The atmospheric electric potential gradient variation at land stations

Arch. Met. Geoph. Biokl., Ser. A, 18, 345--363 (1969)

551.594.11 : 551.594.9

Department of Transport, Meteorological Branch, Toronto, Ontario, Canada

The Atmospheric Electric Potential Gradient Variation at Land Stations BHARTENDU

With 4 Figures

Received April 30, 1969

Summary Electric potential gradient variation at several land stations is studied. Diurnal curves in GMT and local standard time are different from station to station. For a station, fair weather diurnal curves are similar to all weather curves. Seasonal variations are calculated and power spectra are computed. Harmonic analysis is used to compute the percentag e contribution to variance and the time of maximum of 24, 12, 8 and 6 hr. oscillations. Correlation coefficients of the hourly and monthly means are calculated for over one hundred and fifty station pairs. In general, low correlation coefficients are found.

Zusammenfassung Die Schwankungen des luftelektrischen Potentialgradienten an Landstationen Es wurden die Anderungen des elektrischen Potentialgradienten an mehreren Landstationen untersucht. Die Tagesg/inge zeigen nach Weltzeit und nach Orts- zeit Unterschiede yon Station zu Station. An einer Station sind die Tagesg~inge an Sch6nwettertagen den als Durchschnitt aller Tage berechneten Tagesgfingen fihnlich. Es wurden auch jahreszeitliche gnderungen und Potenzspektren berechnet. Harmonische Analysen ergeben den prozentuellen Beitrag zur Varianz und die Eintrittszeiten der Maxima der 24-, 12-, 8- und 6st/indigen Schwingungen. Ffir mehr als 150 Stationspaare wurden Korrelationskoeffizienten fiir die stfindlichen und monatlichen Mittelwerte berechnet; im allgemeinen ergeben sich dabei nur kleine Korrelationskoeffizienten.

1. Introduction

T h e classical g loba l concept of a tmospher i c e lec t r ic i ty envisages the ea r th a n d the ionosphere (equa l i z ing layer) as the two c o n d u c t i n g p la tes of a spher ica l capac i to r s epa ra t ed by an i mpe r f e c t l y i n s u l a t i n g

Arch. Met. Geoph. Biokl. A. Bd. 18, H. 3-4 23

Arch. Met. Geoph. Biokl., Ser. A, 18/3-4

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BHARTENDU

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Springer-Verlag / Wien. New York Druck: H, Hiegberger, Pottenstein

346 BHARTENDU

atmosphere. The electrical current which flows within the capacitor, is, in general, considered to be controlled and maintained by the terrestrial thunderstorm activity. In addition to the global circuit, local electrical circuits caused by man-made and natural events in the environs of the measuring stations influence the atmospheric electricity measurements. One of the most challenging problems to date is to separate the contribution of these two circuits. The electric field at a station is affected by local generators, the local columnar resistance, the potential difference between ionosphere and the ground at the station, and local conductivity. At globally representative stations, it is assumed that during fair weather when the influence of the local generators can be neglected, the columnar resistance is sufficiently constant and hence the electric field is governed by the potential difference between the ionosphere and the ground, and local conductivity. At land stations, the measurements are further complicated because the local columnar resistance is not constant. The stations in polar regions, at oceans, and on mountain tops are usually considered to be globally representative but they also suffer from deficiencies such as possible auroral influences, Blanchard's bubbling effect, and orographic difficulties (H. DOLEZAEEK [1]). The land stations are easily accessible. Enormous data have been collected for land stations over the globe and the studies have in- volved comparison of the results of several land stations using different techniques. S. J. MAUCHLY [2] studied the diurnal variation of the potential gradient over several continental areas and by using harmonic analysis, compared the Carnegie results with those of various land stations. From these he concluded that there was a world-wide effect of twenty-four hour period progressing accord- ing to universal time (GMT). J. G. BROWN [3] calculated the global variation, which he termed unitary variation, for twenty-two land stations by multiplying the ocean variation by the ratio of the mean land-gradient at each station to the mean ocean gradient. N .A. PAI~AMONOV [4] divided sixty extrapolar continental stations in groups of 15 o longitude and computed the diurnal averages for each group in local times. He then arranged these averaged curves for twenty-four groups in GMT and after superimposing them obtained an average curve for land stations which resembled closely the ocean and polar curves. He thus showed that the global effect was dis- cernible also at land stations. Several other studies comparing the diurnal variations of the atmospheric potential gradients for various stations throughout the world have been published, for example, by

Electric Potential Gradient Variation at Land Stations 347

H. HATAKEYAMA and M. KAWANO [5], H. ISRAi~L [6], H. ISRAEL, H. DOLEZALEK and G. FRIES [7], H. DOLEZALEK [8], I. M. IMYANITOV and K. S. SHIFRIN [9], R.V. ANDERSON [10], and H. ISRAi~L and P. DE BRUIJN [11], among others.

This paper discusses the results of the analyses performed on the potential gradient data obtained for a two-year period and published by the atmospheric electricity data centre at Leningrad, U. S. S. R. The diurnal and seasonal variations are studied. A power spectrum analysis is performed to determine the 27-day period component. The correlation coefficients are computed for hourly and monthly means. Harmonic analysis is used to evaluate the amplitude and phase contribution of diurnal, semi-diurnal, terdiurnal and quarto-diurnal components.

2. Data and Analysis

The potential gradient data used in this paper were for a two-year period from January 1964 to December 1965, from the monthly publications titled "Results of Ground Observations of Atmospheric Electricity" and published by U. S. S. R. Chief Administration of the Hydro-Meteorological Service, A. I. Voeikov Main Geophysical Observatory, Leningrad. It is evident from these publications that different definitions of fair weather have been adopted by different scientists, for their stations. Yet it is reasonable to assume that the effect of the local generators will be negligible during fair weather for every station and the effect of the global generator will pene- trate the troposphere to the ground. This assumption does not mean that the global effect will be evident from the records in fair weather. The influence of local columnar resistance is usually large and this will obstruct any recognition of the global effect. However, it is possible that if sufficient data were considered for a long period for various stations around the earth, the local effects of columnar resistance may cancel out and one may obtain a global curve.

The data have been analysed separately for fair weather and all weather and comparisons were made. Diurnal variations have been computed by determining the average curves in GMT and local standard time (LST) for all months in 1964 and 1965. The above- mentioned publications give the values only in GMT. The local standard times for the stations were obtained from the "Rand McNally Commercial Atlas and Marketing Guide" 75th Edition. Rand McNally and Company, New York, 1944.

23*

348 BHARTENDU

The correlation and harmonic analysis formulae are available in standard text books. Instead of computing the usual Fourier amplitude and phase coefficients (H. ISRAi~L [12], S. J. MAUCHLY [2]), the percentage contribution to the total variance and the time of maximum (H. PANOFSKY and G. W. BRIER [13]) of 24-, 12-, 8- and 6-hour period waves are calculated. This ensures easy comparison. The power spectrum analysis procedure has been described by R. B. BLACKMAN and J. W. TUKEr [14]. The Nyquist frequency for the spectra is fixed at 0.5 cycle per day and the maximum lag is 108 days (about 15 % of the total duration).

3. Results

3.1. D i u r n a l V a r i a t i o n

The daily variation of the potential gradient during fair weather for sixteen stations is shown in Fig. 1. The diurnal variation during all weather is also exhibited in the figure. The surprising result is the similarity of all weather and fair weather curves. Except for the station Irkutsk and Bolshaja Elan, both curves are similar. For Lisboa and Socorro, the curves are almost superimposed on each other. With the exception of Bolshaja Elan, the daily mean value of the potential gradient during all weather is lower than that during fair weather. This is due to the general lowering or reversing of the potential gradients during disturbed weather. Some local source of positive charge at Bolshaja Elan is likely to be responsible for the anomaly present there.

The all weather, as mentioned in the above-mentioned publication, includes severe weather phenomena like snow, rain, etc. when the potential gradients jump to very high positive or negative values. The atmospheric electricity instrumentation, unless it consists of a logarithmic recorder, or an automatic switching system, or a twenty-four hour human supervisor, will exclude the extreme bad weather values for they will simply be off scale. The publications do not provide descriptions of stations or instrumentation and hence it is difficult to determine as to how effective this limitation actually is but it appears likely that this instrumental limitation is responsible for the similarity of all weather and fair weather curves as exhibited in Fig. 1. If the instrumentation has a large dynamic range, severe weather values will be recorded and in that case the all weather variations may not be similar to the fair weather curves.


The diurnal variation in local time for flat land stations with small pollution shows one maximum in the afternoon and is called "Pots- tam type" (H. ISRAi/C [15]) and for stations in polluted areas shows two maxima and is called "Kew type" (H. ISRai/L [15]). H. ISRAi~L [15] has further shown that for several stations the diurnal variation does not fall into either of these two defined groups and is complex and even for the stations where the diurnal curve may be identified by one of the two groups, there is a seasonal variation. The diurnal variations in local standard time, for the sixteen stations, are presented in Fig. 1 and, es evident from Fig. 1, are different. The curves for Budapest, Dourbes, and Uecle are "Kew type", and for Lisboa and Potsdam are "Potsdam type". The daily curves for Irkutsk, Kakioka, and Murmansk are like "Kew type" but the time of maxima and minima are different. The diurnal variation curves for Dusheti, Odessa, and Socorro are mirror images of "Potsdam type" curve. The behaviour of diurnal potential gradient curves at Voeikovo, Vysokaya Dubrava, Kiev, Memambetsu, and Bolshaja Elan is quite different. The diurnal curves in GMT, as exhibite d in Fig. 1, are quite dissimilar and it is likely to be due to different variations of columnar resistance and local conductivity at these stations.

3.2. S e a s o n a l V a r i a t i o n

The seasonal variations of the potential gradient during fair weather and all weather were computed and are exhibited in Fig. 2. The fair weather mean potential gradient is, in general, maximum in northern hemispheric winter. This is in agreement with the observations of H. ISRAi/L [15] who has asserted that annual variation is composed of global and local component and also has a seasonal variation. This seasonal variation is similar to the seasonal variation of the ionospheric potential (B. B. HUDDAR, G. P. SRIVASTAVA, and A. MANI [16]), which shows maximum in December--February and minimum during June--August. The seasonal behaviour of the all weather potential gradients is similar to that of fair weather. The objections of the all weather values as pointed out before may be valid here too and may be responsible for the similarity. The seasonal variation is, however, opposite to that for thunderstorm. H. C. KRUMM [17] has shown that earth experiences maximum thunderstorms during June--August , and minimum during Decem- be r -February . It may be argued that the data used by H. C. KRUMM [1 7] is weighted in favour of northern hemisphere where land area

KAKIOKA

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BI~A~TEYDU: Electric Potential Gradient Variation at Land Stations 35l

is more than in the southern hemisphere and does not include thunderstorm values over oceans accurately because of the scarcity of observers on the seas. During the northern hemispheric winter, the southern hemisphere experiences summer and is likely to have more thunderstorms, but they are simply not recorded because the land area is relatively small. Until accurate data of thunderstorms are available, it will be difficult to say with certainty that seasonal variation of the potential gradient is opposite to that of the thunderstorm.

3.3. P o w e r S p e c t r u m

It has been shown (e. g. A. K. KAMRA and N. C. VARSI4N~YA [18]) that the electric potential gradient shows remarkable variation during solar eclipse. H. ISRAEL [15] has discussed a 27-day period component in the potential gradient variation.

Power spectra for nineteen stations were computed. It is found that three stations show a definite maximum in the spectrum at 27-day period oscillation, and three stations show no presence of maximum. The data analysed are only for two years and hence it is difficult to make the frequency resolution A[ in the spectrum better than 4.625.10 -8 day -1 without sacrificing the stability of the spectra. Consequently, the next higher period than 27-day in the spectrum is 31-day and the next lower than the 27-day is 24-day. Seven

spectra exhibited maximum in the frequency range of (~-7--A/)

t o (~ -7+A/ ) day -1. Six spectra showed a maximum at day -1

afrequencywithin(~--~+_2A[) day -1.

Fig. 3 shows spectral density estimates (power spectra) of four stations. The spectral density estimates for Socorro shows a maximum

27-day period, for Kiev, at 24-day period ]frequency (~@-@ t

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4.625 �9 10-3 ) day-~ J, for Lisboa at 31-day period [ frequency ( 217

4.625.10-a/day-~| , and for Murmansk shows no maximum. x - 1

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3.4. H a r m o n i c A n a l y s i s

Table 1 summarizes the annual values of the percentage contribution to the total variance and the time of maximum in GMT of 24-, 12-, 8- and 6-hour components during fair and all weather.

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BHARTENDU: Electric Potential Gradient Variat ion at Land Stations 353

The total percentage contribution to variance of the diurnal, semidiurnal, terdiurnal, and quarto-diurnal components is over eighty percent for Murmansk and Vysokaya Dubrava, and over ninety percent for all the remaining stations. The fair weather diurnal component contribution is greater than that of all weather with the exception of Murmansk, Budapest, Uccle, and Socorro where the reverse is true. This suggests that, in general, the weather responsible for reverse potential gradients, suppresses the diurnal component.

The variance is found to be maximum either for diurnal component or for semi-diurnal component. Fig. 4 illustrates the contributions to variance of diurnal component (ca), semi-diurnal component (c2),

Table 1. Harmonic Coefficients of the Electric Potential Gradient

Station Period Fair Weather All Weather hr. Time of Var. % Time of Var. o/o

max. GMT max. GMT

Bolshaja 24 19.1 92.6 20.2 81.7 Elan, USSR 12 10.8 0.2 0.2 11.9 (46 o 55' N, 8 6.0 4.3 7.1 1.5 1420 44' E, 31 m) 6 2.3 1.4 1.7 0.8 Vysokaya, 24 13.5 69.2 18.7 33.5 Dubrava, 12 6.2 9.4 6.4 37.0 USSR 8 4.8 8.3 5.5 18.9 (560 44' N, 6 6.0 0.6 1.4 2.2 61 o 04'E, 290 m) Irkutsk, 24 9.7 66.5 19.1 64.8 USSR 12 1.5 22.1 4.1 22.9 (520 16' N, 8 2.5 4.8 1.1 1.2 104 o 19'E, 467 m) 6 1.8 4.3 2.6 7.6 Lisboa, 24 14.8 93.1 14.3 90.4 Portugal 12 9.1 3.9 9.8 6.7 (380 46' N, 8 0.8 1.4 1.4 1.5 090 09'E, 81 m) 6 1.9 1.1 1.8 0.9 Odessa, 24 12.2 70.9 15.0 50.8 USSR 12 8.0 19.5 8.0 43.2 (46 ~ 29' N, 8 7.0 1.I 2.5 0.6 30 ~ 38' E, 20 m) 6 4.8 1.5 2.6 1.8 Uccle, 24 14.2 48.8 14.5 54.0 Belgium 12 8.8 47.6 8.8 36.8 (500 48' N, 8 1.3 0.5 0.4 0.6 40 21'E, 100 m) 6 1.9 1.7 2.1 2.0 Budapest, 24 16.2 31.1 16.0 81.7 Hungary 12 10.3 53.8 9.9 16.1 (470 26' N, 8 1.5 6.4 0.5 t.3 19 o I I ' E , 139m) 6 3.3 5.0 3.7 0.2 Dusheti, 24 10.9 75.3 10.1 57.8 USSR 12 7.4 14.2 7.3 30.7 (420 05' N, 8 6.8 7.3 7.0 4.6 440 42' E, 910 m) 6 0.8 2.5 1.5 1.2

354 BHARTENDU

Table 1. Continued

Station Period Fair Weather All Weather hr. Time of Var. % 'rime of Var. ~

max. GMT max. GMT

Kakioka, 24 0.7 40.8 0.0 36.9 Japan 12 0.2 52.2 11.8 49.3 (36 ~ 14' N, 8 0.5 3.1 0.0 7.0 1400 11' E) 6 5.4 2.3 4.9 3.4

Memambetsu, 24 2.0 9.9 0.5 6.0 Japan 12 1.2 62.6 0.8 80.8 (43 ~ 55' N, 8 0.8 20.8 0.5 9.2 1440 12' E) 6 1.4 1.8 1.3 1.8

Potsdam, 24 16.0 50.8 13.6 36.8 Germany 12 8.8 37.3 8.7 55.0 (520 23' N, 8 5.6 7.0 7.5 3.5 13 o 04' E, 106 m) 6 1.6 0.6 2.1 2.7

Voeikovo, 24 15.4 73.9 15.1 69.1 USSR 12 8.3 22.3 7.6 18.1 (590 57' N, 8 7.1 2.5 6.8 I1.0 300 42'E, 72m) 6 1.8 0.6 2.1 0.2

Dourbes, 24 15.1 58.7 16.2 28.2 Belgium 12 9.2 36.9 9.1 54.1 (50 ~ 06' N, 8 3.3 2.9 7.4 3.7 040 36' E, 220 m) 6 3.6 0.3 0.7 3.4

Kiev, 24 14.1 74.8 15.6 67.9 USSR 12 9.6 9.2 8.5 25.5 (500 27' N, 8 6.7 8.9 6.3 2.4 30 o 30' E, 166 m) 6 4.9 0.3 5.9 0.5

Murmansk, 24 15.5 64.5 16.8 85.6 USSR 12 4.8 14.8 8.5 7.2 (680 57 'N, 8 4.1 0.8 6.7 4.2 33 o 03' E, 63 m) 6 1.0 4.2 1.1 0.6

Socorro, 24 19.4 82.6 19.9 87.2 USA 12 7.8 16.5 7.7 11.9 (340 04' N, 8 3.4 0.3 5.0 0.1 1060 55' W, 1440 m) 6 5.2 0.1 3.0 0.0

terdiurnal component (ca) and quarto-diurnal component (q). For Odessa and Vysokaya Dubrava, cl is maximum, for Memambetsu c~ is maximum, and for Uccle ct and c2 are almost equal. For Odessa, cl and q are much greater than c a and c A and ratios cJq, q /q , cJq, ca/c 2 and q/c~ are 0.3, .02, .02, .06, and .08, respectively. For Vyso- kaya Dubrava, c2 and c a are close to each other; the ratio c~/c2 being .9. For Memambetsu, c 2 and c a are larger than q. The ratio cJq and ca/c a are 6.3 and 2.1 respectively.

It is also noted that, with the exception of Vysokaya Dubrava, Potsdam, Dourbes and Budapest, whether the ratio c2/q, is larger or smaller than 1 during fair weather, it remains so also during all weather.


It was convenient to divide the stations into two groups; group A which shows that in the harmonic analysis for the data averaged for whole year, the diurnal component (q) is maximum, and group B where semidiurnal component (Q) is maximum. On the basis of seasonal variation of harmonic coefficient, group A stations were further subdivided into type A 0, A a, A2 and A 3. The type A0 stations showed that the diurnal component was maximum in all the four season. Socorro, Dusheti and Lisboa are type A0 stations. Type A1 stations which included Odessa, Bolshaja Elan, Dourbes, Kiev, Irkutsk, Vysokaya Dubrava and Murmansk showed that in one season the semidiurnal component was maximum instead of the diurnal component, although in the yearly averages, the diurnal component showed largest value. The stations Odessa, Bolshaja Elan and Murmansk showed that in winter Q was greater than ca, while this was so in spring for the rest of the stations. Type A2 stations which showed that c a was greater than q in two seasons included Voeikovo and Uccle. Both of these stations exhibited this behaviour in spring and summer. The example of type A 3 stations was Pots- dam which showed that in the three seasons, spring, summer and autumn, the semidiurnal component was greater than the diurnal component.

The type B stations which included Japanese stations Kakioka and Memambetsu did not show that ca was greater than ca in all seasons. For Memambetsu this was true only in winter and for Kakioka in winter and autumn. During spring, cl and ca are almost equal at Memambetsu.

The times of maximum in GMT are variable. The time of maximum of the diurnal component varies from station to station. At oceans, the time of maximum of the diurnal component is at 17--19 GMT (S. J. MAUCHLY [2]). Only at Bolshaja Elan and Socorro the maximum is found near this time. It also appears that the times of maximum for the stations in the same geographical area are close to each other. The difference in the times of maximum for the Japanese stations Memambetsu and Kakioka is about 1 hour. The European stations also exhibit maxima relatively close to each other. This suggests that the local variations of conductivity and columnar resistance may be varying on a synoptic scale. The semi-diurnal, terdiurnal and quarto-diurnal contribution to variance is in general smaller than that of diurnal component, and hence the results of the time of maximum for 12-, 8- and 6-hour components are variable and not much confidence can be placed in results. The diurnal con-

356 BHARTENDU

tribution must be subtracted from the data in order to obtain significant phase results for higher frequency components.

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Fig. 4

The seasonal variation of the phase coefficient showed that the time of maximum in GMT of the diurnal component occurred earlier in the day during the summer season, an observation in disagreement with the Carnegie results (S. J. MAUCHLY [2]). The exception to this was noted at Voeikovo, Bolshaja Elan and Socorro stations.

3.5. C o r r e l a t i o n s

The correlation coefficients of hourly fair weather averages for all the months (or for the months for which data were available) in 1964 and 1965 were calculated for various stations. In this case, each month had twenty-four hourly mean values and there were twenty-


four months of data available. Hence, the maximum number of hourly values for any station was 576. Table 2 shows such correla-

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0 I 2 3 4, 5 6 ? 8 9 I0 I I 12 13 14 15 16 I?' 18 19 80 21 22 23 24 TIME OF MAXIMUM (GMT)

Fig. 4. Variation of the amplitude and phase of diurnal (cl), semidiurnal (c~), terdiurnal (%), and quarto-diurnal (q) components of the electric potential gradient

tion coefficients for hourly averages in GMT and Table 3 in local standard time. As evident from the tables, mostly small values of correlation coefficients are found. Even negative values are noted. The symbol n in the tables means the number of observations for which the correlation coefficients were calculated. Id Table 2, only 20 station pairs out of about 175 show the correlation coefficient greater than 0.5; for ten station pairs, greater than 0.6, and for four, greater than 0.7. In Table 3, for 34 station pairs the correlation coefficient is greater than 0.5, for 17, greater than 0.6, and for 4 greater than 0.7.

3 5 8 B H A R T E N D U

Table 2. Correlation Coe/ficients o[ the Hourly Means o[

University .47 _+ .16 .60 _+ .04 .40 _+ .10 .63 _+ .04 .75 _+ .04 .34 + .06 .52 _+ .Ii .64 _+ .04 -.13 _~ .06 Park - n = 24 n = 240 n = 72 n = 240 n = 144 n = 192 n = 48 n = 216 n = 240

Uccle - .80 + .08 .30 + .06 .54 ! .06 .77 + .03 ,4V _+ .06 .61 * .04 ,54 + ,04 -43 _+ .05 .01 _~ .06 n ---24 n ---264 n = 120 n = 264 n = 192 n = 264 n = 264 n = 240 n = 264

Tashkent - .00 + .20 -.05 _+ .20 .28 + .19 ........ .04 * .20 -.14 + .20 n = 24 n = 24 n = 24 n = 24 n = 24

Soeorro - .28 _+ .04 .14 _+ .05 .04 + .04 .28 _+ .05 -.07 +_ .04 .03 I .04 n = 576 n = 432 n = 528 n = 28S n = 528 n = 552

Potsdam - -53 _+ .03 .47 + .04 .48 + .04 ,43 -+ .06 .29 Z .0~ .06 _+ .05 n = 432 n = 312 n = 384 n = 216 n = 408 n = 408

Odessa - .29 _+ .04 ~ _+ .05 .17 _+ ,05 .IS _+ ~ .27 + ,04 -.23 _* .04 n=456 n=312 n=408 n=240 n=432 n=408

Murmansk - .31 _~ .04 .47 + ~ .35 _+ .04 .31 _+ .0~ .47 _+ .03 .06 + ~ n = 576 n = 432 n = 528 n = 288 n = 528 n = 552

Montreal - ,29 _+ .19 .19 _+ . 20 -.04 _+ .20 ....... 15 Z ,20 ...... n = 24 n = 24 n. = 24 n = 24

........ �9 32 Z .18 ...... ,=24

-.I0 + .20 .35 _+ .04 .27 + .07 n - - 24 n = 576 n ---192

.21 _+ .19 .38 _+ .04 .31 + .07 n=24 n=432 n:168

�9 33 _+ .18 .08 + .05 .23 _+ .07 n = 24 n = 456 n = 168

-.41_+ .17 .27 ! .O4 .07 _+ .O7 n = 24 n = 576 n = 192

....... 13 + .20 ......... n= 24

Memambetsu - .36 + .18 .40 + .04 -.09 _+ .08 n = 24 n = 504 n = 168

Llsboa - .41 _* .17 .23 + .04 .33 + .07 n = 24 n = 552 n ---168

Kiev - .68 + .ii .25 + ,04 .24 _+ .07 n = ~4 n ~ 456 n = 168

Kskioka - -.51 _+ ,15 .16 + .04 .02 _+ .07 :I=24 n = 5 5 2 n=192

Irkutsk - .J~6 _+ ,16 .28 _+ .04 n = 24 n = 528

Dourbes - .37 _+ .18 .01 + .06 n = 24 n = 288

Dusheti - .81 _+ .07 .19 _+ .04 n = 24 n = 528

Vysokay - .59 + .13 ,26 * ,04 Dubrava n = 24 n = 432

Voelkovo - .23 + .19 .32 _+ .0~ n = 24 n = 576

Budapest ......... .00 + .07 n= 192

BolBhaJa - .02 + .20 1.00 Elan n = 24 n = 576

AaChen - 1.00 n=24

the Potential Gradient

�9 35 +_ .04 .34 + .05 .36 _+ .04 .18 _+ .06 .29 + .04 .27 * ,04 n = 504 n = 384 n = 456 n = 264 n = 456 n ---480

.52_ + .03 .41_ + .04 .47 + .03 .47_ + .05 .33_ + .04 -.01 I .04 n = 552 n = 432 n ---504 n = 264 n = 504 n = 528

�9 29 + .04 .28 _+ .05 .16 _+ .05 .12 ! .07 .39 _+ .04 .02 + .05 n = 456 n = 336 n = 408 n = 192 n = 456 n = 432

�9 08 + .04 .05 ! .05 -.Ol __+ .04 .09 + .06 .i0 * .04 1.00 n = 552 n = 408 n = 504 n = 288 n = 504 n = 552

�9 41 + .04 .57 + .03 .39 _+ .04 .II ! .06 l.SO n = 528 n = ~08 n = 480 n = 264 n = 528

�9 50 _+ .04 .26 + .96 .41 _+ .05 1.00 n = 288 n --'216 n = 288 " n = 288

.49 _+ .04 1.00 n = 408 n = 528

1.00 n = 432

.07 ! .07 n=192

.46 ! .O7 n = 120

-.04 __+ ,08 ,37 __+ .04 n=144 n=528

�9 05 _+ .OS .56 + 0.3 n=144 n=432

.32 ~ .06 1 ,0o n=192 n = 5"76

1.00 n=192

m ~ l m

The correlation coefficients of the yearly hourly values and monthly means are also calculated. The fair weather hourly values were averaged for a two-year period and in this way 24 values for each station were determined. The correlation coefficients of such annual hourly average values in GMT and local standard time are shown in Table 4. Average monthly values for each month were also computed. Data for two years were available and hence 24 such monthly means were obtained for each station and the correlation coefficients between these monthly means were computed. These are also ex-


in GMT for Two Years

�9 43 _+ .06 .54 _+ .05 .I0 + .08 n = 216 n = 240 n = 68

.29 + .07 .60 Z .04 .49 -+ .05 n = 192 n = 240 n = 250

�9 23 + -20 -.43 I .17 .09 I .20 r*=24 n=24 n:24

.07 _+ .05 . 32 * .04 .07 I .04 n = 456 n = 552 n = 504

.37 + .05 .45 ! .04 .29 _* .05 n=360 n=432 n=360

.2"7 + .05 .25 ! .05 .Ii ~ .05 n = 384 n = 4~2 n = 408

,21 * .04 .42 + .03 .31 + .04 n ---456 n = 552 n = 504

......... .19 _+ .20 .2/+ _+ .19 n = 24 n = 24

..07 * .05 .20 ! ,04 i.o0 n = 384 n = 480 n = 504

.25 + .05 1.90 n ---432 n = 552

1.00 n=456

�9 46 I .05 .34 Z .06 .47 _+ .05 n = 240 n = 216 n = 240

.......... 42 Z .05 .26 • .06 .47 -+ .o6 n = 264 n = 216 n = 192

........... Ii _+ .20 -,56 ! .14 -,29 _+ .19 n=24 n=22+ n=24

-.06 _* .20 .17 + .04 .04 _+ .05 .27 + .04 n = 24 n = 576 n = 456 n = 432

�9 32 I .18 .42 ! .04 .16 + .05 1.00 n = 24 n = 432 n --"360 n = 432

.......... ~o _+ .04 1.00 n = 456 n = 456

�9 22 ! ,19 1.00 n = 24 n = 576

1.00 n=24

�9 45 -+ .05 .09 _+ .20 .53 2 .10 n=240 n=24 n=A8

.32 _+ ~ ...... 1.00 n = 264 n = 264

.01 _+ .20 i,00 .=24 n=24

1.00 n = 576

I,~ n = 240

hibited in Table 4. The n in the table specifies the number of months for which the data were available. The limiting value of the correlation coefficient in Table 4 for a 1 percent probability level is 0.49. (R. A. FISHER and F. YATES [19]). As evident from the table, for more than seventy-five percent of station combinations, correlation coefficients less than the limiting value are found. Negative values are also obtained. Only for seven station pairs, Voeikovo - - Potsdam, Vysokaya D u b r a v a - - Dusheti, Vysokaya D u b r a v a - - Murmansk, Vysokaya D u b r a v a - - Potsdam, Dusheti - - Uccle, L i sboa - - Pots-

�9

B ,-+.,..,

e+C

t+..

m.,

P~

c>

~'. +4, ~',, ~,,

�9 ~ .~ .~ ..7. .~

�9 ~ l+ �9 .

!~

+'?, +4, +',+ +',, +h, § +4, +~?, 8~

+,, ++. +'. +'. ++'. ++',, +,. +,. +.,, +~

~+,,~ +,,, +4 +,,, 2 . +'" i ' . +',, "~

+ ~ , ++i+ * i , + + ~+ + ++ ~ ~+ , + . § +~

~,+. +'~ , . , 'm " . �9 "m "~ "~+ +~ "~ "m m +Ill +Iii +Ill +Iii } m~ ~ + m+ m+ + ii11 +'H 11,1 ~11 +111 + 11

�9 '? +,? +,~ +,. ",? +,~ +4, +,?, +4 + +,? +.,,'+ +,. +,,~ +,?, ~,'?+,

++++ +. o ++ +++ ++ +++ ++ +++ ++ +m+ +~ o+++~ +++ -m -+ -+ .m -m . . . . + ~ m..m +~ +,,

+ + + + + .+ + + - + + ? ~ + + . + , ~

. . . . . . i" . . . .

'~ "+~ ',~ ",a -,~ ",~ "~ -~ ",~ +'~ o.,~ ",~ +.~ + +.~ +.~ �9 + + + �9 * ~ + i + i + + i + + * I + i + +~

++ +++ ++++ ++ ++ ++ ++ "+ "+ 1,7, +,?, +,7, ,7, .,,, +4, +.+7 +'I

�9 .+ .+ .~ .+ . .~ ~.+ 0+~ +.~ ore+ +.M +.~ .~ o+m o.+ .~ .~

. . . . . . . . . . . . . , . . . . t "

+ i , + t . . . . . . . + + + ? . + i +~? ++ +~ +', +4, +~?,, +,,

. . . . + . . . . . . + + P +

+ , + + +

" + + +, + +~ + + + + " . i " : ' +' ++ ~ + + . ~+ ++ +. + + j ~ ++~ + + o ~

oa~a~o~

~e~pO

T ~ B n ~

BHARTENDU: Electric Potential Gradient Variation at Land Stations 361

Table 4. Correlation Coefficients of the Hourly Annual Mean in GMT and LST and Monthly Means of the Potential Gradient

University -.84 ,21 -.68 -.76 -.68 .13 .32 -.33 -.67 -.14 -.2~ .76 -.$9 -.81 .98 .15 .33 .03 Park .71 .19 .63 .54 .03 .38 -.18 -.45 .48 .68 -.20 .76 .81 .19 .46 .58 .24 .28 (. = I0)

uo~z, .32 .~. . ~ -.~ .37 .35 .0 .93 .64 -71 .37 .56 (~ ll) .18 .S3 -.47 ,69 ,93 -,51 .79 -.53 .7~ .9o .o2 :~ :fi :~ :~ :~

�9 55 .79 -94 .69 ~ .45 .80 .26 .23 .79 .66 .68 .28 .55 .88

Tashkent -.03 .46 -.43 .01 -.23 .35 -.21 -.52 -.22 .30 -.59 .28 -.12 -.48 -.92 -.13 (n = i) -.15 -.62 -.26 .Ii .92 -.48 .95 -,33 -.23 -.21 -.09 .07 .20 -,09 -.40 -.22

. . . . . . . . g :~ ~ .~ .,4 .45 :~ .~5 . . . ~ .,4 . . . . . ~ ~I "~' ( - = u ) . : .~ -.~9 .59 - -.~o .~o -m .,s .~9 : ~

�9 59 .33 .43 .51 .63 ,40 .51 .59 .Ii :52 .61 .49 -:17

Po%sdam -.64 ,64 .74 .62 .59 .80 79 .24 .56 .69 .35 .07 .67 .74 (n = 18) .54 .64 .~0 .60 .37 .87 -.30 -.s .77 .75 -.61 .52 .49 .58

�9 49 .15 .~ .60 .56 .39 .55 .22 .51 .67 .48 .53 .61

o~ . . . . . . . 9 .~ .~9 .~ .~'~ .~ .~1 .~ .~. .~ e ..060~ ~=19~ - .~ .~4 .~9 .~ .,o .~0 . .~0 .~ -.68 -. . .37 .20 .65 .54 .31 .18 .12 .59 ..18 .45 .33 .36 .58

M~u'm~nsk -,70 .40 .62 .73 .36 .55 .78 -.14 .55 .49 -.06 -.19 (n = 24) .43 .12 *63 .70 .30 .45 .94 -,63 .55 .73 -.35 ,50

�9 41 .ii ,44 .79 .65 .55 .73 .36 .48 .58 .57

Montreal -.61 -,28 -.S5 -.49 -.23 -.38 .54 -,39 -*~ .~ -.2"I (n = Ii) .90 .35 ,55 ,16 -.31 ,36 -.68 -.98 ,45 -,21

_.~:. ~o .49 "~ ~ "~5 -'~.~5 �9 3 ~ -.54 -.62 -.47 -.50 .~ �9 7~ -.32

�9 40 ,29 .52 ,68 .77 e46 e5~ .28 -.08 ~

L~s~oa --74 .&7 .53 .~0 .~ .S5 -66 .32 (n = 23) .39 .39 .92 .71 .~, .95 .15 -.53 ;~

-32 .41 .69 .62 .73 .45 .69 .52 .42

Kiev -.83 .7c~2 .85 ,82 .78 .55 *74 - .19 (n = 19) ,25 o~, .~5 .70 *63 .77 .16 -.46

.56 .94 .30 .34 .22 -.S9 .67 .03

�9 ~5 .~9 -a9 - ~ .~ ,ii -.56 -,79 -.

.28 -.91 .18 .28 .41 -45 .30

~ , o k o : ~ _:~ - . - .16

�9 47 ,09 .58 .74 .52 .33

~o=~ , , - . ~ .59 -5~ .~1 .~o (n = 129 .35 .78 .S9 .58 .~9

-.98 .5"2 .54 .28 .51

Dushe%i - .73 -.77 -69 ,69 (~ = 22) -.49 .04 .50 .~6

�9 39 .17 ,44 .74

Vysokaya - .72 .76 ~i Dubrava .19 .13 ,67 (n = iS) .~ .31 .47

- = . 4 9 �9

�9 ~ -53

Buda~st ,28 (n ='s) .39

-.97

Bolshaja Elan (~ = 24)

1o% II~ = Hourly monthly ~ans in lOCal tl~e for 1964 & 1965 2nd li~e = Ho~ly mo.thly ms~ns in G~T for 1964 & 1965 3rd li~ = Mon%hly Means for 1964 & I~.

d a m , a n d L i s b o a - U c c l e , c o r r e l a t i o n c o e f f i c i e n t s h i g h e r t h a n 0 .6 h a v e b e e n f o u n d f o r t h e a n n u a l h o u r l y m e a n s i n G M T , l o c a l t i m e , a n d f o r t h e m o n t h l y m e a n s .

T h e l o w c o r r e l a t i o n c o e f f i c e n t s a r e c o n s i s t e n t w i t h t h e o b s e r v a t i o n s

Of H . ISRAi~L a n d P. DE BRUIJN [11] w h o a l s o n o t e d l o w v a l u e s f o r s e v e r a l o t h e r s t a t i o n s . I t a p p e a r s t h a t t h e l o c a l v a r i a t i o n s o f c o n - d u c t i v i t y a n d c o l u m n a r r e s i s t a n c e a r e n o t e l i m i n a t e d a t l a n d s t a t i o n s

Arch. Met. Geoph. Biokl. A. Bd. 18, H . 3-4 24

362 BHARTENDU

in two-yea r average values. I t is also possible that the mechanism of spherical capaci tor being charged by thunders torms on a global scale m a y not be as effect ive a cause of the potent ia l gradient var ia t ion as is believed, at least at land stations.

4. Conclusions

T h e dissimilar i ty of d iurnal curves in G M T and local s tandard t ime at d i f ferent stations, the s imilar i ty of fa i r wea ther and all weather curves and the general reduct ion of mean annual values in all wea ther f rom fai r wea ther at a station, the nor thern hemisphere winter m a x i m u m and nor thern hemisphere summer min imum, presence of a m a x i m u m in the range of 24- to 31-day per iod in the power spectra for f i f ty percent of stations, classification of stations depending on the seasonal var ia t ion of percentage var iance of the diurnal component , occurrence of t ime of m a x i m u m close to each other for stations in same geographica l location and also the occurrence of m a x i m u m earl ier in the day dur ing summer, and the low correlat ion coefficients of hour ly and month ly means of the potential gradient are significant conclusions of this paper .

Acknowledgements

The author is grateful to Dr. H. DOLEZALEK for his valuable suggestions and comments. Long discussions held with him were very helpful in improving the content and the presentation of this paper. Thanks are also due to Dr. B. W. CURRIE, Dr. E. GHERZI and Mr. J. D. ~IOLLAI'~D who suggested improvements in the manuscript.

References

1. DOLEZALEK, H.: Discussion of an Atmospheric Electricity Ten-Year Pro- gram. Tech. Rep. No. D-2, Contract No. N00014-66-C0303, Boston College, Mass., 1967.

2. MAUCHLY, S.J.: On the Diurnal Variation of the Potential Gradient of Atmospheric Electricity. Terr. Magn. Atmosph. Electr. 28, 61--81 (1923).

3. BROWN, J. G.: The Local Variation of the Earth's Electric Field. Terr. Magn. Atmosph. Electr. 40, 413--424 (1935).

4. PARAMONOV, N. A.: On the Unitary Variation of the Atmospheric Electric Potential Gradient. Doklady, Akad. Nauk, USSR 70, 37--38 (1950).

5. HATAKEYAMA, H., and M. KAWANO: On the Diurnal Variation of Atmosphe- ric Potential Gradient in the Japan Archipelago. Pap. Meteorol. Geophys. 4, s s -~o (19s33.

6. ISRAi~L, H.: Synoptic Researches on Atmospheric Electricity. Proc. Second Confer. on Atmosph. Electr. Held at Wentworth by the Sea, Portmouth, N.H., 11--20 (1958).


7. ISRAi~L, H., H. DOLEZALEK, and G. FRIES: The Atmospheric Electric Climate at Four Selected Stations in the Swiss Alps. Tech. Note No. 13 to Contract AF 61(514)640 (1957).

8. DOLEZALEX, H.: Problems in Atmospheric Electric Synoptic Investigations. Recent Advances in Atmospheric Electricity, New York: Pergamon Press, 195--212, 1958.

9. IMYANITOV, I .M., and K. S. SHIFRm: Present State of Research on Atmo- spheric Electricity. Soviet Phys., USPEKHI. 5, 292--322 (1962).

10. ANDERSON, R.V.: Measurement of World-Wide Diurnal Atmospheric Elec- tricity Variation. Monthly Weath. Rev. 95, 899--904 (1957).

11. ISRAEL, H., and P. DE BRUIJN: The Present Status of Atmospheric Electric Research. Arch. Met. Geoph. Biokl., A, 16, 281--299 (1967).

12. ISRAi~E, H.: Atmospheric Electric and Meteorological Investigations in High Mountain Ranges. Final Report to Contract AF 61(514)640 (1957).

13. PANOFSKY, H.A. , and G. W. BRIER: Some Applications of Statistics to Meteorology. University Park: The Pennsylvania State University, 128--131, 1958.

14. BLACKMANN, R. B., and J. W. TUXEY: The Measurement of Power Spectra. New York: Dover Publications Inc., 1958.

15. ISRAi~L, K.: Atmosph/irische Elektrizit~it. Bd. II, Leipzig, 1961. 16. HUDDAR, B. B., G. P. SRIVASTAVA, and A. MANI: Studies of Fair Weather

Atmospheric Electrical Potential Gradient in the Free Atmosphere over Poona during IQSY. Indian J. Meteorol. Geophys. 19, 83--88 (1968).

17. KRUMM, H. C.: The Universal-Time Diurnal Variations of the Thunderstorm Frequency. Z. f. Geophys. 28, 85--104 (1962).

18. KAMRA, A.K., and N. C. VARSHNEYA: The Effect of a Solar Eclipse on Atmospheric Potential Gradients. J. Atmosph. Terr. Phys. 29, 327--329 (1967).

19. FISHER, R.A., and F. YATES: Statistical Tables for Biological, Agricultural and Medical Research. Edinburgh: Oliver and Boyd, Ltd., 1963.

Author's address: Dr. BHARTENDU, Department of Transport, Meteorological Branch, 315 Bloor St. W., Toronto 5, Ontario, Canada.

24~. ~

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The atmospheric electric potential gradient variation at land stations