Atmospheric Research 160 (2015) 82–90

Contents lists available at ScienceDirect

Atmospheric Research

j ourna l homepage: www.e lsev ie r .com/ locate /atmos

The impact of the Western Ghats on lightning activity on the

western coast of India

A.K. Kamra a,⁎, A.A. Nair b,1

a Indian Institute of Tropical Meteorology, Dr. Homi Bhabha Road, Pune 411 008, Indiab Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pune 411 008, India

a r t i c l e i n f o a b s t r a c t

nd thea from

Article history:Received 13 June 2014

5

Lightning

⁎ Corresponding author at: Indian Institute411008, India. Tel.: +91 20 2590 4281.

E-mail addresses: kamra@tropmet.res.in (Anairarshad@students.iiserpune.ac.in (A.A. Nair)

1 Tel.: +91 9762308328.

http://dx.doi.org/10.1016/j.atmosres.2015.03.00169-8095/© 2015 Elsevier B.V. All rights rese

The effect of theWestern Ghats on the lightning activity across the west coast of India aroucoastal metropolitan city of Mumbai during the 1998–2012 period is investigated using dat

RMM)ven inormednsoon,of the

Received in revised form 17 March 201Accepted 17 March 2015Available online 24 March 2015

Keywords:

rabiandrawalnsoonfoundsectormaller

served.

the Lightning Imaging Sensor (LIS) onboard the Tropical Rainfall Measuring Mission (Tsatellite. A land–sea contrast of an order of magnitude in the lightning activity is observed ea small area across thewestern coast of India. The shape of a zone of high lightning activity falmost parallel to the Western Ghats during the onset and withdrawal phases of mostrongly suggests the effect of the Western Ghats in its formation. Seasonal variationlightning activity in this area and also in each of its four equal sectors (two each over the ASea and over land) is bi-annual with one peak each in the onset (May/June) and withmonths (September/October) of monsoon and a sharp dip to very low values during themomonths (July/August) of maximum seasonal rainfall. The lightning activity in each sector isto increase over the 1998–2012 period. However, the increase in lightning activity over thecontaining Mumbai is found to be greater during the pre- and post-monsoon periods and sduring the monsoon period as compared to an identical sector immediately south of it.

© 2015 Elsevier B.V. All rights re

Atmospheric electricityClimate change variabilityTropical meteorologyOcean/Atmosphere interactions

1. Introduction

poraof thouthoccurhed ir thg thnentacitielmos

parallel to the west coast of India modulates the southwestmonsoon airflow, which approaches the mountain-range just

recip-gradi-cloudsis toin antellite

uencewind2002;9; Kar. Such

Mountain ranges are known to affect the spatio-temdistribution of precipitation and the spatial variabilitydiurnal cycle of convective activity. During the Indian swest monsoon season (June–September), convectionfrequently at the west coast, where low-level flow enricmoisture and marine aerosols, during its passage oveArabian Sea, flows over the subcontinent. After crossincoastline, the flow is further enriched by the contiaerosols and anthropogenic aerosols released by bigsuch as Mumbai and Pune. The Western Ghats running a

erosolsationplets,louds,

of Tropical Meteorology, Pun

.K. Kamra),.

06rved.

le-sneelst

perpendicular to it. Interactions of convective activity, pitation, aerosols, and terrain (landmass and altitudinalents) are crucial to the occurrence of lightning in theformed over such regions. The purpose of this studyinvestigate the spatio-temporal distributions of lightningarea across the west coast of India with the help of sadata.

Several studies made in the last decade report the inflof large cities on the lightning activity over and/or downof these urban areas (Orville et al., 2001; Steiger et al.,Naccarato et al., 2003; Pinto et al., 2004; Farias et al., 200et al., 2009; Lal and Pawar, 2011; Niyogi et al., 2011)influence can result from the heat island concept or the aconcept in which the enhanced number of cloud condennuclei causes more numerous but smaller water drowhich transportmorewater to themixed-phase level in c

e

where they can participate in the electrification process(Williams et al., 2002). The enhanced aerosol particle concen-

in thownteige2012lasheet alnerie

ed tmpletnin, ands (Xureporlectivopicsposedllutedagatute trmedoduco thsuch

o thBlyth

nce octivited bainfa

Measuring Mission (TRMM) satellite for the 1998–2012 periodis used for this study.

′E), B9°38′west2°50′0 km. 1, isHG islar tog theted iny overer theg theesternrier ofkm in

ion ofia.gov.tisticsmajorries tootherGhats,ttp://(~3.7aha-

tor 1.

83A.K. Kamra, A.A. Nair / Atmospheric Research 160 (2015) 82–90

tration over urban areas has also been proposed to explaenhanced cloud-to-ground lightning flashes over and dwind of urban and industrial areas (Orville et al., 2001; Set al., 2002; Steiger and Orville, 2003; Yuan et al., 2011,and the enhancement in the positive cloud-to-ground fassociated with forest fires (Lyons et al., 1998; Murray2000; Lang and Rutledge, 2006) and over oil refi(Changnon, 1981).

Factors other than these have also been identifiinfluence the lightning activity in thunderclouds. For exarecent investigations reveal the dependence of lighactivity on regime variations of continental, monsoonoceanic deep convection over the tropics. These studieet al., 2010; Liu et al., 2012; Xu and Zipser, 2012)relationships between lightning flash rates and radar refity structures in thunderstorms over the tropics and subtr

Recently, Bhalwankar and Kamra (2013) have prothat the enhanced distortion and break-up of the podrops and their characteristics to trigger and propdischarge in lower electric field can significantly contribthe enhancement of lightning activity in the clouds foover big cities. Emissions from cities are also likely to intra larger number of freezing nuclei and thus lead tformation of more ice crystals in clouds formed overurban areas, which is generally considered vital telectrification processes in clouds (Dye et al., 1988;et al., 2001).

Here, we study the land–ocean contrast and the influethe Western Ghats on the distribution of lightning aacross the west coast of India. The lightning data collectthe Lightning Imaging Sensor (LIS) aboard the Tropical R

Fig. 1. The topography of the area of investigation ABCD oriented in the smetropolitan city ofMumbai is on themidway of EO. Pune is another major citover the ocean.

e-r)s.,s

o,g

t-.

eo

ee

e

fyyll

2. Area of investigation and its climatology

An area, ABCD with coordinates A (19°11′N 68°54(20°26′N76°26′E), C (16°54′N77°01′E), andD (15°40′N6E), oriented in the southwest–northeast direction on thecoast of India and including the city ofMumbai (18°59′N7E), is selected for investigation. This area spanning 80× 400 km, illustrated on a topographical map in Figdivided into four equal area sectors, 1, 2, 3, and 4 such thatin southwest–northeast direction and almost perpendicuthe western coastline, and EF is approximately alonwestern coastline of India. The city of Mumbai is locaSector 1 on themid-way of EO. Sectors 2 and 3 lie entirelthe Arabian Sea and Sectors 1 and 4 are almost entirely ovcontinent. The Western Ghats, a mountain range alonwestern side of India, runs almost parallel to the wcoastline at a distance of 30–50 km and provides a barapproximately uniform height with peaks as high as ~1this area.

The metropolitan city of Mumbai, with a populat~12.7 million (Census of India at http://www.censusindin, 2011), ~1.8 million automobiles (Motor Transport Staof Maharashtra at http://mahatranscom.in, 2011), ashipyard, an international airport, and some major industits north, is a major source of pollution in this area. Anmoderately big city of Pune on the lee side of theWesternhaving a population of ~4.8 million (Census of India at hwww.censusindia.gov.in, 2011), but a larger numbermillion) of automobiles (Motor Transport Statistics of Mrashtra at http://mahatranscom.in, 2011) also lies in Sec

outhwest–northeast direction. EF is approximately along the west coast of India. They in the area of interest as indicated. Sectors 1 and 4 are over land and Sectors 2 and 3 are

The major climatic feature of the area is the southwestmonsoon, which normally sets-in in the second week of June

. Thrly istureurnef theiare

asonae are4). Iterlieandand 4tivele preOctohav

ii) tha an1 kmd thmos

ts. Thareas- an

3. Data-set

tningsuringorbited toauticsspacehe LISinter-tningwithedingof 5–000),73 ±er, itscasescur inay beidered

ovidesUTC),s, andunder.limate

84 A.K. Kamra, A.A. Nair / Atmospheric Research 160 (2015) 82–90

and withdraws at the end of September in this areaprevailing winds dominantly change to the southwestedirection during the monsoon season (Fig. 2). The moiladen southwesterlies in this season, after their long joover the Indian Ocean and the Arabian Sea, shed most omoisture west of the Western Ghats. As a result, thelocated immediately west of theWestern Ghats gets a serainfall approximately three times more than that of thimmediately east of the Western Ghats (Raghavan, 196the southwest monsoon season, when the southwesstrike the west coast almost perpendicularly, Sectors 2introduce marine/anthropogenic aerosols into Sectors 1respectively. However, these aerosols are not as effectransported to the east of the Western Ghats during thmonsoon (March–April–May) and the post-monsoon (ber–November) seasons, because (i) winds are weak andno preferential direction (Fig. 2) during these seasons, (coastal areaswest of theWestern Ghats experience the seland breeze conditions with a vertical depth of aboutabove mean sea level, and (iii) the westerly airflow antransfer of aerosols in the lower boundary layers, whereof the aerosol content lies, is blocked by theWestern Ghawhole area, inclusive of oceanic and continentalexperiences peak thundercloud activity during the prepost-monsoon seasons (Manohar and Kesarkar, 2003).

Fig. 2. Seasonal winds in winter (DJF), pre-monsoon (MAM), mo

en-yralans3,y--eed

ete,d

Here, we use the lightning data obtained from the LighImaging Sensor (LIS) aboard the Tropical Rainfall MeaMission (TRMM) satellite, launched into the low-Earthwith an altitude of 350 km, and subsequently rais402.5 km, and an inclination of 35° by the National Aeronand Space Administration (NASA) and the Japan AeroExploration Agency (JAXA) on November 27, 1997. Tdetects and locates cloud-to-ground, intra-cloud, andcloud lightning in the tropical regions by identifying lighfrom the associated changes in cloud brightness, evensunlit clouds in the background. It has a field of view exce580 × 580 km2 at the cloud top, a storm-scale resolution10 km, a temporal resolution of 2 ms (Christian et al., 2and a flash detection efficiency of 93 ± 4% at night and11% during daytime (Boccippio et al., 2002). Howevdetection efficiency may be slightly an underestimate inof intense convective systems where the flashes that ocrapid succession illuminating the same cloud region mgrouped together when observed by the LIS and be consas the same flash.

The LIS product, LIS Space Time Domain Search, prindividual flash information indicating flash time (latitude and longitude, radiance, duration, groups, eventthe orbit-ID. The LIS data was obtained from http://thmsfc.nasa.gov/, hosted by the Global Hydrology and C

nsoon (JJAS), and post-monsoon (ON) seasons in the area of investigation.

Center (GHCC). During the 15-year period from January 1998to December 2012, the total area ABCD exhibited a total of

44 in

ainedodaatheDatOa

ente.orn

in thity i2 andiculatnins andnthlmosre thtivelne o5 th0 kmof thent oghouimumJune

and withdrawal (September/October) months of monsoon,when the accumulation of aerosols west of the Western Ghats

d thetrongis thein thehift inuenceity ofg thentain

creasethe

onsets. The50 kmase inay bemmern thetober,o theof the

of theg thecounto Junennual). Thember

85A.K. Kamra, A.A. Nair / Atmospheric Research 160 (2015) 82–90

19,758 flashes — 8483 in Sector 1, 1222 in Sector 2, 12Sector 3, and 8809 in Sector 4.

Wind data (10mU and Vwind component) was obtfrom http://data-portal.ecmwf.int/data/d/interim_mhosted by the European Centre for Medium-Range WeForecasts (ECMWF). Global 30 Arc-Second ElevationSet (GTOPO30), for the topography, was obtained fromRidge National Laboratory Distributed Active Archive C(ORNL DAAC) through their website on http://webmapgov/wcsdown/wcsdown.jsp?dg_id=10003_1/.

4. Results

4.1. Spatial distribution of lightning

Fig. 3 shows spatial distribution of lightning activityarea ABCD for the 1998–2012 period. Lightning activcomparativelymuch lower over the oceanic area (Sectors3) than over the land area (Sectors 1 and 4). Of partimportance is the development of a zone of high lighactivity, running almost parallel to the Western Ghatlocated between the coastline and theWestern Ghats. Moevolution of this zone of high lightning activity ispronounced in the months of June and October, which amonths of arrival and withdrawal of monsoon, respec(Fig. 4). To understand the time evolution of this zomaximum lightning activity, we have plotted in Fig.monthly curves of average flash count in each of the 5wide column parallel to the coastline, versus the distancecolumn from the coastline. An ocean to land enhancemlightning activity can be seen to a variable degree, throuthe year. Moreover, the formation of the zone of maxlightning activity is most pronounced during the onset (

Fig. 3. Spatial distribution of lightning in the area ABCD during the 1998–20shown in the background.

/rakrl.

es

rg

yteyfe

eft

)

is maximum as explained in Section 2. The shape anlocation of this zone of peak lightning activity suggest a srole of the Western Ghats in its formation. Noticeableeastward shift of the zone of maximum lightning activitynorthern part of Sector 1, where this zone follows the sthe Western Ghats' position. The Western Ghats can inflthe lightning activity by modifying the convective activthe region due to orographic convection and by affectinseasonal distribution of aerosols on either side of themourange.

Another important feature depicted in Fig. 5 is the inin lightning activity at a distance of 250–400 km fromcoastline in the pre-monsoon (March–May), monsoon(June), and post-monsoon (September–October) monthlightning activity also shows a dip at a distance of 100–2from the coastline in the same months. While the increlightning activity of 250–400 km from the coastline massociated with the continental convection during the sumonths of March–June and with the instability iwithdrawal phase of the monsoon during September–Octhe dip in the lightning activity may be related tdownward motion in the atmosphere on the lee sideWestern Ghats.

4.2. Monthly mean flash count

Fig. 6 shows that the variation of the monthly meannumber of lightning flashes over the area ABCD durin1998–2012 period is bi-annual. The monthly mean flash(FC) starts increasing from itsminimum value inwinter tand shows two peaks in the months of June (19% of the amean FC) and September (17% of the annual mean FClightning activity is almost nil in the months of Dece

12 period. Each dot indicates the location of a lightning flash. Topography of the area is

(0.53% of the annualmean FC) and January (0.06% of the annualmean FC). Further, the lightning activity rapidly decreases to

.5% on FC)

when the area receives the maximum rainfall of the monsoonseason.

rawnnnual

Fig. 4. Spatial month-wise distribution of lightning in the area ABCD during the 1998–2012 period. Each dot indicates the location of a lightning flash. Thick solid lineshows the approximate position of Western Ghats in the height range 700–1000 m.

86 A.K. Kamra, A.A. Nair / Atmospheric Research 160 (2015) 82–90

very low values in the peak monsoon months of July (3the annual mean FC) and August (2.1% of the annual mea

f,

The curves of the monthly mean flash count dseparately over each of Sector 1 to 4 also show bi-a

variation (Fig. 7). The following major differences in lightninactivity over the different sectors are noticed:

ceaniatelr th

m thtor 4nnuactor 1flashalueely, oes aresma

(~23%mber ove~14%

(4) Magnitudes of the first and second peaks are approxi-mately equal over the oceanic Sectors 2 and 3. However,

e firstude oftor 4.r thande ofeak in

unt isnd in

ber of1, 2, 3,wn inr thes well–2012area.

Fig. 5. Variation of the monthly number of flashes in each of the 50 km widecolumns, parallel to the coastline, with distance of the column from thecoastline, during the 1998–2012 period.

Fig. 7. Variations of the monthly averaged flash counts in Sectors 1, 2, 3, and 4during the 1998–2012 period. Vertical bars show the standard errors.

87A.K. Kamra, A.A. Nair / Atmospheric Research 160 (2015) 82–90

(1) Values of themonthlymean flash count over the osectors (2 and 3) are, on the average, approximan order of magnitude smaller than those ovecontinental sectors (1 and 4).

(2) The increase in the monthly mean flash count frowinter to pre-monsoon season is steeper in Secwhere it reaches higher peak value (~22% of the amean flash count) in May itself as compared to Sewhere the peak value (~19% of its annual meancount) reaches only in June. The corresponding vfor Sector 2 and 3 are ~33% and ~27%, respectivtheir annual mean flash count in June; these valuhowever, not statistically significant because of thenumber of total flashes in these sectors.

(3) The second peak in themonthlymean flash countof the annual mean flash count) appears in Septeover the continental Sector 1 but only in OctobeSectors 2, 3, and 4where they are ~25%, ~28%, andrespectively, of their annual mean values.

Fig. 6. Variation of the monthly averaged flash count in the area ABCDduring the 1998–2012 period. Vertical bars show the standard errors.

g

cye

e,l,

sf,ll

rr,

on continental sectors, while the magnitude of thpeak is greater in Sector 4 than in Sector 1, magnitthe second peak is greater in Sector 1 than in SecAlso, while the magnitude of first peak is greatethat of the second peak in Sector 4, the magnituthe second peak is greater than that of the first pSector 1.

(5) Over the oceanic sectors, monthly mean flash covery low or almost nil from December to April aJuly and August.

4.3. Annual flash count

Figs. 8 and 9 show the annual variations of the numflashes in thewhole area ABCD and separately in Sectorsand 4, respectively, for the 1998–2012 period. Also shoeach panel of these figures are the regression lines forespective data. Annual flash counts in the whole area, aas in the individual sectors, increased during the 1998period, the increase being as much as ~38% in the whole

Fig. 8. Variation of the annual flash count in the area ABCD for the 1998–2012period. Also shown is the regression line and equation.

Over the continental sectors, the increase in flash count is largerand steeper over Sector 4 (~47%) than over Sector 1 (~8%).

% ans aresma

easinues ienniassiblriodiwinphereO oics isz andtninr, the thpauswarquenin thpth ined i

1 an

f thths or. Wasses4 i

efine

ð1

where N1, N2, N3, and N4 are monthly mean values of flashcount over Sectors 1, 2, 3, and 4, respectively, for the 1998–

angesctor 1ths oflues ofN 1 inSectorrawalng theity ineason.

6. Discussions

inutes, sinceyears,senta-

tors 1m thetning2003;ent, inin theraphicion ofobbs,mentlayas,tning

nentale andnentalraturesmostg the

88 A.K. Kamra, A.A. Nair / Atmospheric Research 160 (2015) 82–90

Corresponding increases in annual flash counts are ~258~132% over Sector 2 and 3, respectively; these valuehowever, not statistically significant because of thenumber of flashes in these sectors.

Figs. 8 and 9, in addition to showing a long-term incrtrend in lightning activity, show its high and low valalternate years. Although the reason for such a bivariability in lightning activity is not known, its polinkage with quasi-biennial oscillation (QBO), a quasi-peoscillation of 24–30 months of the equatorial zonalbetween easterlies and westerlies in the tropical stratosneeds to be examined. Possible influence of the QBlightning production and deep convection in the tropalready indicated by Hernandez (2008) and HernandeSchumacher (2008). Effect of the QBO in modifying lighactivity is not within the scope of this paper. HoweveQBO's role in affecting the factors which can influencoccurrence of lightning in a cloud, such as the tropotemperature, and height (Collimore et al., 2003), the upand downwardmotions in Hadley cell circulation, the frecy of the southwest monsoon cyclonic disturbancesIndian continent (Bhalme, 1972), and aerosol optical detropical regions (Beegum et al., 2009) need to be examidetail.

5. Relative variations of lightning activity over Sectors4 in different seasons

Over the oceanic Sectors 2 and 3, mean values omonthly flash count and their peak values in the monJune and October are approximately equal to each othehave used this fact to get a non-dimensional number tothe difference in lightning activity over Sectors 1 anddifferent seasons. The non-dimensional number, N, is das:

N ¼ N1=N2ð Þ = N4=N3ð Þ

Fig. 9. Variations of the annual flash count in Sectors 1, 2, 3, and 4 during th1998–2012 period. Also shown are the regression lines and equations fodifferent sectors.

d,ll

gnlecd,n

2012 period. Fig. 10 shows themonthly variation of N. Chin N represent the changes in monthly flash count in Sewith respect to those in Sector 4. Values of N for the monNovember toMarch are not plotted in Fig. 10 since the vaN2 and/or N3 in those months are about zero. Values of NMay and October mean that the lightning activity in the1 is more than in Sector 4 at the times of onset and withdof the monsoon. On the other hand, values of N b 1 duriJuly–September period mean that the lightning activSector 1 is less than that in Sector 4 during themonsoon s

geeed-enn

d

efesnd

Þ

In this study, the LIS data is collected only for a fewmeach day during satellite passes over a region. Howeverthe statistical averages are calculated for a period of 15the analyzed variations are likely to be reasonably repretive of the area.

Higher values of the annual mean flash count over Secand 4 as compared to those over Sectors 2 and 3 confirland–ocean contrast of an order of magnitude in lighactivity (Orville and Henderson, 1986; Christian et al.,Ramesh Kumar and Kamra, 2012a). Such an enhancemthis case, may be mainly associated with the differencecontinental and oceanic convections and with the oroglifting of the air mass by the Western Ghats. Accumulataerosols or formation of mountain waves (Wallace and H2006; Ramesh Kumar and Kamra, 2012b) for the developof an arc of high lightning activity in the foothills of Himamay contribute to the formation of the zone of high lighactivity west of the Western Ghats as well.

Monthly variations of flash count over the contisectors show one peak, each in the months of May/JunSeptember/October.While theMay/June peak over contisectors can be attributed to the increasing surface tempefrom January toMay/June, the September/October peak iprobably due to the instability of the atmosphere durin

er

Fig. 10. Monthly variation of the mean values of the non-dimensional numberN (defined in Eq. (1)). Values of N N 1 or b1 show whether the flash count isgreater or smaller over Sector 1 than over Sector 4with respect to Sectors 2 and3, respectively. Values of N from November to March are not plotted for thereasons explained in the text. Vertical bars show the standard errors.

withdrawal phase of themonsoon. The sharp decrease and lowvalues of flash count in July/August may be associated with the

solaasinarth's ma

ues ingationin thesizedwhichn canwhich2008of theededuch

er ther thts arer thses inand 3reaten andg. 10)ls ard andion oity ansoonscopiditiontnin002)ls, the alsrosoln thlity ot thag thss tKhainthu

vity ine thes onsoonols iner inctivitxplainhes inresulher

hwesailinarin

aerosols into Sector 4, but both marine and anthropogenicaerosols into Sector 1. On the other hand, N is greater than 1 in

k andgh ofioned,or theother, mayes in

howsution,f theesternoceanctivitymbai.ctivitynnualar themati-ths of

rea byavingmeanarea

ientistKVPY,ssionsrithmGHCCo thef.int/,ed onk Mr.

d, Y.N.,Atmos.

eries ofeophys.

ing thehys. 94,

., 2001.vil ice59-60,

t of theedicted/dx.doi.

89A.K. Kamra, A.A. Nair / Atmospheric Research 160 (2015) 82–90

cutting-off, by absorption and scattering, of short-waveradiation from reaching the Earth's surface by increcloudiness during monsoon season. Cooling of the Esurface by the rainfall during those peakmonsoonmonthalso contribute to these low values.

Our results of total lightning showing high and low valalternate years in Figs. 8 and 9 suggest a detailed investiof the postulated linkage of QBO and lightning activitytropics. Such a linkage may develop through two hypothmechanisms, i.e. (i) modulation of the tropopause heightmay determine the altitude up to which deep convectiopenetrate and (ii) modulation of cross-tropopause shearmay affect the shearing of cloud tops (Hernandez,Hernandez and Schumacher, 2008). Possible associationbiennial variabilities in AOD and QBO is another factor nto be investigated to understand the possible link of svariability in lightning activity.

Small and almost equal values of annual flash count ovoceanic Sectors 2 and 3 are dramatically enhanced ovcontinental Sectors 1 and 4. However, these enhancemennot equal over Sectors 1 and 4; being larger and faster ovSector 4 than the Sector 1. Moreover, the relative increaflash count over Sectors 1 and 4with respect to Sectors 2respectively, are not equal in different seasons, being gduring the onset and withdrawal phases of the monsoosmaller during the monsoon months of peak rainfall (FiThese observations may possibly be explained if aerosoconsidered as modulator of lighting activity (RosenfelLensky, 1998; Rosenfeld andWoodley, 2001, 2003). Additaerosols can, both, increase or decrease the lightning activexplained below. Southwesterlies in the southwest moseason introducemarine aerosolswhich are rich in hygrocloud condensation nuclei (CCN) into Sectors 1 and 4. Adof these marine aerosols adds to the enhancement of lighactivity over the continental sectors (Williams et al., 2However, in addition to the abundance of marine aerosoanthropogenic aerosols emitted by the city of Mumbai arinducted into Sector 1. The combined concentration of aedue to both, marine and anthropogenic, sources isouthwest monsoon season may increase the availabicloud condensation nuclei in Sector 1 to the extenprevents the growth of cloud droplets from reachincritical size required for the charge separation proceoperate (Rosenfeld and Lensky, 1998; Rosenfeld, 2000;et al., 2001; Rosenfeld and Woodley, 2001, 2003) andreduce the thundercloud electrification and lightning actiSector 1. Thus, the effect of aerosols may be to enhanclightning activity in the onset and withdrawal phasmonsoon and reduce the lightning activity in the momonths of peak rainfall. These opposite effects of aerosdifferent seasons may approximately nullify each othSector 1 when the change in annual values of lightning ais examined over a longer period. Such a hypothesis can ethe observation of almost no change in the number of flasSector 1 over the 1998–2012 period in Fig. 9. Thesupporting the above conclusion is illustrated in Fig. 10, wthe values of N remain less than 1 during the soutmonsoon months of June–September when the prevsouthwesterlies in the area systematically induct only m

rgsy

e

;e

a

eeee

,r

.e

fs

c

g.eosefteo

s

ef

y

tetge

May and October, when the prevailing winds, being weahaving no preferential direction, do not induct enoumarine aerosols into Sectors 1 and 4. It must be cauthowever, that aerosols are certainly not the sole driver fvariability in lightning over Sectors 1 and 4 and thatfactors, such as those discussed in the introductioncontribute or even dominate for causing such changlightning activity.

7. Conclusions

Our analysis of the LIS data for the 1998–2012 period sa strong effect of the Western Ghats on lightning distribespecially during the onset and withdrawal phases omonsoon season, between the coastline and the WGhats. Further, the present analysis confirms a land–contrast of about an order ofmagnitude in the lightning awithin a small area across thewest coast of India nearMuThemonsoon season exerts a strong effect on lightning aover land areas. Lightning activity undergoes a bi-avariation in this area. While the flash count peaks neonset and withdrawal phases of monsoon season, it dracally falls to very low values during the monsoon monmaximum rainfall.

Annual mean value of flash count increases in this a38% during the 1998–2012 period. Over land, the sector hMumbai undergoes only an 8% increase in the annualvalue of flash as compared to an increase of 47% in animmediately south of Mumbai.

Acknowledgments

AKK acknowledges the support under INSA Senior ScProgram. AAN acknowledges the support from IAS SRFP,and IISER Pune. AAN thanks Ms. Kshiti Mishra for discuthat led to the improvement of the data processing algoused in this study. The authors are grateful to the NASAfor LIS data hosted on http://thunder.msfc.nasa.gov/, tECMWF for wind data hosted on http://data-portal.ecmwand to the NASA ORNL DAAC for topography data hosthttp://webmap.ornl.gov/. The authors also wish to thanPenki Ramesh Kumar for his help in drawing diagrams.

References

Beegum, S.N., Moorthy, K.K., Babu, S.S., Reddy, R.R., Gopal, K.R., Ahme2009. Quasi‐biennial oscillations in spectral aerosol optical depth.Sci. Lett. 10 (4), 279–284. http://dx.doi.org/10.1002/asl.243.

Bhalme, H.N., 1972. Trends and quasi-biennial oscillation in the scyclonic disturbances over the Indian region. Indian J. Meteorol. G23, 355–358.

Bhalwankar, R., Kamra, A.K., 2013. Role of drop distortion in enhanclightning activity in clouds formed over cities. J. Atmos. Sol. Terr. P65–70. http://dx.doi.org/10.1016/j.jastp.2012.12.018.

Blyth, A.M., Christian Jr., H.J., Driscoll, K., Gadian, A.M., Latham, JDetermination of ice precipitation rates and thunderstorm ancontents from satellite observations of lightning. Atmos. Res.217–229. http://dx.doi.org/10.1016/S0169-8095(01)00117-X.

Boccippio, D.J., Koshak,W.J., Blakeslee, R.J., 2002. Performance assessmenoptical transient detector and lightning imaging sensor. Part I: Prdiurnal variability. J. Atmos. Ocean. Technol. 19, 1318–1332. http:/org/10.1175/1520-0426(2002)019%3C1318:paotot%3E2.0.co;2.

Changnon, S.A., 1981. Impacts of urban modified precipitation conditions, inMETROMEX: a review and summary. Meteorol. Monogr. Ser. 40, 153–177.

orithmSenso

Drisco., 2003Optica0.1029

., 2003. J. Climb2552

hin tweteoro

malouo urba.1016/

d deevailabl.ghtnineteorhttp:

ent oAtmo4.f sma/dx.do

er fou/dx.do

of thL03804

onshiptures i6 (D6

., 1998gestin0.1126

ity ove19–824Centrays. Re6.aerosoer larg. http:

hen, Fvationaregion0.1175

htning. http:

Orville, R.E., Huffines, G., Nielsen-Gammon, J., Zhang, R.Y., Ely, B., Steiger, S.,Phillips, S., Allen, S., Read, W., 2001. Enhancement of cloud-to-ground

7–2600.

ffect on-Brazil.

infall athys. 15,

activityos. Res.

ghtning/dx.doi.

trial airce.287.

pitationds. Bull.5/1520-

14 (2),

cloudphysics.Tropical59–80

nt over.org/10.

ghtninges. 107

Survey

nson, I.,Franca,Piva, H.,slee, R.,enbach,ver the(D20),

inental,L07802.

etweenpitation0.1029/

ence oforation.46052.g, K.E.,indirectos. 117,

90 A.K. Kamra, A.A. Nair / Atmospheric Research 160 (2015) 82–90

Christian, H.J., Blakeslee, R.J., Goodman, S.J., Mach, D.M., 2000. AlgTheoretical Basis Document (ATBD) for the Lightning Imaging(LIS). Tech. rep. 53. NASA/Marshall Space Flight Center.

Christian, H.J., Blakeslee, R.J., Boccippio, D.J., Boeck, W.L., Buechler, D.E.,K.T., Goodman, S.J., Hall, J.M., Koshak, W.J., Mach, D.M., Stewart, M.FGlobal frequency and distribution of lightning as observed by theTransient Detector. J. Geophys. Res. 108 (D1). http://dx.doi.org/12002JD002347 (ACL 4-1 ACL 4-15).

Collimore, C.C., Martin, D.W., Hitchman, M.H., Huesmann, A., Waliser, D.EOn the relationship between the QBO and tropical deep convection16, 2552–2568. http://dx.doi.org/10.1175/1520-0442(2003)016otrbtqN2.0.co;2.

Dye, J.E., Jones, J.J., Weinheimer, A.J., Winn, W.P., 1988. Observations witregions of change during initial thunderstorm electrification. Q. J. R.MSoc. 114, 1271–1290. http://dx.doi.org/10.1002/qj.49711448306.

Farias, W.R.G., Pinto Jr., O., Naccarato, K.P., Pinto, I.R.C.A., 2009. Anolightning activity over the Metropolitan Region of Sao Paulo due teffects. Atmos. Res. 91 (2-4), 485–490. http://dx.doi.org/10atmosres.2008.06.009.

Hernandez, C.A., 2008. The QBO's influence on lightning production anconvection in the tropics. Master's thesis, Texas A&M University (Aelectronically from http://hdl.handle.net/1969.1/ETD-TAMU-3106)

Hernandez, C.A., Schumacher, C., 2008. The QBO's influence on liproduction in the tropics. 28th Conf. On Hurricanes and Trop. MAmer. Meteor. Soc, Orlando, FL (2008. Available electronically fromgeotest.tamu.edu/userfiles/227/2008-tropical-qbo.pdf).

Kar, S.K., Liou, Y.-A., Ha, K.-J., 2009. Aerosol effects on the enhancemcloud-to-ground lightning over major urban areas of South Korea.Res. 92 (1), 80–87. http://dx.doi.org/10.1016/j.atmosres.2008.09.00

Khain, A., Pinsky, M., Shapiro, M., Pokrovsky, A., 2001. Collision rate ograupel and water drops. J. Atmos. Sci. 58 (17), 2571–2595. http:/org/10.1175/1520-0469(2001)058%3C2571:crosga%3E2.0.co;2.

Lal, D.M., Pawar, S.D., 2011. Effect of urbanization on lightning ovmetropolitan cities of India. Atmos. Envron. 45 (1), 191–196. http:/org/10.1016/j.atmosenv.2010.09.027.

Lang, T.J., Rutledge, S.A., 2006. Cloud-to-ground lightning downwind2002 Hayman forest fire in Colorado. Geophys. Res. Lett. 33 (3),http://dx.doi.org/10.1029/2005GL024608.

Liu, C., Cecil, D., Zipser, E.J., Kronfeld, K., Robertson, R., 2012. Relatibetween lightning flash rates and radar reflectivity vertical structhunderstorms over the tropics and subtropics. J. Geophys. Res. 11http://dx.doi.org/10.1029/2011JD017123.

Lyons, W.A., Nelson, T.E., Williams, E.R., Cramer, J.A., Turner, T.REnhanced positive cloud-to-ground lightning in thunderstorms insmoke from fires. Science 282 (5386), 77–80. http://dx.doi.org/1science.282.5386.77.

Manohar, G.K., Kesarkar, A.P., 2003. Climatology of thunderstorm activthe Indian region: a study of east–west contrast. Mausam 54 (4), 8

Murray, N.D., Orville, R.E., Huffines, G.R., 2000. Effect of pollution fromAmerican fires on cloud-to-ground lightning in May 1998. GeophLett. 27 (15), 2249–2252. http://dx.doi.org/10.1029/2000GL01165

Naccarato, K.P., Pinto Jr., O., Pinto, I.R.C.A., 2003. Evidence of thermal andeffects on the cloud-to-ground lightning density and polarity ovurban areas of Southeastern Brazil. Geophys. Res. Lett. 30 (13), 1674dx.doi.org/10.1029/2003GL017496.

Niyogi, D., Pyle, P., Lei, M., Arya, S.P., Kishtawal, C.M., Shepherd, M., CWolfe, B., 2011. Urban modification of thunderstorms: an obserstorm climatology andmodel case study for the Indianapolis urbanJ. Appl. Meteorol. Climatol. 50, 1129–1144. http://dx.doi.org/12010JAMC1836.1.

Orville, R.E., Henderson, R.W., 1986. The global distribution ofmidnight ligDecember 1977 to August 1978. Mon.Weather Rev. 114, 2640–2653dx.doi.org/10.1175/1520-0493(1986)114b2640:GDOMLSN2.0.CO;2.

r

ll,.l/

.

.:

ol.

snj.

pe

g.,//

fs.

lli.

ri.

e.

sn).

.g/

r.ls.

le//

.,l./

://

lightning over Houston, Texas. Geophys. Res. Lett. 28 (13), 259http://dx.doi.org/10.1029/2001GL012990.

Pinto, I.R.C.A., Pinto Jr., O., Gomes, M.A.S.S., Ferreira, N.J., 2004. Urban ethe characteristics of cloud-to-ground lightning over BeloHorizonteAnn. Geophys. 22 (2), 697–700.

Raghavan, K., 1964. Influence of the Western Ghats on the monsoon rathe coastal boundary of the peninsular India. Ind. J. Met. Geop617–620.

Ramesh Kumar, P., Kamra, A.K., 2012a. Land–sea contrast in lightningover the sea and peninsular regions of South/Southeast Asia. Atm118, 52–67. http://dx.doi.org/10.1016/j.atmosres.2012.05.027.

Ramesh Kumar, P., Kamra, A.K., 2012b. Spatiotemporal variability of liactivity in the Himalayan foothills. J. Geophys. Res. 117, 1–15. http:/org/10.1029/2012JD018246.

Rosenfeld, D., 2000. Suppression of rain and snow by urban and induspollution. Science 287, 1793–1796. http://dx.doi.org/10.1126/scien5459.1793.

Rosenfeld, D., Lensky, I.M., 1998. Satellite-based insights into preciformation processes in continental and maritime convective clouAm. Meteorol. Soc. 79 (11), 2457–2476. http://dx.doi.org/10.1170477(1998)079%3C2457:sbiipf%3E2.0.co;2.

Rosenfeld, D., Woodley, W.L., 2001. Pollution and clouds. Phys. World33–37.

Rosenfeld, D., Woodley, W.L., 2003. Closing the 50-year circle: fromseeding to space and back to climate change through precipitationIn: Tao, W.-K., Adler, R. (Eds.), Cloud Systems, Hurricanes, and theRainfall Measuring Mission. TRMM. Meteorol. Monogr 51, pp.(Chapter 6).

Steiger, S.M., Orville, R.E., 2003. Cloud-to-ground lightning enhancemesouthern Louisiana. Geophys. Res. Lett. 30 (19), 1975. http://dx.doi1029/2003GL017923.

Steiger, S.M., Orville, R.E., Huffines, G., 2002. Cloud-to-ground licharacteristics over Houston, Texas: 1989–2000. J. Geophys. R(D11), 4117. http://dx.doi.org/10.1029/2001JD001142.

Wallace, J.M., Hobbs, P.V., 2006. Atmospheric Science. An Introductorysecond ed. Academic, New York.

Williams, E.R., Rosenfeld, D., Madden, N., Gerlach, J., Gears, N., AtkiDunnemann, N., Frostrom, G., Antonio, M., Biazon, B., Camargo, R.,H., Gomes, A., Lima, M., Machado, R., Man-haes, S., Nachtigall, L.,Quintiliano, W., Machado, L., Artaxo, P., Robarts, G., Renno, N., BlakeBailey, J., Boccippio, D., Betts, A., Wolff, D., Roy, B., Halverson, J., RickT., Fuentes, J., Avelino, E., 2002. Contrasting convective regimes oAmazon: implications for cloud electrification. J. Geophys. Res. 1078082. http://dx.doi.org/10.1029/2001JD000380.

Xu, W., Zipser, E.J., 2012. Properties of deep convection in tropical contmonsoon, and oceanic rainfall regimes. Geophys. Res. Lett. 39,http://dx.doi.org/10.1029/2012GL051242.

Xu, W., Zipser, E.J., Liu, C., Jiang, H., 2010. On the relationships blightning frequency and thundercloud parameters of regional precisystems. J. Geophys. Res. 115, D12203. http://dx.doi.org/12009JD013385.

Yuan, T., Remer, L., Pickering, K.E., Yu, H., 2011. Observational evidaerosol enhancement of lightning activity and convective invigGeophys. Res. Lett. 38, L04701. http://dx.doi.org/10.1029/2010GL0

Yuan, T., Remer, L.A., Bian, H., Ziemke, J.R., Albrecht, R., PickerinOreopoulos, L., Goodman, S.J., Yu, H., Allen, D.J., 2012. Aerosoleffect on tropospheric ozone via lightning. J. Geophys. Res.-AtmD18213. http://dx.doi.org/10.1029/2012JD017723.