Synergic impact of Aerosols and Humidity on Lightning Activity: Inference from Global Study

doi:10.21203/rs.3.rs-4861359/v1

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Synergic impact of Aerosols and Humidity on Lightning Activity: Inference from Global Study

https://doi.org/10.21203/rs.3.rs-4861359/v1

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The study analysed the impact of aerosol (represented by aerosol optical depth, AOD) and relative humidity (RH) on lightning activities (LA) for distinct five locations around the world: South Africa (R1, 5⁰N to -1⁰S, 9⁰E to 18⁰E), North-western South America (R2, 2⁰N to 5⁰S, -77⁰W to -67⁰W), Indonesia (R3, 10⁰N to 17.5⁰N, 100⁰E to 109⁰E), South America (R4, 31⁰S to 21⁰S, -61⁰W to -53⁰W) and North America (R5, 29⁰N to 34⁰N, -96⁰W to -81⁰W). Based on the study, it was found that the LA is not uniformly associated with AOD or RH individually, rather their synergic impact defines the LA. Results reveal that the association between RH and LA is weaker when AOD is high, such as for regions R1 and R3, whereas it was substantially intense when RH dominates (regions R4 and R5). Based on the study, it was concluded that the humidity per aerosol is critical in lightning formation and is more effective in assessment of the LA than aerosol or humidity alone.

Aerosol Optical Depth

lightning flash density

relative humidity

nonlinear relation

Lightning describes the properties of aerosol-associated clouds (Waner and Twomey 1967; Twomey 1974; Twomey 1977; Radke et al., 1989; Kaufman and Fraser 1997; Ackerman et al., 2000; Chameides et al., 2002; Bre´on et al., 2002; Feingold et al., 2003; Feingold et al., 2005; Spichtinger and Cziczo 2008; Lal et al., 2013 and 2018). High aerosol concentrations increase the cloud droplets numbers with decreased size (Gunn and Phillips 1957; Twomey 1977; Bre´on et al., 2002; Feingold et al., 2003, Lal et al., 2013). Smaller droplets have less efficiency to become raindrops, resulting in rainfall inhibition, enhancement in clouds holding liquid water time, cloud lifetime, and total cloud coverage, etc. (Albrecht 1989; Feingold et al., 2001; Koren et al., 2005, 2010; Kaufman et al., 2005; Loeb and Schuster 2008; Yuan et al., 2011; Small et al., 2011; Wang et al., 2013). Also, smaller cloud droplets reach high altitude (mixed-phase region) and increase the altitude of supercooled water containing ice-based clouds (Jayaratne et al., 1983; Saunders et al., 1991; Takahashi 1978). Ice particle are fundamental element for the cloud electrification (Lal et al., 2014: Lal and Pawar 2009). Thus, aerosol-associated clouds produce lightning (LA) (Waner and Twomey 1967; Twomey 1974; Twomey 1977; Radke et al., 1989; Kaufman and Fraser 1997; Ackerman et al., 2000; Chameides et al., 2002; Bre´on et al., 2002; Feingold et al., 2003; Feingold et al., 2005; Spichtinger and Cziczo 2008; Lal et al., 2013 and 2018). In this process, electrified cloud releases its potential to other clouds, to ionosphere, or to the ground.

Lal et al. (2013) examined the role of aerosol in changing cloud base height and reported that increased aerosol reduces the low-level cloud cover (LCC) and enhances high-level cloud cover (HCC). They have also reported an enhancement in the convective strength over high aerosol regions. It suggests that aerosols are one of the prime elements in the regulation of convection, cloud deepness, strong updraft, cloud ice and cloud hails (Andreae et al., 2004; Wang 2005; Koren et al., 2005; Zhang et al., 2007; Rosenfeld et al., 2008; Wang et al., 2011; Peng et al., 2016). A positive correlation exists between updraft velocity and cloud ice with LA (Workman and Reynolds 1949; Williams and Lhermitte 1983; Dye et al., 1989; Carey and Rutledge 1996; Rutledge et al., 1992; Petersen et al., 1996, 1999; Blyth et al., 2001; Lal and Pawar 2009; Lal et al., 2014). Aerosols are prime driver in varying lightning frequency over land and ocean (Zipser 1994; Williams and Stanfill 2002) along with thermodynamic convection (Williams and Stanfill 2002; Yuan et al., 2011, 2012), and play crucial roles in determining the charge polarity of cloud apart from atmospheric temperature, liquid water content, condensation, evaporation and sublimation (Williams et al., 1991; Saunders et al., 2006). Contrarily, unfavourable conditions for lightning, such as enhanced precipitation (Khain et al., 2005; Lynn et al., 2005; Kawamoto 2006; Phillips et al., 2007), decreased cloud liquid water path (CLWP) (Matsui et al., 2006) and many more have been reported over high aerosol area. Lal et al. (2018) suggested that lightning increases with increasing aerosol at some instant, and then it decreases. Jnanesh et al. (2022) investigated a non-linear correlation between lightning and aerosol.

Mid-altitude level relative humidity along with lifting condensation level (LCL) and equilibrium level (EL) are other factors that influence lightning formation (Lal et al., 2024). Low height LCL and high concentrated relative humidity increases lightning. Lal et al. (2018) investigated how the local atmospheres influence lightning generation. They have found a rising force when two separate air streams, one is cold and moist and the other one is dry and hot, coincide or flow together (Met office version-1 2007, http://cedadocs.badc.rl.ac.uk/253/1/factsheet01.pdf), with significant lightning. They extended his findings to the Tibetan plateau and showed different lightning frequency associated with the nature of ground winds (Lal et al., 2022). In addition, land surface homogeneities, mountain valley-plateau wind, thermally driven wind and soil type among other factors (Orville 1965a, b; Raymond and Wilkening 1980; Holroyd 1982; Klitch et al., 1985; Toth and Johnson 1985), all contribute to lightning formation. It reveals that lightning formation mechanism is very complicated, especially its link with aerosols.

Study considered five places, such as (i) R1 (South Africa: Lat: 5⁰N to -1⁰S, Long: 9⁰E to 18⁰E) (ii) R2 (North-western South America: Lat: -5⁰S to 2⁰N, Long: -77⁰W to -67⁰W) (iii) R3 (Indonesia: Lat:10⁰N to 17.5⁰N, Long: 100⁰E to 109⁰E), (iv) R4 (South America: Lat: -31⁰S to -21⁰S, Long: -61⁰W to -53⁰W) and (v) R5 (North America: Lat: 29⁰N to 34⁰N, Long: -96⁰W to -81⁰W), across the globe to reinvestigate the link between aerosol and lightning at various humidity (Fig. 1a). The considered locations are homogeneous in aerosol and lightning concentrations; however, their concentrations are inhomogeneous from region to region (Fig. 1b).

The average aerosol concentration and lightning frequency over the considered regions from 2005 to 2014 are shown in Fig. 1b. Region R1 shows high aerosol optical depth (AOD, ~ 0.46), and LA (~ 4.20×10^− 4 lightning/km2/day) (Albrecht et al., 2016; Finney et al., 2020). High aerosol over the region is due to massive local anthropogenic activities, biomass burning from central and southern Africa and dust transportation from nearby Sahara and Sahel desert (Mari et al., 2008; Menut et al., 2018; Haslett et al., 2019; Marticorena and Bergametti 1996). The aerosol is also high in the region R2 (AOD: 0.32) and R3 (AOD: 0.38), but marginally less than R1 region. The causes of the aerosol in R2 are biomass burning (Castellanos et al., 2015), vehicles emissions (Cuellar et al., 2016; Zárate et al., 2007), and industrial-agricultural activities (Kumar et al., 2016; Reddington et al., 2015; Rojas et al., 2015; Fajardo and Rojas 2012), however, forest fires, crops burning, agricultural residues burning, and vehicle exhaust are the cause of R3 region (Suriyawong et al., 2023). Comparatively less lightning as per declined aerosol concentration is seen in the regions R2 and R3. Regions R4 (AOD: 0.20) and R5 (AOD: 0.22) are significantly less aerosol loading and high lightning (~ 4.20×10^− 4 lightning/km²/day and ~ 1.78×10^− 4 lightning /km²/day, respectively) zone. At first glance, it reveals that lightning follows the aerosol across the regions R1, R2, and R3; whereas it is extremely difficult to say for regions R4 and R5 (Fig. 1b and Table.1).

Table.1

Regions	AOD	LA
R1	0.45	4.20×10^− 4
R2	0.32	6.39×10^− 5
R3	0.37	1.72×10^− 4
R4	0.20	3.14×10^− 4
R5	0.22	1.78×10^− 4

In the study LA, relative humidity, AOD and surface wind data have been obtained from a lightning imaginary sensor (LIS), Atmospheric infrared sounder (AIRS), Moderate Resolution Imaging Spectroradiometer (MODIS) and ERA5 reanalysis, respectively. Lightning imaginary sensor (LIS) detects total lightning distribution and its variability in tropical and subtropical regions using a footprint size of 3.9 km (nadir) × 5.4 km (limb) and field view 550×550 km. The detection efficiency of the LIS sensor is nearly 90% (Christian et al., 1999). The study collected daily LA data from all 16 ascending and descending orbits of the Total Rainfall Monitoring Mission (TRMM) satellite that encapsulate the LIS, each with a spatial resolution of 550×550 km. The data that fell into our domain region was then isolated and used in the study. The LIS-TRMM LA data is available at https://ghrc.nsstc.nasa.gov/pub/lis/orbit_files/data/science/.

Atmospheric infrared sounder (AIRS) has been used to retrieve relative humidity (RH) data of grid resolution 1⁰×1⁰, since 2002. This instrument is on board NASA’s Aqua satellite and provides three-dimensional (3D) measurements of temperature, water vapor, trace gases, and surface and cloud properties through the atmospheric column. AOD was retrieved from MODIS’s MYD08_D3 V6.1 sensor, Level 3, with grid resolution 1⁰×1⁰. MODIS is a key instrument for viewing the entire Earth’s surface every 1–2 days, acquiring data from 36 spectral bands. Wind data was obtained from ERA5 reanalysis, with a resolution 0.25⁰×0.25⁰. ERA5 refers to the Fifth Generation of the European Centre for Medium-Range Weather Forecasts Reanalysis project and utilises the data from various sources, such as satellites, weather stations, and ocean buoys (http://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc). The aforesaid data were considered only when days of lightning occurred.

AOD data ranging from less than 0.2 to 2.0 are grouped into 13 bins with a bin size of 0.1. The AOD of each bin is then added to obtain the mean AOD of the respective bin. Lightning and RH corresponding to the AOD of each bin is similarly added and the mean LA as well as RH for each bin has been obtained.

Figure 2 shows the monthly variation of AOD and lightning over the study regions. For region R1 (South Africa), aerosol concentration decreased from February (AOD: 0.59) till May (AOD: 0.33), with January being almost equal to February (AOD: ~0.56). AOD started increasing in June (AOD: 0.67), followed by a decrease till October (AOD: ~ 0.26), and an increase till December (AOD: 0.51). For this polluted region, R1, LA increased from January (~ 0.71×10^− 5 lightning/km²/day) till March (~ 1.82×10^− 4 lightning/km²/day), followed by a decrease for July and August (~ 0.42×10^− 5 lightning/km²/day). The LA, however, increased in November (~ 1.27×10^− 4 lightning/km²/day) and then marginally decreased in December (~ 0.74×10^− 5 lightning/km²/day) over the region.

In region R2, (NW South America), AOD increased from January (~ 0.44) to May (~ 0.55) and then decreased to about ~ 0.29 in October, followed by an increase till December (~ 0.37). For this region, LA decreased from January (~ 0.09×10^− 6 lightning/km²/day) to May (~ 0.028×10^− 4 lightning/km²/day) and follows the reverse trend of aerosol. The LA increased to ~ 0.3×10^− 5 lightning/km²/day in September, and then decreased till December (~ 0.1×10^− 5 lightning/km²/day). For this region, generally opposite trend was noticed between AOD and lightning.

In the humid region of Indonesia (R3), AOD increased from January (~ 0.30) to March (~ 0.59), followed by a decrease in June-July (~ 0.30), an increase in October (~ 0.40), and a decrease in November-December (~ 0.24). Lightning over Indonesia increased from January (~ 0.01×10^− 7 lightning/km²/day) to May (~ 1.12×10^− 4 lightning/km²/day) and decreased during December (~ 0.03×10^− 6 lightning/km²/day) with a slightly increase in August and September (~ 0.6×10^− 5 lightning/km²/day). Like region R2, an opposite relationship is also noticed between AOD and lightning over this region (R3).

In the low aerosol loading region, R4 (South America), AOD decreased from January (~ 0.14) to July (~ 0.11), with marginal augmentation in June (~ 0.13), followed by an increase in September (~ 0.34) and a decrease in December (~ 0.15). For this region, the LA decreased from January (9.52×10^− 5 lightning/km²/day) to June-July (5.21×10^− 5 lightning/km²/day) and followed the decreasing trend of AOD. The LA increased in October (1.45×10^− 4 lightning/km²/day) and decreased in December (1.22×10^− 4 lightning/km²/day).

For region R5 (North America), AOD increased from January (~ 0.10) till August (~ 0.32) and then steeply decreased till October (0.12) and mildly decreased till December (~ 0.10). The LA increased from January (0.27×10^− 5 lightning/km²/day) to July (2.48×10^− 4 lightning/km²/day), and then it decreased in December (0.21×10^− 5 lightning/km²/day). A positive correlation was revealed between AOD and LA in this region.

Figure 3 depicts the annual variation in AOD and LA over the region. Figure shows that aerosol continued to increase from 2005 to 2014 (r = 0.62, at a significant level of more than 95%) in region R1, however, it decreased in region R2, R4, and R5 (r = -0.64, r = -0.39, and r = -0.74, respectively, at a significant level more than 95%), and for region R3, aerosol remained uniform (r = − 0.12, at a significant level of more than 95%) during 2005 to 2014. Annual LA over the region is almost consistent for all the regions, R1 to R5 (r = − 0.03, r = 0.13, r = 0.03, r = 0.06, and r = 0.17, respectively, at a significant level of more than 95%).

The LA versus AOD and relative humidity are shown in Fig. 4. For R1, LA was about 3.75×10^− 4 lightning/km²/day when AOD was around 0.16, and it increased to nearly 4.51×10^− 4 lightning/km²/day for AOD about 0.25. The LA decreased (4.00×10^− 4 lightning/km²/day) for 0.35 AOD, increased (4.64×10^− 4 lightning/km²/day) for 0.45 AOD, and decreased again to 3.95×10^− 4 lightning/km²/day for 0.55 AOD. The LA continued to decrease from 4.84×10^− 4 to 3.84×10^− 4 lightning/km²/day when AOD increased from 0.63 to 1.04 and augmented slightly at AOD 1.34 (4.13×10^− 4 lightning/km²/day). A positive correlation (r = 0.19, at a significant level of more than 95%) has been seen between relative humidity and LA (Fig. 4R1c).

In region R2, LA decreased from 6.32×10^− 5 lightning/km²/day to 5.91×10^− 5 lightning/km²/day when AOD increased from 0.15 to 0.33 (Fig. 4R2a). The LA increased (7.17×10^− 5 lightning/km2/day), decreased (6.64×10^− 5 lightning/km2/day) and then again increased to 1.20×10^− 4 lightning/km2/day at AOD 0.44, 0.55, and 0.63, respectively. The LA dropped to 2.87×10^− 5 lightning/km²/day at AOD 0.75 and augmented to 1.82×10^− 4 lightning/km²/day at AOD 1.02. It further decreased to 3.48×10^− 4 lightning/km²/day (at AOD 1.26) and to 3.37×10^− 5 lightning/km²/day (at AOD 2.21). For this region R2, a highly negative correlation (r= -0.86, at a significant level of more than 95%) has been observed between relative humidity and LA (Fig. 4R2c).

In region R3, LA was about 1.54×10^− 4 lightning/km²/day at AOD 0.15 and increased marginally to 1.87×10^− 4 lightning/km²/day at AOD 0.34. It decreased to 1.19×10^− 4 lightning/km²/day at AOD 0.83 and to 8.06×10^− 5 lightning/km²/day at AOD 2.47, followed by increased lightning to 2.01×10^− 4 lightning/km²/day and 1.68 ×10^− 4 lightning/km²/day at AOD 0.75 and 0.95, respectively. The correlation between relative humidity and LA was almost non-existent (r = 0.03, at a significant level of more than 95%).

In region R4, LA increased from 3.15×10^− 4 lightning/km²/day at AOD 0.12 to 4.36×10^− 4 lightning/km²/day at AOD 0.53. It decreased to 1.92×10^− 4 lightning/km²/day at AOD 1.02 and then increased to 7.05×10^− 4 lightning/km²/day at AOD 1.27. The LA retained almost the same density at higher AOD. A negative correlation between LA and relative humidity (r= -0.56, at a significant level of more than 95%) has been observed for R4 (Fig. 4R4a-c).

For region R5, LA was 1.16×10^− 4 lightning/km²/day at AOD 0.13 and increased to 2.93×10^− 4 lightning/km²/day at AOD 0.53. The LA decreased to 1.92×10^− 5 lightning/km²/day at AOD 0.70 and augmented to 5.54×10^− 4 lightning/km²/day at AOD 0.82. An opposite relationship between relative humidity and LA has been seen over the region R5. A negative correlation between relative humidity and lightning (r= -0.57, at a significant level of more than 95%) has also been observed.

The relationship between aerosol concentration and LA at various relative humidity is underway to understand. Lal et al. (2018) has suggested that LA increases with increasing aerosol at some instant and decreases thereafter. Working on two specific regions of India, Jnanesh et al. (2022) claim that lightning is non-linear but synergistically related to aerosol and atmospheric humidity. They discovered a substantial negative correlation between lightning and relative humidity across the locations.

The current study considered five regions around the world to find the consistency of relationship as shown by Jnanesh et al. (2022). These regions are specifically chosen on the basis of their climatic conditions, geography, wide distribution of aerosol on the global map and availability of LA, as (i) R1 (South Africa: Lat: 5⁰N to -1⁰S, Long: 9⁰E to 18⁰E) (ii) R2 (North-western South America: Lat: -5⁰S to 2⁰N, Long: -77⁰W to -67⁰W) (iii) R3 (Indonesia: Lat:10⁰N to 17.5⁰N, Long: 100⁰E to 109⁰E) (iv) R4 (South America: Lat: -31⁰S to -21⁰S, Long: -61⁰W to -53⁰W) and (v) R5 (North America: Lat: 29⁰N to 34⁰N, Long: -96⁰W to -81⁰W). In these regions, LA is not uniformly associated with aerosol. However, negative correlation between relative humidity and lightning has only been seen for three regions, namely, R2, R4 and R5. On the contrary, no significant correlation was found between relative humidity and LA in regions R1 and R3, however, they possess higher contents of aerosols, with AOD of around 0.46 and 0.38, respectively, compared to R2 (AOD: 0.33), R4 (AOD: 0.20), and R5 (AOD: 0.22). In the generation of clouds, whether it rain or carry LA, moisture, along with aerosols, is required, and their ratio (aerosol/moisture) determines the nature of clouds. It is observed that the moisture over R1 and R3 was quite significant, i.e., ~ 65% and ~ 69%, respectively (Fig. 5a), along with aerosol, whereas moisture per AOD (an integrated extinction coefficient over a unit cross section of vertical column aerosol) is quite low (Fig. 5b). Results show that aerosol dominated over moisture in R1 and R3, leading in a reduced association between relative humidity and lightning. As relative humidity improves to aerosol in the region R2, the relationship between relative humidity and lightning emerges (r= -0.86, at a significant more than 95%), and LA density decreased accordingly (Fig. 5b). It is quite confirmed that dominance of one ingredient over another diminishes the role of the remaining element in the ratio.

The LA is non-linearly associated with aerosol and negatively correlated with relative humidity in regions R4 and R5 as Jnanesh et al. (2022) reported. It is noted that the AOD and relative humidity are less in R4 and R5 (Fig. 1b and 5a), and relative humidity per AOD is high (Fig. 5b). Results reveal that humidity dominates over aerosol in these regions, which is a finding opposite to the regions R1 and R3. As per reported by Lal et al. (2013, 2018), when humidity dominates over aerosol, it diminishes the convective strength and lightning occurrence, despite, high LA has been seen over the region.

To further investigate the cause, the study examined the winds nature at the time of significant LA. The winds on 8th October 2005, when LA was quite significant (~ 379 strikes: 3.82×10^− 4 lightning/km²/day), were analysed for region R4. To prevent undue loading on the text, only one day's wind analysis is provided here. It has been observed that negative omega (vertical pressure velocity), i.e., ascending force, with significant lightning occurs when two different winds interact with each other. On October 8, 2005, Northerly winds interacted with southerly winds at 08.00UTC, which run diagonally from latitude 21⁰ S and longitude 61⁰W to latitude 28⁰ S and longitude 53⁰W (assigned as elliptical circle 1 in Fig. 6). Negative omega and huge lightning can be seen over the region. The finding shows that winds are critical to lightning generation in the region. Another similar event of the wind’s convergence was recorded with massive lightning over the north-east at 16.00-17.00UTC in the region R4 (elliptical-circle 2 Fig. 6), strengthen the winds role in lightning generation. LIS-TRMM passes only two times over the region (one ascending at about 08.30 UTC, and one descending at about 16.14UTC, Fig. 8a and b).

On October 8, 2005, relative humidity and AOD were ~ 60% and ~ 0.30, respectively, resulting in a ratio of roughly 200, equivalent to the yearly ratio of relative humidity and AOD across region R3 (~ 182) (Fig. 5b). However, on October 8, 2005, there was three times more lightning (3.82×10^− 4 lightning/km2/day) than in the region R3 (1.22×10 − 4 lightning/km2). Results reveal that surface winds were the predominant cause of significant lightning in region R4. Observing less lightning in region R5 while relative humidity per AOD was as high as in R4, further supporting that the excess lightning in region R4 was due to the surface winds.

In the study relationship between aerosol, lightning, and relative humidity has been investigated for 5 different locations around the globe. Results revealed the following outcome:

Annually LA is almost stable over entire regions.
Non-linear relationship between lightning and aerosol across the globe
Negative correlation between relative humidity and lightning for R2 (North-western South America), R4 (South America), R5 (North America).
No significant correlation between relative humidity and lightning in high loaded aerosol area R1 (South Africa) and R3 (Indonesia)
Significant correlation between relative humidity and lightning in humidity dominated areas R2 (North-western South America), R4 (South America) and R5 (North America)
The ratio between relative humidity and aerosol is high in region R4 (South America) and R5 (North America), even though, aerosol and relative humidity significantly low.
Ratio of aerosol to relative humidity is critical in lightning formation.

Results reveal that lightning activities are non-linearly associated with aerosol, whereas relative humidity is not necessarily negatively associated with lightning. In high aerosol-loaded regions, the relationship between relative humidity and lightning is less, and it is high in low-loaded aerosol areas. High lightning activity occurs in aerosol-dominated areas. Humidity per aerosol is more effective in the assessment of lightning, rather than aerosol or humidity alone. In the formation of lightning, surface winds play critical role over Southern American region R4.

Acknowledgments

Author also thankful to Director IITM for providing all necessary facility required in the study. Author MKS is thankful to ISRO-ARFI for support. Authors are thankful to Giovanni (nasa.gov) for providing free data.

Ethical Approval-

The manuscript is not submitted to more than one journal for simultaneous consideration. Submitted work is an original and not published elsewhere in any form or language (partially or in full), and used data is original.

Consent to Participate ----Not applicable.

Consent to Publish -------- Not applicable.

Authors Contributions

Authors DML and MKS conceptualized the study, performed the analysis, and prepared the manuscript. Author NU cured the data and assisted in the data analysis. All authors read and approved the final manuscript. Origin 8.5 software has used for the analyses.

Funding

Although IITM is funded by Ministry of Earth Science, Government of India, but as an individual, the author does not get any fund.

Competing Interests

The authors declare that they have no competing interests in this section.

Availability of data and materials-

Study used lightning data from the lightning imaginary sensor (LIS) from (https://ghrc.nsstc.nasa.gov/pub/lis/orbit_files/data/science, Aerosol Optical Depth (AOD) from (https://giovanni.gsfc.nasa.gov/giovanni/#service=ArAvTs&starttime=2003-01-01T00:00:00Z&endtime=2014-12-31T23:59:59Z&bbox=88,22,96,30&data=AIRX3STM_006_RelHumid_A(z%3D925)%2CAIR, Relative humidity from Atmospheric infrared sounder (AIRS), Giovanni platform https://giovanni.gsfc.nasa.gov/giovanni/#service=TmAvMp&starttime=&endtime=&variableFacets=dataProductPlatformInstrument%3AAIRS%3B&dataKeyword=Relative%20Humidity, Wind data from ERA5 (http:// apps. ecmwf.int/ datasets/ data/interim-full-daily/levtype=sfc)

Author information

Affiliations

Indian Institute of Tropical Meteorology, Pune, India
Department of Geophysics, Banaras Hindu University, Varanasi, India

Corresponding author

Correspondence to

(a) D. M. Lal.

(i) [email protected], [email protected]

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Synergic impact of Aerosols and Humidity on Lightning Activity: Inference from Global Study

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Introduction

Aerosol and Lightning Climatology in the considered regions

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