskum and its environs during the study period, and this serves as good indicator of climate change in the study area. Therefore, it is recommended that Nigeria should develop capacity for research and data collection, to monitor climate change impacts, formulate and implement policies to protect natural resources, including forests, and conserve energy based on clean and low carbon technologies.

Modeling the influence of the intensive crystallization level height on the cumulonimbus cloud parameters

The importance of information on the ice particles amount and formation height in understanding the processes taking place in a cumulonimbus cloud is shown. In radar meteorology the intense crystallization level NIC is one of the criteria for the cloud transition to the thunderstorm activity stage. Modeling of a cumulonimbus cloud parameters with the intensive crystallization level height change has been carried out. With an increase in NIC there is a decrease in the hydrometeors number entering the crystallized area, an increase in the area volume with the highest water content in the cloud center, its rise, and a change in the orientation of the large drops «nursery» with a water content of more than 8 g/m3 from horizontal to vertical shape. The dependence of the hydrometeor size in the central part of the cloud jet and the lifetime on the NIC level has been detected.

Atmospheric electrical effects during a strong explosive eruption of Bezymyanniy volcano (Kamchatka Peninsula, Russia) on December 20, 2017

A set of parameters of various geophysical methods is considered, which made it possible to quite clearly represent the mechanism of the explosive eruption of Bezymyanny volcano on January 20, 2017. The explosion began according to the «soft» scenario, which was reflected both in the seismic method and in the thunderstorm activity of the eruptive cloud (EC). The transition to Plinian activity was accompanied by the generation of an infrasonic signal and an increase in lightning discharges in the EC. The two-tiered EC was well traced in the potential gradient response in atmospheric electric field. The combination of various geophysical methods provides a detailed understanding of the mechanism of explosive eruptions and contributes to a better understanding of the physics of the explosive process on volcanoes.

The Perfect Storm: Thunderstorm-Related Asthma

Thunderstorm asthma refers to the increase in acute asthma symptoms during or immediately after severe storm activity, especially during certain seasons. Epidemic thunderstorm asthma occurs when large numbers of patients are affected by thunderstorm activity. These thunderstorm asthma cases can be anywhere from mild to severe symptoms and requiring serious medical attention. Epidemic thunderstorm asthma events emphasize the importance of preventative and ongoing asthma and allergic rhinitis identification and management along with community education and awareness. This review highlights the significant impact on the emergency medical system and the need for risk assessments, asthma action plans, and overall advanced emergency preparedness.

Modelling deep convective activity using lightning clusters and machine learning

AbstractRetrieving 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.

Estimation of a Tropospheric Electric Field Associated with the African Zone of Thunderstorm Activity that Penetrates the Ionosphere

Estimation of a Tropospheric Electric Field Associated with the African Zone of Thunderstorm Activity that Penetrates the Ionosphere

Estimation of voltage waveform at top of transmission line tower struck by lightning of negative and positive polarity

The object of research is a circuit that simulates a lightning strike to a tower of 220 kV power transmission line, taking into consideration the reflection of a current wave from 10 nearest towers. Computation of the voltage arising at the top of the struck tower is necessary further to determine the lightning performance of transmission line by various methods. The lightning current has several maxima, in the case of a positive impulse polarity and, accordingly, several minima, in the case of a negative polarity, which are generally being called peaks. In addition, the lightning current impulse has a non-constant steepness in the entire area of current rise up to the first peak. The approximation of the real lightning current by simplified mathematical expressions cannot take into account all its real features. For a more detailed study of transient processes caused by thunderstorm activity, there is a need to use oscillograms of real lightning currents when modeling. The problem of determining the voltage at the top of the stricken transmission line tower was solved using circuit simulation. For an in-depth study of how the shape of the lightning current impulse affects the shape of the voltage at the top of the tower struck, digitized oscillograms of real lightning currents were used. The simulation was carried out for 7 negative lightning impulses with the first peak varying from –33.380 kA to –74.188 kA. In the case of positive lightning, 3 oscillograms were used with the first peak varying from +38.461 kA to +41.012 kA. The article shows that the shape of the front of the lightning current impulse and the amplitude of the first peak of the lightning current have a decisive effect on the maximum voltage value at the top of a power transmission line tower struck by lightning. The maximum voltage occurs precisely at the front of the current wave before the first peak of the lightning current. Therefore, the back flashover of the insulation from the tower to the phase conductor is most likely at a moment in time at the front of the current wave. By the time the maximum current is reached, the voltage at the top of the tower will be reduced by several tens of percent, compared to the maximum voltage at the tower, which occurs much earlier at the front of the current wave. The conducted research contributes to the development of methods for calculating the lightning performance of power lines and extends the scope of application of circuit simulation programs.

Time distribution of thunderstorms observed at Odesa AMSC at the beginning of the 21st century

The article presents the results of the research of thunderstorm activity at Odesa AMSC for the period of 2000-2019. Under conditions of intense warming, thunderstorm activity responds to the changes of temperature, humidity, radiation regime and atmospheric composition. Modern climate changes that are characterized by rising air temperatures have a decisive influence on the conditions under which dangerous weather phenomena are formed, thus monitoring of the thunderstorms formation in Ukraine is of great importance.
 The research includes the analysis of synoptic conditions of thunderstorm activity formation such as air-mass processes, frontal activity, and studies daily and daytime variability of the number of thunderstorm cases for the given period. The results of everyday meteorological observations of atmospheric phenomena conducted by Odesa AMSC within the period of 2000-2019 were used as input data to determine the characteristics of thunderstorm activity over city of Odesa. In order to identify the presence, time and duration of thunderstorm activity aviation weather diaries AV-6 were also reviewed. Certain synoptic materials were used to analyze the types of phenomena. Such materials include interactive database ARMsyn, surface synoptic charts for the periods of observation before and during the thunderstorms.
 It was established that during the period under study air-mass thunderstorms were formed in 370 cases of thunderstorm activity observed at the given observation post. Frontal thunderstorms occur less often: 241 cases over 20 years. The largest number of such thunderstorms is cold front thunderstorms amounting to 129 cases. 75 of them were identified as occlusion front thunderstorms. The least frequent were warm front thunderstorms – only 37 cases constituting 15% of the total number of frontal formations.
 During the studied period a total number of 620 thunderstorm cases was recorded, 195 of which are dry thunderstorms. Considerable attention is paid to the daily and daytime variability of thunderstorm cases number recorded by Odesa AMSC. With relation to the daily variation, more thunderstorms are observed during daytime amounting to 393 cases, 130 of which are dry thunderstorms. Night thunderstorms amount to 227 cases, 65 of which are dry thunderstorms. With relation to daytime distribution, more thunderstorms were detected in the afternoon.

Spatial Characteristics of Precipitation in the Greater Sydney Metropolitan Area as Revealed by the Daily Precipitation Concentration Index

In this study; the spatial distribution of the Daily Precipitation Concentration Index (DPCI) has been analyzed inside the Greater Sydney Metropolitan Area (GSMA). Accordingly, the rainfall database from the Australian Bureau of Meteorology archive was utilized after comprehensive quality control. The compiled data contains a set of 41 rainfall stations indicating consistent daily precipitation series from 1950 to 2015. In the analysis of the DPCI across GSMA the techniques of Moran’s Spatial Autocorrelation has been applied. In addition, a cross-covariance method was applied to assess the spatial interdependency between vector-based datasets after performing an Ordinary Kriging interpolation. The results identify four well-recognized intense rainfall development zones: the south coast and topographic areas of the Illawarra district characterized by Tasman Sea coastal regions with DPCI values ranging from 0.61 to 0.63, the western highlands of the Blue Mountains, with values between 0.60 and 0.62, the inland regions, with lowest rainfall concentrations between 0.55 and 0.59, and lastly the districts located inside the GSMA with DPCI ranging 0.60 to 0.61. Such spatial distribution has revealed the rainstorm and severe thunderstorm activity in the area. This study applies the present models to identify the nature and mechanisms underlying the distribution of torrential rains over space within the metropolis of Sydney, and to monitor any changes in the spatial pattern under the warming climate.

Abrupt Southern Great Plains thunderstorm shifts linked to glacial climate variability

Thunderstorms in the Southern Great Plains of the United States are among the strongest on Earth and have been shown to be increasing in intensity and frequency during recent years. Assessing changes in storm characteristics under different climate scenarios, however, remains highly uncertain due to limitations in climate model physics. We analyse oxygen isotopes from Texas stalactites from 30–50 thousand years ago to assess past changes in thunderstorm size and duration using a modern radar-based calibration for the region. Storm regimes shift from weakly to strongly organized on millennial timescales and are coincident with well-known abrupt climate shifts during the last glacial period. Modern-day synoptic analysis suggests that thunderstorm organization in the Southern Great Plains is strongly coupled to changes in large-scale wind and moisture patterns. These changes in the large-scale circulation may be used to assess future predictions and palaeo-simulations of mid-latitude thunderstorm climatologies. Thunderstorm activity in the Southern Great Plains was closely coupled to abrupt climate shifts during the last glacial period, according to an analysis of oxygen isotopes in modern rainfall and ancient speleothems from Texas.

Alternative evaluation of voltage at top of transmission line tower stricken by lightning

The object of the research is a circuit that simulates a lightning strike to a tower of 220 kV power transmission line, taking into consideration the reflection of a current wave from 10 nearest towers. Computation of the voltage arising at the top of the stricken tower is necessary further to determine the lightning performance of transmission line by various methods. For Indian conditions, the average number of lightning strikes to this power line per 100 kilometers per year is about 77, which is a fairly high figure. As a rule, for the tasks of lightning protection, the lightning current is approximated by some analytical expression. In most cases, such expressions are various combinations of exponential functions. However, the waveform of real lightning currents on oscillograms differs significantly from the waveform attributed to them and approximated by relatively simple exponential expressions. For a more detailed study of transient processes caused by thunderstorm activity, there is a need to use oscillograms of real lightning currents when modeling. The problem of determining the voltage at the top of the stricken transmission line tower was solved using circuit simulation. To simulate the lightning current, digitized oscillograms of real lightning currents with peak values of –5.256 kA and –133.586 kA were applied. The article shows that the proposed approach gives a more accurate and visual representation of the transient process at the top of the stricken tower than the approximation of the lightning current by simple exponential expressions. Applying a simplified exponential description of the lightning current leads not only to a simplification of the nature of the transient process at the tower top, but also to an underestimation of the results to 8.8%. The selection of the equivalent circuit for the power line towers also affects the result. Representation of towers in the equivalent circuit with lumped inductances leads to slightly higher values compared to application of surge impedances in the circuit. In this case, the smaller the current amplitude, the greater the difference (8.6 % in the domain of low currents and 1.9 % in the domain of high currents). Since this leads to some reserve during the computations of lightning performance, it is recommended to use an equivalent circuit with lumped inductance for a transmission line tower. The conducted research contributes to the development of methods for calculating the lightning performance of power lines and extends the scope of application of circuit simulation programs.

Smart Localization of Thunderstorm Charge for Human 4IR Applications

The relationship between smart devices and human beings is one of the research hotspots of the Fourth Industrial Revolution (4IR). In this regard, we explored the practical relationship between the 3D electric field components measured by the smart 3D atmospheric electric field apparatus (AEFA) and the thunderstorm activity from the perspective of the observer. Especially, in the application of AEFA, a smart calibration method is proposed to solve the problem of inconvenient thunderstorm data acquisition. Firstly, in order to obtain the thunderstorm charge position from the observation angle of the apparatus, this paper establishes a 3D electric field measurement model. According to the mirror method theory, we further obtain the charge potential distribution at AEFA. Then, the electric field components are derived by using the potential distribution formula with permittivity. In addition, based on the vector relation of the model, the thunderstorm charge azimuth and elevation angles are obtained. Finally, after the establishment of a new coordinate system, the calibration of charge localization is carried out, based on the observation point. Meanwhile, a preliminary solution is given to the problem that the elevation of the apparatus position affects the localization performance. Results show that the method matches the data of radar map and microphone array, which reflects the advantages of the method. Besides, this method can be used not only in sound source localization but also in AI thunderstorm monitoring system to realize a big data net observation.

Statistical and dynamical based thunderstorm prediction over southeast India

Thunderstorms, associated with lightning and heavy rain, are a weather hazard causing human deaths, urban floods and damage to crops. Current work attempted to study the thunderstorms over Andhra Pradesh, coastal state in southeast India, using multiple satellite datasets, gridded rainfall, Doppler Radar Images and Advanced Research Weather Research and Forecasting (ARW) model simulations during the pre-monsoon seasons of 2017 and 2018. Thermodynamic stability indices computed using INSAT-3D/3DR satellite data were used to identify precursors and lead time of prediction. India Meteorological Department (IMD) daily gridded rainfall data were used to identify the thunderstorm occurrence days, and Doppler Radar Images and INSAT imagery were conjointly used to fix the location. Eight severe thunderstorm cases were analyzed to assess the precursors and the predictability. Further, ARW model predictions for two thunderstorm cases were performed and stability indices computed using model output were compared with satellite-based indices for evaluation. Statistical metrics had shown good agreement of ARW model-based stability indices with satellite-based stability indices. Model had simulated rainfall and cloud properties associated with thunderstorm activity. The results illustrated the predictability of the location and intensity of thunderstorms with 3–4 hrs lead time, which would find usefulness in the real-time prediction of thunderstorms.

Rare Wintertime Thunderstorms Recorded over the U.S. Gulf Coast

“Thundersnow”—thunderstorm activity accompanying a winter storm—was spotted near southern Texas earlier this year.

Study of Ionospheric Effects and Earthquake Precursors Using Radio Engineering Methods

Features of the remote sensing of seismic disturbances in the lower ionosphere are considered according to observation data of lightning electromagnetic signals passing over the earthquake epicentre, in Yakutsk. The technique has the ability to scan a large seismically active region or even several regions directly from one point, though in some azimuths there are limitations due to insufficiently high lightning activity. The location of the signal receiving point allows you to explore such seismic regions Kamchatka, Japan, China, the Philippines and Indonesia, South Yakutia, and Baikal, provided there is a good thunderstorm activity.