Variability of lightning hazard over Indian region with respect to ENSO Phases

The El-Nino Southern Oscillation (ENSO) modulates the lightning flash rate (LFR) variability over India during pre-monsoon, monsoon, and post-monsoon seasons. The impact of ENSO phases on the LFR over the Indian subcontinent is studied using the data obtained from Optical Transient Detector and Lightning Imaging Sensors onboard the TRMM satellite. The study shows that irrespective of ENSO phases, the LFR is maximum over northeast India (NEI) in the pre-monsoon season, and the peak is shifted to the north of northwest India (NNWI) in the monsoon season. The LFR over Northeast India (NEI) 5 and southern peninsular India (SPI) intensified (reduced) during the warm (cold) phase of ENSO in the pre-monsoon season. In the monsoon season, NEI (NNWI) is showing above normal LFR in the warm (cold) ENSO phase. It is fascinating that the three hotspots of LFR over the Indian land region became more prominent in the last decade of the monsoon season. A widespread increase of LFR is observed all over India during the warm phase of ENSO in the post-monsoon season. However, a marked increase in the LFR is confined mostly over the NNWI in the cold ENSO phase. The subtropical westerly jet stream 10 is shifted south in association with the warm phase, and an increase in the geopotential height (GPH) is also noticed all over India in the same period. ENSO’s warm phase indirectly influences the LFR over India during the post-monsoon season by pushing the mean position of subtropical westerly towards south latitudes.

(Warm), La-Nina (Cold), and Neutral. The ENSO is a crucial player in the transport of heat, moisture, and momentum and modulates the frequency, intensity, and location of deep convection and the associated lightning activity (Williams, 1992;Kulkarni and Siingh, 2014). Higher Lightning Flash Rate (LFR) areas are located away from the equator during the warm phase and coincide with regions of anomalous jet stream circulation enhanced by the meridional heat transport (Chronis et al., 2008). Kandalgaonkar et al. (2010) has reported that lightning activity during the El-Nino year of 2002 increased by 18% over 30 the Indian land region compared to the La-Nina years during 1998-2011. On a global scale, lightning activity shows strong regional preference during different ENSO Phases.
The changes in the lower and upper air circulations associated with different ENSO phases have been found to influence the storm frequency and intensity (Yang et al., 2002;Hsu and Wallace, 1976), which in turn affect the lightning activity (Goodman et al., 2000). Kent et al. (1995) observed that ENSO could dictate the distribution of clouds over the tropics and 35 subtropics. Owing to the presence of anomalous subsidence over the western Pacific and adjacent landmass, deep convective clouds are inhibited; hence the rainfall is less during the warm phase (Cess et al., 2001). A southward/eastward shift in the global lightning activity is visible during the warm phase, and the latitudes corresponding to the descending limb of the Hadley circulation exhibit the most significant contrast of LFR between the warm and cold phase of the ENSO (Sátori et al., 2009).
Generally, lightning activity is controlled by the clouds growing deep into the atmosphere. The deep convective cores present 40 over the east coast of India during the pre-monsoon season shift to the foothills of western Himalayas during the monsoon (Romatschke et al., 2010). Cecil et al. (2014) documented that the offshore regions of India and the maritime continent are prone to deep convection. The vertical growth of cloud systems is amplified by the intense updraft, promoting ice crystals and supercooled liquid (mixed-phase) inside the convective system. The interaction between these hydrometeors is mainly responsible for the electrification inside the cloud (Takahashi et al., 1999;Williams, 2001). Topography plays a critical role in 45 the development of deep convective clouds and impacts the distribution of lightning activity (Kilinc and Beringer, 2007). Earlier studies have observed that elevated landmass favors the development of deep convective clouds (Zipser et al., 2006;Houze Jr et al., 2007;Rasmussen and Houze Jr, 2011) and thereby leading to higher LFR. The dynamic and thermodynamic states of the atmosphere also modulate the lightning activity over a region (Williams, 1992;Zipser, 1994;Petersen et al., 1996;Rosenfeld, 1999). Another agent that plays a decisive role in generating lightning activity is aerosols. Higher aerosol loading increases 50 the available liquid water in the mixed-phase condition, which is an essential factor for cloud electrification and lightning activity (Williams et al., 2002). Venevsky (2014) reported a significant correlation between lightning and concentration of annually-averaged cloud condensation nuclei over both land and ocean.
The awareness of lightning safety among the public is relatively low. The present study provides vital information on the risky lightning periods over the Indian subcontinent and how the large scale phenomenon, ENSO, is influencing the same. We are 55 detailing the modulation of LFR under different ENSO phases with the help of a vertical profile of hydrometeors (graupel and snow) inside the cloud systems and related atmospheric dynamics during pre-monsoon, monsoon, and post-monsoon seasons in India. The variability of LFR and hydrometeor distribution inside the convective system with different ENSO phases is very rare in the literature. 1995. The LIS/OTD data product from July 1995 to December 2013 gives the LFR at a spatial resolution of 2.5 • × 2.5 • and a temporal resolution of 1 day. The TRMM-3A12 data provide the distribution of hydrometeors (graupel, snow, rainwater) inside the convective systems. The monthly averaged vertical profiles of hydrometeors, and latent heat used in this study are from above data set. The data set is having a spatial resolution of 0.5 • × 0.5 • , and it available from January 1998 to December 2013.
It has 28 vertical levels, which start from 0.5 km, and each level is separated by 0.5 km. The modulation of Geopotential height (GPH) at 500 hPa, wind at 200 hPa, and specific humidity (SH) at 300 hPa are also examined with the ENSO phases from July 1995 to December 2013. The above parameters are obtained from the NCEP-NCAR reanalysis data with a similar spatial and 70 temporal resolution of LFR. Oceanic Nino Index (ONI) is the standard used to identify different phases of ENSO. The average value of ONI is determined during pre-monsoon, monsoon, and post-monsoon season by using Hadi SST data and detailed in table 1. If ONI value is above +0.5 • (-0.5 • ) C, it is taken as the warm (cold) phase, and the neutral phase corresponds to the ONI index lies between -0.5/+0.5 • C .
3 Results and discussion 75 3.1 Composite LFR with respect to ENSO phases Figure 1 represents the LFR composites for pre-monsoon, monsoon, and post-monsoon seasons corresponding to the three ENSO phases. Irrespective of ENSO phases, the LFR peak is located over northeast India (NEI) during the pre-monsoon season while its peak shifts to the north of northwest India (NNWI) in the monsoon season. Kamra and Athira (2016) have previously reported a similar type of swing in LFR between pre-monsoon and monsoon seasons. The Himalayan orography 80 favours the formation of deep convective systems over the NEI (Goswami et al., 2010) and is evidenced by the high values of LFR over the region. Rather than the altitude, the steep topographic gradient is responsible for producing deep convection.
The deep convective clouds developed in the conditionally unstable atmosphere during the pre-monsoon season are electrically more active . Lau et al. (2008) proposed that during the pre-monsoon months, dust and black carbon from neighbouring sources accumulates over the Indo-Gangetic plain against the foothills of Himalayas and act as an elevated 85 heat pump (EHP). The enhanced warming in the middle and upper troposphere contributes to the genesis of deep clouds and higher LFR.
Compared to monsoon and post-monsoon seasons, convective available potential energy (CAPE) is higher during the premonsoon season. The maximum values appear over the southern peninsular region and the east coast of India, and the average value is above 1500 J/kg all over India (Murugavel et al., 2014). The regions of higher values of LFR (Figure 1) during the 90 pre-monsoon season coincide with the regions of CAPE maxima reported by (Murugavel et al., 2014 limit the vertical development of convective clouds during the summer monsoon under the influence of maritime air mass (Kumar et al., 2014;Tinmaker et al., 2015), which leads to a decline in the cloud electrification during the monsoon season.
Among the three seasons, post-monsoon shows a minimum of LFR over the Indian region (Figure 1), and the NW to the NE gradient of LFR is also observed to be weak in this season. The average value of CAPE during the season is less than 500 J/kg 95 over most parts of India (Murugavel et al., 2014), which is quite low to favour the development of deep convection and hence lightning.

Distribution of LFR during pre-monsoon season with respect to ENSO phases
There are three hot spots of high lightning activity over the Indian subcontinent (Figure 1 (Figure 2 (a, b)). However, the same region exhibits an increase of LFR during the normal phase (Figure 2 (c)).   (Figure 2 (d, e)). While analysing the 300 hPa SH variability, we noticed that the amount of SH over that region is high during the warm and low during the cold phase (Figure 7 (d, e)). The NEI is showing positive anomaly of LFR during both warm and cold phases of ENSO. Figure 3  cold phase (during the monsoon season) show an increase in LFR over NEI. The similarity in the LFR anomaly is noticeable in the distribution of graupel and snow during the two phases (Figure 4 (b), 5 (b)). In contrast, the LFR is enhanced (suppressed) over NNWI during the cold (warm) period due to the presence of a larger (smaller) amount of graupel and snow. There is no noticeable change in the distribution of LFR over SPI in the three phases of ENSO (Figure 2 (d, e, f). Anomaly pattern of LFR in individual years is not exhibiting any particular pattern corresponding to different ENSO phases over SPI (Figure 3 (h)). It is interesting that during the 12 years from 2002 to 2013, 11 years have shown above-average values of LFR over the NEI and NNWI regions (Figure 3 (b, e)), demonstrating the intensification of deep convective cloud formation during the recent 9 https://doi.org/10.5194/nhess-2020-292 Preprint. Discussion started: 16 November 2020 c Author(s) 2020. CC BY 4.0 License.    of LFR throughout the country, and it is maximum over north-central India (Figure 2 (g)). In contrast, in the cold phase, intense 155 LFR is concentrated only over the NNWI (Figure 2 (h)). The NEI and NNWI are not showing any significant difference in the vertical profile of snow and graupel with different ENSO phases during the post-monsoon season (Figures 4 (c, f) and 5 (c, f)). Zubair and Ropelewski (2006) reported that there exists a significant role for ENSO on controlling the post-monsoon rainfall over SPI. The SPI is showing an increase of LFR in the warm phase of ENSO during the season due to the presence of clouds 11 https://doi.org/10.5194/nhess-2020-292 Preprint. Discussion started: 16 November 2020 c Author(s) 2020. CC BY 4.0 License. having higher graupel and snow content over that region (Figures 2 (g), 4 (i), 5 (i)). The entire years grouped under the warm 160 phase of ENSO during the post-monsoon season show an increase of LFR over SPI. On the other hand, in the years of the cold phase, the LFR anomaly pattern is not uniform (Figure 3 (i)). Climate variability, like ENSO, can alter the position of jet streams and hence the distribution of WD (Hunt et al., 2018). Syed et al. (2006) identified that the intensification of WDs during the El-Nino is associated with the weakening of Siberian high. The depressions formed over the South Bay of Bengal, and the Arabian Sea can also modulate WDs' path (Rao et al., 1969). The 500 hPa GP surface drops-down (go up) from the 25 • N 165 towards the north and indicates the suppression (enhancement) of convection over that region during the warm (cold) phase of ENSO (Figure 8 (a, b)). In contrast, a higher (lower) GP surface is visible all over India during the warm (cold) phase, which is an indication of an increase (decrease) in the convective activity during the respective phases. By considering the anomalous circulation at 200 hPa level, an anomalous westerly (easterly) wind is prevalent over entire India during warm (cold) periods ( Figure 8 (a, b)). The upper-level wind pattern and variability in the GPH together indicate the southward extension of WD 170 during ENSO's warm phase. The sharp increase (decrease) of SH lies precisely over the region of the maximum undulation of GPH during the warm (cold) phase (Figure 7 (g, h)). This suggests that ENSO indirectly influences the LFR over India during the post-monsoon season by modulating WDs' path.

Conclusion
In this study, we have discussed the influence of ENSO on LFR during pre-monsoon, monsoon, and post-monsoon seasons 175 over India. Regardless of ENSO phases, the LFR is peaking at the time of pre-monsoon season over NEI and SPI. However, the NNWI exhibits a peak LFR during the monsoon season. The LFR is increased (decreased) over NEI and SPI during the warm (cold) phase of ENSO, and anomalies of the charge generating hydrometeors show a similar kind of swing. The entire years under the cold (warm) phase during the pre-monsoon season taken in this study is characterized by a decrease (increase) of LFR over NEI (SPI), which firmly indicates that the cold phase suppresses the LFR over NEI, and the warm phase enhance