Figure - available from: Natural Hazards and Earth System Sciences
This content is subject to copyright.
Seasonal average (brown dotted curve) and anomaly composite of graupel concentration during different ENSO phases. (a, d, g) Premonsoon season. (b, e, h) Monsoon season. (c, f, i) Postmonsoon season.
Source publication
The El Niño–Southern Oscillation (ENSO) modulates the lightning flash density (LFD) variability over India during premonsoon, monsoon and postmonsoon seasons. This study intends to shed light on the impact of ENSO phases on the LFD over the Indian subcontinent using the data obtained from Optical Transient Detector (OTD) and Lightning Imaging Senso...
Similar publications
Lightning flashes are potentially hazardous, albeit locally rare events. Despite this rareness, generalized additive models (GAMs) have succeeded in producing a climatology of lightning occurrence for the eastern Alps and surrounding lowlands with an unprecedented resolution of 1 km2 for each day from April to September based on data from the ALDIS...
Citations
... These climatic phenomena are associated with changes in SST in the Pacific and Indian Oceans, respectively [19,59,60]. It was reported that lightning activity increases (decreases) during El Niño (La Niña) years compared to neutral phase years [3,42]. Similarly, enhanced (suppressed) lightning activity was recorded during positive (negative) IOD years. ...
This study aims to explore the relationship between Sea Surface Temperature (SST) and various dynamic-thermodynamic parameters in connection with convective mechanisms that lead to lightning activity over Kerala, the southernmost state in India, and its surrounding areas. The analysis reveals that peak lightning activity occurs in May for the overall region, but April is particularly notable for Kerala. Furthermore, the investigation into large-scale climate phenomena indicates that strong El Niño events and transitions from El Niño to La Niña are associated with increased lightning activity in this region. Similarly, positive Indian Ocean Dipole (IOD) periods have significant impact than weak El Niño events. Spatial correlation analysis shows a strong connection between Convective Available Potential Energy (CAPE) and lightning activity, especially in April, May, and October. Additional analyses demonstrate significant positive relationships between lightning and various meteorological factors in the eastern Arabian Sea (AS), particularly north of 10°N during April and May, and in the central to southern AS (below 15°N) during the post-monsoon period. SST levels exceeding 29.6 °C during the pre-monsoon season significantly influence convective activity, with strong spatial correlations observed in May and the post-monsoon period. The study highlights that these factors play a crucial role in the formation of thunderclouds in the region by bringing moist air aided by wind patterns. Moist Static Energy (MSE) profiles support these findings, indicating greater atmospheric instability during months with high lightning activity. Vertical MSE distributions show a warm, moist lower atmosphere conducive to thunderstorm formation, particularly in May. This study emphasizes the complex interactions among dynamic-thermodynamic variables and SST in shaping the conditions that lead to lightning activity.
... Coastal regions, particularly those influenced by warm ocean waters, often experience elevated lightning densities, whereas cooler waters and subsidence contribute to lower lightning activity along the coastline. The east coast of India, influenced by warm equatorial ocean currents, exhibits higher lightning density than the west coast (Capozzi et al., 2018;Kamra & Ramesh Kumar, 2021;Siingh et al., 2014;Sreenath et al., 2021). While numerous studies have explored lightning characteristics over maritime and continental regions, a comprehensive understanding of lightning activity in India's coastal zones remains limited. ...
This study analyzed lightning activity along the east and west coasts of India using Lightning Imaging Sensor (LIS) for a 20-year period (1995–2014). For this study, we divided the coasts into four sub-regions with 5° × 5° grid resolution: R1 & R2 on the west coast (Maharashtra & Goa, Kerala respectively) and R3 & R4 on the east coast (Tamil Nadu & Southern Andhra Pradesh, West Bengal & Orissa respectively). To understand the factors influencing these different regional patterns, we investigated various meteorological parameters such as rainfall, wind, specific humidity, brightness temperature (BT), Convective Available Potential Energy (CAPE), lifted index (LI), K-index (KI) and total totals index (TTI). During the pre-monsoon months, R4 on the east coast and R2 (Kerala) on the west coast displayed the most lightning activity compared to other regions. However, during monsoon R3 and R4 on the east coast displayed the most lightning activity. Both coasts exhibited peaks in CAPE coinciding with peaks in lightning activity, suggesting CAPE plays a role in modulating lightning characteristics. The convergence of moisture transporting south-easterlies and westerlies potentially contributes to its high pre-monsoon lightning activity over R4. In contrast, westerly winds might influence post-monsoon activity in the western and southern regions (R2 & R3). The study also revealed a potential association between regional variations in lightning activity and the width of the mixed-phase region, along with its Ice water content (IWC) and Liquid water content (LWC). Conversely, rainfall is positively correlated with higher LWC in the lower atmosphere rather than in the mixed-phase region. Our findings underscore the importance of continuous lightning monitoring in dynamic coastal regions to deepen our understanding of these natural phenomena and enhance lightning prediction and safety measures.
... The highest lightning activity occurred in 2010, featuring the highest standard deviation and mean value, exceeding 0.06 flash counts km -2 day -1 . The peak lightning activity during 2010, especially in pre-monsoon season are agreement with the findings from various regions in India and Bangladesh (Guha et al. 2017;Sreenath et al. 2021). Similarly, the linear trend during MAM period also showed a positive significant trend. ...
The study addresses the elevated occurrence of lightning activity and associated incidents over Kerala, India, where the topography is complex. It aims to systematically investigate the spatiotemporal variations in lightning activity while elucidating the intricate relationships of lightning occurrences with dynamic and thermodynamic variables. Lightning distribution over India indicates relatively prominent lightning activity in Kerala. Analysis of climatological data reveals that the peak of lightning activity in Kerala is observed in April, in the pre-monsoon season, with an average of 0.2 ∓ 0.05 flashes km⁻² day⁻¹. Notably, the Kottayam district and its nearby areas exhibited high lightning frequencies of ≥ 0.3 flashes km⁻² day⁻¹ during this period. A secondary peak in lightning activity was recorded in October from the post-monsoon season, though comparatively less intense than during the pre-monsoon season (0.05 ∓ 0.008 flashes km⁻² day⁻¹). However, the regions west of the Palakkad Gap (PG) experience less lightning incidence. Further, the spatial analysis of dynamic and thermodynamic parameters (Convective Available Potential Energy (CAPE), K-Index, and pressure vertical velocity at 500 hPa) proved a clear and causative association with lightning occurrences in Kerala. The study also analyses the moisture transport to explore its migration during periods of heightened lightning activity. The trends observed in CAPE exhibit a significant correlation with lightning activity, especially during the pre-monsoon season.
... These small cloud droplets are transported above the freezing level by a stronger updraft, which increases the supercooled water content in a thunderstorm, significantly enhancing the ice-phase process. The freezing process releases more latent heat to develop convection, allowing more ice particles to participate in the electrification process of collision-coalescence and charge separation, thereby enhancing lightning activity with reduced rainfall during El Niño years (Berdeklis and List, 2001;Yuan et al., 2011;Guo et al. 2016;Shi et al., 2018Shi et al., , 2019Zhao et al., 2020;Sreenath et al., 2021;Tinmaker et al., 2022). ...
... During an El Niño year, the warmer SST (27.5 ºC) enhances sensible and latent heat fluxes from the sea surface towards the adjacent air mass, increasing the temperature at the lower atmosphere and inducing a steeper environmental lapse rate, which, in combination with cool air aloft (which helps to enhance convection and hence high lightning activity) reduces the amount of rainfall during El Niño years (Kandalgaonkar et al., 2002;Tinmaker et al., 2014;Kotroni and Lagouvardos, 2016). The high positive anomalies of the Niño 3.4 index are strongly El Niño years : (2002,2004,2006,2009,2014) Mean rainfall ( associated with El Niño, the warm phase of ENSO characterized by an increase in the average SSTs in the eastern Pacific Ocean and a higher air pressure in the western Pacific Ocean than in the eastern Pacific Ocean (Sreenath et al., 2021). A positive Niño 3.4 index also leads to high lightning activity during the El Niño year of the Indian summer monsoon. ...
The Indian summer monsoon rainfall (June-September) on a regional scale is critically important for agriculture and water management in India. The current study presents the lightning-rainfall relationship during El Niño (drought) and La Niña (flood) events in the Indian summer monsoon over central India. The results show that the flash count, Bowen ratio, surface maximum temperature, total heat flux, aerosol optical depth (AOD), sea surface temperature (SST), and Niño 3.4 index are increased by 36, 62, 19, 12, 46, 4.7%, and 0.3 ºC (warmer), whereas the rainfall is decreased by 15% during El Niño years with respect to normal years. The flash count, Bowen ratio, surface maximum temperature, and AOD are found to decrease by 15, 11, 3.5, and 11.1% during La Nina years, whereas the rainfall, total heat flux, SST, and Niño 3.4 index are found to increase by 2.4, 1.72, 0.36%, and –0.68 ºC (cooler) during La Niña years with respect to normal years. The increase in the flash count and the reduction in rainfall are associated with the warm phase of El Niño-Southern Oscillation (ENSO) (El Niño), which causes the weakening of the Indian summer monsoon. The decrease in flash count and increase in rainfall is due to the cold phase of ENSO (La Niña) and is associated with the strengthening of the Indian monsoon season. The increase in the number of break days and low-pressure systems also plays an important role in El Niño and La Niña years, respectively, over central India during the Indian summer monsoon.
... One such parameter that can affect thunderstorm formation is the turbulent heat fluxes (Toumi and Qie 2004;Chate et al. 2016;Tinmaker et al. 2019;Sreenath et al. 2021;Gautam et al. 2022). ...
Thunderstorm activity and lightning have been extensively studied due to their link with severe weather phenomenon. Intense thunderstorms have higher lightning flash rates (LFR), and this study investigates the causative mechanisms of such higher LFR over the Indian land region. Higher LFR occurs over India during pre-monsoon, monsoon and post-monsoon seasons. The results show that flash rates over the Indian land region depend on local heating and moisture availability enhanced by the heat content and moisture advection from the surrounding sea. The increase in the heat content of the Arabian Sea and Bay of Bengal during the pre-monsoon, monsoon and post-monsoon periods causes deep convection over the Seas to a higher altitude, which is then advected into the land by the winds. This increases the heat and turbulent heat flux over the land, and hence fuelling the thunderstorms, subsequently altering the flash rate. Multiple regression and correlation analysis show that the heat content and moisture advection from the Arabian Sea and Bay of Bengal have a major influence on the regions with higher LFR.
... This section presents the synoptic distribution and temporal evolution of integral cloud characteristics, representative of cloud and precipitation types, during extreme rainfall, using CERES-MODIS and TRMM-GPM-derived cloud properties. The latent heating of the atmosphere can be shaped by warm and cold cloud processes, which can change the updraft and downdraft structure of clouds and, ultimately, the distribution of precipitation (Colle and Zeng, 2004;Wang et al., 2007;Huang et al., 2014;Sreenath et al., 2021b). Additionally, the latent heating coupled with the precipitation process affects the circulation pattern during the summer monsoon (Choudhury and Krishnan, 2011). ...
... A dominant component of the observed variation of convection and rainfall over the Indian region arises from the fluctuations on the intra-seasonal scale between active spells with greater than normal rainfall and weak spells or break spells with below normal rainfall (Rajeevan et al. 2010). Most often, the strengthening or weakening of the ISM rainfall (ISMR) is directly linked with the establishment of the water vapor-laden monsoon winds at lower levels known as the monsoon low level jet-LLJ (Sreenath et al. 2021). The LLJ transports moisture from the surrounding oceans to the Indian land mass and hence regulates the quantum of ISMR (Sandeep and Ajayamohan 2015). ...
The remote influence of west Pacific typhoons on the historic Kerala flood in the 2018 Indian summer monsoon (ISM) season is investigated using the weather research and forecasting (WRF-ARW) model. The flood occurred as a result of vigorous monsoon intra-seasonal activity with some districts receiving excess rainfall exceeding 405%. Observational data reveals that a deflection of the monsoon low level jet (LLJ) occurred from south westerly to north westerly direction together with a slow-down of cloud movement over the central Kerala region due to a split in the LLJ core nearby the Arabian sea coast. The split and deflection of LLJ core produced cyclonic vorticity along 10° N latitude which favored severe convection. Nevertheless, a detailed analysis of the flow pattern reveals that the simultaneous formation of a low-pressure system (near Orissa coast in the Bay of Bengal) and several typhoons in the west-Pacific Ocean had a crucial role in the deflection and hence the production of cyclonic vorticity. By employing the tropical cyclone bogussing scheme in WRF-ARW, the formation of a west-Pacific typhoon was suppressed and subsequently a comparison was made against the control run in order to quantify the typhoon’s effect on the Kerala rainfall. It is found that the presence of low-latitude typhoon was primarily responsible for the deflection of the monsoon LLJ and hence the production of cyclonic vorticity through remote forcing. The study thus provides an insight into the teleconnection of west-Pacific typhoons on the intraseasonal variation of ISM and associated extreme rainfall events.
... The ONI [ ? 0.5°C (\ -0.5°C) is characterized as the warm (cold) phase, i.e., El Niño (La Niña) phase, while the ONI lying between -0.5 to ? 0.5°C is listed as the neutral phase of ENSO (hereafter neutral ENSO) (Dowdy, 2016;Sreenath et al., 2021). Table 1 lists the years lying in El Niño, La Niña and neutral phases. ...
... Notably, 1993 had ONI [ ? 0.5°C in only four consecutive overlapping seasons (3 months running mean from February-May) which led us to consider Table 1 List of years falling in El Nin˜o, La Nin˜a and Neutral phases of ENSO during the pre-monsoon and post-monsoon months with respect to ONI [ (\) ? 0.5 (-0.5)°C (Dowdy, 2016;Sreenath et al., 2021) Phases MAM (pre-monsoon) OND (post-monsoon) ...
The Tropical Cyclonic Disturbances (TCDs) over the Bay of Bengal (BoB) have always disrupted life, economy and environment across the coastal regions. The present study evaluates the ability of COoordinated Regional Climate Downscaling Experiment (CORDEX) constituting regional climate model (here REMO2009) in simulating the behaviour of some precursors of TCDs, frequency of TCDs and their intensity over the BoB. Furthermore, the impacts of El Niño Southern Oscillations (ENSO) and Indian Ocean Dipole (IOD) are addressed to determine the sensitivity of the model in capturing large-scale ocean-atmosphere coupled phenomena. The model outputs (resolution 0.44° × 0.44°) are evaluated against the recorded observations of India Meteorological Department and ERA-Interim reanalysis (resolution 0.25° × 0.25°) over the time period 1979–2005. Evaluation of TCD frequencies and intensities on a year-to-year basis shows the model performing reasonably well against observations but intensity is largely reduced. Also, we find an overestimated number of TCDs in the model as pre-monsoon (post-monsoon) shows + 195% (+ 80%) more TCDs. The large-scale environmental fields associated with TCDs show spatiotemporal biases of varying magnitudes in the model however are consistent in capturing TCDs and their behaviours. The mean climatology shows clear differences in environmental fields during days with TCDs and without TCDs. The genesis geolocations in observations are coherent with their environmental fields and are firmly reproduced in the model albeit with spatial differences. The intensity in the model is found to be mostly low showing weak TCDs besides overestimating (underestimating) TCDs of moderate (high) intensities. The REMO2009 model is found satisfactorily simulating the TCDs (year-to-year basis) and associated large-scale environmental fields against the observations and reanalysis. The impacts of large climatic teleconnections (ENSO and IOD) are also captured in the model with warm ENSO phase suppressing the TCDs activities while cold phase triggering the TCDs. On the similar watch, a negative dipole over the Indian Ocean triggers the TCDs while a positive dipole suppresses the TCDs formation in the model. The present study using the regional climate model (RCM) REMO2009 is moreover a needed baseline for the future projections and evaluation of other RCMs under the CORDEX domains.
... Seasonal distributions of lightning activity have been explored in several studies (Kandalgaonkar, 2005;Ranalkar and Chaudhari, 2009;Tinmaker et al., 2010). In the El-Niño (La-Nina) period of the pre-monsoon and monsoon seasons over India, there is an increase (decrease) in the flash density as compared to the Non-ENSO period (Ahmad & Ghosh, 2017;Ramesh Kumar and Kamra, 2012;Sreenath et al., 2021). In another study, Kulkarni (2015) has revealed that for rainfall prediction atmospheric electricity can be used as a proxy parameter. ...
Plain Language Summary
Lightning, atmospheric hazards have an impact on the loss of human life, forest fire, health, agriculture, and economy across the globe. However, due to its chaotic nature, the tendency of seasonal forecasting of lightning is considered not viable as the understanding of the predictability of lightning is still incomplete. Here, we have explored the possibility of seasonal forecasting of lightning activity and provided a scientific basis as the lightning flashes are found to be tied with slowly varying remote forcings (e.g., El Niño and Southern Oscillation, or other global predictors). Correlation of flash count with different indices (Nino, Pacific decadal oscillation, North Atlantic oscillation, and Extra tropics, etc.) demonstrate the potential of seasonal forecasting of lightning. The multiple regression analysis enhances the skill. The climatology of lightning flash density from the Goddard Earth observing system model is compared with observation. The pattern correlation between observation and model is very high (∼0.7) over global tropics hints at the predictability of lightning flashes on a seasonal time scale. Therefore, better climate models that capture crucial couplings between ocean, atmosphere, and land processes could make skillful predictions of lightning and opens up a possibility for lightning forecast in one season advance.
Lightning studies are highly focused on spatial and temporal variability in various scales but very limited studies are focused on dominant spatial modes of variability. This study intends to identify the possible spatial modes of climate variability of lightning over India during different seasons and relate them to regional and large-scale climate modes. Empirical orthogonal function analysis of lightning has been carried out and the first three orthogonally independent modes are considered in order to retrieve the maximum variance explained by each mode. To understand the role of remote and local teleconnections on the lightning flash rate (LFR) variability, we have analyzed two Pacific Ocean modes (El Niño Southern Oscillation; ENSO, Pacific Decadal Oscillation; PDO) and two Indian Ocean modes (Indian Ocean Dipole; IOD and Bay of Bengal (BOB) meridional Sea Surface Temperature (SST) gradient). First mode is positively correlated with the warm phase of ENSO and PDO whereas second and third modes are negatively correlated with the warm phase of ENSO and PDO during pre-monsoon, post-monsoon and winter. Reverse is true for the monsoon season due to the shift in walker cell caused by the changes in the location of the heat sources and sinks. A strong positive correlation of IOD and BOB meridional SST gradient with first mode, suggests the vital role of nearby Indian Ocean in explaining the typical lightning flashes over India due to the enhanced zonal and meridional circulation, thereby moisture supply to the Indian subcontinent. The impact of Nino-3.4, IOD and BOB meridional SST gradient on lightning over India further suggest the role of SST in local and remote influence on lightning variability through the distribution and transport of heat and moisture.
