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Search Results (317)

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19 pages, 7762 KiB  
Article
An Exploratory Study on the Use of Root-Mean-Square Vertical Acceleration Data from Aircraft for the Detection of Low-Level Turbulence at an Operating Airport
by Christy Yan Yu Leung, Ping Cheung, Man Lok Chong and Pak Wai Chan
Appl. Sci. 2025, 15(16), 8974; https://doi.org/10.3390/app15168974 - 14 Aug 2025
Abstract
Low-level turbulence is a meteorological hazard that disrupts the operation of airports and is particularly pronounced at Hong Kong International Airport (HKIA), which is impacted by various sources of low-level turbulence (e.g., terrain disrupting wind flow, sea breeze, and thunderstorms). The possibility of [...] Read more.
Low-level turbulence is a meteorological hazard that disrupts the operation of airports and is particularly pronounced at Hong Kong International Airport (HKIA), which is impacted by various sources of low-level turbulence (e.g., terrain disrupting wind flow, sea breeze, and thunderstorms). The possibility of using root-mean-square vertical acceleration (RMSVA) data from Automatic Dependent Surveillance–Broadcast (ADS-B) for low-level turbulence monitoring is studied in this paper. Comparisons are performed between RMSVA and Light Detection And Ranging (LIDAR)-based Eddy Dissipation Rate (EDR) maps and the aircraft-based EDR. Moreover, the LIDAR-based EDR map, aircraft EDR, and pilot report for turbulence reporting are compared for two typical cases at HKIA. It was found that the various estimates/reports of turbulence are generally consistent with one another, at least based on the limited sample considered in this paper. However, at very low altitudes close to the touchdown of arrival flights, RMSVA may not be available due to a lack of ADS-B data. With effective quality control and further in-depth study, it will be possible to use RMSVA to monitor low-level turbulence and to alert pilots if turbulence is reported by the pilot of the preceding flight based on RMSVA. The technical details of the various comparisons and the assumptions made are described herein. Full article
(This article belongs to the Section Earth Sciences)
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20 pages, 5334 KiB  
Article
A Case Study on the Vertical Distribution and Correlation Between Low-Frequency Lightning Sources and Hydrometeors During a Thunderstorm
by Sulin Jiang, Fanchao Lyu, Steven A. Cummer, Tianxue Zheng, Mingjun Wang, Yan Liu and Weitao Lyu
Remote Sens. 2025, 17(15), 2676; https://doi.org/10.3390/rs17152676 - 2 Aug 2025
Viewed by 199
Abstract
Understanding the interplay between lightning activity and hydrometeor distribution is crucial for advancing knowledge of thunderstorm electrification processes. Using three-dimensional lightning mapping and dual-polarization radar observations, this study investigates the spatiotemporal correlations between low-frequency (LF) lightning sources and hydrometeors during a severe thunderstorm [...] Read more.
Understanding the interplay between lightning activity and hydrometeor distribution is crucial for advancing knowledge of thunderstorm electrification processes. Using three-dimensional lightning mapping and dual-polarization radar observations, this study investigates the spatiotemporal correlations between low-frequency (LF) lightning sources and hydrometeors during a severe thunderstorm on 11 June 2014, in North Carolina, USA. The results reveal that lightning sources are predominantly observed above 6 km (near the −10 °C isotherm) and stabilize into a dual-peak vertical distribution as the storm progresses into its mature stage, with peaks located at 6–7 km (−10 °C to −15 °C) and 10–11 km (approximately −40 °C). Low-density graupel (LDG) and aggregates (AGs) dominate at lightning locations. Stronger updrafts lead to higher proportions of LDG and high-density graupel (HDG), and lower proportions of AG. LDG exhibits the strongest positive correlation with LF lightning sources, with a peak correlation coefficient of 0.65 at 9 km. During the vigorous development stage, HDG and hail (Ha) also show positive correlations with LF lightning sources, with peak correlation coefficients of 0.52 at 7 km and 0.42 at 8 km, respectively. As the storm reaches its mature phase, the correlation between LDG and lightning sources also displays a dual-peak vertical distribution, with peaks at 7–8 km and 13–14 km. Both the peak correlation coefficient and its corresponding height increase with the strengthening of updrafts, underscoring the critical role of updrafts in microphysical characteristics and driving electrification processes. Full article
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19 pages, 5148 KiB  
Article
Analysis of the Charge Structure Accompanied by Hail During the Development Stage of Thunderstorm on the Qinghai–Tibet Plateau
by Yajun Li, Xiangpeng Fan and Yuxiang Zhao
Atmosphere 2025, 16(8), 906; https://doi.org/10.3390/atmos16080906 - 26 Jul 2025
Viewed by 231
Abstract
The charge structure and lightning activities during the development stage of a thunderstorm with a hail-falling process in Datong County of Qinghai Province on 16 August 2014 were studied by using a multi-station observation network composed of a very-high-frequency, three-dimensional, lightning-radiation-source location system [...] Read more.
The charge structure and lightning activities during the development stage of a thunderstorm with a hail-falling process in Datong County of Qinghai Province on 16 August 2014 were studied by using a multi-station observation network composed of a very-high-frequency, three-dimensional, lightning-radiation-source location system and broadband electric field. The research results show that two discharge regions appeared during the development stage of the thunderstorm. The charge structure was all a negative dipolar polarity in two discharge regions; however, the heights of the charge regions were different. The positive-charge region at a height of 2–3.5 km corresponds to −1–−10 °C and the negative-charge region at a height of 3.5–5 km corresponds to −11–−21 °C in one discharge region; the positive-charge region at a height of 4–5 km corresponds to −15–−21 °C and the negative-charge region at a height of 5–6 km corresponds to −21–−29 °C in another region. The charge regions with the same polarity at different heights in the two discharge regions gradually connected with the occurrence of the hail-falling process during the development stage of the thunderstorm, and the overall height of the charge regions decreased. All the intracloud lightning flashes that occurred in the thunderstorm were of inverted polarity discharge, and the horizontal transmission distance of the discharge channel was short, all within 10 km. The negative intracloud lightning flash, negative cloud-to-ground lightning flash, and positive cloud-to-ground lightning flash generated during the thunderstorm process accounted for 83%, 16%, and 1% of the total number of lightning flashes, respectively. Negative cloud-to-ground lightning flashes mainly occurred more frequently in the early phase of the thunderstorm development stage. As the thunderstorm developed, the frequency of intracloud lightning flashes became greater than that of negative cloud-to-ground lightning flashes, and finally far exceeded it. The frequency of lightning flashes decreases sharply and the intensity of thunderstorms decreases during the hail-falling period. Full article
(This article belongs to the Section Meteorology)
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21 pages, 11032 KiB  
Article
Convective–Stratiform Identification Neural Network (CONSTRAINN) for the WIVERN Mission
by Federico Mustich, Alessandro Battaglia, Francesco Manconi, Pavlos Kollias and Antonio Parodi
Remote Sens. 2025, 17(15), 2590; https://doi.org/10.3390/rs17152590 - 25 Jul 2025
Viewed by 484
Abstract
The WIVERN mission promises to deliver the first global observations of the three-dimensional wind field and the associated cloud and precipitation structure in a wide range of atmospheric phenomena, including isolated thunderstorms, tropical cyclones, mid-latitude frontal systems, and polar lows. A critical element [...] Read more.
The WIVERN mission promises to deliver the first global observations of the three-dimensional wind field and the associated cloud and precipitation structure in a wide range of atmospheric phenomena, including isolated thunderstorms, tropical cyclones, mid-latitude frontal systems, and polar lows. A critical element in the development of the mission’s wind products is the differentiation between stratiform and convective regions. Convective regions are defined as those where vertical wind velocities exceed 1 m/s. This work introduces CONSTRAINN, a family of U-Net-based neural network models that utilise all of WIVERN observables—including vertical profiles of reflectivity and Doppler velocity, as well as brightness temperatures—to reconstruct convective wind activity within the Earth’s atmosphere. Results show that the retrieved convective/stratiform masks are well reconstructed, with an equitable threat score exceeding 0.6. Ablation experiments further reveal that Doppler velocity signals are the most informative for the reconstruction task. Full article
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17 pages, 752 KiB  
Article
A Soft-Fault Diagnosis Method for Coastal Lightning Location Networks Based on Observer Pattern
by Yiming Zhang and Ping Guo
Sensors 2025, 25(15), 4593; https://doi.org/10.3390/s25154593 - 24 Jul 2025
Viewed by 209
Abstract
Coastal areas are prone to thunderstorms. Lightning strikes can damage power facilities and communication systems, thereby leading to serious consequences. The lightning location network achieves lightning location through data fusion from multiple lightning locator nodes and can detect the location and intensity of [...] Read more.
Coastal areas are prone to thunderstorms. Lightning strikes can damage power facilities and communication systems, thereby leading to serious consequences. The lightning location network achieves lightning location through data fusion from multiple lightning locator nodes and can detect the location and intensity of lightning in real time. It is an important facility for thunderstorm warning and protection in coastal areas. However, when a sensor node in a lightning location network experiences a soft fault, it causes distortion in the lightning location. To achieve fault diagnosis of lightning locator nodes in a multi-node data fusion mode, this study proposes a new lightning location mode: the observer pattern. This paper first analyzes the main factors contributing to the error of the lightning location algorithm under this mode, proposes an observer pattern estimation algorithm (OPE) for lightning location, and defines the proportion of improvement in lightning positioning accuracy (PI) caused by the OPE algorithm. By analyzing the changes in PI in the process of lightning location, this study further proposes a diagnostic algorithm (OPSFD) for soft-fault nodes in a lightning location network. The simulation experiments in the paper demonstrate that the OPE algorithm can effectively improve the positioning accuracy of existing lightning location networks. Therefore, the OPE algorithm is also a low-cost and efficient method for improving the accuracy of existing lightning location networks, and it is suitable for the actual deployment and upgrading of current lightning locators. Meanwhile, the experimental results show that when a soft fault causes the observation error of the node to exceed the normal range, the OPSFD algorithm proposed in this study can effectively diagnose the faulty node. Full article
(This article belongs to the Special Issue Internet of Things (IoT) Sensing Systems for Engineering Applications)
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16 pages, 1939 KiB  
Article
Exploring the Explainability of a Machine Learning Tool to Improve Severe Thunderstorm Wind Reports
by Elizabeth Tirone, William A. Gallus and Alexander J. Hamilton
Atmosphere 2025, 16(7), 881; https://doi.org/10.3390/atmos16070881 - 18 Jul 2025
Viewed by 695
Abstract
Output from a machine learning tool that assigns a probability that a severe thunderstorm wind report was caused by severe intensity wind was evaluated to understand counterintuitive cases where reports that had a high (low) wind speed received a low (high) diagnosed probability. [...] Read more.
Output from a machine learning tool that assigns a probability that a severe thunderstorm wind report was caused by severe intensity wind was evaluated to understand counterintuitive cases where reports that had a high (low) wind speed received a low (high) diagnosed probability. Meteorological data for these cases was compared to that for valid cases where the machine learning probability seemed consistent with the observed severity of the winds. The comparison revealed that the cases with high winds but low probabilities occurred in less conducive environments for severe wind production (less instability, greater low-level relative humidity, weaker lapse rates) than in the cases where high winds occurred with high probabilities. Cases with a low speed but a high probability had environmental characteristics that were more conducive to producing severe wind. These results suggest that the machine learning model is assigning probabilities based on storm modes that more often have measured severe wind speeds (i.e., clusters of cells and bow echoes), and counterintuitive values may reflect events where storm interactions or other smaller-scale features play a bigger role. In addition, some evidence suggests improper reporting may be common for some of these counterintuitive cases. Full article
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9 pages, 16281 KiB  
Data Descriptor
Advancements in Regional Weather Modeling for South Asia Through the High Impact Weather Assessment Toolkit (HIWAT) Archive
by Timothy Mayer, Jonathan L. Case, Jayanthi Srikishen, Kiran Shakya, Deepak Kumar Shah, Francisco Delgado Olivares, Lance Gilliland, Patrick Gatlin, Birendra Bajracharya and Rajesh Bahadur Thapa
Data 2025, 10(7), 112; https://doi.org/10.3390/data10070112 - 9 Jul 2025
Viewed by 444
Abstract
Some of the most intense thunderstorms and extreme weather events on Earth occur in the Hindu Kush Himalaya (HKH) region of Southern Asia. The need to provide end users, stakeholders, and decision makers with accurate forecasts and alerts of extreme weather is critical. [...] Read more.
Some of the most intense thunderstorms and extreme weather events on Earth occur in the Hindu Kush Himalaya (HKH) region of Southern Asia. The need to provide end users, stakeholders, and decision makers with accurate forecasts and alerts of extreme weather is critical. To that end, a cutting edge weather modeling framework coined the High Impact Weather Assessment Toolkit (HIWAT) was created through the National Aeronautics and Space Administration (NASA) SERVIR Applied Sciences Team (AST) effort, which consists of a suite of varied numerical weather prediction (NWP) model runs to provide probabilities of straight-line damaging winds, hail, frequent lightning, and intense rainfall as part of a daily 54 h forecast tool. The HIWAT system was first deployed in 2018, and the recently released model archive hosted by the Global Hydrometeorology Resource Center (GHRC) Distributed Active Archive Center (DAAC) provides daily model outputs for the years of 2018–2022. With a nested modeling domain covering Nepal, Bangladesh, Bhutan, and Northeast India, the HIWAT archive spans the critical pre-monsoon and monsoon months of March–October when severe weather and flooding are most frequent. As part of NASA’s Transformation To Open Science (TOPS), this data archive is freely available to practitioners and researchers. Full article
(This article belongs to the Section Spatial Data Science and Digital Earth)
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20 pages, 6074 KiB  
Article
Characterization of Hybrid Lightning Flashes Observed by Fast Antenna Lightning Mapping Array in Summer Thunderstorms
by Dongdong Shi, Jie Shao, Rubin Jiang, Daohong Wang, Ting Wu and Li Wang
Atmosphere 2025, 16(7), 765; https://doi.org/10.3390/atmos16070765 - 22 Jun 2025
Viewed by 291
Abstract
Using the observation data from Fast Antenna Lightning Mapping Array, we have sub-divided 288 hybrid flashes that are obviously different from traditional intracloud (IC) and negative cloud-to-ground (NCG) flashes into three types: IC–NCG lightning (85), NCG–IC lightning (95), and the flashes (108) with [...] Read more.
Using the observation data from Fast Antenna Lightning Mapping Array, we have sub-divided 288 hybrid flashes that are obviously different from traditional intracloud (IC) and negative cloud-to-ground (NCG) flashes into three types: IC–NCG lightning (85), NCG–IC lightning (95), and the flashes (108) with negative leaders originating from the upper parts of bi-level structures of IC flashes. Hereinafter, we refer to these hybrid flashes as hybrid A, B, and C, respectively. The statistical comparisons indicate that characteristics from preliminary breakdown (PB) to return stroke (RS) are significantly different. On average, hybrid A and C flashes have higher initiation altitudes, larger PB–RS intervals, and longer propagation lengths than hybrid B flashes (7.9, 7.8 vs. 5.7 km; 430.3, 239.3 vs. 54.4 ms; 6.4, 7.8 vs. 2.3 km). Compared to 1562 IC and 844 CG flashes, hybrid flashes unsurprisingly have much larger horizontal flash sizes (189, 210, and 126.9 km2 vs. 86.1 and 80.2 km2). In addition, hybrid B flashes tend to produce more RSs and larger RS1st peak currents. The striking points of hybrid C flashes appear to be close to or out of the cloud edge. Based on these statistical results, we discuss the formation mechanisms of three types of hybrid flashes. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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15 pages, 6161 KiB  
Article
Machine Learning Indicates Stronger Future Thunderstorm Downbursts Affecting Southeast Australian Airports
by Milton Speer, Lance Leslie and Shuang Wang
Climate 2025, 13(6), 127; https://doi.org/10.3390/cli13060127 - 15 Jun 2025
Viewed by 776
Abstract
Thunderstorms downbursts can be hazardous during aircraft landing and take-off. A warming climate increases low- to mid-level troposphere water vapor, typically transported from high sea-surface temperature regions. Consequently, the future occurrence and intensity of destructive wind gusts from wet microburst thunderstorms are expected [...] Read more.
Thunderstorms downbursts can be hazardous during aircraft landing and take-off. A warming climate increases low- to mid-level troposphere water vapor, typically transported from high sea-surface temperature regions. Consequently, the future occurrence and intensity of destructive wind gusts from wet microburst thunderstorms are expected to increase. Wet microbursts are downdrafts from heavily precipitating thunderstorms and are several kilometers in diameter, often producing near-surface extreme wind gusts. Brisbane airport recorded a wet microburst wind gust of 157 km/h in November 2016. Numerous locations in eastern Australia experience warm season (October to March) wet microbursts. Here, eight machine learning techniques comprising forward and backward linear regression, radial basis forward and backward support vector regression, polynomial-based forward and backward support vector regression, and forward and backward random forest selection were employed. They identified primary attributes for increased atmospheric instability by warm moist air influx from regions of high sea-surface temperatures. The climate drivers detected here are indicative of increased future eastern Australian warm season thunderstorm downbursts, occurring as wet microbursts. They suggest a greater frequency and intensity of impacts on aircraft safety and operations affecting major east coast airports, such as Sydney and Brisbane, and smaller aircraft at inland regional airports in southeastern Australia. Full article
(This article belongs to the Special Issue Extreme Weather Detection, Attribution and Adaptation Design)
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30 pages, 14172 KiB  
Article
Synoptic and Dynamic Analyses of an Intense Mediterranean Cyclone: A Case Study
by Ahmad E. Samman
Climate 2025, 13(6), 126; https://doi.org/10.3390/cli13060126 - 15 Jun 2025
Viewed by 628
Abstract
On 3 February 2006, a powerful Mediterranean cyclone instigated a widespread dust storm across Saudi Arabia. Meteorological observations from one station recorded strong westerly to southwesterly winds, with gusts reaching 40 m/s, accompanied by thunderstorms and dust storms. This study delves into the [...] Read more.
On 3 February 2006, a powerful Mediterranean cyclone instigated a widespread dust storm across Saudi Arabia. Meteorological observations from one station recorded strong westerly to southwesterly winds, with gusts reaching 40 m/s, accompanied by thunderstorms and dust storms. This study delves into the formation and development of this significant Mediterranean cyclone, which impacted the Mediterranean basin and the Arabian Peninsula from 26 January to 4 February 2006. Utilizing ECMWF ERA5 reanalysis data, this research analyzes the synoptic and dynamic conditions that contributed to the cyclone’s evolution and intensification. The cyclone originated over the North Atlantic as cold air from higher latitudes and was advected southward, driven by a strong upper-level trough. The initial phase of cyclogenesis was triggered by baroclinic instability, facilitated by an intense upper-level jet stream interacting with a pre-existing low-level baroclinic zone over coastal regions. Upper-level dynamics enhanced surface frontal structures, promoting the formation of the intense cyclone. As the system progressed, low-level diabatic processes became the primary drivers of its evolution, reducing the influence of upper-level baroclinic mechanisms. The weakening of the upper-level dynamics led to the gradual distortion of the low-level baroclinicity and frontal structures, transitioning the system to a more barotropic state during its mature phase. Vorticity analysis revealed that positive vorticity advection and warm air transport toward the developing cyclone played key roles in its intensification, leading to the development of strong low-level winds. Atmospheric kinetic energy analysis showed that the majority of the atmospheric kinetic energy was concentrated at 400 hPa and above, coinciding with intense jet stream activity. The generation of the atmospheric kinetic energy was primarily driven by cross-contour flow, acting as a major energy source, while atmospheric kinetic energy dissipation from grid to subgrid scales served as a major energy sink. The dissipation pattern closely mirrored the generation pattern but with the opposite sign. Additionally, the horizontal flux of the atmospheric kinetic energy was identified as a continuous energy source throughout the cyclone’s lifecycle. Full article
(This article belongs to the Section Weather, Events and Impacts)
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7 pages, 168 KiB  
Brief Report
Possible Anxiolytic Effects of Cannabidiol (CBD) Administration on Feline Responses to a Fear Response Test
by Nobuo Masataka
Animals 2025, 15(11), 1642; https://doi.org/10.3390/ani15111642 - 3 Jun 2025
Cited by 1 | Viewed by 919
Abstract
In humans, cannabidiol (CBD), the primary non-addictive component of cannabis, is known to possess considerable therapeutic potential. The purpose of this study was to investigate the effects of CBD administration on reducing sound-induced fear in healthy domestic cats in a laboratory model of [...] Read more.
In humans, cannabidiol (CBD), the primary non-addictive component of cannabis, is known to possess considerable therapeutic potential. The purpose of this study was to investigate the effects of CBD administration on reducing sound-induced fear in healthy domestic cats in a laboratory model of thunderstorm simulation. A total of 40 cats, each naïve to the current testing, were randomly assigned into either of two administration groups (CBD and placebo). Each group was then exposed to the thunderstorm test twice; once at the beginning of the administration (the administration of CBD at 4.0 mg/kg/day over a 2-week-period or the administration of the same amount of sunflower oil as a placebo) and once after the end of the administration. When undesirable urination was observed, occurrences of this behaviour were found to decrease significantly when CBD was administered. However, no such changes were recorded when the placebo was administered. These results indicate that CBD could be an effective option for the treatment of noise-induced fear. Full article
(This article belongs to the Section Companion Animals)
17 pages, 4685 KiB  
Article
The Development and Application of a Three-Dimensional Corona Discharge Numerical Model Considering the Thunderstorm Electric Field Polarity Reversal Process
by Zhaoxia Wang, Bin Wu, Xiufeng Guo, Nian Zhao, He Zhang, Yubin Zhao and Yuhang Zheng
Atmosphere 2025, 16(5), 612; https://doi.org/10.3390/atmos16050612 - 17 May 2025
Viewed by 475
Abstract
The study of the ground tip corona discharge is an important part of the lightning strike mechanism and lightning warning research. Because the characteristics of the corona charge distribution are difficult to observe directly, simulation research is indispensable. However, most of the previous [...] Read more.
The study of the ground tip corona discharge is an important part of the lightning strike mechanism and lightning warning research. Because the characteristics of the corona charge distribution are difficult to observe directly, simulation research is indispensable. However, most of the previous models have been unipolar models, which cannot reflect the characteristics of the tip corona discharge under electric field reversal during real thunderstorms. Therefore, the development of three-dimensional positive and negative corona discharge models is of great significance. In this study, a three-dimensional corona discharge numerical model considering the polarity reversal process of the electric field was developed with or without a wind field and simulated the tip corona discharge characteristics under this reversal. The reliability of the model was verified by comparing the observed results. Compared with the unipolar corona discharge model, this model could effectively evaluate the impact of the first half-cycle corona discharge on the second half-cycle opposite-polarity corona discharge and invert the spatial separation distribution characteristics of different polar corona charges released in both cycles under the influence of wind and the spatial electric field distribution characteristics generated by the corresponding corona charges. Comparing unipolar corona discharges under the same wave pattern and amplitude of the background electric field, it was assumed that the unipolar corona discharge occurred in the half cycle after the polarity reversal of an electric field, and there was also an opposite-polarity corona discharge process before it. Due to the influence of the first half cycle, the background electric field required for a corona discharge was smaller, and the corona current was generated earlier, but the end time was equivalent. At the same time, due to the neutralization effect of positive and negative corona charges, the peak value of the total corona charge in the second half cycle was significantly smaller than that of the unipolar model. At different building heights, the peak difference in the corona current and the peak difference in the corona charge between the two models increased linearly with an increase in height. It could be seen that this model had better simulation results and wider application value. Full article
(This article belongs to the Section Meteorology)
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28 pages, 18246 KiB  
Article
Forecasting Cumulonimbus Clouds: Evaluation of New Operational Convective Index Using Lightning and Precipitation Data
by Margarida Belo-Pereira
Remote Sens. 2025, 17(9), 1627; https://doi.org/10.3390/rs17091627 - 3 May 2025
Viewed by 1292
Abstract
Deep convective clouds, such as towering cumulus and Cumulonimbus, can endanger lives and property, also being a major hazard to aviation. This study presents the convective index (IndexCON) used operationally at the Portuguese Meteorological Watch Office. Moreover, IndexCON is evaluated against [...] Read more.
Deep convective clouds, such as towering cumulus and Cumulonimbus, can endanger lives and property, also being a major hazard to aviation. This study presents the convective index (IndexCON) used operationally at the Portuguese Meteorological Watch Office. Moreover, IndexCON is evaluated against lightning and precipitation data for two years, between January 2022 and December 2023, over mainland Portugal and its surrounding areas. This index combines several European Center for Medium-Range Weather Forecasts (ECMWF) prognostic variables, such as stability indices, cloud water content, relative humidity and vertical velocity, using a fuzzy-logic approach. IndexCON performs well in the warm season (May–October), with a probability of detection (POD) of 70%, a false alarm ratio (FAR) of 30% and a probability of false detection (POFD) less than 5%, leading to a Critical Success Index (CSI) above 0.55. However, IndexCON performs worse in the cold season (November–April), when dynamical drivers are more relevant, mainly due to overestimating the convective activity, resulting in CSI and Heidke Skill Score (HSS) values below 0.3. Optimizing the membership functions partially reduces this overestimation. Finally, the added value of IndexCON was illustrated in detail for a thunderstorm episode, using satellite products, lightning and precipitation data. Full article
(This article belongs to the Special Issue Cloud Remote Sensing: Current Status and Perspective)
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27 pages, 5861 KiB  
Article
Analysis and Trends of the Stability Indices During Hail Days Derived from the Radiosonde Observations from Belgrade (Serbia)
by Dragana Vujović, Vladan Vučković and Aleksandar Zečević
Atmosphere 2025, 16(5), 520; https://doi.org/10.3390/atmos16050520 - 29 Apr 2025
Viewed by 599
Abstract
Forecasting thunderstorms, along with their intensity and phenomenon, is still one of the most challenging tasks in modern weather forecasting. One of the methods for this prediction is based on the indices of convective instability in the atmosphere. For the first time, we [...] Read more.
Forecasting thunderstorms, along with their intensity and phenomenon, is still one of the most challenging tasks in modern weather forecasting. One of the methods for this prediction is based on the indices of convective instability in the atmosphere. For the first time, we analysed the values and trends of 23 stability indices on days when hail occurred. From 2005 to 2020, the most frequently observed hailstones had a diameter between 13 and 20 mm, which accounted for 35.8% of all hail days, which was 826. Huge hailstones with a greater than 50 mm diameter were observed on only two days. Eight of the 23 stability indices show a monotonically decreasing (Showalter Index, Lifted Index, Lifted Index using the virtual temperature, and Humidity Index) or increasing trend (K Index, Convective Available Potential Energy for the most unstable air parcel and for mixing layer, and Convective Available Potential Energy in the layer between air temperatures −10 and −30 °C). These trends indicate that the environment is becoming increasingly favourable for the formation of thunderstorms. However, this potential does not appear to be fully realised, as the frequency of severe and large hail (with diameters of 21 mm or more) has not increased during the period studied. Full article
(This article belongs to the Section Meteorology)
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18 pages, 9721 KiB  
Article
A Multi-Year Investigation of Thunderstorm Activity at Istanbul International Airport Using Atmospheric Stability Indices
by Oğuzhan Kolay, Bahtiyar Efe, Emrah Tuncay Özdemir and Zafer Aslan
Atmosphere 2025, 16(4), 470; https://doi.org/10.3390/atmos16040470 - 17 Apr 2025
Viewed by 1097
Abstract
Thunderstorms are weather phenomena that comprise thunder and lightning. They typically result in heavy precipitation, including rain, snow, and hail. Thunderstorms have adverse effects on flight at both the ground and the upper levels of the troposphere. The characteristics of the thunderstorm of [...] Read more.
Thunderstorms are weather phenomena that comprise thunder and lightning. They typically result in heavy precipitation, including rain, snow, and hail. Thunderstorms have adverse effects on flight at both the ground and the upper levels of the troposphere. The characteristics of the thunderstorm of Istanbul International Airport (International Civil Aviation Organization (ICAO) code: LTFM) have been investigated because it is currently one of the busiest airports in Europe and the seventh-busiest airport in the world. Geopotential height (m), temperature (°C), dewpoint temperature (°C), relative humidity (%), mixing ratio (g kg−1), wind direction (°), and wind speed (knots) data for the ground level and upper levels of the İstanbul radiosonde station were obtained from the Turkish State Meteorological Service (TSMS) for 29 October 2018 and 1 January 2023. Surface data were regularly collected by the automatic weather stations near the runway and the upper-level data were collected by the radiosonde system located in the Kartal district of İstanbul. Thunderstorm statistics, stability indices, and meteorological variables at the upper levels were evaluated for this period. Thunderstorms were observed to be more frequent during the summer, with a total of 51 events. June had the highest number of thunderstorm events with a total of 32. This averages eight events per year. A total of 72.22% occurred during trough and cold front transitions. The K index and total totals index represented the thunderstorm events better than other stability indices. In total, 75% of the thunderstorm days were represented by these two stability indices. The results are similar to the covering of this area: the convective available potential energy (CAPE) values which are commonly used for atmospheric instability are low during thunderstorm events, and the K and total totals indices are better represented for thunderstorm events. This study investigates thunderstorm events at the LTFM, providing critical insights into aviation safety and operational efficiency. The research aims to improve flight planning, reduce weather-related disruptions, and increase safety and also serves as a reference for airports with similar climatic conditions. Full article
(This article belongs to the Special Issue Weather and Climate Extremes: Past, Current and Future)
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