on the short term variations of solar activity during solar cycle 21

6
ON THE SHORT TERM VARIATIONS OF SOLAR ACTIVITY DURING SOLAR CYCLE 21 TAMER ATAC Kandilli Observatory, Boga& University, Cengelktiy, Istanbul, Turkey (Received 14 June, 1989) Abstract. Short-term variations ot the last solar activity cycle were studied by the flare and coronal indices using Gleissberg method. Systematic short-term variations are found from their course during the 21st solar activity cycle. Comparison of their autocorrelograms constructed by the new set of data obtained from the magnitude of the fluctuations showed us the existence of the phase shift between the temporal variations of the two indices. 1. Introduction The statistical analysis of the time series obtained from the different indicators of the solar activity showed us its variability in the stellar aspect. Recently, from the reviews on solar variability by Lean (1987) and by Hudson (1987), it can be seen that the cyclic variations of the different indices vary from phenomenon to phenomenon. This idea led us to compare the short-term variations Of the flare and corona] indices which are the activity indicators of the different layers of the solar atmosphere. The daily flare index derived from the observations of the Ha flares, was first introduced by Kleczek (1952). It is calculated by the quantity 9 = i . r, assuming that this relationship gives roughly the total energy emitted by the flare. In this relation, i represents the intensity scale of the Ha importance and t duration of the flare. This index is one of the suitable indicators of the chromospheric activity given for each day. Meanwhile, the daily coronal index calculated by Rybanskg et al. (1988) is a numerical expression of the coronal irradiance derived from the emission line 530.3 nm, which belongs to the forbidden transition 2P3,2 - 2P,,2, ion Fe XIV. During the last cycle, the intensities of the 530.3 nm coronal line were deter- mined by the patrol observations at the following observatories: Kislovodsk, Lomnicky Stit, Norikura and Sacramento Peak. The index was determined from these observations but before the calculations the data obtained from the different observatories were converted to the uniform scale of Lomnickjl &it. It can be expected to a certain degree that the coronal index may replace the analogous full disc solar indices like the calcium plage index and the 10.7 cm radio flux. According to Lean (1987) the differences between the detailed temporal variations of the various solar activity indices are consistent with their derivation from different active region phenomena which are dominated by different physi- Earth, Moon, and Planets 47, 165-170, 1989. 0 1989 Kluwer Academic Publishers. Printed in the Netherlands.

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Page 1: On the short term variations of solar activity during solar cycle 21

ON THE SHORT TERM VARIATIONS OF

SOLAR ACTIVITY DURING SOLAR CYCLE 21

TAMER ATAC

Kandilli Observatory, Boga& University, Cengelktiy, Istanbul, Turkey

(Received 14 June, 1989)

Abstract. Short-term variations ot the last solar activity cycle were studied by the flare and coronal indices using Gleissberg method. Systematic short-term variations are found from their course during the 21st solar activity cycle. Comparison of their autocorrelograms constructed by the new set of data obtained from the magnitude of the fluctuations showed us the existence of the phase shift between the temporal variations of the two indices.

1. Introduction

The statistical analysis of the time series obtained from the different indicators of the solar activity showed us its variability in the stellar aspect. Recently, from the reviews on solar variability by Lean (1987) and by Hudson (1987), it can be seen that the cyclic variations of the different indices vary from phenomenon to phenomenon. This idea led us to compare the short-term variations Of the flare and corona] indices which are the activity indicators of the different layers of the solar atmosphere.

The daily flare index derived from the observations of the Ha flares, was first introduced by Kleczek (1952). It is calculated by the quantity 9 = i . r, assuming that this relationship gives roughly the total energy emitted by the flare. In this relation, i represents the intensity scale of the Ha importance and t duration of the flare. This index is one of the suitable indicators of the chromospheric activity given for each day.

Meanwhile, the daily coronal index calculated by Rybanskg et al. (1988) is a numerical expression of the coronal irradiance derived from the emission line 530.3 nm, which belongs to the forbidden transition 2P3,2 - 2P,,2, ion Fe XIV. During the last cycle, the intensities of the 530.3 nm coronal line were deter- mined by the patrol observations at the following observatories: Kislovodsk, Lomnicky Stit, Norikura and Sacramento Peak. The index was determined from these observations but before the calculations the data obtained from the different observatories were converted to the uniform scale of Lomnickjl &it. It can be expected to a certain degree that the coronal index may replace the analogous full disc solar indices like the calcium plage index and the 10.7 cm radio flux.

According to Lean (1987) the differences between the detailed temporal variations of the various solar activity indices are consistent with their derivation from different active region phenomena which are dominated by different physi-

Earth, Moon, and Planets 47, 165-170, 1989. 0 1989 Kluwer Academic Publishers. Printed in the Netherlands.

Page 2: On the short term variations of solar activity during solar cycle 21

166 TAMER ATAC

cal mechanisms localized in different layers of the solar atmosphere. From this point of view it will be interesting to compare the short-term variations of the flare and coronal indices during the 21st solar cycle.

2. Data and Analysis

Our data, the observed monthly mean of coronal and flare indices for the 21st solar cycle, were calculated by Rybansky et al. (1988) and by Atac (1987) respectively. We have not mentioned here the details of their calculations. Many examples of time series such as coronal and flare ones led us to regard a time series as composed of three constituent items, a long-term movement or trend, a short-term systematic movement and an unsystematic or random component (Yule and Kendall, 1964). So, one of our principal problems was to isolate these components for a separate study. As it can be seen from Figure 1, similar fluctuations occur in each index during the long-term variations.

First of all, for the study of the randomness of these occurrence, we applied the method developed by Gleissberg (1947). The application of this method to the solar cycles for the study of the short-term variations is very well described in a paper by Ball] (1955). For applying Gleissberg method we prepared a new set of data from the observed monthly mean of the coronal and flare indices. We

Fig. 1. Time history of monthly observed values of the flare and coronal indices during cycle.

1st solar

Page 3: On the short term variations of solar activity during solar cycle 21

SHORT TERM VARIATIONS OF SOLAR ACTIVITY

calculated the smoothed indices values by using Waldmeier’s formula

167

R-6 + R+b + 2 f Ri I?()= -s

24

Then we subtracted the observed values from their smoothed ones. Thus we obtained two sequences of a difference type indices. This type of index is useful to clarify the magnitude of the fluctuations. In order to show the relations among the short-term variations of the two indices, we ,plotted the magnitude values of the fluctuations versus time in Figure 2.

Our new data set, as it can be seen from Figure 2 covered a sequence of runs which are created by the random occurrence of the two states. Runs are defined as uninterrupted sequences of the same state, in our data they appeared as positive and negative fluctuations. Gleissberg (1947) showed that in order to see if the sequence is ranged by chance or not, the probability had to be calculated by the following expression.

P= l-erf(x).

Flare Index

Coronal Index

Fig. 2. Comparison of the short-term variations of the flare and coronal indices for the period 1976-1986.

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168 TAMER ATAC

Where the symbol erf represents the error function defined as x

erfx=2/rr edy2dy. I 0

If the calculated value of the probability is P = 1, we can say that the sequence is ranged by chance, contrary if P # 1, in that case it can be considered that the sequence showed systematic variations. Finally, the calculation method of the quantities which is necessary to calculate the error function, is given in a paper by Ball1 (1955). By these quantities we determined the values of the probability for the coronal and flare indices as PC = 0.00 and Pr = 0.03 respectively. These results showed us that each index contains systematic short-term variations during the 21st solar cycle.

On the other hand, we know that correlograms help to reveal the charac- teristics of time series. In order to see how the short-term variations of the two series move within themselves and to compare them with each other, the autocorrelograms were constructed. They are calculated using the method developed by Davis (1986) from the monthly fluctuation magnitude values. Then in Figure 3, we compared them in order to determine how well the troughs and the peaks matched.

0.6

0.4

0.2

0

-0.2

-0.4

1 . ‘.

I CI -*-

i FI -

i I ‘\ I!’ i.i

. ’ 1 a . . I I

0 4 8 12 16 20 24 28

LAG (Months)

Fig. 3. The autocorrelograms for the same time interval are plotted for comparison.

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SHORT TERM VARIATIONS OF SOLAR ACTIVITY 169

3. Results and Discussion

In our study, we found that the flare and coronal indices showed systematic short-term variations during the course of the 21st solar cycle. This event is determined by previous authors for the past cycles using different indicators of solar activity. Recently, Dodson and Hedeman (1972) have shown that the solar activity, as measured classically by sunspot numbers and 2800 MHz flux, appears to advance by series of pulses or episodes. The important review of Kuklin (1976) drew the attention to the fluctuations of a solar activity. Then, Vitinskii (1980) has compiled data about strong fluctuations of a solar activity using the activity indices, sunspot relative numbers and the total area of sunspots. In the last few years from the idea of the quantitative study of strong fluctuations, many authors have reported that the duration of the fluctuations ranged in time from five months to a year. At first the extensive analysis of monthly mean sunspot data made by Wolf (1983) using statistical analysis techniques has to be mentioned. Rieger et al. (1984) and Kiplinger et ckl. (1984) found strong evidence for a S-month periodicity in the occurrence pattern of energetic solar flares. This result appears to have been confirmed also by the studies of Bogart and Bai (1985), Ichimoto et al. (198.5), Raychaudhuri (1986), Bai and Sturrock (1987), and finally ozgiic and Atac (1989).

The low correlation between the coronal and the flares indices is calculated by the author (1989). In Figures 2 and 3, this low correlation is confirmed by the comparison of the fluctuation curves and their correlograms. As it can be seen from the figures, in the autocorrelograms the peaks of the coronal index are matched with the troughs of the flare index ones. Recently the disagreements between the temporal variations of the different activity indices are discussed by several authors. Rybansky et al. (1988) showed that maxima of the coronal index and Wolf relative numbers do not coincide; the difference is about two years. Lean (1987) in her extended review on the solar ultraviolet irradiance variations drew the attention to this phenomenon: and she added, more generally, emissions from the upper photosphere and chromosphere vary more like each other than like radiation emitted from the corona. In the same review, it can also be seen that the cross-correlation function of the solar chromospheric irradiance at 28.4 nm versus the indicator of coronal emission at 10.7 cm are not identical.

4. Conclusions

During the 21st solar cycle the course of the flare and coronal indices showed systematic short-term variations, but from the comparison of their correlograms and from the calculated low correlation coefficient we conclude that their temporal variations showed a phase shift. This result gave us the idea that the energy which came from the solar interior evolved differently along the different layers of the solar atmosphere. So we need a long sequence of other activity

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170 TAMER ATAC

indices data which will represent the activity of the different heights of the solar atmosphere to understand the basic mechanism of the solar activity.

Acknowledgement

I should like to thank Dr. A. 6zgiig for his critical reading of the manuscript.

References

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Inc. Dodson, H. W. and Hedeman, R. E.: 1972, in E. R. Dyer (ed.), Solar-Terrestrial Physics, Part 1,

Kluwer Acad. Publ. Dordrecht, Holland, p. 151. Gleissberg, W.: 1947, Publ. of the Istanbul University Observatory, No. 31. Hudson, S. H.: 1987, Reoiews of Geophysics, (No. 3) 651-662. Ichimoto, K., Kuboto, J., Suzuki, M., Tomura, I., and Kurokawa, H.: 1985, Nature 316, 422. Kiplinger, A. L., Dennis, B. R., and Orning, L. E.: 1984, Bull. Amer. Astron. Sot. 16, 891. Kleczek, J.: 1952, Publ. Centr. Astron. Inst. Czechoslovakia, No. 22. Kuklin, G. V.: 1976, ‘Basic Mechanisms of Solar Activity’, in V. Bumba and J. Kleczek (eds.), IAU

Symp. 71, 147. Lean, J.: 1987, J. of Geophys. Res. 92, No. Dl, 839-869. ijzgit$, A. and Ataq, T.: 1989, Solar Phys. 123, 357. Raychaudhuri, P.: 1986, Solar Phys. 106,421. Rieger, E., Share, G. H., Forrest, D. J., Kanbach, G., Reppin, C., and Chupp, E. L.: 1984, Nature

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