. Lightning activity constitute the major destructive component of
thunderstorms over India. Hence, an understanding of the long-term variability
in lightning occurrence and intensity and their interrelation with various
causative factors is required. Long-term (1998–2014) Tropical Rainfall
Measuring Mission (TRMM) satellite-based lightning observations depict the
most frequent lightning occurrences along the Himalayan foothills, the
Indo-Gangetic plains and coastal regions, while the intensity of these
lightning strikes is found to be strongest along the coastal regions and in the
Bay of Bengal. In addition, both of the abovementioned lightning properties show a very strong
intensification ( ∼  1 %–2.5 % annually) across all Indian
regions during the 1998–2014 period with the maximum trends along the coasts.
Accordingly, a detailed statistical dominance analysis is performed which
reveals total column water vapor (TCWV) to be the dominant factor behind the
intensification in lightning events, while instability, measured by the
convective available potential energy (CAPE), and aerosol optical depth
(AOD) jointly control the lightning frequency trends. An increase in surface
temperatures has led to enhanced instability and, hence, stronger moisture
transport to the upper-troposphere and lower-stratosphere regions, especially along the coasts. This transported moisture helps deplete the ozone
concentration, leading to reduced temperatures and elevated equilibrium
levels, which finally results in stronger and more frequent lightning events,
as also evidenced by the trend analysis. Consequently, the relationships
between lightning and its causative factors have been expressed in the form of
multilinear regression equations, which are then employed in multiple global
circulation models (GCMs) to understand the long-term impact of urbanization
on lightning over the period from 1950 to 2100. The analysis reveals a uniform
increase in lightning occurrence and intensity using both urbanization
scenarios; however, accelerated growth is observed in the RCP8.5
projections after the year 2050, as also observed from the surface warming
trends. As a result, lightning frequency and intensity values across the
Indian region are expected to increase ∼  10 %–25 % and 15 %–50 %, respectively, by the end of the century with the
highest risk along the coasts; hence, this requires immediate attention
from policymakers.

/pdf/lightning-occurrences-and-intensity-over-the-indian-region-3p5tclan8e.pdf

Lightning occurrences and intensity over the Indian region: long-term trends and future projections

Characteristics of lightning-caused wildfires in central Brazil in relation to cloud-ground and dry lightning

Influence of the COVID-19 lockdown on lightning activity in the Po Valley

The effect of aerosols on lightning has been noted in many studies, but much less is known about the long-term impacts in air-polluted urban areas of China. In this paper, 9-year data sets of cloud-to-ground (CG) lightning, aerosol optical depth (AOD), convective available potential energy (CAPE), and surface relative humidity (SRH) from ground-based observation and model reanalysis are analyzed over three air-polluted urban areas of China. Decreasing trends are found in the interannual variations of CG lightning density (unit: flashes km−2day−1) and total AOD over the three study regions during the study period. An apparent enhancement in CG lightning density is found under conditions with high AOD on the seasonal cycles over the three study regions. The joint effects of total AOD and thermodynamic factors (CAPE and SRH) on CG lightning density and the percentage of positive CG flashes (+CG flashes/total CG flashes × 100; PPCG; unit: %) are further analyzed. Results show that CG lighting density is higher under conditions with high total AOD, while PPCG is lower under conditions with low total AOD. CG lightning density is more sensitive to CAPE under conditions with high total AOD.

Cloud-to-Ground Lightning Response to Aerosol over Air-Polluted Urban Areas in China

Abstract Accurate and timely prediction of lightning occurrences plays a crucial role in safeguarding human well-being and the global environment. Machine-learning-based models have been previously employed for nowcasting lightning occurrence, offering advantages in computation efficiency. However, these models have been hindered by limited accuracy due to inadequate representation of the intricate mechanisms driving lightning and a restricted training dataset. To address these limitations, we present a machine learning approach that integrates aerosol features to more effectively capture lightning mechanisms, complemented by enriched satellite observations from the Geostationary Lightning Mapper (GLM). Through training a well-optimized LightGBM model, we successfully generate spatially continuous (0.25° by 0.25°) and hourly lightning nowcasts over the Contiguous United States (CONUS) during the summer season, surpassing the performance of competitive baselines. Model performance is evaluated using various metrics, including accuracy (94.3%), probability of detection (POD, 75.0%), false alarm ratio (FAR, 38.1%), area under curve of precision–recall curve (PRC-AUC, 0.727). In addition to the enriched dataset, the improved performance can be attributed to the inclusion of aerosol features, which has significantly enhanced the model. This crucial aspect has been overlooked in previous studies. Moreover, our model unravels the influence of aerosol composition and loading on lightning formation, indicating that high aerosol loading consisting of sulfates and organic compounds tends to enhance lightning activity, while black carbon inhibits it. These findings align with current scientific knowledge and demonstrate the immense potential for elucidating the complex mechanisms underlying aerosol-associated lightning phenomena. 

Lightning nowcasting with aerosol-informed machine learning and satellite-enriched dataset

https://rmets.onlinelibrary.wiley.com/doi/epdf/10.1002/asl.957

Influence of aerosols on lightning activities in central eastern parts of China

Numerical simulations are performed to investigate the effect of varying CCN (cloud condensation nuclei) concentration on dynamic, microphysics, electrification, and charge structure in weak, moderate, and severe thunderstorms. The results show that the response of electrification to the increase of CCN concentration is a nonlinear relationship in different types of thunderclouds. The increase in CCN concentration leads to a significant enhancement of updraft in the weak thunderclouds, while the high CCN concentration in moderate and severe thunderclouds leads to a slight reduction in maximum updraft speed. The increase of the convection promotes the lift of more small cloud droplets, which leads to a faster and stronger production of ice crystals. The production of graupel is insensitive to the CCN concentration. The content of graupel increases from low CCN concentration to moderate CCN concentration, and slightly decreases at high CCN concentration, which arises from the profound enhancement of small ice crystals production. When the intensity of thundercloud increases, the reduction of graupel production will arise in advance as the CCN concentration increases. Charge production tends to increase as the aerosol concentration rises from low to high in weak and moderate thundercloud cases. However, the magnitude of charging rates in the severe thundercloud cases keeps roughly stable under the high CCN concentration condition, which can be attributed to the profound reduction of graupel content. The charge structure in the weak thundercloud at low CCN concentrations keeps as a dipole, while the weak thunderclouds in the other cases (the CCN concentration above 100 cm−3) change from a dipole charge structure to a tripole charge structure, and finally disappear with a dipole. In cases of moderate and severe intensity thunderclouds, the charge structure depicts a relatively complex structure that includes a multilayer charge region.

A Numerical Study of Aerosol Effects on Electrification with Different Intensity Thunderclouds

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Papers

Influence of aerosols on lightning activities in central eastern parts of China

Cloud-to-Ground Lightning Response to Aerosol over Air-Polluted Urban Areas in China

A Numerical Study of Aerosol Effects on Electrification with Different Intensity Thunderclouds