Thunderstorm Environments Research Articles

A thunderstorm climatology of Romania (1941―2022)

Thunderstorms and their associated hazards pose a significant threat to society and the economy. In Europe, between 1980 and 2022, thunderstorms caused an estimated EUR 190 billion in economic losses. In Romania, the rate of cloud-to- ground (CG) lightning fatality is one of the highest in Europe. This study aims to reevaluate the risk of lightning in Romania by updating the CG lightning climatol- ogy for the period 2010–2022 and analysing long-term changes (1941-2022) in the frequency of thunderstorm environments. Data were obtained from the Arrival Time Difference Lightning Network (ATDnet) and the ERA5 reanalysis. On average, ap- proximately 760,000 flashes occurred each year in Romania during the study period, with a maximum mean annual flash density of approximately 6.5 flashes km−2 yr−1 over the Southern Carpathians. Approximately 75% of all flashes were detected in June–August, with a peak in the afternoon hours. There is a general decrease in flash density in Romania, but this trend is statistically significant only in western Romania. The highest number of hours with thunderstorm environments (270–390 hours yr−1) was predominantly observed in the mountainous regions of central and western Ro- mania. There is a significant increase in the number of hours with thunderstorms per decade, especially in eastern and southern Romania (>4 hours per decade). The re- sults of this study allow for a better understanding of the risk posed by CG lightning in Romania, improved forecasting of thunderstorms, and serve as a basis for developing mitigation strategies to reduce the impact of CG lightning.

Lightning-Fast Convective Outlooks: Predicting Severe Convective Environments With Global AI-Based Weather Models.

Severe convective storms are among the most dangerous weather phenomena and accurate forecasts mitigate their impacts. The recently released suite of AI-based weather models produces medium-range forecasts within seconds, with a skill similar to state-of-the-art operational forecasts for variables on single levels. However, predicting severe thunderstorm environments requires accurate combinations of dynamic and thermodynamic variables and the vertical structure of the atmosphere. Advancing the assessment of AI-models toward process-based evaluations lays the foundation for hazard-driven applications. We assess the forecast skill of the top-performing AI-models GraphCast, Pangu-Weather and FourCastNet for convective parameters at lead-times up to 10days against reanalysis and ECMWF's operational numerical weather prediction model IFS. In a case study and seasonal analyses, we see the best performance by GraphCast and Pangu-Weather: these models match or even exceed the performance of IFS for instability and shear. This opens opportunities for fast and inexpensive predictions of severe weather environments.

Urban land patterns can moderate population exposures to climate extremes over the 21st century

Climate change and global urbanization have often been anticipated to increase future population exposure (frequency and intensity) to extreme weather over the coming decades. Here we examine how changes in urban land extent, population, and climate will respectively and collectively affect spatial patterns of future population exposures to climate extremes (including hot days, cold days, heavy rainfalls, and severe thunderstorm environments) across the continental U.S. at the end of the 21st century. Different from common impressions, we find that urban land patterns can sometimes reduce rather than increase population exposures to climate extremes, even heat extremes, and that spatial patterns instead of total quantities of urban land are more influential to population exposures. Our findings lead to preliminary suggestions for embedding long-term climate resilience in urban and regional land-use system designs, and strongly motivate searches for optimal spatial urban land patterns that can robustly moderate population exposures to climate extremes throughout the 21st century.

An Analytic Formula for Entraining CAPE in Midlatitude Storm Environments

Abstract This article introduces an analytic formula for entraining convective available potential energy (ECAPE) with an entrainment rate that is determined directly from an environmental sounding, rather than prescribed by the formula user. Entrainment is connected to the background environment using an eddy diffusivity approximation for lateral mixing, updraft geometry assumptions, and mass continuity. These approximations result in a direct correspondence between the storm-relative flow and the updraft radius and an inverse scaling between the updraft radius squared and entrainment rate. The aforementioned concepts, combined with the assumption of adiabatic conservation of moist static energy, yield an explicit analytic equation for ECAPE that depends entirely on state variables in an atmospheric profile and a few constant parameters with values that are established in past literature. Using a simplified Bernoulli-like equation, the ECAPE formula is modified to account for updraft enhancement via kinetic energy extracted from the cloud’s background environment. CAPE and ECAPE can be viewed as predictors of the maximum vertical velocity wmax in an updraft. Hence, these formulas are evaluated using wmax from past numerical modeling studies. Both of the new formulas improve predictions of wmax substantially over commonly used diagnostic parameters, including undiluted CAPE and ECAPE with a constant prescribed entrainment rate. The formula that incorporates environmental kinetic energy contribution to the updraft correctly predicts instances of exceedance of by wmax, and provides a conceptual explanation for why such exceedance is rare among past simulations. These formulas are potentially useful in nowcasting and forecasting thunderstorms and as thunderstorm proxies in climate change studies. Significance Statement Substantial mixing occurs between the upward-moving air currents in thunderstorms (updrafts) and the surrounding comparatively dry environmental air, through a process called entrainment. Entrainment controls thunderstorm intensity via its diluting effect on the buoyancy of air within updrafts. A challenge to representing entrainment in forecasting and predictions of the intensity of updrafts in future climates is to determine how much entrainment will occur in a given thunderstorm environment without a computationally expensive high-resolution simulation. To address this gap, this article derives a new formula that computes entrainment from the properties of a single environmental profile. This formula is shown to predict updraft vertical velocity more accurately than past diagnostics, and can be used in forecasting and climate prediction to improve predictions of thunderstorm behavior and impacts.

Making a Superbolt: Reconciling Observations of the Optically Brightest Lightning on Earth From Different Satellites

AbstractWe previously documented geographic distributions of the optically brightest lightning on Earth—known as “superbolts”—using two space‐based instruments: the photodiode detector (PDD) on the Fast On‐orbit Recording of Transient Events (FORTE) satellite and the Geostationary Lightning Mapper (GLM) on NOAA's Geostationary Operational Environmental Satellites. In this study, we further examine the superbolts identified by the PDD and GLM to reconcile the differences between their geographic distributions. We find that both the physical extent of the parent flash and the development speed of its leaders are important for making a superbolt. The oceanic PDD superbolts tend to occur early in flashes that rapidly expand laterally into long horizontal “megaflashes.” The top GLM superbolts occur over land at later times in particularly large megaflashes. These land‐based flashes grow more slowly until they extend over multiple hundreds of kilometers. The FORTE PDD missed these delayed superbolts due to limitations in its triggering. Coincident Tropical Rainfall Measuring Mission measurements show that the warm season megaflash superbolts detected by Lightning Imaging Sensor/GLM and wintertime oceanic superbolts observed by the PDD occur in otherwise similar thunderstorm environments. Both are marked by: low storm heights (<10 km), widespread precipitation near the surface, small infrared brightness temperature gradients, and low flash rates. We suggest that the vertically compact, stratiform nature of these clouds provides favorable conditions for superbolt production.

Thunderstorm environments in Europe

Abstract. Meteorological environments favorable for thunderstorms are studied across Europe, including rare thunderstorm conditions from seasons with climatologically few thunderstorms. Using cluster analysis on ERA5 reanalysis data and EUCLID (European Cooperation for Lightning Detection) lightning data, two major thunderstorm environments are found: wind-field thunderstorms, characterized by increased wind speeds, high shear, strong large-scale vertical velocities, and low CAPE values compared to other thunderstorms in the same region, and mass-field thunderstorms, characterized by large CAPE values, high dew point temperatures, and elevated isotherm heights. Wind-field thunderstorms occur mainly in winter and more over the seas, while mass-field thunderstorms occur more frequently in summer and over the European mainland. Several sub-environments of these two major thunderstorm environments exist. Principal component analysis is used to identify four topographically distinct regions in Europe that share similar thunderstorm characteristics: the Mediterranean, Alpine–central, continental, and coastal regions, respectively. Based on these results it is possible to differentiate lightning conditions in different seasons from coarse reanalysis data without a static threshold or a seasonal criterion.

The Relationship between High-Presentation Asthma Days in Melbourne, Australia, and Modeled Thunderstorm Environments

Abstract Epidemic asthma events represent a significant risk to emergency services as well as the wider community. In southeastern Australia, these events occur in conjunction with relatively high amounts of grass pollen during the late spring and early summer, which may become concentrated in populated areas through atmospheric convergence caused by a number of physical mechanisms including thunderstorm outflow. Thunderstorm forecasts are therefore important for identifying epidemic asthma risk factors. However, the representation of thunderstorm environments using regional numerical weather prediction models, which are a key aspect of the construction of these forecasts, have not yet been systematically evaluated in the context of epidemic asthma events. Here, we evaluate diagnostics of thunderstorm environments from historical simulations of weather conditions in the vicinity of Melbourne, Australia, in relation to the identification of epidemic asthma cases based on hospital data from a set of controls. Skillful identification of epidemic asthma cases is achieved using a thunderstorm diagnostic that describes near-surface water vapor mixing ratio. This diagnostic is then used to gain insights on the variability of meteorological environments related to epidemic asthma in this region, including diurnal variations, long-term trends, and the relationship with large-scale climate drivers. Results suggest that there has been a long-term increase in days with high water vapor mixing ratio during the grass pollen season, with large-scale climate drivers having a limited influence on these conditions. Significance Statement We investigate the atmospheric conditions associated with epidemic thunderstorm asthma events in Melbourne, Australia, using historical model simulations of the weather. Conditions appear to be associated with high atmospheric moisture content, which relates to environments favorable for severe thunderstorms, but also potentially pollen rupturing as suggested by previous studies. These conditions are shown to be just as important as the concentration of grass pollen for a set of epidemic thunderstorm asthma events in this region. This means that weather model simulations of thunderstorm conditions can be incorporated into the forecasting process for epidemic asthma in Melbourne, Australia. We also investigate long-term variability in atmospheric conditions associated with severe thunderstorms, including relationships with the large-scale climate and long-term trends.

SPC Mesoscale Analysis Compared to Field-Project Soundings: Implications for Supercell Environment Studies

Abstract A total of 257 supercell proximity soundings obtained for field programs over the central United States are compared with profiles extracted from the SPC mesoscale analysis system (the SFCOA) to understand how errors in the SFCOA and in its baseline model analysis system—the RUC/RAP—might impact climatological assessments of supercell environments. A primary result is that the SFCOA underestimates the low-level storm-relative winds and wind shear, a clear consequence of the lack of vertical resolution near the ground. The near-ground (≤500 m) wind shear is underestimated similarly in near-field, far-field, tornadic, and nontornadic supercell environments. The near-ground storm-relative winds, however, are underestimated the most in the near-field and in tornadic supercell environments. Underprediction of storm-relative winds is, therefore, a likely contributor to the lack of differences in storm-relative winds between nontornadic and tornadic supercell environments in past studies that use RUC/RAP-based analyses. Furthermore, these storm-relative wind errors could lead to an under emphasis of deep-layer SRH variables relative to shallower SRH in discriminating nontornadic from tornadic supercells. The mean critical angles are 5°–15° larger and farther from 90° in the observed soundings than in the SFCOA, particularly in the near field, likely indicating that the ratio of streamwise to crosswise horizontal vorticity is often smaller than that suggested by the SFCOA profiles. Errors in thermodynamic variables are less prevalent, but show low-level CAPE to be too low closer to the storms, a dry bias above the boundary layer, and the absence of shallow near-ground stable layers that are much more prevalent in tornadic supercell environments. Significance Statement A total of 257 radiosonde observations taken close to supercell thunderstorms during field programs over the last 25 years are compared with a model-based analysis system (the SFCOA), which is often used for studying supercell thunderstorm environments. We present error characteristics of the SFCOA as they relate to tornado production and distance to the storm to clarify interpretations of environments favorable for tornado production made from past studies that use the SFCOA. A primary result is that the SFCOA underpredicts the speed and shear of the air flowing toward the storm in many cases, which may lead to different interpretations of variables that are most important for discriminating tornadic from nontornadic supercell thunderstorms. These results help to refine our understanding of the conditions that support tornado formation, which provides guidance on environmental cues that can improve the prediction of supercell tornadoes.

Severe Thunderstorm Environments in a Warming Climate: Differing Trends for Europe and the United States

Severe Thunderstorm Environments in a Warming Climate: Differing Trends for Europe and the United States

An eight-year climatology of the warm-season severe thunderstorm environments over North China

Using proximity soundings taken during the warm seasons (May–September) of 2011–2018 over North China, this work investigated the environments of severe thunderstorms that caused the following four types of convective hazards: only hail (H), only thunderstorm high winds (W), only short-duration heavy rainfall (R), and two or three types of the above three hazards (hybrid). The environments for non-severe thunderstorms and no-rain days were also studied for comparison. Soundings in each weather category were further classified into mountain and plain groups. A set of parameters was tested for skill in discriminating between various categories. Results indicate that the environments over the plains, compared with those over the mountains, are generally characterized by stronger instability, more moisture, and higher vertical wind shear. Over both mountains and plains, the precipitable water (PW) shows the greatest skill overall in discriminating between various categories; the instability parameters show considerable skill in discriminating between the severe thunderstorm, non-severe thunderstorm, and no-rain categories but rather limited skill in discriminating between the four severe thunderstorm categories; the wind shear parameters show very limited skill in discriminating between various categories; the lifting condensation level (LCL) distinguishes well the environments of no-rain and R from those of other categories; and the mid-tropospheric pseudo-equivalent potential temperature is the only parameter investigated here that shows utility in discriminating between H and W environments. Probability distributions in two-parameter spaces reveal that great variations exist regarding the environments under which different weather types are most likely to occur.

The differing role of weather systems in southern Australian rainfall between 1979\u20131996 and 1997\u20132015

Most of the rainfall in southern Australia is associated with cyclones, cold fronts, and thunderstorms, and cases when these weather systems co-occur are particularly likely to cause extreme rainfall. Rainfall declines in some parts of southern Australia during the cool half of the year in recent decades have previously been attributed to decreases in the rainfall from fronts and/or cyclones, while thunderstorm-related rainfall has been observed to increase, particularly in the warm half of the year. However, the co-occurrence of these systems, particularly the co-occurrence of cyclones or fronts with thunderstorms, can be very important for rainfall in some areas, particularly heavy rainfall, and changes in the frequency of these combined weather systems have not been previously assessed. In this paper we show that the majority of the observed cool season rainfall decline between 1979–1996 and 1997–2015 in southeast Australia is associated with a decrease in the frequency of fronts and cyclones that produce rainfall, while there has simultaneously been an increase in the frequency of cold fronts and thunderstorms that do not produce rainfall in some regions. Thunderstorm rainfall has increased in much of southern Australia, particularly during the warm half of the year, including an increase in rainfall where a thunderstorm environment occurs at the same time as a cyclone or front.

Severe Convective Storms across Europe and the United States. Part II: ERA5 Environments Associated with Lightning, Large Hail, Severe Wind, and Tornadoes

AbstractIn this study we investigate convective environments and their corresponding climatological features over Europe and the United States. For this purpose, National Lightning Detection Network (NLDN) and Arrival Time Difference long-range lightning detection network (ATDnet) data, ERA5 hybrid-sigma levels, and severe weather reports from the European Severe Weather Database (ESWD) and Storm Prediction Center (SPC) Storm Data were combined on a common grid of 0.25° and 1-h steps over the period 1979–2018. The severity of convective hazards increases with increasing instability and wind shear (WMAXSHEAR), but climatological aspects of these features differ over both domains. Environments over the United States are characterized by higher moisture, CAPE, CIN, wind shear, and midtropospheric lapse rates. Conversely, 0–3-km CAPE and low-level lapse rates are higher over Europe. From the climatological perspective severe thunderstorm environments (hours) are around 3–4 times more frequent over the United States with peaks across the Great Plains, Midwest, and Southeast. Over Europe severe environments are the most common over the south with local maxima in northern Italy. Despite having lower CAPE (tail distribution of 3000–4000 J kg−1 compared to 6000–8000 J kg−1 over the United States), thunderstorms over Europe have a higher probability for convective initiation given a favorable environment. Conversely, the lowest probability for initiation is observed over the Great Plains, but, once a thunderstorm develops, the probability that it will become severe is much higher compared to Europe. Prime conditions for severe thunderstorms over the United States are between April and June, typically from 1200 to 2200 central standard time (CST), while across Europe favorable environments are observed from June to August, usually between 1400 and 2100 UTC.

Differing Trends in United States and European Severe Thunderstorm Environments in a Warming Climate

AbstractLong-term trends in the historical frequency of environments supportive of atmospheric convection are unclear, and only partially follow the expectations of a warming climate. This uncertainty is driven by the lack of unequivocal changes in the ingredients for severe thunderstorms (i.e., conditional instability, sufficient low-level moisture, initiation mechanism, and vertical wind shear). ERA5 hybrid-sigma data allow for superior characterization of thermodynamic parameters including convective inhibition, which is very sensitive to the number of levels in the lower troposphere. Using hourly data we demonstrate that long-term decreases in instability and stronger convective inhibition cause a decline in the frequency of thunderstorm environments over the southern United States, particularly during summer. Conversely, increasingly favorable conditions for tornadoes are observed during winter across the Southeast. Over Europe, a pronounced multidecadal increase in low-level moisture has provided positive trends in thunderstorm environments over the south, central, and north, with decreases over the east due to strengthening convective inhibition. Modest increases in vertical wind shear and storm-relative helicity have been observed over northwestern Europe and the Great Plains. Both continents exhibit negative trends in the fraction of environments with likely convective initiation. This suggests that despite increasing instability, thunderstorms in a warming climate may be less likely to develop due to stronger convective inhibition and lower relative humidity. Decreases in convective initiation and resulting precipitation may have long-term implications for agriculture, water availability, and the frequency of severe weather such as large hail and tornadoes. Our results also indicate that trends observed over the United States cannot be assumed to be representative of other continents.

Projected changes to severe thunderstorm environments as a result of twenty-first century warming from RegCM CORDEX-CORE simulations

Hazardous weather related to the occurrence of severe thunderstorms including tornadoes, high-winds, and hail cause significant damage globally to life and property every year. Yet the impact on these storms from a warming climate remains a difficult task due to their transient nature. In this study we investigate the change in large-scale environments in which severe thunderstorms form during twenty-first century warming (RCP2.6 and RCP8.5) in a group of RegCM CORDEX-CORE simulations. Severe potential is measured in terms of Convective Available Potential Energy (CAPE) and vertical wind-shear during the severe seasons in three regions which are known to currently be prone to severe hazards: North America, subtropical South America, and eastern India and Bangladesh. In every region, environments supportive for severe thunderstorms are projected to increase during the warm season months in both the RCP2.6 and RCP8.5 scenarios during the twenty-first century. The number of days supportive for severe thunderstorms increases by several days per season over the vast majority of each region by the end of the century. Analyzing the CAPE and shear trends during the twenty-first century, we find seasonally and regionally specific changes driving the increased severe potential. Twenty-first century surface warming is clearly driving a robust increase in CAPE in all regions, however poleward displacement of vertical shear in the future leads to the displacement of severe environments over North America and South America. The results found here relate that severe impacts in the future cannot be generalized globally, and that regionally specific changes in vertical shear may drive future movement of regions prone to severe weather.

Future Changes in Euro-Mediterranean Daytime Severe Thunderstorm Environments Based on an RCP8.5 Med-CORDEX Simulation

Convective scale processes and, therefore, thunderstorm-related hazards cannot be simulated using regional climate models with horizontal grid spacing in the order of 10 km. However, larger-scale environmental conditions of these local high-impact phenomena can be diagnosed to assess their frequency in current and future climates. In this study, we present a daytime climatology of severe thunderstorm environments and its evolution for a wide Euro-Mediterranean domain through the 21st century, using regional climate model simulations forced by Representative Concentration Pathway (RCP) 8.5 scenario. Currently, severe convective weather is more frequently favored around Central Europe and the Mediterranean Sea. Our results suggest that with a steady progress until the end of the century, Mediterranean coasts are projected to experience a significantly higher frequency of severe thunderstorm environments, while a slight decrease over parts of continental Europe is evaluated. The increase across the Mediterranean is mostly owed to the warming sea surface, which strengthens thermodynamic conditions in the wintertime, while local factors arguably keep the shear frequency relatively higher than the entire region. On the other hand, future northward extension of the subtropical belt over Europe in the warm season reduces the number of days with severe thunderstorm environments.

Significant decrease of lightning activities during COVID-19 lockdown period over Kolkata megacity in India

The outbreak of COVID-19 has now created the largest pandemic and the World health organization (WHO) has declared social distancing as the key precaution to confront such type of infections. Most of the countries have taken protective measures by the nationwide lockdown. The purpose of this study is to understand the effect of lockdown on air pollutants and to analyze pre-monsoon (April and May) cloud-to-ground and inter-cloud lightning activity in relation to air pollutants i.e. suspended Particulate matter (PM10), Nitrogen dioxides (NO2) Sulfur dioxide (SO2), Ozone (O3) and Aerosol concentration (AC) in a polluted tropical urban megacities like Kolkata. After the strict lockdown the pollutants rate has reduced by more than 40% from the pre-lockdown period in the Kolkata megacity. So, decreases of PM10, NO2, SO2, O3 and AC have a greater effect on cloud lightning flashes in the pre-monsoon period. In the previous year (2019), the pre-monsoon average result shows a strong positive relation between the lightning and air pollutants; PM10 (R2 = 0.63), NO2 (R2 = 0.63), SO2 (R2 = 0.76), O3 (R2 = 0.68) and AC (R2 = 0.83). The association was relatively low during the lock-down period (pre-monsoon 2020) and the R2 values were 0.62, 0.60, 0.71, 0.64 and 0.80 respectively. Another thing is that the pre-monsoon (2020) lightning strikes decreased by 49.16% compared to the average of previous years (2010 to 2019). The overall study shows that the reduction of surface pollution in the thunderstorm environment is strongly related to the reduction of lightning activity where PM10 and AC are the key pollutants in the Kolkata megacity.

Lightning modelling for the research of forest fire ignition in Portugal

The study aims to assess the applicability of the current Meso-NH electrical scheme (CELLS) in the investigation of forest fire ignition. Therefore, the challenge is to diagnose cloud-to-ground (CG) lightning at 1 km spatial resolution and, subsequently, preferred regions where Forest Fire Events (FFE) could be naturally ignited. The afternoon of 17th June 2017 has been considered for the study, since the dry thunderstorm environment configured a perfect scenario for natural ignition and evolution of some fires. The Pedrógão Grande wildfire ignited in this period and was the deadliest single fire event in the Portuguese history, with at least 60 people killed. The available observational data are used to validate the numerical results and to provide a brief characterization of the meteorological environment when jointly analysed with the simulation. In addition, cloud microphysics and cloud electrical structure are explored from the model results. The spatial distribution of the simulated CG lightning showed a good agreement with the lightning strokes obtained from the national lightning detection network. Overall, this paper introduces a possible application of the Meso-NH electrical scheme, namely the study of forest fire ignition by lightning strokes.

Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques

Lightning discharges in the atmosphere owe their existence to the combination of complex dynamic and microphysical processes. Knowledge discovery and data mining methods can be used for seeking characteristics of data and their teleconnections in complex data clusters. We have used machine learning techniques to successfully hindcast nearby and distant lightning hazards by looking at single-site observations of meteorological parameters. We developed a four-parameter model based on four commonly available surface weather variables (air pressure at station level (QFE), air temperature, relative humidity, and wind speed). The produced warnings are validated using the data from lightning location systems. Evaluation results show that the model has statistically considerable predictive skill for lead times up to 30 min. Furthermore, the importance of the input parameters fits with the broad physical understanding of surface processes driving thunderstorms (e.g., the surface temperature and the relative humidity will be important factors for the instability and moisture availability of the thunderstorm environment). The model also improves upon three competitive baselines for generating lightning warnings: (i) a simple but objective baseline forecast, based on the persistence method, (ii) the widely-used method based on a threshold of the vertical electrostatic field magnitude at ground level, and, finally (iii) a scheme based on CAPE threshold. Apart from discussing the prediction skill of the model, data mining techniques are also used to compare the patterns of data distribution, both spatially and temporally among the stations. The results encourage further analysis on how mining techniques could contribute to further our understanding of lightning dependencies on atmospheric parameters.

Characteristics of acoustic response from simulated impulsive lightning current discharge

Acoustic observation of laboratory simulated lightning discharge can greatly avoid the observation difficulties under natural thunderstorm environment. An acoustic observation experiment based on the impulsive current generation system and a microphone array was carried out and illustrated in this study. A quantitative study on characteristics of response sound pressure initiated from simulated lightning current was performed. The first arrived acoustic N-waves measured at different distances initiated from different discharge amplitudes were compared and analysed. The acoustic amplitude, rise time and duration time defined for N-waves and peak frequencies were found to have an obvious correlation with the discharging amplitudes of simulated lightning currents and the observing distances. The linear change of acoustic amplitude is more obvious than that of the other parameters with the changed discharging amplitude or observing distance. A certain degree of shape change of the simulated lightning current except for the amplitude may not significantly affect the response acoustic characteristics when comparing the first acoustic N-waves from 8/20 μs lightning current and another kind of impulsive current which has a wider shape and two subsequent peaks. The subsequent current peaks in short time delays were proved to successively generate acoustic N-waves independently without overlapping, which meanwhile, indicated a consistent linear relationship of amplitude and time delay between electrical and acoustic pulses.

A Climatology of Thunderstorms across Europe from a Synthesis of Multiple Data Sources

AbstractThe climatology of (severe) thunderstorm days is investigated on a pan-European scale for the period of 1979–2017. For this purpose, sounding measurements, surface observations, lightning data from ZEUS (a European-wide lightning detection system) and European Cooperation for Lightning Detection (EUCLID), ERA-Interim, and severe weather reports are compared and their respective strengths and weaknesses are discussed. The research focuses on the annual cycles in thunderstorm activity and their spatial variability. According to all datasets thunderstorms are the most frequent in the central Mediterranean, the Alps, the Balkan Peninsula, and the Carpathians. Proxies for severe thunderstorm environments show similar patterns, but severe weather reports instead have their highest frequency over central Europe. Annual peak thunderstorm activity is in July and August over northern, eastern, and central Europe, contrasting with peaks in May and June over western and southeastern Europe. The Mediterranean, driven by the warm waters, has predominant activity in the fall (western part) and winter (eastern part) while the nearby Iberian Peninsula and eastern Turkey have peaks in April and May. Trend analysis of the mean annual number of days with thunderstorms since 1979 indicates an increase over the Alps and central, southeastern, and eastern Europe with a decrease over the southwest. Multiannual changes refer also to changes in the pattern of the annual cycle. Comparison of different data sources revealed that although lightning data provide the most objective sampling of thunderstorm activity, short operating periods and areas devoid of sensors limit their utility. In contrast, reanalysis complements these disadvantages to provide a longer climatology, but is prone to errors related to modeling thunderstorm occurrence and the numerical simulation itself.