Solar Activity, Lightning and Climate

Devendraa Siingh • R. P. Singh • Ashok K. Singh • M. N. Kulkarni •

A. S. Gautam • Abhay K. Singh

Received: 10 April 2010 / Accepted: 9 May 2011 / Published online: 21 May 2011� Springer Science+Business Media B.V. 2011

Abstract The physics of solar forcing of the climate and long term climate change is

summarized, and the role of energetic charged particles (including cosmic rays) on cloud

formation and their effect on climate is examined. It is considered that the cosmic ray-

cloud cover hypothesis is not supported by presently available data and further investi-

gations (during Forbush decreases and at other times) should be analyzed to further

examine the hypothesis. Another player in climate is lightning through the production of

NOx; this greenhouse gas, water vapour in the troposphere (and stratosphere) and carbon

dioxide influence the global temperature through different processes. The enhancement of

aerosol concentrations and their distribution in the troposphere also affect the climate and

may result in enhanced lightning activity. Finally, the roles of atmospheric conductivity on

the electrical activity of thunderstorms and lightning discharges in relation to climate are

discussed.

Keywords Solar irradiance � Galactic cosmic rays � Thunderstorm/Lightning � Upper

tropospheric water vapour � Atmospheric chemistry � Aerosols � Climate

1 Introduction

The terrestrial climate is driven by solar energy incident on the Earth’s atmo-

sphere, * 1.365 kWm-2 at the top of the atmosphere. On average, about 50% of the

energy from the Sun is absorbed by the surface and about 30% is reflected back into the

space. The reflected energy consists of *20% reflected by clouds, 6% backscattered by air

D. Siingh (&) � M. N. Kulkarni � A. S. GautamIndian Institute of Tropical Meteorology, Pune 411 008, Indiae-mail: devendraasiingh@tropmet.res.in; devendraasiingh@gmail.com

R. P. Singh � A. K. SinghDepartment of Physics, Banaras Hindu University, Varanasi 211 005, India

A. K. SinghPhysics Department, Lucknow University, Lucknow 226 007, India

123

Surv Geophys (2011) 32:659–703DOI 10.1007/s10712-011-9127-1

and *4% reflected by the surface (Hanslmeier 2007). About 16% is absorbed by the

atmosphere (mostly by aerosol and dust particles in the troposphere, and by ozone). About

79% of the received energy is returned to space in the form of thermal radiation in the long

wave infrared part of the spectrum. Some 21% is transmitted from the Earth’s surface to

the atmosphere by conduction (termed the sensible heat flux), and by latent heat flux

(through the evaporation of H2O leading to the surface cooling). The variation in the

climate may be attributed, at least in part, to the variation of solar energy incident on the

Earth’s atmosphere.

The variation of solar energy incident on the Earth’s atmosphere depends on solar

activity, which varies on time scales from hours to billions of years, and depends on various

processes operating inside/on the surface of the Sun. It is also affected by the rotation of the

Sun, the precession of the Earth and the obliquity of the Earth’s rotational axis and changes

due to the eccentricity of Earth’s orbit (Berger et al. 2003). The Sun’s magnetic field varies

in a complex manner, including the well known sunspot cycle of *11 years periodicity and

longer period modulations. The total solar irradiance (the total electromagnetic power per

unit area of cross section at the top of the Earth’s atmosphere) varies not only through the

solar cycle (Frohlich 2006) but also in a much more complex manner.

The radiation incident on the terrestrial atmosphere is affected by the different atmo-

spheric constituents. For example, additional ozone in the stratosphere reduces the

downward short wavelength (ultraviolet) fluxes and increases the upward long wavelength

fluxes. The systematic change in the global average temperature termed global warming is

mainly attributed to changes in the concentrations of atmospheric constituents which

absorb infrared radiation, the so called greenhouse gases. These produce a radiative forcing

of *3 Wm-2 (IPCC 2007). Scafetta and West (2006, 2008) suggest that solar variability

accounts for *69% of global warming in the twentieth century, and 25–35% warming

since 1980. This is about a factor of two larger warming than in prior studies (Camp and

Tung 2007). Benestad and Schmidt (2009) discussed the weaknesses of the method

adopted by Scafetta and West (2006, 2008) and showed that the most likely contribution

from solar forcing to global warming is 7 ± 1% for the twentieth century and with a

negligible contribution to warming since 1980. The long term drift in the radiative forcing

is of great importance in climate change; it is *0.017 Wm-2 per decade (Frohlich 2006,

Gray et al. 2010). The current rate of increase in trace greenhouse gas radiative forcing is

*0.30 Wm-2 per decade (Hofmann et al. 2008).

The global climate change in terms of increasing concentrations of greenhouse gases in

the atmosphere and variations of solar radiation has been summarized in the report of

Intergovernmental Panel on Climate Change (2007). The report has also stressed that some

weather conditions including flash floods are often related to intense thunderstorms and

lightning activity. The strong dependence of the lightning strike rate on cloud top prop-

erties (Williams 1985), the correlation of lightning flash rate with the surface temperature

(Williams 1992), the association of intense rainfall with the lightning flash rate (Price and

Federmesser 2006), the effect of doubling the amount of CO2 in the atmosphere on changes

in cloud height (Price and Rind 1994), the production of NOx by lightning and thereby

modification of the amount of ozone in the atmosphere (Schumann and Huntrieser 2007),

etc., are some of the factors which stress the present need to understand the relation

between solar activity, lightning and climate.

The major driver of climate is the Sun, which is also at the origin of thunderstorm

formation leading to rainfall and the production of lightning. The convective processes

caused by differential heating at the Earth’s surface lead to both rainfall and lightning. The

deeper and stronger updrafts in convection may produce lightning (Baker et al. 1999;

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Boccippio 2001), whereas modest lifting results in rainfall (Williams and Stanfill 2002;

Williams 2005). Chronis et al. (2004) discussed the possibility of using lighting as a proxy

of intense convective rainfall in remote regions. This was supported by the analysis of

satellite data showing a positive connection between Mediterranean lightning activity and

convective rainfall and also between the El Nino cycle and thunderstorms (Price and

Federmesser 2006). The intense thunderstorms in eastern Africa influence the stability of

the African Easterly waves, which ultimately may result in Atlantic hurricanes about a

week later (Price et al. 2007).

In this paper we briefly discuss direct and indirect forcing of solar irradiance on climate,

the impact of energetic charged particles (in the solar wind, solar energetic proton events

associated with solar flares, and cosmic rays) on climate through cloud formation and

consequent atmospheric cooling or warming. Also, the global observation of lightning, the

association of lightning with the amount of upper tropospheric water vapour (UTWV) and

atmospheric aerosols, and the impact of lightning on atmospheric constituents and their

relation with climate are discussed. Modifications of the electrical conductivity of the

atmosphere affect the vertical electric current between the surface and the ionosphere

which can affect cloud formation and result ultimately in changes to the climate.

2 Long Term Climate Variations, Solar Irradiance and Cosmic Rays

One main agent responsible for climate variation is the variation in solar irradiance and/or

variation of the solar spectrum (Haigh et al. 2010). Other factors responsible for variations

in the Earth’s climate are variations in the concentrations of atmospheric constituents

(partly controlled by the Sun), galactic cosmic rays (GCRs), processes taking place at the

surface of the Earth, and man-made changes in the troposphere (King 1975). The contri-

bution of each process to climate is qualitatively discussed but a quantitative estimate for

each separate process is not available (Gray et al. 2005).

There are three probable mechanisms which link solar variability with variations of

climate (Carslaw et al. 2002): (a) changes in solar irradiance leading to changes in heat

input to the lower atmosphere, (b) changes in solar ultraviolet radiation coupled to changes

in the ozone concentration affecting the heat budget of the stratosphere, and (c) solar and

galactic cosmic rays (GCR) affecting cloud formation. These effects are modulated by long

term solar activity, by changes of the galactic and solar cosmic rays and by changes of the

Earth’s magnetic field.

Figure 1 shows a schematic diagram of the direct and indirect effects at different

altitudes of solar radiation changes (either total solar irradiance (TSI) or ultraviolet (UV))

on climate with respect to Smax (solar maxima), GCR and corpuscular radiation (Kodera

and Kuroda 2002). The TSI affects the surface temperature, whereas UV affects the

stratospheric temperature through the modification of the ozone concentration there.

Upward propagating planetary waves from the troposphere to the stratosphere are sensitive

to the background winds present. Positive feedback (rF [ 0) arises through the wind

anomaly which moves poleward and downward with time and grows significantly in

amplitude (Kodera and Kuroda 2002). The wave forcing (rF [ 0) weakens the strength of

large scale equatorial upwelling (w* in Fig. 1). In solar maxima (Smax) years the polar

lower stratosphere is colder because of a less disturbed polar vortex. In Smin (solar minima)

years the effect would be reversed (Kodera and Kuroda 2002). In the return upwelling arm

(equatorial region) weak circulation during Smax years will result in less adiabatic cooling,

resulting in a warmer equatorial stratosphere. In this mechanism a small temperature

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(1–2 K) anomaly at the equatorial stratopause is transferred to the lower polar stratosphere

in the amplified form. This feedback mechanism also modulates the transport of ozone

(Hood 2004; Gray et al. 2009). The current I flowing in the global electric circuit (GEC)

generated in thunderclouds is also shown in Fig. 1.

2.1 Solar Irradiance and Climate (Direct Mechanism)

The variation in solar irradiance may result from variations in (a) nuclear conditions in the

Sun’s core, (b) the solar magnetic field generated below the convective zone, and

(c) orbital conditions, such as solar rotation, changes in the Earth’s orbit or inclination of

the Sun’s rotational axis with respect to the ecliptic plane. These processes are expected to

produce very long term changes, up to several million years (Shaviv 2003). The evolution

of solar magnetic field, the structure of the solar wind and coronal mass ejections (CMEs)

(Wagner 1984; Gopalswamy 2004; Singh et al. 2010) involve time scales ranging from

hours to years (Williams et al. 2001; Kudela et al. 2002; Labitzke and Matthes 2003;

Muscheler et al. 2003; Delmonte et al. 2005; Christiansen et al. 2007). Details of these

variations are given in Table 1, which summarizes the time scale, origin of the variations

Fig. 1 The direct and indirect effects of total solar irradiance changes (TSI) and UV radiation changes withrespect to solar maximum conditions, as well as corpuscular radiation effects (energetic charged particlesand GCR), on climate are schematically shown. T is the atmospheric temperature; SST is the sea surfacetemperature. The thin blue arrows represent the global electric circuit (GEC). Here w* denotes theweakened equatorial upwelling at solar maximum associated with reduced planetary wave forcing. W* isvertical velocity, U is wind speed and F is forcing at the top of the atmosphere. The black arrow representstransport associated with planetary waves, AO is the Arctic Oscillation, NAO is the North AtlanticOscillation, ENSO is the El Nino Southern Oscillation, QDO is the Quasi-Decadal Oscillation, and QBO isthe Quasi-Biennial Oscillation. The two dashed purple arrows denote the coupling between the stratosphereand the troposphere and the coupling between the ocean and the atmosphere (after Kodera and Kuroda,2002; Gray et al. 2010)

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Table 1 Processes responsible for solar variability, their origin, time scales and the climate parametersaffected (modified from Christiansen et al. 2007)

Time scale Solar origin Climate effect Reference

*109 years Solar evolution andgalactic arm traverses(encounter of intensecosmic ray bursts)

Reduced solar irradianceand enhanced low cloudcover cause glaciations;colder climate, reducedprecipitation, morevigorous large scaleatmospheric circulation

Shaviv (2003),Christiansen et al. (2007)

*105 years TSI variations caused byorbital changes due toeccentricity of Earth’sorbit

Change in seasonalduration and intensity ofTSI. Effects are oppositein each hemisphere, andlargest at low latitudes

Berger et al. (1984), Petitet al. (1999), Imbrie et al.(1992)

*4.1 9 104 years TSI variation due toobliquity of the Earth’srotational axis

Equal effects of TSI in bothhemispheres, strongerpole wards. Moreradiation at summer poleat large obliquity

Berger et al. (1984), Petitet al. (1999), Imbrie et al.(1992)

*2.3 9 104 years TSI variation due toprecession of Earth’srotational axis

Different seasonal cyclestructures, produceing acomplex effect onclimate

Berger et al. (1984), Petitet al. (1999), Imbrie et al.(1992)

*2.3 9 103 years(Hallstatt cycle)

TSI variation due tomodulation of the solardynamo

Lower temperatures,reduced precipitationand changed large scaleatmospheric circulation

Denton and Karlen (1973),Damon and Jirikowic(1992)

*205 years (deVries cycle)

TSI variation due tomodulation of the solardynamo

Solar forcing amplifiedthrough ocean–atmosphere interactions,changing sea surfacetemperatures and sea-iceextent

Muscheler et al. (2003),Delmonte et al. (2005)

88 years(Gleissbergcycle)

TSI variation due tomodulation of the solardynamo

Changes of globaltemperature (both airand ocean temperatures)and of atmosphericcirculation. Climaticfluctuations induced atthe turning points of thiscycle

Hoyt and Schatten (1997),Fairbridge (1967)

22 years (Halecycle)

TSI variation due tooscillation of the solardynamo

Changes of temperatureand precipitation.Droughts in US followthis pattern

Mitchell et al. (1979)

11 years (Schwabecycle)

TSI variation due tooscillation of the solardynamo. About 0.1%variation of TSI betweensolar maximum andminimum

As a result of changes ofozone concentration,geopotential height andtemperatures in thestratosphere vary,modifying meriodionalcirculation, low cloudcoverage and Arcticoscillations

Labitzke and Matthes(2003), Shindell et al.(1999), Svensmark(1998), Reid (1991),Friis-Christensen andLassen (1991)

Surv Geophys (2011) 32:659–703 663

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and related climate parameters (Christiansen et al. 2007). The time scales involved due to

variations in the precession of the Earth’s rotation axis and obliquity and eccentricity of the

Earth’s orbit are 23,000, 41,000 and 100,000 years, respectively (Petit et al. 1999).

The most well known 11 year sunspot cycle, the Schwabe cycle (1844), the 22 year

Hale cycle and their modulation, with a period of about 88 years, known as the Gleissberg

cycle, are evident in sunspot data (Frick et al. 1997; Ogurtsov et al. 2002), solar cosmic ray

activity (McCracken et al. 2001) and solar energetic particle (SEP) events (Reames 2004).

During the Maunder Minimum (1645–1715), sunspots were almost absent (Fig. 2a). High

sunspot numbers coincide with warm weather and low sunspot numbers with cool weather

(Hoyt and Schatten 1997).

Figure 2b shows the variation of reconstructed total solar irradiance from 1610–2003

based on sunspot data (Lean et al. 2002) and the solar cycle amplitude for secular varia-

tions (Solanki and Krivova 2003). Lean et al. (2002) have used a 2.7 Wm-2 increase in

total solar irradiance since the Maunder Minimum, whereas Solanki and Krivova (2003)

used a 2.15 Wm-2 increase. This long term positive drift in TSI between the Maunder

Minimum and the present day is somewhat uncertain. Foukal et al. (2004) suggested that

there may not be any change, whereas Krivova et al. (2007) considered a smaller positive

drift than previously estimated (Lean et al. 2002). Krivova et al. (2007) found a value of

1.3 Wm-2 with an uncertainty range of 0.9–1.5 Wm-2. The reconstructed total solar

irradiance has been compared with independent records of solar activity obtained from

cosmogenic isotopes in tree-rings and ice-cores (Beer et al. 1994; Lean et al. 1995). The

correlation between solar irradiance and northern hemisphere surface temperature is

*0.86 in the pre-industrial period (1610–1800 years) (Lean et al. 1995).

The global surface temperature is usually used as the key parameter for demonstrating

the average state of the Earth’s climate. Therefore, the average global sea surface tem-

perature (SST) anomaly and running mean of the annual sunspot number for the period

1860–1985 are shown in Fig. 3a (Reid 1991, 2000; Christiansen et al. 2007); they show

similar variations. This finding has been corroborated by White et al. (1997) using two

independent SST data sets, i.e. surface marine weather observations (1900–1991) and upper

ocean bathythermograph temperature profiles (1955–1994). They reported the maximum

global average temperature change of 0.08 ± 0.02 K on the 11 year period scale and

0.14 ± 0.02 K on the 22 year cycle. The highest correlation with ocean temperatures lags

solar activity by 1–2 years, a time scale expected for the upper layers of the ocean (\100 m)

to reach radiative equilibrium following a perturbation in the total solar irradiance.

Figure 3b shows the variation of solar cycle length from less than 9 years to more than

12 years and the northern hemisphere land temperature anomaly from 1860 to 1990 (Friis-

Christensen and Lassen 1991; Christiansen et al. 2007); a shorter solar cycle, which could

indicate higher activity, corresponds to warmer conditions. This assumption is not based on

Table 1 continued

Timescale

Solar origin Climate effect Reference

1.3 years Solar dynamo bifurcation(observed periodicity insolar wind velocity)

May change atmospheric circulation andgeomagnetic activity

Paularena et al.(1995), Kudelaet al. (2002)

27 days Solar rotation results in 27 dayvariability of solar UVradiation

Photochemistry, composition (ozone),temperature and dynamics ofstratosphere are modified

Williams et al.(2001)

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physical arguments and doubts have been expressed on its ability to represent solar irra-

diance (Solanki et al. 2000). The northern hemisphere surface temperature has been

considered because most of the southern hemisphere is covered with sea whose temper-

ature lags the air temperature over the ocean. Comparing Fig. 3a, b, lower temperatures

during the 1970 s occur when the Sun is less active than usual. There is breakdown in such

a correlation after 1985 which is attributed to an increasingly dominant effect of the

greenhouse gases responsible for global warming (Thejll and Lassen 2000). The surface

temperature (both sea and land) includes contributions from many factors besides green-

house gases, such as ENSO, volcanic eruptions, aerosol changes, and other anthropogenic

contributions.

Lean and Rind (2008) performed a multivariate analysis using the best available esti-

mates of natural and anthropogenic impacts on surface temperature, regionally as well as

globally, and showed that natural influences produce *0.2 K warming during major

ENSO events, *0.3 K cooling following larger volcanic eruptions and 0.1 K warming

1600 1700 1800 1900 2000 2100

0

25

50

75

100

125

150

175

200

Sun

spot

Num

ber

Year

(a)

(b)

Fig. 2 a Smoothed yearly variation of sunspot number for the period 1610–2003. The 11 year sunspotcycle modulated with a 88 year Gleissberg cycle is clearly seen with the distinct Maunder Minimum(1645–1715) when there were no visible sunspots (reproduced after Christiansen et al. 2007). b Thevariation of reconstructed total solar irradiance [black (Lean, 2000) and red (Gray et al. 2005)] for the period1610–2003 (after Gray et al. 2005)

Surv Geophys (2011) 32:659–703 665

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near the maximum of the recent solar cycle. The temperature changes due to a volcanic

eruption last about 1–2 years (Trenberth et al. 2007). They showed that solar forcing

contributed negligible long-term warming in the past 25 years and 10% of the warming in

the past 100 years, not 69% as claimed by Scafetta and West (2008). Volcanoes inject a

large quantity of dust and gases such as SO2 into the atmosphere which lead to the

formation of aerosols. Enhanced aerosol amounts reduce the solar energy input to the

atmosphere resulting in cooling, over a period of about 2 years following a major eruption

(Hansen et al. 1992).

Using ocean heat content anomaly data for the period 1993–2008, Lyman et al. (2010)

estimated a global warming trend of 0.63 ± 0.28 W/m2. Positive radiative imbalance was

also reported by Trenberth and Fasullo (2010). Knox and Dauglass (2010) claimed that the

result of Lyman et al. (2010) is not representative of the recent (2003–2008) warming/

Fig. 3 a 11 year running mean of annual sunspot numbers (upper panel thin curve) from 1870 to 1985, andthe mean global sea surface temperature anomaly (lower panel thin curve) for the period 1860–1980. Thebold curve represents a 7th degree polynomial least squares fit to the data. The units for the lower curve are0.01 K departures from the 1951–1980 average (after Christiansen et al. 2007). b Solar cycle length (SCL, inyears, right hand scale, dotted curve) versus the northern hemisphere temperature anomaly over land(T, degrees K, solid curve) for the period 1860–2000 (after Christiansen et al. 2007)

666 Surv Geophys (2011) 32:659–703

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cooling rate because of a flattening of ocean heat content anomaly data that occurred

around 2001–2002; using data only for the period 2003–2008, they showed a cooling, not

warming. Recently, Easterling and Wehner (2009) suggested that naturally induced surface

temperature changes can dominate current anthropogenic warming of *0.2�C per decade.

Lockwood and Frohlich (2007) demonstrated that the observed rapid rise in global mean

temperature after 1985 cannot be ascribed to solar variability, no matter how much the

solar variation is amplified. Lockwood et al. (2010a, b) presented evidence for a long term

drift in the solar UV irradiance, which produces intense effects on both stratospheric and

tropospheric winds and temperature. As a result a top-down climate effect may arise; this

may be out of phase with the bottom-up solar forcing (Lockwood et al. 2010a). In the top-

down model, climate–chemistry models in the stratosphere become very important and

could change the spatial response patterns. Thus top-down climate effects become very

important for making regional/seasonal climate predictions.

Solar irradiance affects the stratospheric temperature and zonal winds which also

exhibit 11 year solar cycle variations (Crooks and Gray 2005; Shibata and Deushi 2008;

Frame and Gray 2010). The response is a maximum in the tropical upper stratosphere

where the percentage change in ozone also has its maximum response to solar cycle

variations (Soukharev and Hood 2006). Gray et al. (2009) reported that half of the

temperature response is due to the solar irradiance change and half due to the additional

ozone feedback mechanism. A second region of statistically significant temperature

response is the tropical and subtropical lower stratosphere, indicative of changes in net

equatorial upwelling rates (Shibata and Kodera 2005; Gray et al. 2009). The polar winter

vortex in the Smax years is less disturbed and the polar lower stratosphere is colder than

average because of the weaker adiabatic heating in the descending arm of the Brewer-

Dobson (B-D) circulation. As a result, the return upwelling arm of the B-D circulation at

the equator is weakened, leading to less adiabatic cooling and a warmer equatorial lower

stratosphere.

Zonal winds in the upper stratosphere and lower mesosphere also show a positive

response with 11 year solar cycle changes, especially in the winter hemisphere (Crooks

and Gray 2005; Frame and Gray 2010). The zonal wind anomaly propagates downward

with time during winter seasons (Kodera and Kuroda 2002) and wave-mean-flow inter-

actions are involved in producing the response (Kodera et al. 2003). The easterly and

westerly zonal winds in the equatorial lower stratosphere exhibit the quasi-biennial

oscillation (QBO), showing the presence of solar activity effects in the stratosphere

(Labitzke 1987; Labitzke and van Loon 1988; Baldwin et al. 2001; Gray et al. 2010). It is

essential to improve our understanding of the vertical structure of the stratospheric tem-

perature response to solar cycle variations at tropical latitudes. Data of spectrally-resolved

irradiances from SORCE satellite/SIM (spectral irradiance monitor) measurements for

longer duration could be used to understand complex zonal wind and stratospheric tem-

perature anomaly. Recently Haigh et al. (2010) showed that the observed spectral changes

by the SIM instrument lead to a significant decline from 2004 to 2007 in stratospheric

ozone below an altitude of 45 km and an increase above this altitude. They have also

shown that solar radiation forcing of surface climate is out of phase with solar activity, a

finding contrary to the current expectations (Lean and Rind 2009; Cahalan et al. 2010).

Independent calibration issues of the SIM instrument remain, however.

The solar irradiance is linked with the magnetic variability of the Sun; however, the

physical process of linkage is not clearly understood, although magnetic observations have

been used to model the observed solar irradiance variability. The surface temperature,

stratospheric temperature and zonal wind show 11 year solar cycle variations.

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2.2 Solar UV Changes and Ozone (Indirect Mechanism)

The total solar irradiance discussed in the previous section could explain the trend of the

changes in climate, but its magnitude and other effects were both underestimated (Stott

et al. 2003). Computations also showed an underestimate of the near surface temperature

(North and Wu 2001) and tropospheric temperature (Hill et al. 2001) by a factor of 2–3.

The deficiency requires us to look into other mechanisms, which may be termed indirect

mechanisms of solar irradiance, and also the direct influence of solar wind, energetic

charged particles and cosmic rays.

Ultraviolet (UV, wavelengths\300 nm) radiation reinforces the solar irradiance effect

via variations in ozone concentrations and a corresponding response in stratospheric

temperature and dynamics (Balachandran and Rind 1995; Shindell et al. 1999; Haigh 2003;

Matthes et al. 2004). Model computations show significantly less latitudinal structure and

an underestimation of the ozone concentration in the upper stratosphere, whereas in the

lower stratosphere computations match the observed changes (Shindell et al. 1999; Gray

et al. 2005). The computation of annual mean temperature changes for solar minimum and

maximum conditions with relevant total solar irradiance input did not compare well with

observations, specially the secondary temperature maximum near the equator in the lower

stratosphere and the temperature signal at high latitudes (Austin et al. 2003; Langematz

et al. 2005; Haigh et al. 2005).

Although UV radiation is a small portion of the total solar irradiance, it has a relatively

large 11 years SC (solar cycle) variation. About 100% variation is present at wavelengths

near 100 nm, 6% near 200 nm (where O2 dissociation and O3 production occurs) and up to

4% variation in the region 240–320 nm (where absorption of stratospheric ozone is

dominant) (Gray et al. 2010). Harder et al. (2009), based on measurements of solar spectral

irradiance (SSI) by the SORCE/SIM instrument, suggest that variations in UV may be

much larger (by a factor of 4–6) than previously assumed. Such a large variation may result

in a very different response in both stratospheric ozone and temperature (Roy and Haigh

2010). Enhanced UV radiation produces additional heating in the stratosphere, leading to

increased positive feedback discussed earlier. Even the additional production of ozone

reduces the downward shortwave fluxes and increases the long wave fluxes. Thus the

feedback mechanism is reinforced. The feedback mechanism driving global circulation

ultimately results in changes in lower atmospheric dynamics (Rind et al. 2002; Gleisner

and Thejll 2003), which may feedback on the chemical composition of the atmosphere;

because the reaction rates of the chemical species are temperature sensitive. Thus, a small

change of the solar UV radiation in the stratosphere could produce significant dynamical

change in the lower atmosphere and affect climate. However, the forcing due to feedback is

not properly understood and quantified; further data analysis and modeling are needed.

Smith et al. (2007) forecast a rapid warming after 2008. Keenlyside et al. (2008),

accounting for meridional circulation, forecast the opposite, ‘‘that global surface temper-

ature may not increase over the next decade, as natural climate variations in the North

Atlantic and tropical Pacific temporarily offset the projected anthropogenic warming’’.

Lean and Rind (2009) forecast that ‘‘from 2009 to 2014 projected rises in anthropogenic

influences and solar irradiance will increase the global surface temperature by

0.15 ± 0.03�C, at a rate 50% greater than predicted by IPCC’’ (2007). Lean and Rind

(2009) suggested that, as a result of declining solar activity in the subsequent 5 years, the

average temperature in 2019 could be only 0.03 ± 0.01�C warmer than in 2014. Benestad

and Schmidt (2009) predicted a likely contribution of solar forcing to global warming to be

7 ± 1% for the twentieth century, with negligible contribution to warming since 1980.

668 Surv Geophys (2011) 32:659–703

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The climate forecast is based on the current trend of variations in climate variables and

the dubious assumption that the response will continue to be linear over the next few

decades. Even processes which were unimportant in the recent past may become important.

For example, Arctic sea ice changes can lead to a rapid amplification of the high latitude

response and become important. An enhanced average surface temperature can cause ice

melting of the Himalayan region and produce nonlinear changes in local and global climate

response. Abrupt industrialization and sudden commencement of war will also cause an

anthropogenic effect larger than predicted by a linear response. An enhancement in pol-

lution will reinforce changes in climate variables which may not be linear (Gray et al.

2010). These factors make climate modeling and forecasting a very difficult task.

2.3 High Energy Charged Particles (Solar Wind, Magnetospheric Energetic

Charged Particles)

Plasma and energetic charged particles emitted from the Sun in the form of the solar wind,

solar energetic particles (SEPs), solar flares, and galactic cosmic rays (GCRs) could also

play a role in the Earth’s weather/climate. The solar wind coupled with the magnetosphere

drives ionospheric currents at high latitudes (Rycroft et al. 2000; Singh et al. 2004, Siingh

et al. 2005, 2007, 2008; Tinsley 2008) producing modifications to the global electric circuit

(GEC), which may couple to the neutral atmosphere. North Atlantic Oscillations (NAO),

possibly a manifestation of solar wind electric field effects on atmospheric pressure over

the North Atlantic, cause significant climate variations over a wide range of scales in the

Atlantic sector (Marshall et al. 2001). It is claimed that the effect of solar wind induced

geomagnetic activity on the stratosphere is comparable to that of UV flux variations

between solar minimum and maximum (Arnold and Robinson 2001; Bucha and Bucha

1998). The coupling solar wind-magnetosphere-ionosphere-atmosphere could be through

charged particles precipitating from the magnetosphere or through magnetospheric current

systems closing in the ionosphere and thereby depositing Joule heating energy to the

thermosphere, the uppermost layer of the atmosphere. These particles could ionize the

atmosphere, changing the number density of ions and changing the vertical current flowing

in the GEC. The effect could fluctuate by several orders of magnitude between quiet times

and magnetic storm/substorm conditions. Christiansen et al. (2007) have shown that the

energies involved are extremely small compared to the total solar irradiance or flux of UV

radiation; thus, some amplifying mechanism (currently unknown) is required for the

magnetosphere-ionosphere system to have a significant impact on the lower atmosphere,

the troposphere, and hence on climate.

The energetic charged particles both of solar origin and precipitated from the magne-

tosphere during wave-particle interactions create ionization directly or via bremsstrahlung

radiation in the middle atmosphere. They can cause an effect on the GEC (Farrell and

Desch 2002), and alter atmospheric chemistry by affecting the concentration of NOx, O3

and sulphate aerosols (Jackman et al. 1995, 2006). Thus the Earth’s radiation budget could

also be affected. The charged particles could also affect the nucleation of water droplets

and the formation of clouds (Tinsley 2000). Energetic solar proton events could produce

small holes in Arctic ozone layer (Shumilov et al. 1995; Gray et al. 2009), could trigger the

formation of cirrus clouds (Gray et al. 2005), which decrease the flux of solar radiation to

the Earth’s surface and hence affect the evolution of weather systems (Pudovkin and

Babushkina 1992).

Energetic electrons of magnetospheric origin produce NOx in the mesosphere and

thermosphere, which could be transported by polar downwelling into the winter polar

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stratosphere where it can affect ozone abundances (Randall et al. 2005, 2006). Seppala

et al. (2004, 2007a) studied the relative contributions of ionization due to solar proton

events, energetic electron precipitation and low energy (1–10 keV) electron precipitation

on NOx production and its subsequent downward transport to the upper stratosphere. They

showed that NOx generated from the large solar proton storm (the 2003 Halloween event)

was transported into the upper stratosphere in agreement with model simulations, whereas

aurorally generated NOx descended later in the winter. Seppala et al. (2007b) showed that

night time NO2 enhancement during polar winters in the Arctic and Antarctic was well

correlated with high energy charged particle precipitation. They further showed that the

NO2 column density in both hemispheres was linearly correlated with geomagnetic activity

(Ap and Dst). Rodger et al. (2007) showed that lightning generated whistler-induced

electron precipitation was a significant source of energy input into some part of the lower

ionosphere but did not play a significant role in the neutral chemistry of the mesosphere.

Such effects are limited to the polar vortex zone. Outside this zone, the effect is insig-

nificant except during very large events (Thomas et al. 2007; Ganguly 2010). Some studies

(Callis et al. 2000, 2001; Langematz et al. 2005) reported that energetic particle induced

NOx effects on ozone at low latitudes may be comparable to the effects of solar UV

radiation, but this was not supported by the recent data analysis of Marsh et al. (2007).

Hence, based on present evidence/knowledge, it may be argued that the effect of energetic

particle produced NOx has little effect on the climate. Rigorous data analysis and simu-

lations are required to either accept or reject the above idea.

2.4 Cosmic Rays and Clouds

Cosmic rays also affect climate through the cloud cover/cloud formation, rather than direct

energy input into the atmosphere which is *10-5 times smaller than the solar input

(Frohlich and Lean 1998, Siingh 2008; Siingh and Singh 2010; Singh et al. 2010, 2011).

Ney (1959) originated the idea that cosmic ray changes could directly influence the

weather. Dickinson (1975) considered that the modulation of the galactic cosmic ray

(GCR) flux by solar activity might affect cloudiness and hence the climate. He proposed

that GCR-induced ions could trigger the formation of sulphate aerosols (and cloud con-

densation nuclei, CCN) and hence could influence cloudiness. Tinsley (2000) proposed

another route through the global electric circuit (GEC). GCR-induced ions in the atmo-

sphere modify the vertical current flowing through the atmosphere. The vertical current

passing through clouds causes charging of local droplets and aerosols at the lower and the

upper boundaries of the clouds (Tinsley 2000), as recently observed at a lower cloud

boundary by Nicoll and Harrison (2010).

Charging can modify the microphysics of clouds and hence the GEC could provide a

possible link between solar variability and clouds. The vertical current Jz of the GEC is

known to flow through regions of water droplets and clouds. Bennett and Harrison (2009)

argued that the vertical conductivity gradient could be greater than 10 fSm-2 at the cloud

boundary. During cloudy (overcast) conditions the vertical current density was found to be

inversely proportional to the cloud optical thickness (Nicoll and Harrison 2010). Thick

cloud reduced Jz by 12% compared to thin cloud. Recently Harrison and Usoskin (2010)

showed that the lower troposphere vertical current density and potential gradient were

significantly increased at CR maximum (solar minimum), with a proportional change

greater than that of the CR change.

The net effect on climate depends on the altitude of the GCR-created clouds. If the

cloud is enhanced at lower altitudes then the dominant effect would be increased reflection/

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scattering of incoming short wave solar radiation due to their high albedo, leading to a

cooling effect. However, in the case of enhancement of cloud amounts at higher altitudes,

that would cause trapping of outgoing long wavelength radiation, resulting in a warming of

the atmosphere.

Svensmark and Friis-Christensen (1997) analysed International Satellite Cloud Clima-

tology Project (ISCCP) data and neutron monitor cosmic ray data. They reported a cor-

relation between cosmic ray variations and low altitude cloud cover variations. Sun and

Bradley (2002) reanalyzed the same data sets, included additional satellite-based and

ground-based data; they showed that no meaningful relationship between cloud cover and

GCR could be found. They extended the analysis for cloud cover for the period 1987–1993

and separated the low, middle and high altitude cloud level analyses for the data collected

over the North Atlantic (0�–60�N). They reported correlation coefficients between GCR

and cloud cover to be 0.19, 0.07 and 0.00, respectively. Laut (2003) re-analysed the graphs

of Svensmark and Friis-Christensen (1997) and Svensmark (1998) and showed that the

apparent strong correlation displayed on these graphs might be due to incorrect handling of

the data.Svensmark (2007) compared data from the International Satellite Cloud Climatology

Project and the Huancayo cosmic-ray station and showed that cloud cover and cosmic rays

show almost no correlation at high ([6.5 km) and middle (6.5–3.2 km) altitude, but a good

match at low altitudes (\3.2 km). Figure 4 shows the variation of low altitude cloud

amount and change in cosmic rays for the period 1982–2005 (Svensmark 2007). He

considered that plenty of cosmic rays are always present at high altitudes in the atmosphere

but they and the ions that they produce are in short supply at low altitudes; thus, increases/

decreases in the cosmic ray flux due to changes in scattering by fluctuations of the

interplanetary magnetic field may have more consequences at lower altitudes than at high

altitudes. Svensmark et al. (2007) claimed that electrons released in the atmosphere by

cosmic rays act as good catalysts and significantly accelerate the formation of stable ultra-

small clusters of water molecules and sulphuric acid, the building blocks for the cloud

condensation nuclei. However, this mechanism does not have quantitative support (Sorokin

and Arnold 2009).

Low level clouds cover more than a quarter of the Earth and exert a strong cooling

effect at the Earth’s surface. Figure 4 shows that a change of *2% in low altitude clouds

during the 23rd solar cycle could result in a *1.2 W m-2 change in the solar energy heat

input at the Earth’s surface. Using this argument, one may try to explain some part of

global warming in the twentieth century as a reduction in cosmic ray fluxes which may

have caused a decrease in low cloud coverage. This argument is also favoured if one looks

into the past history of terrestrial climate. Figure 5 shows changes in the flux of galactic

cosmic rays from 1700 to 2005 (Svensmark 2007). Lower altitude cloud amounts (from

Fig. 4) normalized to observational cosmic ray data from Climax for the period 1953 to

2005 are also shown in the figure. The high cosmic ray activity during the Maunder

Minimum (1645–1715), when the area of sunspots was extremely small and the solar

magnetic field was exceptionally weak, coincided with the coldest phase of climate known

as the Little Ice Age (Eddy 1976; Kirkby 2007; Siingh 2008; Siingh and Singh 2010; Singh

et al. 2011). The Dalton minimum of the early nineteenth century, another cold phase, also

coincides with the enhanced cosmic ray counts. Svensmark (2007) claimed that Fig. 4

reveals the overall trend in the past, between cold 1700 and warm 2000 years, of high

resolution climate-related switch between high and low cosmic ray counts. Even the

reconstruction of the sea surface temperature anomaly and relative cosmic ray flux during

the past 600 million years show four switches from warm ‘hot house’ to cold ‘ice house’

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during the Phanerozoic periods. This was explained in terms of four encounters of the solar

system with spiral arms of the Milky Way galaxy which might have resulted in locally

enhanced cosmic ray fluxes (Shaviv and Veizer 2003; Svensmark 2007).

Kernthaler et al. (1999) studied the possible relation between GCRs and different types

of clouds; they could not find any clear relationship between individual cloud types and

GCR. Erlykin et al. (2009a) also searched for cosmic ray effects on major low level cloud

components (stratiform and cumuliform) considering different sensitivities to the cloud

condensation nuclei. Cumuliform clouds have much higher upthrust velocities and hence

are expected to be less affected by the cosmic ray induced cloud modification. However,

even this approach of dividing low level clouds into stratiform and cumuliform could not

produce any support for the GCR and low cloud hypothesis. The evidence of long term

correlation between low cloud cover (LCC) and the absence of short term correlation

indicates that there is no direct causal connection between GCR and LCC. Erlykin et al.

(2009b) proposed that, under certain circumstances, GCR-produced showers could leave a

signature in cloud ‘‘near vertical or cigar shaped clouds’’. However, such structures have

not yet been observed. Sloan and Wolfendale (2008) analysed the ISCCP infrared data for

cloud cover and GCR data during the period of solar cycle 22 and estimated that less than

23% of the 11 year cycle change in the globally averaged cloud cover is due to the change

in the rate of ionisation from the solar modulation of cosmic rays.

The hypothesis of cloud cover and GCRs based on the variations in the concentration

and efficiency of CCN through ionization during a Forbush decrease (Fd) was also studied

(Palle Bago and Butler 2001; Harrison and Stephenson 2006; Todd and Kniveton 2001,

2004; Kniveton 2004; Kristjansson et al. 2008; Harrison and Ambaum 2010). Palle Bago

and Butler (2001) analyzed ISCCP cloud data and Irish radiation data combined but could

not find any correlation between cloud cover and Fd. Harrison and Stephenson (2006) used

radiation measurements to infer cloud cover and reported a positive correlation between

cloud cover and Fd for UK sites. Significant correlations between the Fd and high clouds at

high altitudes from ISCCP data were reported in several studies (Todd and Kniveton 2001,

2004; Kniveton 2004). However, significant inhomogeneities in the ISCCP data sets have

been pinpointed (Evan et al. 2007).

Kristjansson et al. (2008) considered the high spatial and spectral resolution of MODIS

(Moderate-resolution Imaging Spectro-radiometer) data to study cloud microphysical

Fig. 4 Variation of low cloud cover and cosmic ray counts (monthly average counts) (red line) recorded atHuancayo for the period 1985–2005 (after Svensmark 2007)

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parameters such as droplet size, water content and optical depth, in addition to cloud cover.

They analyzed data corresponding to 22 Fd events but failed to find statistically significant

correlations between GCRs and any of these four cloud parameters. They considered

separately six intense Fd events but even in these cases a consistent GCR signal in cloud

parameters could not be deciphered. Kristjansson et al. (2008) commented that ‘‘whether

such a signal exists at all can not be ruled out on the basis of the present study, due to the

small number of cases and because the strongest Fd events indicate slightly higher cor-

relations than the average events’’.

Calogovic et al. (2010) analysed cloud data during six Fd events in detail but could not

find any response of global/local cloud cover to Fd at any altitude and latitude. Svensmark

et al. (2009) analysed data for low clouds during 26 Fd events and claimed significant

reductions in cloud water content (SSM/I data), cloud cover (MODIS, ISCCP data) and

aerosol concentrations (AERONET). Laken et al. (2009) re-analysed the liquid water cloud

fraction (LCF) data obtained by MODIS and found the LCF variations to be unrelated to Fd

events. Thus, the relationship between GCRs and clouds could not be established defini-

tively for these specific periods of satellite-retrieved cloud data. However, this does not

rule out the significance of GCRs in cloud formation processes.

Cosmic rays produce ionization in the atmosphere, which maximizes at around

10–20 km altitude (Neher 1971). Hence any likely effect should be in the high altitude

cloud rather than in low level cloud as claimed (Svensmark 1998, 2007). Erlykin et al.

(2009c) tried to estimate the effect of extra-ionization produced in the atmosphere on

clouds by ionizing agents—cosmic rays, radon and nuclear fallout—but, in a broad search,

could not find evidence for a role of ions in enhancing the probability of cloud droplet

formation, at least in the lower atmosphere (below 3.2 km altitude).

Simulation results of Yu and Turco (2001) showed that charged clusters have a larger

probability of resisting evaporation than uncharged ones, indicating a beneficial influence

on particle formation by GCRs. Kazil et al. (2006) and Yu et al. (2008) presented

Fig. 5 Variation of changes in galactic cosmic ray fluxes derived from 10Be data (light blue), open solarcoronal flux (blue) and low altitude cloud amount (orange) from Fig. 4 scaled and normalized to theobservational cosmic ray data from Climax (red) for the period 1953–2005; note that both scales areinverted (after Svensmark 2007)

Surv Geophys (2011) 32:659–703 673

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simulation results under various atmospheric conditions and found support for the role of

electrical charge for aerosol nucleation. However, no physical process is known through

which the nucleated aerosols could grow to large enough sizes to be of climate relevance.

The hypothesis of GCR-induced ionisation and formation of CCN has been tested in a

climate model that calculates aerosol microphysics in response to GCR (Pierce and Adams

2009). They found that GCR-induced changes in CCN are two orders of magnitude too

small to account for observed changes in cloud properties. Carslaw (2009) has discussed

the negative result of Pierce and Adams (2009) and argued that CCN may be more

sensitive and model dependent and there could be different models/different conditions not

explored by them, where GCR-induced CCN may account for observed changes in cloud

properties. He has also suggested that ‘‘ion-aerosol near-cloud’’ mechanism (Carslaw et al.

2002) is more probable and attention should be shifted to this mechanism.

The observed long term correlation between GCRs and LCC could be explained con-

sidering the influence of solar activity (Erlykin et al. 2009d). The enhanced solar irradiance

causes a rise of the mean surface temperature (Christiansen et al. 2007) and results in

enhanced vertical convection. From below 3 km warm air rises to greater heights and

causes the LCC to decrease and the medium cloud cover (MCC) to increase. During high

solar activity the strength and turbulence level of the interplanetary magnetic field becomes

high, leading to an enhanced shielding of GCRs. Thus, the flux of GCRs reaching the

Earth’s surface decreases. In this way GCRs and LCC both decrease during high solar

activity. Based on this argument no causal connection between GCRs and LCC could be

established (Erlykin et al. 2009d).

The enhanced low altitude cloud coverage and consequent cooling is not valid over the

Antarctic ice sheets, which are dazzling white snow having a higher albedo than the cloud

tops. Snow surfaces act as a better scatterer than the cloud surface so that cloud cover

causes warming rather than cooling. Satellite and meteorological measurements confirm

this (Svensmark 2007).

The cloud cover, cosmic ray and climate hypothesis does not find support from data

analysis and interpretations. Kirkby (2007) reviewed the relation between solar/cosmic

rays and climate variability. He had discussed diverse reconstructions of past climate

change (last millennium, last 10 ky, last 3 My, last 550 My) revealing clear association

with cosmic ray variations recorded in cosmogenic isotope archives, providing evidence

for solar/cosmic ray forcing of climate variability. Physical mechanisms relating cosmic

ray and clouds were also discussed and the need for a thorough experimental study of the

fundamental microphysical interactions between cosmic rays and clouds was emphasised.

Finally he has discussed the upcoming experimental facility known as CLOUD (Cosmics

Leaving OUtdoor Droplets) at CERN (Switzerland). Some of the problems proposed to be

studied are ion-induced nucleation, growth of condensation nuclei into cloud condensation

nuclei, activation of cloud condensations nuclei into cloud droplets, ice particle formation,

collision efficiency of aerosols and droplets and freezing mechanism of polar stratospheric

clouds. Recently Duplissy et al. (2010) based on CLOUD experiments reported a few

events to be related to ion-induced nucleation or ion-ion recombination to form stable

neutral clusters. This seems to be inconclusive evidence on the role of small ions in cloud

formations in ambient atmospheric conditions. In the complex physical process induced by

cosmic ray produced ionisation, such as (a) the production of cloud condensation nuclei

acting as seeds for the cloud droplet formation and (b) modification produced in the GEC

which influences the cloud charging process, there are many unanswered questions (Gray

et al. 2005; Siingh and Singh 2010; Singh et al. 2011). Precise measurements of electrical

parameters from the top to the bottom of clouds, together with measurements of size of

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aerosol particles and droplet parameters and precipitation current could provide some

answers to the understanding of involved complex mechanism in cloud formation.

3 Lightning Discharges and Lightning Activity

3.1 Thunderstorms and GCR Induced Discharges

The occurrence of lightning discharges is a clear manifestation of processes that generate,

separate and lastly neutralize electrical charges in nature. The generation of charge during

thunderstorm development can be grouped under inductive and non-inductive charging

mechanisms. The inductive process relies on the pre-existing electric field to induce

polarisation charges in suspended particles in the atmosphere so as to enhance the electric

field (Yair 2008; Saunders 1993, 2008; Siingh et al. 2008). Such polarisation in the

presence of fair weather electric field will cause an excess positive charge to accumulate in

the lower part of the particle, while negative charge will be located preferably in the upper

part. The non-inductive process is independent of electric field and charge transfer takes

place during particle collisions, drop break–up, ion charging and convection process

(Saunders 2008). During graupel and ice particle collisions, the smaller ice crystals are

charged positively and carried to the upper region whereas large graupel particles charge

negatively and descend relative to the smaller particles due to gravity (Yair 2008; Siingh

et al. 2008). Charging takes place due to temperature differences of the interacting particles

(Saunders 1993). Drop break-up charging occurs when a bubble containing positively

charged liquid inside collides with stronger particles/bubbles. Bursting of such bubbles

releases positively charged jet droplets which are carried into clouds by the local air

current (Blanchard 1963). In the ion charging process, ions produced by energetic particles

are selectively captured and transported to the cloud site (Saunders 2008) by natural

convection. Charge separation is a very sensitive function of temperature, and usually

occurs between the levels where the temperature lies between 0�C and -40�C (Saunders

2008).

Experimental evidence as well as Monte-Carlo calculations suggest that the electric

field strength in the clouds is much lower than the threshold electric field required to

initiate electrical breakdown (Marshall et al. 2005; Dwyer et al. 2006; Stolzenburg et al.

2007). This inhibits the application of the breakdown discharge process to explain the

numerous lightning discharges observed during the active period of a thunderstorm.

Gurevich and Zybin (2001, 2005) proposed the runaway breakdown mechanism operating

at a lower excitation threshold to explain lightning discharges. In the runaway mechanism,

high energy particles (GCRs) in the presence of an electric field generate secondary

electrons of various energies due to the ionization of neutral molecules. The secondary

electrons having sufficiently high energy are accelerated by the electric fields to become

‘‘runaway’’ electrons. This process is repeated many times and, as a result, an exponential

growing avalanche of runaway electrons develops. Simultaneously an immensely large

number of slow electrons are also generated which leads to electric breakdown. In the air,

the conventional breakdown electric field at atmospheric pressure is *23 kVcm-1 and the

runaway breakdown electric field is *2.16 kVcm-1 (Gurevich et al. 2009a). Accurate

measurements of electric fields in thunderstorm show that the field strength never reaches

the value required for conventional discharges (Marshall et al. 2005; Stolzenburg et al.

2007). Thus, runaway breakdown is much more probable than the conventional breakdown

in creating lightning discharges in a thunderstorm. GCRs with energies *1014–1016 eV

Surv Geophys (2011) 32:659–703 675

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could initiate extensive air showers (EASs) and produce energetic secondary electrons and

initiate lightning discharges (Gurevich et al. 2009a, b; Chubenko et al. 2009; Chilingarian

et al. 2009). However, it is not yet possible to identify the percentage of lightning dis-

charges triggered by GCRs. This is a preliminary result and much more work is to be done

before this route of GCR effect on climate can be considered to be effective. It will also

need to be quantified.

A discharge in the presence of a large number of energetic electrons should be

accompanied by a strong pulse of gamma rays. In a number of experiments, a burst of

gamma radiation during thunderstorms has been observed (Eack et al. 1996; Chubenko

et al. 2003; Dwyer et al. 2005; Howard et al. 2008). Gurevich et al. (2009b) reported 4

events of runaway breakdown while an EAS passes through a thunderstorm. Pulses of

gamma radiation in coincidence with EAS were recorded. Exactly at the EAS trigger

moment a strong pulse of radio emission (0.1–30 MHz) frequency band is also measured.

One event was recorded during the initial phase of a thunderstorm and three during the

main phase.

Chubenko et al. (2009) measured the energy spectrum of gamma radiation during the

stepped leader of lightning and the total energy is estimated as *10-3 to 10-2 J. The

measurements were carried out at the Tien-Shan mountain cosmic ray observatory situated

at the height of 3.34 km above sea level, which is an average height of thunderclouds at

Tien-Shan. Thunderstorms are abundant above the observatory during May–September.

The spectrum of gamma-ray emissions observed in the balloon experiment (Eack et al.

1996) and at Tien Shan is in good agreement with the runaway breakdown theory. Pow-

erful emissions of terrestrial gamma ray flashes (TGFs) observed on the CGRO and

RHESSI satellites (Smith et al. 2005) are correlated with high-altitude lightning (Dwyer

and Smith 2005); therefore, they may have resulted from the runaway electron breakdown

effect.

3.2 Lightning Activity and Solar Activity

The dependence of climate on various factors associated with lightning has enhanced

interest in the study of lightning. NASA satellites using sensors such as OTD (Optical

Transient Detector) and LIS (Lightning Imaging Sensor) are continuously supplying

important information on lightning’s spatial and temporal distribution around the planet

(Christian et al. 2003). Analyses of these data yield a global flash rate 44 ± 5 flashes per

second (Christian et al. 2003; Ushino 2003). Higher flash rates have also been reported

(Kotaki and Katoh 1983; Mackerras et al. 1998). The lightning activity is mainly con-

centrated over the tropics; *78% of all lightning flashes occur between ±30� latitude.

There are far more over the land than over the ocean; the average land/ocean occurrence

ratio being about 10:1 (Christian et al. 2003).

Figure 6 shows the variation of sunspot number and lightning flash rates during the

period 1988–2010 (sunspot cycle 22, 23). Lightning flash rates are for the geographical

regions covering the USA, Brazil and the Indian Peninsular region. In the Indian Peninsular

region lightning flash rates and sunspot numbers show an opposite behaviour, whereas

observations at Sao Paulo (Brazil) do not follow that trend—they show maxima when the

sunspot number shows maxima (Pinto and Pinto 2008). There is a secondary maximum

when the sunspot number shows a decreasing trend. Lightning frequency over the USA

shows a minimum when the sunspot number is a maximum and then it shows an almost

constant behaviour (www.slac.stanford.edu/cgi-wrap/getdoc/slac-wp-02-ch11g-kirkby.pdf).

Thus, a complex relation between sunspot number and lightning flash rate is observed.

676 Surv Geophys (2011) 32:659–703

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Based on these limited data it is very difficult to draw any conclusion about the relation

between sunspot number and lightning activity.

Fritz (1878) made the first attempt to correlate thunderstorm frequencies with the rel-

ative sunspot numbers, analysing data collected at different stations in Europe and North

America between 1755 and 1875 and showed a positive correlation at some stations and at

others a negative one. Later on Brooks (1934) using worldwide data reported a low

correlation at mid-latitude and enhanced correlation towards the pole and the equator. He

also found the interesting result that the correlation coefficient changed significantly over

relatively short distances. Aniol (1952) based on data from South Germany between 1851

and 1950 reported an insignificant correlation coefficient (-0.02) for the whole period,

-0.55 for the years 1889–1913 and ?0.74 for the years 1923–1944.

Stringfellow (1974) studied the annual variation of 5 year running means of lightning

incidence in Britain and sunspot number for the years 1930–1973 and reported an

important result relating to an underlying cyclic variation with a period of about 11 year

and in phase with the solar cycle. The correlation coefficient was found to be *0.8.

Schlegel and Fullekrug (1999) showed that Schumann resonance (SRs) of the Earth-

ionosphere cavity and constituting the longest wavelength ELF waves are definitely

affected by solar activity such as solar electron events and solar proton events. On the other

hand, globally correlated amplitude variations of SRs were found to associate with the

solar rotation period (Fullekrug and Fraser-Smith 1996) and that was attributed to geo-

magnetic activity.

Schlegel et al. (2001) studied correlation between lightning frequency and solar activity

parameters (sunspot number, Ap and F10.7 indices, cosmic ray flux) using data from the

German lightning detection system between the years 1992 and 2000. They obtained a

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

10

20

30

40

50

60

70

80

90

100

110

120

130

140

0

25

50

75

100

125

150

175

200

225

250

(b) USA

(c) Indian Peninsular Region (Pereira et al., 2010)

(d) Sao Paulo (Brazil), (Pinto and Pinto, 2008)

(a) Sun Spot Number

Years

Lightning Flashes (X 103), Peninsular India Lightning Frequency (x 106/years), USA Lightning Flashes (X 103), Brazil

Mon

thly

Ave

rage

Sun

Spo

t Num

ber

Fig. 6 a Yearly variation of sunspot number; b yearly variation of lightning flash counts for Sao Paulo(Brazil) along with a linear fit and three point adjacent averaging smoothing (reproduced from Pinto andPinto 2008); c yearly variation of lightning flash counts for USA along with a linear fit and three pointadjacent averaging smoothing (www.slac.stanford.edu/cgi-wrap/getdoc/slac-wp-02-ch11g-kirkby.pdf);d yearly variation of lightning flash counts for the Indian Peninsular Region (India) along with a linear fitand three point adjacent averaging smoothing (from Pereira Felix et al. 2010)

Surv Geophys (2011) 32:659–703 677

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significant correlation of lightning frequency with Ap (geomagnetic index) and sunspot

number and a significant anti-correlation with CR flux. The study relating lightning

amplitude variation with solar/geomagnetic parameters did not yield significant results,

maybe because the amplitude is most probably controlled by meteorological factors and

the electrification process in thunderstorms. During the period of low CR fluxes the

atmosphere is less conducting and therefore a higher electric field can build up causing

more lightning. Even a reduced CR flux (enhanced solar activity) may affect the global

distribution of weather conditions (such as modifications of the vorticity area index, global

circulation pattern) causing thunderstorms.

Figure 7 shows the global distribution of lightning averaged over 9 years of observa-

tions of the NASA OTD (April 1995–March 2000) and LIS (January 1998–December

2003) satellite data. The annual global lightning activity peaks in the summer hemisphere

in agreement with the seasonal migration of the ITCZ (Inter Tropical Conversion Zone)

and the atmospheric circulation patterns (Price 2006). During spring and fall, the distri-

bution of lightning is fairly symmetric about the equator.

The diurnal variation (Fig. 8) shows that thunderstorms are generally active in the

afternoon local time sector as a result of solar forcing, which maximises between 1600 and

1700 h. However, over the oceans, the thunderstorms are equally distributed during the

daytime, since the ocean temperatures are mostly constant throughout the daytime whereas

the land surface temperature shows a strong diurnal variation. Figure 9 shows the annual

variation of total flash rates decomposed into land and ocean (Fig. 9a), northern and

southern hemisphere (Fig. 9b) and tropics and subtropics (Fig. 9c) (Christian et al. 2003).

Lightning activity over the oceans is about 5 flashes per second at all times. However, the

distribution over the land surface peaks in the months of July and August, varying between

31 and 49 flashes per second; the maximum flash rate for the northern hemisphere is

significantly larger than for the southern hemisphere. Sato et al. (2008) showed that

thunderstorms/lightning are mainly continental phenomena and occur more often in the

Fig. 7 Global distribution of lightning (annual flash rate) from 9 years of observations of the NASA OTD(1995–2000) and LIS (1998–2003) instruments (http://sprg.ssl.berkeley.edu/atmos/tgf/UCB-TGF.pdf)

678 Surv Geophys (2011) 32:659–703

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northern hemisphere summer than in the southern hemisphere summer. Figure 9c shows

lightning activity for the globe subdivided into zones of 5�S–5� N latitude, 10�S–10�N

latitude, 20�S–20�N latitude and 30�S–30�N latitude to separate the tropical and sub-

tropical contributions.

Satori et al. (2009) analysed Schumann resonances recorded at Nagycenk (Hungary)

and satellite data from the OTD and the LIS. They showed that more lightning was

observed in the tropical and extra tropical land regions during the warm El Nino periods,

especially in South East Asia, along with minor contribution from oceanic regions, a result

consistent with that reported in Fig. 9c. In the cold La Nina phase, global lightning is

slightly suppressed.

LIS/OTD observations do not provide information about the intensity of lightning fla-

shes (Christian et al. 2003) which is available from other observations (Baker et al. 1995,

1999; Schumann and Huntrieser 2007). Very high frequency (VHF) electromagnetic

radiation observed at ground stations has been used to collect lightning statistics which are

independent of day/night and ocean/land differences (Bondiou-Clergerie et al. 2004; Boeck

et al. 2004; Noble et al. 2004).

Recently Kumar and Kamra (2010) analyzed TRMM (Tropical Rain Measuring

Mission) satellite data over three islands (Carnicobar, Little Andaman and North

Andaman) situated in the south of the Bay of Bengal, in order to resolve the question of size

of an island which is able to exhibit a land–ocean contrast. They have shown that the flash

density and flash rate increase with the increasing area of island. Their results favour the

traditional thermal hypothesis but could not distinguish between the thermal and aerosol

hypothesis (Williams et al. 2004) for the enhancement of lightning activity over islands.

3.3 Lightning Activity, Rainfall and Surface Temperature

Lightning discharges are the result of electrical activity in thunderstorms. The electrical

activity and rainfall are associated with the microphysics and dynamics of deep convective

clouds (Williams et al. 1989), a result supported by a positive correlation between rainfall

and lightning activity in individual thunderstorms (Petersen and Rutledge 1998; Price and

Federmesser 2006; Gungle and Krider 2006). A quite different scenario emerges when data

are analysed on a regional basis over long time scales. The analysis of the long term data

from the TRMM satellite provide three thunderstorm ‘‘chimneys’’ which, ranked from the

most active to the least active, are 1- Africa, 2- South America and 3- South East Asia. The

ranking based on rainfall is 1- South East Asia, 2- South America, and 3- Africa (Christian

et al. 2003; Price 2000, 2009). Thus, the long term data display the opposite relationship

between regional/global lightning activity and rainfall. This paradox is also supported by

the presence of lightning maxima over Argentina, North America, South Africa and the

Himalayas, which are not regions with the highest rainfall (Price 2009).

Williams and Satori (2004) studied the differences between tropical Africa and

tropical South America; they showed that the main difference between lightning activity

in Africa and South America is due to Africa being hotter and drier than South America.

A drier surface may permit the development of a deeper reservoir of unstable air during

the day and can lead to higher cloud base heights and a suppression of warmer rain

coalescence between the 0�C isotherms (Williams et al. 2004, 2005). Carey and Buffalo

(2007) demonstrated that thunderstorms with predominantly positive lightning were

more probable in a drier climate. The above paradoxical behaviour may also be due to

differences in geography, meteorology or other local factors in these regions (Price

2009).

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In order to understand the relation between lightning activity and rainfall, model sim-

ulation studies have also been carried out. These show that lightning activity will increase

in a warmer climate (Price and Rind 1994; Grenfell et al. 2003; Shindell et al. 2006), a

result consistent with the suggestion based on the study of seasonal variations in lightning

activity on the Tibetan Plateau (Toumi and Qie 2004). Model studies also show that, for

every 1�K of global warming, a *10% increase in lightning activity may arise (Shindell

et al. 2006; Futyan and Del Genio 2007). Nath et al. (2009) analyzed satellite data for a

5 year period (1995–1999) over land and ocean regions of India and claimed that a cooling

of 1�C in the surface temperature results in the reduction of ~3.5 thunderstorms per month

per station.

This result is in accordance with the suggestion of Kandalgaonkar et al. (2005) that

every rise of 1�C in surface air temperature may correspond to a 20–40% enhancement of

the lightning flash density. Del Genio et al. (2007) showed that in a warmer environment

the frequency of thunderstorms decreases but the updrafts in the developed thunderstorms

are strengthened by *1 m/s due to a rise in the height of the freezing level; as a result the

developed thunderstorm will be much more intense and hence result in a higher lightning

flash rate. This is consistent with the observations of Williams et al. (2005), yet it con-

tradicts the claims of Williams et al. (2000) that changes of global lightning activity are

mainly caused by changes in the number of thunderstorms. Price (2009) reported that

‘‘drier climate conditions result in fewer thunderstorms and less rainfall; the thunderstorms

that do occur are more explosive, resulting in more lightning activity’’.

The role of surface temperature and humidity on the lightning activity has been

investigated and discussed briefly. Different regions on the surface of the Earth differ in

elevation and topography, atmospheric circulation patterns, proximity to the ocean,

vegetation, industrialization and pollution, all of which may influence the lightning

activity and hence climate. The effects of all these parameters on lightning activity

need to be studied and modelling studies including these factors should be carried

out.

Fig. 8 Diurnal variation (local time) of the global lightning over the land and oceans (http://sprg.ssl.berkeley.edu/atmos/tgf/UCB-TGF.pdf)

680 Surv Geophys (2011) 32:659–703

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Fig. 9 The annual cycle of global flash rate calculated with a 55 day moving average and decomposed into(a) land and ocean contributions, (b) northern and southern hemisphere contributions, and (c) tropical andsubtropical contributions (after Christian et al. 2003)

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4 Lightning, Aerosols and Climate

Studies conducted in different geographic locations on the globe show the urban area effect

on local weather (Orville et al. 2001; Steiger et al. 2002; Soriano and Pablo 2002). Almost all

of them indicate the possible role of air pollution. Westcott (1995) for the first time showed

the urban effect on enhancing cloud-to-ground (CG) lightning activity. Later on many

studies showed that the percentage of positive CG flashes decreases and the total number of

flashes (flash density) increases as an effect of urban area/pollution (Steiger et al. 2002;

Soriano and Pablo 2002; Naccarato et al. 2003; Koren et al. 2005; Stallins and Rose 2008;

Kar et al. 2009). However, no evidence of an increase in peak current of either positive or

negative CG flashes has been reported. These results are explained considering that urban air

pollution contains increased particulate matter/aerosols, which act as cloud condensation

nuclei (CCN). Urban pollution also affects the charge separation mechanism (Jayaratne et al.

1983) in thunderstorms and may enhance negative CG lightning activity (Steiger et al. 2002;

Kar et al. 2009). High concentrations of pollutants in supercooled cloud droplets lead to

negative charging of graupel at higher cloud temperatures, which could extend towards the

cloud base, covering the positive charge centre region (Pruppacher and Klett 1997). This

newly created stretched region of negative charge makes a tripolar charge distribution in the

thunderstorm (MacGorman and Rust 1998). As a result more negative CG flashes are pro-

duced. Enhanced negative CG flashes decrease the relative frequency of positive CG flashes.

Williams et al. (1999) proposed that under continental and polluted boundary layer

conditions, the available liquid water in the storm updraft is shared by an innumerable

number of small droplets, thereby suppressing the mean droplet size and thwarting the

coalescence process. The more available cloud water reaches the mixed phase region to

participate in excess cloud buoyancy, in precipitation formation, and in electric charge

separation and increased lightning activity (Orville et al. 2001; Williams et al. 2002).

Rosenfeld and Lensky (1998) and Kar et al. (2009) showed a deep mixed-phase zone and

ice forming at higher levels for clouds over polluted regions compared to less polluted rural

clouds.

Satellite measurements have shown a dramatic increase of the aerosol concentration over

many countries in Asia due to urbanization/industrialization (Lelieveld et al. 2001; Massie

et al. 2004). This might enhance deep convection and mixed phase processes leading to

elevated electrification and enhanced lightning activity (Zhang et al. 2004). Koren et al.

(2005) analyzed aerosol optical depth and cloud-top pressure data from satellites, studied

the correlation between the aerosol concentration and the structural properties of clouds, and

suggested cloud invigoration by aerosols/pollutants. Recently Altaratz et al. (2010) ana-

lyzed lightning data from WWLLN (World Wide Lightning Location Network) measure-

ments and aerosol and cloud data from Aqua-MODIS. They showed the intricate and

complex relations between the aerosols (biomass burning smoke particles) and lightning

activity in the Amazon basin. They have shown that low aerosol loading increases the CCN

concentration and produces invigoration of the clouds whereas higher values of aerosol

loading inhibit deep convection clouds and diminish their electrical activity.

Aerosols can also affect cloud properties by altering the microphysical processes of

clouds absorbing and scattering solar radiation by modifying the droplet size distributions.

This affects condensation and evaporation rates, latent heat release and collision coales-

cence efficiency (Rosenfeld et al. 2008). In the case of the Amazon basin, heavy smoke

from fires reduced the cloud droplet size (Altaratz et al. 2010) which resulted in a delay of

precipitation onset causing stronger updraft, large hail and intense convection (Andreae

et al. 2004). Cloud simulations have also shown that an enhancement in aerosols/pollutants

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in moist unstable atmosphere can induce clouds to develop stronger updrafts and down-

drafts, grow taller and trigger secondary storm development (Khain et al. 2005; van den

Heever et al. 2006). The absorption and scattering of solar radiation by aerosols result in

the cooling of the surface below the aerosol layer; this stabilizes the lower atmosphere. The

surface fluxes are suppressed, inhibiting deep convective cloud formation (Koren et al.

2004, 2008; Davidi et al. 2009).

The microphysical processes linking aerosols with cloud processes occur in two ways,

namely: (a) by the formation of cloud condensation nuclei (CCN) (Yu and Turco 2001) and

(b) by the modification of the population of freezing of super-cooled water drops (Tinsley

et al. 2001; Tripathi and Harrison 2002). CCN formation can take place via ion induced

nucleation. The observed major ions in the troposphere and stratosphere are complex cluster

ions, containing H2SO4, H2O, HNO3, (CH3)2CO and CH3CN molecules (Viggiano and

Arnold 1995). Out of these gases H2SO4 is a powerful nucleating agent. In the atmosphere,

the OH reaction with SO2 leads to the formation of H2SO4, which rapidly condenses on pre-

existing aerosols. Measurements of SO2 concentrations reveal a high degree of spatial

variability (Speidel et al. 2007). This implies highly variable concentrations of H2SO4 and

hence highly variable nucleation rates and particle growth rates. Thus, the formation and

growth of CCN depend on the spatial and temporal variations of SO2 concentrations in the

upper troposphere. Therefore, precise information on SO2 concentrations in the upper

troposphere and their spatial and temporal variability are needed for use in climate models.

The transport of H2SO4 aerosols to the lower troposphere as well as into the stratosphere

requires careful attention; such clouds markedly affect the Earth’s albedo.

In the second case, the electric field directly affects aerosol and cloud hydrometeor

processes on the edges of cloud boundary by modifying charge-mediated processes. Space

charges are created at cloud boundaries (Nicoll and Harrison 2010), and the region may

become turbulent. Increased ice nucleation and increased scavenging rates of aerosols may

take place. Measurements of the interactions between ions, aerosols and cloud particles are

required; these are difficult. Hence an alternate approach is to make such studies using

simulations and in laboratory experiments.

These discussions indicate that the spatial and temporal variations of the aerosol con-

tent, the availability of moisture in the troposphere and boundary layer instabilities are the

geographical variable phenomena that constrain thunderstorm formation and lightning

production (Stallins and Rose 2008). Even the concentration of aerosols induces cloud

formation in a very complex manner. Large aerosol concentrations may suppress cloud

formation. To investigate this hypothesis additional data from different geographical

locations over the short and long terms and simulation studies, including the contributions

of aerosol concentrations and their size distributions, are required.

5 Lightning, Upper Tropospheric Water Vapour and Climate

Atmospheric water vapour plays a key role in the atmosphere; it is an important trace gas

controlling weather and climate. It is the primary source of the hydroxyl radical in the

atmosphere (Levy 1971), and it influences the heterogeneous chemical reactions that

destroy stratospheric ozone (Rodriguez et al. 1988; Hofmann and Oltmans 1992). Thus an

increased water amount in the upper troposphere/stratosphere leads to a greater ozone loss

and decreased warming of the atmosphere. Climate models predict a 10% increase in water

vapour in the upper troposphere for every 1�K increase of temperature in that layer.

Some models predicted a 20% increase for every 1�K increase in surface temperature

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(Rind 1998). This sensitivity is greater than that predicted by the Clausius-Clapeyron

equation (*6% per 1�K change at 300�K) (Price 2000). This suggests that upper tropspheric

water vapour (UTWV) is greatly influenced by transport from the lower atmosphere.

The transport of water vapour during convection depends on temperature. An increase

in surface temperature enhances the intensity of convection which transports larger

amounts of water into upper level clouds and also increases the cloud height (Price 2000;

Price and Asfur 2006). Intense convection modifies the electrification processes in the

clouds and enhances the lightning frequency, which is correlated with the peak velocity of

updrafts (Baker et al. 1999). After the development stage, a thunderstorm decays which

results in the evaporation/sublimation of clouds and consequently a large amount of water

vapour is deposited in the upper troposphere. This process is shown schematically in

Fig. 10 (Price and Asfur 2006). They showed that about 6 h is required for the develop-

ment of a thunderstorm and the initiation of lightning discharges. A time lag of 8 h

between upper tropospheric cloud amount and upper tropospheric humidity has been

reported (Udelhofen and Hartmann 1995). However, Price (2000) reported a time lag of

*24 h between the lightning activity and upper tropospheric water vapour. Further, there

is a critical temperature (*295�K) above which the surface temperature has to be con-

sidered. Williams and Renno (1993) noted that at many tropical stations lightning activity

was not observed when the surface wet-bulb temperature was below 296 K. They reported

that an increase/decrease of surface temperature by 1 K could cause the lightning intensity

to increase/decrease by 25%. A similar sensitivity based on other studies was reported by

Williams (2005).

The correlations between lightning activity and climate variables (UTWV, humidity,

precipitation) are studied on diurnal temporal scales. It is not clear whether the same

Fig. 10 Schematic diagram showing the stages of development over a 30 h period of tropicalthunderstorms (Price and Asfur, 2006). a The morning temperature—density anomaly at the surface resultsin large-scale updrafts X. b In the afternoon the temperature rises, deep convection develops, continues intothe night hours and is accompanied by rainfall and lightning activity. The updraft also transports largeamounts of water into the upper troposphere. c During the decay of the storm, the rainout process and theentrainment with the dry environment lead to the evaporation-sublimation of the cloud. This deposits largeamounts of water vapour in the upper troposphere as shown in (d) (after Price and Asfur 2006)

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relation would hold for longer time scales such a monthly, seasonal, yearly and even longer

time scales. More studies covering different regions and data for longer time durations are

required to validate the dependence of lightning on UTWV and other variables. It is

believed that on long time scales enhanced tropical convection stabilizes the atmosphere

due to the vertical transport of water vapour to the upper troposphere where the maximum

warming is predicted to occur (Hansen et al. 1984). This is not in line with the proposed

mechanism of Price and Asfur (2006). Therefore detailed studies of lightning activity and

climate associated micro- phenomena are needed either to prove or disprove the hypothesis

of Price and Asfur (2006).

6 Lightning, Atmospheric Chemistry and Climate

The influence of lightning on climate occurs via the production of nitrogen oxides (NOx,

i.e. NO (nitric oxide) and NO2) followed by the production of ozone, one of the efficient

greenhouse gases. Since the initial proposal by von Liebig in 1827, lightning discharges

have been considered to be the largest natural sources of NOx production in the atmo-

sphere (Galloway et al. 2004; Schumann and Huntrieser 2007). The other sources are

microbial actions in the soil (Yienger and Levy 1995; Granier et al. 2004), oxidation of

atmospheric NH3 and the burning of biomass and fossil fuels (Olivier et al. 2005).

The global contribution to NOx from fossil fuel burning is *28–32 Tga-1, from bio-

mass burning *4–24 Tga-1, soil *4–16 Tga-1 (Lee et al. 1997), nitrogen oxide (N2O)

degradation in the stratosphere *0.1–1.0 Tga-1 (Martin et al. 2006), and aircraft exhausts

*0.7–1 Tga-1 (Eyers et al. 2005). Fossil fuel burning also includes NOx emission from

ships (*3–6 Tga-1) (Olivier et al. 2005). Lightning produced NOx amounts to *5 Tga-1

(Christian et al. 2003). The latitudinal distribution of NOx shows that the major contri-

bution comes from the northern hemisphere, in line with lightning activity. The share of

lightning contribution *10% on the global basis, but it rises to *23% in the 35�S–35�N

region (Bond et al. 2002; Neubert et al. 2008). The contribution from lightning was

computed using lightning data for the period 1998–2000 years and assuming production of

6.7 9 1026 and 6.7 9 1025 NO molecules for each cloud-to-ground and intra-cloud flash,

respectively (Bond et al. 2002; Neubert et al. 2008). The field experiment TROCCINOX

shows greatly enhanced concentrations in thunderstorms anvils and enhanced ozone

concentrations downwind (Huntrieser et al. 2007).

The global estimation of NOx production by lightning and thunderstorms is based on

only a few individual measurements; it remains highly uncertain because of the different

types of discharge and differing characteristics such as energy, length, peak current, tor-

tuosity, altitude, number of return strokes, etc. In addition to tropospheric discharges, the

upward discharges between cloud-tops and the ionosphere also contribute to the production

of NOx in the atmosphere (Enell et al. 2008; Sentman et al. 2008; Gordillio-Vazquez 2008,

Neubert et al. 2008; Siingh et al. 2008; Fadnavis et al. 2009). The NOx production per

upward discharge could be taken as *1023–1025 molecules (Neubert et al. 2008: Sentman

et al. 2008) and a total production *1031 molecules per year (based on three events per

minute), which is of the same order as the minimum production of NOx, N2O, N2O5 and

HNO3 by solar proton events during a quiet year (Singh et al. 2005). During an intense

thunderstorm, there could be a significant impact on the local production and budget of

NOx. Based on the measurements by the GOMOS instrument onboard the ENVISAT

satellite, Rodger et al. (2008) showed enhancements of NOx on a local basis but that was

not found on the larger regional scale.

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Nitrogen oxides critically affect the abundance of ozone (O3) and the hydroxyl radical

(OH) in the troposphere (Rohrer and Berresheim 2006). Figure 11 shows the dependence

of OH concentration and O3 production rate on the NOx mixing ratio (Ehhalt and Rohrer

1994; Schumann and Huntrieser 2007). Under clean air condition OH is mainly produced

by O3 photolysis and reactions of the resultant atomic oxygen with water vapour. Under

more polluted conditions, OH is also formed by the photolysis of NO2 during the oxidation

of carbon monoxide (CO), methane (CH4) and non-methane hydrocarbons (Jaegle et al.

2001; Olson et al. 2006).

Tropospheric ozone has an impact on the atmospheric radiative forcing (Hansen et al.

2005). Toumi et al. (1996) showed that a 100% increase in lightning activity enhances the

global mean radiative forcing via tropospheric O3 by *0.3 Wm-2. Hopkins (2003)

computed the global average total radiative forcing due to O3 formed by lightning induced

NOx (*6.5 Tga-1) to be *0.1 Wm-2. Model studies show an increase in lightning

activity and lightning induced NOx due to global warming (Price and Rind 1994; Unger

et al. 2006; Schumann and Huntrieser 2007). However, Stevenson et al. (2005) and

Sanderson et al. (2006) did not find any change in global lightning emissions over the

projected period 1990–2030, but found significant changes in their regional distribution.

Doherty et al. (2006) showed a correlation between the El Nino phenomena and ozone. In

fact both lightning occurrence and NOx increase during El Nino periods, explaining the

inter-annual ozone variability of *3% in the tropical upper atmosphere (Grewe 2007).

The reaction of NO2 with OH during daytime forms HNO3, and during the nighttime

NO2 reacts with O3 to form NO3 and oxidation of NO2 by NO3 forms N2O5 (van Noije

et al. 2006). The oxidation products leave the atmosphere in the form of ‘‘acid rain’’

(Logan 1983). Brasseur et al. (2006) have shown that an increased tropospheric water

vapour concentration may dampen O3 increases from increased lightning induced NOx.

Nitrogen oxides act as a feedback agent between lightning and climate, for which the

precise knowledge of the lightning-induced NOx production, distribution, and its role in the

production/destruction of ozone is important. In addition, a detailed understanding of the

oxidizing capacity of the atmosphere and the lifetime of the trace gases destroyed by

reactions with OH is essential in quantifying the feedback processes between climate and

Fig. 11 Variation of the OH concentration and the net production rate of O3 with the mixing ratio of NOx

shown. A steady state box model for the diurnal average in June at 10 km altitude and 45� latitude has beenused. The other parameters used are O3 mixing ratio: 100 nmol-1; H2O: 47 lmol mol-1 CO:120 nmol mol-1; CH4: 1,660 nmol mol-1 (Enhalt and Rohrer 1994; Schumann and Huntrieser 2007)

686 Surv Geophys (2011) 32:659–703

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lightning. There is large error in estimating the annual production of NOx by lightning

(Neubert et al. 2008; Schumann and Huntrieser 2007). The uncertainty range is much more

than the total production of NOx; hence future work should aim to reduce the uncertainty

range from the present value of ±3 Tga-1 (Schumann and Huntrieser 2007).

7 Atmospheric Conductivity, Lightning and Climate

The electrical conductivity of the atmosphere depends upon the distribution of both

positive and negative ions in the atmosphere. The principal source of ionization in the

lower and middle atmosphere is galactic cosmic rays; near the ground additional ionization

is produced due to the release of radioactive gases from the soil. Above 60 km altitude

solar far ultraviolet radiation becomes an important source. The solar cycle variation in

GCR flux could produce a 5% variation in the ionization of the troposphere and strato-

sphere at low latitudes and about 10–20% at high latitudes (Tinsley 2008). However,

during a magnetic storm, ionization due to energetic electron precipitation from the

magnetosphere, auroral electrons and auroral X-ray bremsstrahlung radiation, along with

that produced by proton bombardment (during solar proton events, SPEs) becomes sig-

nificant, especially in the high-latitude polar atmosphere (Kokorowski et al. 2006).

The conductivity of the upper stratosphere and mesosphere occasionally increases when

there is an unusually large flux of energetic solar protons (*100 MeV) within the polar

cap (Von Biel 1992), or at mid latitudes (Stephenson and Scourfield 1991) during a

relativistic electron precipitation (REP) events. Even lightning-generated whistler mode

waves cause the precipitation of energetic electrons which may enhance the electrical

conductivity locally (Singh et al. 2004; Siingh et al. 2005, 2007, 2008; Rycroft et al. 2007;

Inan et al. 1988, 2007). Upward lightning discharges (sprites, elves, blue jets, blue starters

and gigantic jets) from the top of a thundercloud to the lower ionosphere cause local

electrical breakdown of the atmosphere and produce a transient and localized enhancement

in conductivity in addition to that produced by precipitated energetic electrons (Inan et al.

1988, 1996, 2007; Singh et al. 2005; Fadnavis et al. 2009). The conductivity inside a

thundercloud and in the fair-weather region depends on geomagnetic latitude, height and

aerosol pollution, varying between *10-14 Sm-1 (at the surface of the Earth) and

*10-7 Sm-1 in the ionosphere (at *80 km height) (Rycroft et al. 2008). The enhance-

ment in conductivity may lower the ionosphere above a thundercloud sufficiently to trigger

an upward lightning discharge between the cloud and the ionosphere (Armstrong 1987).

Variations in the vertical conductivity of the troposphere and stratosphere cause vari-

ations in the fair weather vertical current Jz. Apart from the variations caused by external

sources, the vertical current is also affected by day-to-day variations in the ionospheric

potential due to changes in the thunderstorm sources, the highly electrified deep convective

clouds mainly over the humid low latitude land areas of Africa, the Americas and northern

Australia/Indonesia (Tinsley et al. 2007). Regional and global changes in the conductivity

of the atmosphere due to changes in natural and anthropogenic aerosol loading also cause

variations in the ionospheric potential and hence in the vertical current. The ionospheric

potential is positively correlated with both global temperature and global lightning activity

(Markson and Price 1999). Reeve and Toumi (1999) considered that a warmer atmosphere

leads to a more deep convection resulting in higher ionospheric potentials.

The current Jz causes space charges to be formed at the top and bottom of clouds. These

may affect their microscopic/macroscopic processes and droplet formation related to

clouds in the fair weather region, and may produce an integrated effect which could result

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into short term/long term variations in weather/climate (Tinsley 2000; Williams 2005;

Price and Asfur 2006; Siingh et al. 2007, 2008). The space charge created attaches to

aerosol particles, cloud condensation nuclei (CCN) and ice forming nuclei (Tinsley et al.

2001). An increase in Jz may cause the enhancement of electro-scavenging and ice for-

mation, depending on the droplet size distribution (Tinsley 2000), or modify droplet

evaporation (Harrison and Ambaum 2008). This enhanced electroscavenging of larger

CCN and aerosol particles may protect the smaller CCN and aerosol particles from

scavenging (Tinsley 2004) and may result in a narrowing of the droplet size distribution.

As a consequence of this, there may be both reduced precipitation and enhanced cloud life.

These two processes simultaneously compete and the net result depends upon local tem-

perature, the aerosol environment, the GCR flux and cloud dynamics.

Measurements show the presence of droplet of radii *6 to 8 lm and positive charges of

80–90 electronic charges (e) in downdrafts at cloud tops and droplets of negative charges

(50–90 e) in updrafts near the cloud base (Beard et al. 2004). The magnitude and sign of

the charges near the cloud boundaries are consistent with the calculations of droplet

charging caused by the flow of Jz through clouds (Zhou and Tinsley 2007; Tinsley et al.

2007). The charging time constants range from minutes to hours, which are comparable

with the characteristic time scales of convection and turbulence in the troposphere (Tinsley

2008). This shows the need to develop a time dependent cloud and aerosol charging model,

including turbulence and convection processes.

Figure 12 shows variation of surface air temperature and observed thunder days in

Fairbanks, Alaska (65�N) for the period 1950–2005 (Williams 2009); a linear fit to the data is

shown. The variation has been considered for summer months (June, July, August and

September). The data show an increase of about 2�C over 68 years (Williams 2009) which is

correlated with the increase in the number of thunderstorm days. The enhancement in

thunderstorm activity as the surface temperature increases is in accordance with the

hypothesis that surface warming enhances the convection process and thunderstorm activity.

The response of atmospheric conductivity/vertical current and lightning to climate and

vice versa are known based on the analysis of short periods of data and different regions on

the Earth’s surface. Because both climate and lightning on a local/regional basis are also

influenced by a number of factors such as topography, ocean currents, atmospheric cir-

culation, vegetations, precipitation pattern, etc.; isolated regional and short term studies do

not reflect the global and long term behaviour. Therefore any modelling work on the basis

of short period input data would represent its applicability to that region only. For global

modelling, one requires input data over larger areas of the globe and the trend should be

valid for the long term.

Atmospheric temperature changes show correlations with thunderstorm activity and also

with the measured or inferred changes in the Earth-ionosphere vertical current density Jz.

These responses are consistent in onset time, duration and sign of the response. The pro-

duction of electric space charges at the conductivity gradient at the edges of clouds by the

flow of Jz through them (Nicoll and Harrison 2010) needs to be related to the electrical

scavenging and other cloud processes. However, their quantitative overall effect on cloud

formation, and the cloud cover at different latitudes and altitudes, remains to be worked out.

8 Summary

In this paper, we have briefly summarized our present understanding of the terrestrial

climate as affected by solar forcing, galactic cosmic rays (GCRs), lightning discharges and

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associated processes. The importance of solar irradiance on climate has been reviewed; it is

shown that the ‘‘little ice age’’ and other climate variations could be explained based on

observations/modelled variations in the intensity of galactic cosmic rays (Sect. 2.4).

Cosmic rays may influence the complex electrical processes involved in cloud develop-

ment. The tops of clouds scatter the Sun’s radiation back into space, producing a cooling

effect, and high level clouds reflect back long wavelength thermal radiation emitted by the

Earth, leading to a warming effect (Sect. 2.4).

Solar irradiation varies according to solar magnetic activity; however, the physical

processes linking magnetic activity to solar irradiance is not worked out. Solar irradiance

measurements, the trend of the variations and anthropogenic effects have been used to

forecast global warming over the next decades. Non-linear processes, which are hard to

model, are involved. The complexity of the physical processes involved, deficiencies in

long term data sets and further refinements in data analysis techniques require further

research to improve our understanding of climate forcing by the Sun and other processes.

Enhanced solar activity results in a decreased cosmic ray intensity reaching the Earth’s

surface due to enhanced GCR scattering by irregularities of the interplanetary magnetic

field. The correlation between GCR and cloud cover was initially proposed to be the result

of cosmic ray induced cloud formation. But reanalyses of the same satellite cloud data and

grouping them under different types of cloud did not support the cosmic ray induced cloud

cover hypothesis (Sect. 2.4). Even the detailed analysis using different cloud parameters

during Forbush decreases (sudden reduced cosmic ray intensity events) did not support the

cosmic ray cloud cover hypothesis. However, some weak signatures of GCR in cloud cover

during a rather small number of relatively intense Forbush decreases events are observed

1950 1960 1970 1980 1990 2000 2010

0

5

10

15

20

Num

ber

of T

hund

er D

ays

Years

Linear Fit

Summer Thunder Days,Fairbanks, AK

52

54

56

58

60

62

Tem

pera

ture

(0 F)

Linear fit

Summer Average Temperature,Fairbanks, AK 1950-2005

Fig. 12 Variation of a summer time surface air temperature (upper panel) and the number of thunder days(June, July, August, September) (lower panel) for Fairbanks, Alaska (after Williams 2009)

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(Sect. 2.4), or in analysis of non-satellite cloud data specific to a single location. There is

some experimental evidence that the initiation of lighting discharges may be caused by

high energy cosmic ray particles (Sect. 3.1). Enhanced solar activity causes enhanced

vertical convection (due to the increased Earth surface temperature) leading to increased

medium and high altitude cloud cover whereas low altitude cloud cover is decreased

(Sect. 2.4).

Recent observations show that, due to an increase in the Earth’s surface temperature,

both thunderstorm occurrence and lightning flash rates are enhanced, while model studies

show that the thunderstorm rate will decrease but the storms will be vigorous and may

produce higher flash rates (Sect. 3.2). Such model studies have not yet included the role of

aerosols which play significant role in cloud formation processes. Even the small, 1�C

change in surface temperature associated with global warming is expected to change the

aerosol distribution in the troposphere and the vegetation of the land surface, affecting the

distribution of humid air and the rainfall (Sect. 3.3). These parameters will affect thun-

derstorm formation and dynamics; their role should be included in any realistic model

study. Further, our present knowledge of lightning-climate relationships is based on very

limited data in space and time. Hence much more data collection and analysis, along with

theoretical studies, are required to understand future trends of lightning activity and their

relation to climate.

The enhanced surface temperature leads to enhanced convection and enhanced upward

transport of water vapour, creating a drier land surface (Sect. 5). Observations show that

intense rainfall is associated with less lightning and vice versa. These observations are

explained by assuming that drier climates have fewer but more intense thunderstorms, as

confirmed by model studies. Increased convective activity moistens the upper troposphere

by transporting additional water vapour upwards (Price and Asfur 2006). This enhanced

‘‘moisturising’’ due to UTWV may drive the maximum warming in climate models in a

double-CO2 world (Price 2009). The enhancement in surface temperature will also affect

the distribution of aerosols in the troposphere resulting in enhanced lightning activity

(Sect. 4). Thus, efforts should be made to separate the thermodynamic and aerosol effects

quantitatively in future modelling work.

Lightning discharges are a major source of NOx production in the atmosphere, which

affects the stratospheric ozone population, a major controller of solar ultraviolet radiation

reaching the Earth’s surface. The latitudinal and longitudinal distribution of lightning cause

similar variations in the production of atmospheric NOx. The spatial and temporal varia-

tions of aerosol content, UTWV, pollution, NOx, local surface temperature and boundary

layer instabilities are geographically varying phenomena that constrain thunderstorm

formation and the production of lightning. Hence, extensive study is required taking data

from different regions in order to arrive at more precise conclusions (Sects. 5, 6).

Meteorological effects, such as cloud cover changes, temperature changes in the tro-

posphere, and changes of UTWV in both disturbed and fair weather parts of the Earth

affect the electrical activity of thunderstorms/lightning discharges and the vertical con-

duction current density, Jz. The responses in the vertical current with changes in solar

activity and internal forcing are consistent in onset time, duration and sign of the current

(Sect. 7). The microphysical phenomena involved in the formation of cloud condensation

nuclei, the ion-assisted formation of ultrafine aerosols, electro-scavenging of ice-forming

nuclei, ice nucleation capability of charged aerosols, and the effects of cloud droplet charge

on precipitation efficiency are not yet quantitatively tested. More work in this area is

required.

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Acknowledgments This work was inspired by discussions which DS had with Prof. B.N. Goswami andsuggestions given by him during his previous work on the role of cosmic rays in the Earth’s atmosphere.RPS acknowledges the facilities provided by the Head, Department of Physics. BHU, Varanasi. The authorsthank the four anonymous reviewers for their critical comments which helped to improve this paper. Theyalso express their gratitude to Prof. M. J. Rycroft for his valuable suggestions.This work was supportedunder the collaboration programme of IITM, Pune and BHU, Varanasi, and also partially supported underCAWSES programme (DS). The authors thank Mr Kirankumar Johare for help with correcting the figures.

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