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A triggered lightning flash (TLF) provides a unique perspective on the relationship between spatiotemporal proximity flashes, owing to its determined location and time, convenient direction measurement, and explicit association with the charge region. In this study, 3-D lightning location, current measurement, and atmospheric average electric field (AAEF) data were used to investigate the spatiotemporal relationship of TLFs (68 samples in South China) with adjacent natural lightning flashes (NLFs). The TLF-related negative charge regions had an average core height of 5.2 km and ambient temperature of approximately −1.7 °C. The effective negative charge region (the charge density that was high enough for the occurrence of lightning discharge) can be approximately equivalent to a circle with an average diameter of 10.3 km. For approximately 93% of (all) the TLFs, no NLF channel (initiation) was located within 5 km of the flash-triggered position, within 5 s before and after their occurrence. In situations where spatiotemporally adjacent NLFs and TLFs occurred, they were either associated with different charge layers or the same charge layer but different charge positions. Most NLFs that caused significantly sharp AAEF changes just before or after the TLFs were not associated with the TLF-related negative charge. Therefore, the recovery of the AAEF, which has usually been referenced as the timing choice of the triggering operation, was not directly associated with the TLF-related charge region. The average interval between the TLFs and NLFs that occurred within 10 min before and after the TLFs and neutralized the TLF-related negative charge was approximately 145 s.

The lightning flash frequency (LFF, also referred to as lightning flash rate) in four models from the Coupled Models Intercomparison Project, phase 6 is examined. For the present day (PD, 1995–2014), the models exhibit very divergent simulation of LFF in terms of multi–annual averages, interannual variability, and temperature sensitivity. The global mean multi–annual average flash frequency differs by a factor of two between the models, and only two of four models are within the reasonable distance from the LIS/OTD (Lightning Imaging Sensor/Optical Transient Detector) satellite retrievals. The model–data and inter–model differences are even more pronounced at a regional scale and during northern summer. CMIP6 simulations show a general increase in lightning flash frequency from the present day to the late 21st century, especially for the simulations with higher anthropogenic CO2 emissions into the atmosphere. LFF sensitivity coefficient β, which is based on differences between PD and the late 21st century are positive over most continental areas with typical values from 10 to 20%K-1 for annual mean LFF and from 20 to 60%K-1 for JJA averages over the northern extra–tropical continents (and even up to 100%K-1 in some regions for individual models). At the global scale and for annual averages, this sensitivity is from 5 to 17%K-1. In addition, this sensitivity is markedly different from its counterpart derived from the regression of LFF on surface air temperature for PD period. The latter counterpart is negative at the global scale and changes sign between different regions (i.e, it is positive over the North America south–east and is negative over the south–western part of North America and over the India Peninsula). These regional peculiarities are reasonably simulated by the models.

The predicting of lightning activity using Weather Research and Forecasting coupled with the electrification (ELEC) module, known as the WRF-ELEC model, has been used in this study to simulate lightning flashes over different regions of the Indian subcontinent. The state-of-the-art model is specially developed focusing on the generation of atmospheric lightning activities. IITM-LLN is the observation data used to compare qualitatively and quantitatively with the simulated results for three unique severe thunderstorm events in 2022 (April 10, May 10, and June 13). These events were chosen based on the availability of LLN data, GPM satellite overpasses, and their diverse locations within the subcontinent. The WRF-ELEC model demonstrates impressive accuracy in capturing the initiation and spatial distribution of lightning from these thunderstorm systems, with minimal lag and error. Forecasts show reasonable skill for up to ~15 hrs, though accuracy diminishes with longer lead times. Notably, the model successfully reproduces the diurnal cycle of lightning activity, including the prominent peak observed in typical thunderstorms. However, its performance in capturing the diurnal cycle for complex thunderstorms is reduced under conditions with pre-existing atmospheric instability or complex terrain. Also, for such systems, the peak is also captured by a model with a lead of one hour. Overall, this study assesses lightning forecasting using the state-of-the-art WRF-ELEC model and LLN observation over India and adjoining regions under different meteorological conditions and varied topographical regions.Research highlightsThe WRF-ELEC efficiently simulates the lightning flashes with no spatial shift and no time lag of initiation, but an overestimation in the flash count is observed.ERA5 is the most appropriate source for the IBC for WRF-ELEC for simulating accurate lightning flashes.WRF-ELEC has room for improvement in simulating precise lightning time for extreme events viz. Dima Hasao heavy rainfall event, May 2022.

The association between aerosol and lightning has been investigated with long-term decadal data (2005–2014) for lightning, aerosol optical depth (AOD), relative humidity, and effective cloud droplet size. To understand the complex relationship between aerosol and lightning, two different regions with different climatic and weather conditions, a humid region R1 (22°–29° N, 89°–92° E) and an arid region R2 (23°–28° N, 70°–76° E) of northern India, were chosen for the study domain. The results show that lightning activity was observed to occur more over the humid region R1, i.e., 1141 days (1/3 of total days), than over the arid region R2, i.e., 740 days (1/5 of total days). Also, over the humid region R1, the highest lightning flash density was recorded as nearly 4.6 × 10–4 flashes/km2/day observed for 18 days (1.5%); on the contrary, over the arid region R2, the maximum lightning flash density was observed to be 2.5 × 10–4 flashes/km2/day and occurred for about 22 days (2.9%). The analysis shows that a nonlinear relationship exists between aerosol and lightning with a highly associated influence of relative humidity. A very significant positive and negative co-relation that varies with relative humidity has been observed between AOD and lightning for both humid and arid regions. This shows relative humidity is the key factor in determining the increase or decrease of lightning activity. This study also shows that the larger the cloud droplet size, the higher the relative humidity and vice versa. This study emphasizes that aerosol concentration in the atmosphere influences cloud microphysics by modulating the size of cloud droplets and thereby regulating the lightning frequency. The atmospheric humidity is the driving factor in deciding the positive or negative co-relationship between aerosol and lightning.

Product of Bowen ratio with the sum of precipitation rate and evaporation rate has been used as proxy to evaluate the seasonal and annual spatial distributions of lightning flash rate over South/Southeast Asian region (60–120° E, 0–40° N) with 9 models from the Coupled Model Inter-comparison Project-Phase 5 (CMIP5). The model-simulated mean LFR with each model is positively correlated with the satellite-observed LFR on both seasonal and annual scales. The satellite-observed LFR is correlated with the ensemble mean LFR of the models with a correlation coefficient of 0.93 over the region. The model-simulated LFR has also been used for projection of lightning in the late twenty-first century. Overall, the projected LFR over whole study area shows a 6.75% increase during the (2079–2088) period in high radiative forcing scenario (RCP8.5) as compared to the historic period of (1996–2005). Rise in LFR is also identified using another projected period (2051–2060) and a lower radiative forcing scenario condition (RCP4.5), though lesser in magnitude, as expected. For the projected period (2051–60) in the RCP8.5 case, LFR over the domain shows an increase of 4.3%; whereas for a lower future scenario condition (RCP4.5), it indicates a rise by 5.36% at the end of the twenty-first century. Moreover, results indicate an increase in extreme events of severe convective storms with intense lightning in mountainous dry regions at the end of the twenty-first century. It is suggested that the proxy used here is favourable for projection of LFR in this region and perhaps for the whole tropical area.

The impacts of elevation, terrain slope and vegetation cover on lightning activity are investigated for contrasting environments in the north-east (NE) (21– 29 ∘ N ; 86– 94 ∘ E ) and the north-west (NW) (28– 36 ∘ N ; 70– 78 ∘ E ) regions of the Himalayan range. Lightning activity is more at a higher terrain slope/elevation in the dry NW region where vegetation cover is less, whereas it is more at a lower terrain slope/elevation in the moist NE region where vegetation cover is more. In the wet NE, 86% (84%) of the annual lightning flash rate density (LFRD) occurs at an elevation < 500 m (terrain slope < 2 % ) and then sharply falls off at a higher elevation (terrain slope). However, only 49% (47%) of LFRD occurs at an elevation of < 500 m (terrain slope < 2 % ) and then rather gradually falls off at a higher elevation (terrain slope) in the dry NW. The ratio of the percentages of LFRD and elevation points is much higher in the NW than in the NE above an elevation of ∼ 1000 m . The impacts of terrain slope and elevation in enhancing the lightning activity are stronger in the dry NW than in the moist NE. The correlation coefficient of the LFRD with the normalised difference vegetation index is higher in the NW than in the NE on both the regional and annual scales. Results are discussed as a caution in using any single climate variable as a proxy for projecting a change in the lightning–climate relationships in the scenario of global warming.

At present, there is still some uncertainty in the evaluation of the performance of the Fengyun 4A Lightning Mapping Imager (LMI), which is mainly limited by the detection performance of the reference detection system and the suitability of the evaluation method. In this paper, a one-to-one performance evaluation of the LMI was performed based on total lightning flash data from the lightning Low-Frequency Electric field Detection Array (LFEDA). It was found that there were significant systematic biases in the discharge results detected via LMI, with a median of −0.946 s, −0.0817°, and −0.0245° in time bias, longitude bias, and latitude bias, respectively. The evaluation results after removing the systematic biases indicated that the relative detection efficiency for flashes of LMI was 17.6%, the mean and median time errors were both 0.647 s, and the mean and median distance errors were 6.09 km and 5.02 km, respectively. The relative detection efficiency for groups of LMI was 9.8%, the mean and median time errors were 0.674 s and 0.660 s, and the mean and median distance errors were 7.19 km and 6.54 km, respectively. The detection efficiency of LMI for both flashes and groups at nighttime was significantly higher than its detection efficiency during the daytime. The relative detection efficiency for flashes of LMI at nighttime was 26.5%, while during the daytime it was 14.4%. The relative detection efficiency for groups of LMI at nighttime was 16.2%, while during the daytime it was only 7.4%. The spatial accuracy for both flashes and groups was always better during the daytime than at nighttime.

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.

Lightning flash rate parameterizations based on polarimetric and multi-Doppler radar inferred microphysical (e.g., graupel volume, graupel mass, 35 dBZ volume) and kinematic (e.g., updraft volume, maximum updraft velocity) parameters have important applications in atmospheric science. Although past studies have established relations between flash rate and storm parameters, their expected performance in a variety of storm and flash rate conditions is uncertain due to sample limitations. Radar network and lightning mapping array observations over Alabama of a large and diverse sample of 33 storms are input to hydrometeor identification, vertical velocity retrieval and flash rate algorithms to develop and test flash rate relations. When applied to this sample, prior flash rate linear relations result in larger errors overall, including often much larger bias (both over- and under-estimation) and root mean square errors compared to the new linear relations. At low flash rates, the new flash rate relations based on kinematic parameters have larger errors compared to those based on microphysical ones. Sensitivity of error to the functional form (e.g., zero or non-zero intercept) is also tested. When considering all factors (e.g., low errors including at low flash rate, consistency with past linear relations, and insensitivity to functional form), the flash rate parameterization based on graupel volume has the best overall performance.

This study investigates the characteristics of negative cloud‐to‐ground (CG) lightning flashes across varying peak current (PCs) ranges by combining 3D location data from 2,597 negative CG flashes with radar observations. The flashes were classified into five PC bins: −25 kA < PC < 0 kA, −50 kA < PC < −25 kA, −75 kA < PC ≤ −50 kA, −100 kA < PC ≤ −75 kA, and PC ≤ −100 kA. Key parameters analyzed include initiation altitude, reflectivity at initiation points, vertical reflectivity cores, lightning extension spaces, horizontal distances between initiation and grounding points (HD), and time differences between the first‐detected radiation source and the first return stroke (TD). Results reveal that while initiation environments were broadly similar across PC ranges, large‐PC flashes tended to initiate at lower altitudes (1–3 km). These flashes form first return strokes faster (the median TD for current bins below −75 kA is less than 44 ms, whereas for bins above −75 kA the median TD is greater than 57 ms) after shorter horizontal propagation (The median HD for current bins below −75 kA is around 1.0 km, while for bins above −75 kA the median HD exceeds 1.2 km), with smaller pre‐return‐stroke extension areas. Despite this, large‐PC flashes usually develop more extensive total channel areas. These findings underscore the distinct environmental conditions that facilitate the initiation and propagation of large‐PC negative CG flashes during thunderstorms. Plain Language Summary Few studies have examined how the characteristics of cloud‐to‐ground (CG) lightning flashes relate to their peak currents. This study investigates the correlation between initiation altitudes, lightning channel extension, and peak currents, as well as the environmental conditions associated with negative CG flashes. By categorizing flashes based on their peak currents, we provide new insights into the differences between large‐peak‐current and low‐peak‐current negative CG flashes, particularly in how they initiate and propagate. Our findings show that while large‐peak‐current negative CG flashes occur in similar overall environments as smaller‐peak‐current flashes, they tend to start at lower altitudes. Additionally, large‐peak‐current flashes exhibit faster formation of the first return stroke after propagating shorter horizontal distances, typically displaying more compact horizontal extension prior to the first return stroke. However, subsequent channel development generally leads to more extensive total channel areas compared to low‐peak‐current flashes. These results help clarify the specific electrical conditions that promote the occurrence of large‐peak‐current negative CG flashes. Key Points Large‐peak‐current negative cloud‐to‐ground (CG) flashes typically initiate at lower altitudes when the vertical reflectivity center is near the ground A large‐peak‐current negative CG flash typically strikes the ground through a near‐vertical channel shortly after initiation A large‐peak‐current negative CG flash is likely initiated by a compact, high‐density negative charge region